Occupant Injury Assessment in an Emergency Landing Condition for a Vertical Take-Off and Landing Aircraft

OCCUPANT INJURY ASSESSMENT IN AN EMERGENCY LANDING CONDITION FOR A VERTICAL TAKE-OFF AND LANDING AIRCRAFT

A Thesis by

Jefferson Douglas Hugen Vieira

Bachelor of Science, Universidade do Estado de Santa Catarina, 2017

Submitted to the Department of Mechanical Engineering and the faculty of the Graduate School of Wichita State University in partial fulﬁllment of the requirements for the degree of Master of Science

The following faculty members have examined the ﬁnal copy of this thesis for form and content, and recommend that it be accepted in partial fulﬁllment of the requirement for the degree of Master of Science, with a major in Mechanical Engineering.

Hamid Lankarani, Committee Chair

Gerardo Olivares, Committee Member

Davood Askari, Committee Member

iii To all the hopeful engineers trying to make a positive difference in this world

iv They didn’t know it was impossible, so they did it Mark Twain

v ACKNOWLEDGMENTS

I would like to thank my parents and my family for the continued support during all the steps that led to this moment. Without a doubt, I would not have accomplished as much without their presence, especially during the most challenging moments. In a similar manner, my dear friend and roommate Rafael Bini is here recognized for his wholehearted friendship, which brought me insights through his technical knowledge, smiles with the plentiful celebrations, and life lessons from our deep talks. A special thank is due to Flavia Ciaccia, who not only has been a dear friend but also was the person that inspired me to pursue my research on the topic of eVTOLs. In addition to that, Flavia was a key person early in my career who allowed me to reach opportunities that would be impossible otherwise, and I’m forever thankful for this trust she once laid in me. My advisor Dr. Lankarani was of fundamental importance to the execution and com- pletion of this research. Since my initial steps in the master’s program, he was an inspiration to me through his challenging classes, unquestionable knowledge, and kind treatment that turned him into a friend. Despite the novelty and difﬁculty of the chosen topic, Dr. Lankarani always trusted and supported me in this path, which was a great motivator at the most daunting moments. The author gratefully acknowledges the support given from the AVET lab at NIAR, particularly to Luis Gomez and Dr. Olivares, who provided vital guidance and insights that led to the work here reported. The use of the AVET Lab computational resources is also greatly appreciated.

vi ABSTRACT

In the next few years, the aeronautical industry is poised to change in a way it has not for decades. There has been a rising interest in deploying Vertical Take-Off and Landing (VTOL) aircraft to serve on-demand transportation across urbanized areas. The recent developments in battery and electric motor technologies have opened the path to achieve quieter and more efficient vehicles capable of using compact infrastructure well suited for urban operation. However, this novel concept introduces several aspects that the current airworthiness regulations lack to address, such as the pure vertical crash landing. Scenarios like this are likely to occur since these aircraft need to gain enough altitude to clear the surrounding buildings before reaching higher horizontal velocities for cruising. The tight weight margins require the use of lightweight structures for such aircraft, which can significantly compromise occupant safety since materials such as carbon fiber rein- forced plastic are mostly ineffective for energy absorption without the proper design of failure mechanisms. Foreseeing such a challenge, the present study is aimed at evaluating and assessing the sensitivity of occupant injury severity in relation to varying structural parameters defined for the seat, subfloor, and landing skid structural systems. A representative multibody model of the pure vertical crash landing scenario has been developed, validated, and utilized, employing Kelvin restraints to model the structural systems and an FAA Hybrid III ATD model in MADYMO to capture the occupant level of injury. Two case studies are conducted using modeFrontier, where the first uses a linear structural model to describe the stiffness of the structures, while the second case considers a non- linear definition to account for component failure. The first study yields trends for identifying the driving factors, where the damping of the landing skid is shown to be dominant over other factors to improve occupant safety. The addition of failure variables to the second study is shown to have an improvement in reducing the injury levels. Yet, the added complexity to the model could underline the value of integrated occupant safety design, as effective energy absorption is required to keep low injury levels.

vii TABLE OF CONTENTS

Chapter Page

1. INTRODUCTION ...... 1

1.1 Background...... 1 1.2 Motivation...... 5

2. THEORETICAL BACKGROUND AND LITERATURE REVIEW ...... 6

2.1 Basics of Injury Biomechanics...... 6 2.1.1 Vertical Loads...... 7 2.1.2 Injury Criteria and Regulations...... 9 2.2 Principles of Crash Dynamics...... 13 2.2.1 Vibration Analysis and Multibody Dynamics ...... 13 2.2.2 Factors for Crash Survivability...... 15 2.3 Literature Review...... 19

3. METHODOLOGY ...... 22

3.1 General Research Methodology...... 22 3.2 Objectives...... 24 3.3 Modeling Methodology...... 25 3.4 Parametric Study ...... 31 3.4.1 Deﬁnition of the Model Parameters ...... 31 3.4.2 Case Study I: Linear Structural Behavior...... 38 3.4.3 Case Study II: Non-linear Structural Behavior...... 40 3.4.4 MADYMO Model of the ATD and eVTOL Aircraft...... 41 3.4.5 DOE Investigation Using modeFrontier ...... 42

4. MODEL VALIDATION ...... 45

4.1 Validation Methodology...... 45 4.1.1 FAA Test 1 Validation ...... 46 4.1.2 Drop Tower Test Validation...... 47 4.2 FAA Test 1 Validation Results ...... 49 4.3 Drop Tower Test Validation Results...... 52

5. PARAMETRIC STUDY ...... 59

5.1 Case Study I: Linear Structural Behavior...... 59 5.1.1 Overview ...... 59 5.1.2 Sample Responses ...... 62 5.1.3 Sensitivity Analysis and General Trends...... 66 5.2 Case Study II: Non-linear Structural Behavior...... 69 5.2.1 Overview ...... 69 5.2.2 Sample Responses ...... 72

viii TABLE OF CONTENTS (continued)

Chapter Page 5.2.3 Analysis of the Results...... 74

6. CONCLUSIONS AND RECOMMENDATIONS ...... 77

6.1 Conclusions...... 77 6.2 Future Work...... 79

BIBLIOGRAPHY ...... 80

ix LIST OF TABLES

Table Page

2.1 DRI values and probability of spinal injury included in Landolt et al. (1996) . . . . 11

2.2 Requirements for emergency landing dynamic test conditions (Federal Aviation Administration, 2016a,b,c,d)...... 13

3.1 Parameter values used for the MB to MB contact deﬁnitions ...... 29

3.2 Aircraft mass (Johnson, Silva, and Solis, 2018) ...... 32

3.3 Mass distributed for each system...... 33

3.4 Computation of the stiffness ranges for each structural system ...... 36

3.5 Computation of the damping ranges for each structural system ...... 36

3.6 Deﬁnition of the failure parameter ranges for each structural system ...... 37

x LIST OF FIGURES

Figure Page

1.1 Potential impacts of the Uber on-demand air transportation. Adapted from Holden and Goel (2016)...... 2

1.2 Companies unveil their concepts for the UAM market (Uber Technologies, 2020). 3

1.3 Typical urban air transportation mission. Adapted from Grandl et al. (2018).... 4

1.4 Interaction of the aircraft structures during an impact event (Littell, 2019)..... 5

2.1 Anatomy of the human spinal cord (Netter, 1989)...... 7

2.2 Spinal injuries for military causalities (Franklyn and Lee, 2017) ...... 7

2.3 Tolerance envelope for acceleration exposure in different directions (Norton et al., 2004; Sanders and McCormick, 1987)...... 8

2.4 Seat restraint conﬁgurations with lap belt and shoulder harness (Chandler, 1993).. 9

2.5 Eiband curve demonstrating the limits for which ejection seats are designed (Franklyn and Lee, 2017) ...... 10

2.6 Hydryd II ATD used on CAMI tests ...... 11

2.7 Correlation between the DRI and lumbar load (Chandler, 1985)...... 11

2.8 Differences between the Hybrid III and the FAA Hybrid III ATDs (D. Y. Hu, Yang, and M. H. Hu, 2009) ...... 12

2.9 Representation of the tests 1 and 2 required by the airworthiness regulations . . . . 13

2.10 Representation and response for a single degree of freedom dampened system . . . 14

2.11 Mathematical modeling of dynamic systems. Adapted from Singiresu et al. (1995) 14

2.12 Examples of multibody models...... 15

2.13 Cumulative frequency distribution of the impact velocity for survivable aircraft accidents. Adapted from Coltman, Bolukbasi, and Laananen (1985) ...... 17

2.14 Typical response of different aircraft types to a vertical crash landing. Adapted from Kindervater (1997) ...... 18

xi LIST OF FIGURES (continued)

Figure Page 2.15 Failure mechanisms designed in energy absorbing seats for occupant injury mitigation (Desjardins, 2006)...... 18

2.16 Technical evaluation of different eVTOL concept vehicles (Johnson, Silva, and Solis, 2018)...... 20

2.17 Model and simulation results reported in Putnam and Littell (2019)...... 21

3.1 Sequence of the research methodology...... 23

3.2 Crash test dummies available in MADYMO...... 26

3.3 Constituent elements of the MADYMO models prepared ...... 26

3.4 Experimental validation for the chest and the full dummy under vertical loads for the FAA Hybrid III ATD (TASS International Software, 2017) ...... 27

3.5 Seat belt arrangements used on the MADYMO models ...... 28

3.6 MB to MB contact deﬁnitions (surfaces in red are master and in blue are slave) . . 29

3.7 MB to FE contact deﬁnitions for the left side belt straps (surfaces in red are master and in blue are slave) ...... 30

3.8 Representation of the single passenger eVTOL aircraft concept (Johnson, Silva, and Solis, 2018)...... 31

3.9 Interpretation of the structural systems...... 33

3.10 Typical subcomponent structure found in rotorcraft. Adapted from Bisagni (2002), Farahmand, Ganji, and Sajadi (2019), and G. J. Hiemenz, W. Hu, and Wereley (2008) 34

3.11 Axial loading in a structural element...... 35

3.12 Deﬁnition of the linear characteristic for each structural system...... 38

3.13 Identiﬁcation of the input and output variables for the case study I ...... 39

3.14 Deﬁnition of the non-linear characteristic for each structural system ...... 40

3.15 Identiﬁcation of the input and output variables for the case study II...... 41

xii LIST OF FIGURES (continued)

Figure Page 3.16 Interpretation of the kinematic relationship...... 42

3.17 Integration nodes available on modeFrontier...... 43

3.18 modeFrontier workﬂow developed to run the study ...... 44

4.1 Setup for the FAA test 1 procedure at the NIAR facility...... 46

4.2 Inputs for the FAA Test 1 simulation...... 47

4.3 Conﬁguration of the test conducted by D. Y. Hu, Yang, and M. H. Hu (2009) . . . . 48

4.4 Comparison between kinematics obtained from the simulation and test presented by D. Y. Hu, Yang, and M. H. Hu (2009)...... 49

4.5 Inputs for the drop tower test simulation...... 50

4.6 Comparison of the kinematics between test and simulation ...... 50

4.7 Comparison of results from test and simulation ...... 51

4.8 Characteristic curves used for the model in D. Y. Hu, Yang, and M. H. Hu (2009) . 53

4.9 Kinematic frames comparison. Adapted from D. Y. Hu, Yang, and M. H. Hu (2009) 54

4.10 Response and evaluation of the head acceleration results ...... 56

4.11 Response and evaluation of the chest acceleration results ...... 56

4.12 Response and evaluation of the lumbar load results ...... 57

4.13 Structural behavior results ...... 57

5.1 Identiﬁcation of error and invalid designs from the analysis for study I ...... 59

5.2 Distribution and correlation matrix of the results for study I...... 60

5.3 Lumbar load distribution by energy level for study I...... 62

5.4 Feasible designs for study I...... 62

5.5 Typical kinematics for the three energy levels for study I ...... 63

xiii LIST OF FIGURES (continued)

Figure Page 5.6 ATD response for the three injury levels for study I ...... 65

5.7 Comparison of the sensitivity analysis for the different energy levels for study I . . 66

5.8 Design relationship visualization through the parallel coordinates plot ...... 67

5.9 Identiﬁcation of data clusters for the velocity of 15 ft/s for study I ...... 67

5.10 Identiﬁcation of data clusters for study I...... 68

5.11 Identiﬁcation of error designs from the analysis for study II...... 69

5.12 Distribution and correlation matrix of the results for study II ...... 70

5.13 Lumbar load distribution by energy level for study II ...... 71

5.14 Feasible designs for study II ...... 71

5.15 Typical kinematics for the three energy levels for study II...... 72

5.16 ATD response for the three injury levels for study II...... 73

5.17 Structural energy absorption ...... 75

5.18 Analysis of the energy absorption contribution by system...... 75

xiv LIST OF ABBREVIATIONS

AGARD Advisory Group for Aerospace Research and Development ATD Anthropomorphic Test Device CAMI Civil Aeromedical Institute CG Center of Gravity DOE Design of Experiments DRI Dynamic Response Index EASA European Aviation Safety Agency eVTOL electrical Vertical Take-Off and Landing FAA Federal Aviation Administration MTOW Maximum Take-Off Weight NASA National Aeronautics and Space Administration UAM Urban Air Mobility ULH Uniform Latin Hypercube VTOL Vertical Take-Off and Landing

xv CHAPTER 1

INTRODUCTION

1.1 Background

During the last century, the way people move has changed dramatically manifold. At the pace the world gets ever more connected has led to the demand for faster, safer, and more reliable means of transportation. The dawn of aviation brought along the vision to reach the corners of the world in a matter of hours rather than days. Today, however, the fast-paced growth of urbanized society has been making the local commute an unexpected everyday challenge since metropolitan conurbation and traffic management limits have been bringing traffic congestion to unprecedented levels. In 2016 Uber published a white paper (Holden and Goel, 2016) proposing an innovative take on urban mobility, where on-demand air transportation would be available to improve the commute on short distances such as in intra or inter-city travel. The revolutionary concept would have the capability to connect locations that today take a few hours to be reached in just a matter of minutes, exemplified in Figure 1.1. To achieve that, emerging and novel technologies need to be fast developed, especially when considering the aeronautical industry, which is known by the slow-paced regulatory framework. The envisioned shift in urban transportation would be enabled by the so-called Verti- cal Take-Off and Landing (VTOL) aircraft, but mostly by the electrically propelled versions of such, commonly referred to as electrical Vertical Take-Off and Landing (eVTOL). In spite of fossil-fueled engines, the usage of electric propulsion can provide several benefits, including reduced noise and CO2 emissions, simplified power transmission, distributed propulsion, improved reliability, and reduced cost of maintenance. Since the Uber white paper’s release, several companies have started developing concepts and prototypes as they share the vision for the potential market to be explored. This emerging opportunity has brought to the industry a diversity of startups that, on another occasion, would not challenge the major duopoly domination observed in the jet passenger aircraft

1 Figure 1.1: Potential impacts of the Uber on-demand air transportation. Adapted from Holden and Goel (2016) market. These new dynamic entrants have been pushing the status quo by unveiling their un- conventional designs and approaches to the Urban Air Mobility (UAM) stage. Just like in a cartoon, the innovative aircraft designs seen in Figure 1.2 mesmerizes even the most experienced engineers in the field as such diversity in the concepts can be easily spotted. Unlike in fiction, however, to be able to fly in our skies, any aircraft is required to undertake a rigorous certification process to be approved by the airworthiness regulators, which have the job to guarantee that a minimum level of safety is achieved. Notably a long, costly, and laborious process, the certification pathway is currently a significant roadblock even in the traditional aeronautical industry. Therefore, it is a matter of great concern when considering that an applicable regulation for these newly born concepts is simply nonexistent. Currently, the available airworthiness regulations are separated between fixed-wing and rotorcraft designs. The concept of eVTOLs brings a mix of those two, but with a number of other aspects that none of these regulations cover, like the existence of an electric-based propulsion system, the in-flight transition phases required by some of the proposed designs, and the issues with battery ignited fires in post-crash conditions.

2 Figure 1.2: Companies unveil their concepts for the UAM market (Uber Technologies, 2020)

In 2018 the European Aviation Safety Agency (EASA) first released a proposed special condition for means of compliance addressing some of the new requirements for the certification process for VTOL aircraft (EASA, 2018). A new version of this document has been published in May of 2020, but work is still in progress, and numerous issues are yet to be handled in terms of the chosen pathway to airworthiness certification. One of them regards the requirements found under 14 CFR*.561 and *.562, which describe the directives for certification related to emergency landing conditions, where new failure modes derived from the operation of VTOL aircraft are not covered (Federal Aviation Administration, 2016a,b,c,d). Aiming to serve urban areas, eVTOL aircrafts are envisioned to use small spaces with no runaway area for take-off and landing operations. Top areas of skyscrapers and parking lots can be adapted for this use, or a dedicated vertiport infrastructure can be built. With such restricted space and surrounded by buildings, these aircraft need to be capable of taking-off and landing vertically, but unlike helicopters, most concepts use an in-flight transition phase to position the propellers for horizontal flight during the cruise phase, as exemplified in Figure 1.3. According to Airbus (2020), over 60% of aircraft accidents occur during the take-off or landing phases. In addition to that, according to Boyd (2017), 94% of civil aviation fatalities are derived from accidents that occurred with general aviation aircraft, which accounts for the lightweight fixed-wing aircraft category. Since most eVTOL concepts can be considered to fall

3 Figure 1.3: Typical urban air transportation mission. Adapted from Grandl et al. (2018) under the light aircraft definition, the challenges to achieve minimum levels of safety can be similarly considered. The additional fact that their operation is intended to fly over cities at low altitude raises additional concern to its safety aspects, being a strong reason to pursue further understanding of the possible critical issues before that happens through experience. Currently, the established regulations for emergency landing conditions do not address any critical condition where the aircraft reaches impact with zero or negligible horizontal velocity when compared to the vertical component. The current requirements came to be as fixed- wing aircraft can glide, while rotorcraft are able to use autorotation to transform the vertical velocity into horizontal velocity, which is not a given for the case of eVTOL aircraft as the regulations are not yet established for this specific case. However, the typical mission for urban air transportation will require that both take-off and landing operations occur nearly vertical since the proximity to surrounding buildings will not allow the space for gliding or autorotation. Another aspect that the current regulations lack attention regards the sole evaluation of the seat and restraint systems for the occupant dynamic response. This means that the combined effects of the structures underneath the occupant, as the landing gear/skid and subfloor structure of the aircraft, are completely disregarded for the injury analysis, unlike what’s seen in Figure 1.4. That is especially important when considering small aircraft that do not have a cargo area beneath the passenger cabin, which could dissipate a significant amount of energy from an emergency landing scenario (Kindervater, 1997). Additionally, the use of composite

4 materials, which has increasingly been adopted for aircraft construction, does not deform as much as metals without the design of failure mechanisms, signiﬁcantly reducing the energy- absorbing capabilities of the structure.

Figure 1.4: Interaction of the aircraft structures during an impact event (Littell, 2019)

Considering these factors, Gerardo Olivares, Caralt, and Vina (2019) introduced the concept of integrated occupant safety, where the analysis of occupant injury takes into account the combined effect of the landing system, the subfloor structure, the seat, and the restraint system. This approach can be beneficial to attain a more similar safety level across different aircraft, and it also allows the consideration of different mission and landing conditions since the loading conditions are not necessarily fixed.

1.2 Motivation

Foreseeing changes on the crashworthiness requirements for the certiﬁcation process of aircrafts, this study is aimed at addressing aspects that are impacted by the deployment of eVTOL aircraft and its associated technologies, like electric propulsion, on the minimum safety conditions. With the variety of already existing concepts and prototypes being developed for this market and the fact that no previous data for this type of aircraft is available to base the establishment of new regulations, conducting research that can provide directions for the implementation of safe and ﬂexible requirements is critical at this moment.

5 CHAPTER 2

THEORETICAL BACKGROUND AND LITERATURE REVIEW

2.1 Basics of Injury Biomechanics

Biomechanics is a multidisciplinary subject that uses physics and engineering principles along with knowledge from the biological and medical fields. A biological system, such as the human body, is studied employing concepts from mechanics to understand the effects that forces have on the motion of bodies (Aruin, 2019). Forces acting on living things can create motion, a stimulus for growth or overload tissues, causing injury (Knudson, 2007). For the latter case, a specific branch of biomechanics, called injury biomechanics, studies the mechanisms of injury in traumatic events, such as those seen in athletic sports and automotive accidents. Medical schools teach their students how to diagnose and treat an injury, but in general, they are not qualified to indicate the injury causation (King, 2018). In contrast, the realm of injury biomechanics seeks to predict and prevent the causation of injury using tools and techniques to determine the specific causes of the trauma. To achieve that, the effect of variables such as the injury mechanism, impact surface, rate of impact, and the material properties of the tissue are considered in order to reduce the likelihood of injury and design better countermea- sures to minimize trauma (Franklyn and Lee, 2017). The causation of injury in a crash event can be classified as a traumatic injury or an environmental injury. The latter is caused by factors specific to the location and conditions of a crash, where fire is the most dangerous hazard. The traumatic injury can be further separated as caused by inertial forces, or contact forces (Shanahan, 1993). An injury caused by inertial forces is derived from the rapid deceleration of the vehicle, which is transmitted to the occupant, and can be fatal depending on the duration and magnitude of the acceleration experienced by the passenger. Injuries originated from contact forces occur on the occasion of relative movement between the occupant and a contacting surface. This type of injury is often more critical when compared to those caused by inertial forces; thus its sought to be avoided as much as possible, whereas the inertial forces are intrinsic from the crash event and can only be minimized.

6 2.1.1 Vertical Loads

One of the great contributors that led to the research in injury biomechanics was Col. John Paul Stapp, who volunteered to ride a rocket-driven sled in order to test the effects of wind blast when a pilot ejects from a disabled aircraft (King, 2018). On such an event, the rapid vertical acceleration of the seat produces high loads that need to be endured by the vertebral column, potentially causing injuries to the vertebrae or the spinal cord. Similar to the case of ejection seats, the event of a helicopter crash also presents a great distribution of spinal injuries as often, the rotorcraft quickly loses vertical altitude. As seen in Figure 2.1, the vertebral column can be divided into three regions, which are the cervical (C), thoracic (T), and lumbar (L) spine. The vertebrae are the main structures that protect the spinal cord and the major load-bearing part of the human body. The lumbar vertebrae are the ones that are subject to the greater loads from the body; for such reason, they are bigger than the other ones.

Figure 2.1: Anatomy of the hu- Figure 2.2: Spinal injuries for military causalities man spinal cord (Netter, 1989) (Franklyn and Lee, 2017)

The head and the spinal cord of the human body are considered the most critical body parts when accounting for the consequences of getting them injured. This is due mainly to the irreversible nature a damaged central nervous system presents after injured (Lankarani, 2018b). In the case of vertical loading, the spinal column becomes the most susceptible body part of getting injured, being spinal fracture the type of injury commonly seen for impact loads. Taking

7 into account the casualties during military operations, the distribution of spinal injuries along the vertebrae for such environment can be seen in Figure 2.2, where 90 incidents occurred as the result of helicopter crashes. From these 90 recorded traumatic events, over 61% of the fractures happened between T12 and L4 (Franklyn and Lee, 2017). In an effort to quantify the tolerance of the human body to injury, Martin Eiband from the National Aeronautics and Space Administration (NASA) developed the Eiband curve (Eiband, 1959) from data derived from experiments conducted during World War II. This curve presents the limits for whole-body tolerance for different directions when a trapezoidal-shaped pulse is applied from a seat, or a platform (Franklyn and Lee, 2017). In Figure 2.3 the whole- body tolerance is shown for all in-plane directions considering the amount of time exposed to accelerations given in g’s. The longer the body is exposed to continuous loading, the more it is susceptible to limitations due to blood circulation, while in cases of loading in a short duration, the mechanisms of injury will vary depending on the direction and intensity of loading.

Figure 2.3: Tolerance envelope for acceleration exposure in different directions (Norton et al., 2004; Sanders and McCormick, 1987)

When a vehicle crashes against a rigid structure, it decelerates very quickly as the ob- stacle brings the vehicle to a stop. At the same time, the occupant continues to move as its body has momentum, which creates the opportunity for a blunt contact that can lead to severe or lethal injury (Caldwell et al., 2012). In order to prevent or reduce occupant injury in a crash

8 event, restraint systems such as seat belts and airbags are added to the vehicle. The restraint conﬁguration commonly employed on helicopter seats can be seen in Figure 2.4; it is composed of a lap belt and one or two shoulder straps that together keep the occupant on the seat in a vertical position.

Figure 2.4: Seat restraint conﬁgurations with lap belt and shoulder harness (Chandler, 1993)

In a vertical impact, an unrestrained occupant tends to move away from the seat during the drop phase, creating a gap between the seat and the occupant that can amplify the impact loads due to the subsequent contact with the seat. For this reason, one of the mechanisms used in ejection seats is the tightening of the seat harness right before it is deployed, reducing any gap between the pilot and the seat. Additionally, the shoulder harness has a crucial role in reducing the probability of injury, which is to maintain the occupant in a vertical position. This guarantees that the vertebral column is aligned with the loads, avoiding additional moment loads and/or the transmission of the load to more fragile body parts.

2.1.2 Injury Criteria and Regulations

The understanding and correlation of the injury mechanisms with experimental tests led to a number of studies that sought to quantify injury levels and their relationship with external factors. The work developed by researchers like Ruff (Ruff, 1950) and Eiband (Eiband, 1959) resulted in tolerance curves correlating the uniform acceleration of the vehicle with the exposure time to that load, as seen in Figure 2.5. One of the approaches taken to model the vertical load impact is based on considering the mass of the upper torso and the response by the spine as a mass, spring, and damper system.

9 Figure 2.5: Eiband curve demonstrating the limits for which ejection seats are designed (Franklyn and Lee, 2017)

Based on the cadaveric data presented by Ruff (1950); Stech and Payne (1969) and Brinkley and Shaffer (1971) obtained structural properties that represent the human body for such system. This model resulted in a dimensionless parameter that today is known as the Dynamic Response Index (DRI), which is given by the Equation 2.1.

δ δ DRI = dyn = dyn (2.1) δstatic 3.5 where δdyn is the total compression in the spine during a dynamic event and δstatic is the compression in the spine due to gravity (3.5 mm). The DRI is a parameter that describes the ratio between the dynamic and the static compression of the spine (Franklyn and Lee, 2017). This criterion was used by the US Air Force to estimate the probability of compression fractures in the lower spine due to vertical acceleration caused by a seat ejection or crash landing of a helicopter (Pilkey, Balandin, and Bolotnik, 2009). Later, the Advisory Group for Aerospace Research and Development (AGARD) adopted the values found in Table 2.1 to evaluate the potential of injury based on the DRI value. In an attempt to use the DRI index to assess the potential of injury in civil aircraft, the Civil Aeromedical Institute (CAMI) found the use of the DRI model problematic. In such a

10 Table 2.1: DRI values and probability of spinal injury included in Landolt et al. (1996)

DRI Risk of Spinal Injury Probability of Injury 15.2 Low 0.5% 18.0 Medium 5% 22.8 High 50% case, the ﬂexible lightweight seat structure found in small airplanes, compared to the rigid military seats, proved to be challenging to consistently measure a single-seat acceleration (Chan- dler, 1985). For this reason, CAMI conducted 12 tests with a Hybrid II Anthropomorphic Test Device (ATD) to measure the lumbar compression to correlate it with the DRI. As seen in Figure 2.7, the DRI of 19 was chosen to indicate human tolerance to vertical load, which corresponds to a lumbar compression of 1500 lbs (6.67 kN). This criterion was then added by the Federal Aviation Administration (FAA) in 1988 and is still currently used. The standard for commercial, civil aircraft FAA 25.562: Emergency Landing Dynamic Conditions for the Cer- tiﬁcation of Airline Passenger Seats, states that the maximum compression between the pelvis and lumbar spine should be less than 1500 lbs (6.67 kN) with an ATD weighing 77 kg, seated in the normal upright position (Federal Aviation Administration, 2016b).

Figure 2.6: Hydryd II Figure 2.7: Correlation between the DRI and lumbar load (Chan- ATD used on CAMI tests dler, 1985)

With the intent to obtain repetitive and consistent test results, mechanical surrogates of the human body are used as the occupants on safety tests. These human surrogates were designed based on requirements for bioﬁdelity, anthropometry, sensitivity, cost, and others (Lankarani, 2018b). Equipped with a number of transducers that can measure acceleration,

11 velocity, and loads, the ATDs provide data that can then be correlated with the injury criteria to identify if the condition presents the potential of injury. The ATD Hybrid II was developed by General Motors in 1972 and has been since the most widely employed human surrogate for the assessment of injury in frontal impact (Nahum and Melvin, 2012). Not long after, an updated version, the Hybrid III was developed to improve bioﬁdelity and provide even more measurements with the instrumentation that was added. However, the FAA later modiﬁed the Hybrid III dummy, as this one has a curved lumbar for a version using some Hybrid II parts to obtain an erect spine, which allows for better prediction of the compressive lumbar loads for aircraft seats (Franklyn and Lee, 2017). A representation of the differences between these two Hybrid III versions is presented in Figure 2.8.

Figure 2.8: Differences between the Hybrid III and the FAA Hybrid III ATDs (D. Y. Hu, Yang, and M. H. Hu, 2009) To account for the different sizes and types of aircraft, the FAA has created subdivisions on the certification documentation, separating fixed-wing aircraft from rotorcraft and civil transport from small private aircraft. Each type of certification has its own set of rules that address the size, flight conditions, and construction differences with the objective to obtain similar levels of safety across the categories. According to section 562 of each certification type, the passenger seats must undergo two separate dynamic test conditions to have their safety evaluated. These are the Emergency Landing Dynamic Conditions, which vary in terms of test specification, as seen in Table 2.2. The two test setups have different orientations, as shown in Figure 2.9, where one has only horizontal velocity, and the other has a combination of horizontal and vertical velocity due to the seat angle of 60◦ with respect to the direction of motion.

12 Table 2.2: Requirements for emergency landing dynamic test conditions (Federal Aviation Administration, 2016a,b,c,d)

Dynamic Test Requirements Part 23 Part 25 Part 27/29 Test 1 Test Velocity [ft/s] 31 (9.5 m/s) 35 (10.7 m/s) 30 (9.2 m/s) Seat Pitch Angle [deg] 60 60 60 Seat Yaw Angle [deg] 0 0 0 Peak Deceleration [g] 19/15 14 30 Time to Peak [s] 0.05/0.06 0.08 0.031 Floor Deformation [deg] 0 0 10 Pitch/10 Roll Test 2 Test Velocity [ft/s] 42 (12.8 m/s) 44 (13.4 m/s) 42 (12.8 m/s) Seat Pitch Angle [deg] 0 0 0 Seat Yaw Angle [deg] ± 10 ± 10 ± 10 Peak Deceleration [g] 26/21 16 18.4 Time to Peak [s] 0.05/0.06 0.09 0.071 Floor Deformation [deg] 10 Pitch/10 Roll 10 Pitch/10 Roll 10 Pitch/10 Roll

Figure 2.9: Representation of the tests 1 and 2 required by the airworthiness regulations

2.2 Principles of Crash Dynamics

2.2.1 Vibration Analysis and Multibody Dynamics

The simplest form to describe a structural dampened dynamic system is to consider a free single degree of freedom mass-spring-damper system, as seen in Figure 2.10a. Its equation of motion is described by Equation 2.2, which gives two solutions, where one describes the vibration of an undampened system (for c = 0) and the second represents the dampened system characteristic (for c > 0). For the dampened solution, three distinct responses can be obtained depending on the system damping ratio, as deﬁned in Equation 2.4 and Equation 2.5 and exempliﬁed in Figure 2.10b. r k ω = (2.3) mx¨ + cx˙ + kx = 0 (2.2) n m

13 √ c p 2 ζ = (2.4) ccr = 2 km (2.5) ωd = 1 − ζ ωn (2.6) ccr

(a) Single degree of freedom dampened dynamic (b) Response in time for different types of damping (Singiresu et al., system 1995)

Figure 2.10: Representation and response for a single degree of freedom dampened system

Although simple, this single degree of freedom model is often used in diverse applications since any structural system can be represented by an equivalent mass-spring-damper system for some degree of accuracy. For systems with higher complexity, its smaller constituent parts can be represented by independent mass-spring-damper systems that interact between them to form a multi-degree of freedom system, as presented in Figure 2.11.

Figure 2.11: Mathematical modeling of dynamic systems. Adapted from Singiresu et al. (1995)

The presented approach for the analysis of dynamic systems is well suited for planar problems, but when spatial motion is necessary to be considered, a modeling methodology employing multibody dynamics is more appropriate (Lankarani, 2018a). In a multibody system, rigid and ﬂexible bodies interact by the deﬁnition of kinematic joints and force elements, as

14 presented in Figure 2.12a (Ambrosio, 2001). Due to its low computational cost, the usage of multibody dynamics is preferred over ﬁnite element models for a wide range of applications, like vehicle dynamics, human motion analysis, and design of occupant protection systems.

(b) Multibody model of a crash dummy with a hybrid belt sys- (a) Representation of a generic multibody system (Ambrosio, tem (TASS International Software, 2001) 2017)

Figure 2.12: Examples of multibody models

2.2.2 Factors for Crash Survivability

Crashworthiness can be deﬁned as the ability of a vehicle and its internal systems and components to protect occupants from injury in the event of a crash (Shanahan, 1993). In order to understand the crash event to maximize the probabilities of survival, aspects regarding the vehicle construction, design of safety systems, and the crash environment have to be taken into consideration. According to Shanahan (1993), the basic principles for crashworthiness can be simpliﬁed to the following aspects:

• Container

• Restraint

• Energy absorption

• Environment (local)

• Postcrash factors

15 The interior of the airframe where the passengers can occupy is the container of the aircraft. In the event of a crash, this container must preserve a survivable volume, which means that the structure does not deform in a way to directly cause injury to the passengers or block any emergency exit. Additionally, a survivable volume also considers that the passengers have an unblocked path to an emergency exit, and no large masses get displaced in a manner that could cause injury to the occupants (Federal Aviation Administration, 2016a,b,c,d). The confined area of the interior of the aircraft makes it very susceptible that an occupant impacts the nearby seats or surrounding monuments, especially if unrestrained. For such reason, the usage of restraint systems is required and verified before any aircraft is certi- fied to fly. Not only the passenger has to be properly restrained, but also the attachments of the seats and surrounding monuments have to be capable of withstanding considerable deformation without breaking loose. As an aircraft comes to impact with the ground, all of its kinetic energy is then dissipated during the crash event. When considering passenger safety, the aircraft systems need to be designed in a way that the least energy possible is transferred to passengers in order to maximize survivability. On events with predominant vertical velocity component, the modes of energy dissipation are even reduced, as the airframe won’t slide over the ground, making it even more critical that energy absorption systems are integrated into the aircraft. The usage of restraint systems can considerably reduce the probability of blunt impact by the occupant, but many times the existence of surrounding structures is necessary, as the instruments for pilots. In these cases, the local environment of the occupant must be designed to be less hazardous, which can be done by avoiding pointy objects or adding some padding. For passengers, usually items can be removed from a striking distance, which is the best option. Even if the occupants survive the crash, there is a chance that postcrash factors cause fatalities in the event. The occurrence of fire or drowning, in the case of a water landing, is considerable, especially for rotorcraft. The addition of flotation devices or distant positioning of electrical and fuel systems are measures that can be taken to minimize these postcrash effects. Regarding the conditions at which a crash landing can happen, the impact velocity is one of the major factors that determine the extent of injury given a certain condition. The kinetic

16 energy of an aircraft at impact is proportional to the square of the velocity, which means that a small increase in the impact velocity can result in the change of injury severity from minor to severe and finally fatal. Addressing that concern, in 1985 Coltman, Bolukbasi, and Laananen (1985) published the compilation of aircraft accidents where the cumulative frequency distribution of the impact velocity for survivable accidents was reported, as seen in Figure 2.13. As noted in the figure, it is based on this data that the impact test velocities on the certification requirements for emergency landing conditions were defined.

Figure 2.13: Cumulative frequency distribution of the impact velocity for survivable aircraft accidents. Adapted from Coltman, Bolukbasi, and Laananen (1985)

As exempliﬁed in Figure 2.14, the type of aircraft can also highly change the probability of injury in an accident. For a civil transport aircraft, for example, the lower half of the fuselage structure is used for luggage and equipment storage, which signiﬁcantly helps on the energy dissipation during the impact event (Kindervater, 1997). Furthermore, the relative distance from the passengers to the ground at the moment of impact guarantees that during the time of structural deformation, the loads are more effectively distributed, lowering the forces experienced by the occupants. For smaller aircraft that do not have such a large area beneath the passenger cabin, the distance from the passengers to the ground is much smaller, hindering the energy dissipation capabilities offered by the deformation of the structure. In such cases, the seat becomes a major

17 Figure 2.14: Typical response of different aircraft types to a vertical crash landing. Adapted from Kindervater (1997) factor in providing the energy absorption necessary to keep the loads under injurious limits. To achieve that, carefully designed failure mechanisms are designed to trigger at a certain load level, as presented in Figure 2.15, so no additional forces are transmitted to the passenger. Additionally, these energy-absorbing seats are capable of holding that triggering load level for a large amount of deformation, which is an effective way to use the deformation of the seat to dissipate the impact energy.

Figure 2.15: Failure mechanisms designed in energy absorbing seats for occupant injury mitigation (Desjardins, 2006)

18 2.3 Literature Review

The novelty of the eVTOL concept hasn’t yet allowed time for the publication of studies specific to its crashworthiness. Still, a few relevant publications touching on that topic have been released just in the past months. On the other hand, the research regarding general occupant safety in the automotive and aeronautical industries has been producing knowledge that directly contributes to the level of safety found in the current means of transportation. Com- bining the lessons learned from years of developments around occupant safety with the trends being presented by recent studies on the specific area of eVTOL safety are the key elements to keep pushing the boundaries of scientific discoveries and engineering innovation. It has not been that long ago that engineers designing safety systems relied majorly on scarce published test results and limited historical data to base their design decisions on. At that time, publications like the work developed by Shanahan (1993) and Harris, Kasper, and Iseler (2000) were instrumental in this process. But with the increased availability of computational tools, the reliance on such hard data decreased, and test-based simulation models started to allow the investigation of factors that previously would not be financially or even physically possible to execute. Following that, a sharp increase in the number of publications in the area of occupant safety has been seen, where studies by Kumakura, Minegishi, and Iwasaki (2000), Lankarani, G. Olivares, and Nagarajan (2003), Fuchs and Jackson (2008), Annett (2010) and Murugan, Yoo, and G. Hiemenz (2014) emerged. Since the publication of Holden and Goel (2016), a variety of market research and technical feasibility studies have been conducted. Grandl et al. (2018) and Goyal (2019) detail a comprehensive study on the market potential for the production and operation of eVTOL aircraft, while Silva et al. (2018) and Johnson, Silva, and Solis (2018) discussed the gap, the current technologies need to overcome to enable the feasibility of the envisioned concept and the characteristics of the likely types of aircraft that can arise from that. Considering the disruption in the aeronautical industry that the implementation of technologies originated from the UAM aspect, Connors (2020) devoted special attention to address the risks linked to the numerous aspects that need to be addressed before any eVTOL aircraft

19 Figure 2.16: Technical evaluation of different eVTOL concept vehicles (Johnson, Silva, and Solis, 2018) takes off. Important considerations were raised regarding the needs for a suitable air traffic management platform, implementation of infrastructure that is capable of serving such operations, and the need for the establishment of airworthiness regulations that can properly address the novel aspects in operation and functionality of such vehicles. Seeking to understand the public perception on the adoption of UAM means of transportation, Edwards and Price (2020) researched on the aspects that are concerning the potential passengers, and the safety aspects of it are presented to be critical for public adoption. Ad- dressing the safety aspect in terms of the occupant protection on emergency landing conditions, Littell (2019) outlines the challenges and possible alternatives related to the development of structures that allow the energy dissipation from the crash event with the aim to improve passenger safety. And finally, Putnam and Littell (2019) undertook the evaluation of a concept vehicle using a finite element model to assess the reduction in occupant injury by employing composite material based energy attenuators, which is presented in Figure 2.17.

20 (a) FE model of eVTOL concept vehicle (b) FE simulation results for different designs

Figure 2.17: Model and simulation results reported in Putnam and Littell (2019)

The present study aimed to add to the scientific community by enlarging the knowledge on the topics the mentioned studies tackled partially or in full. More specifically, if considered the work developed by Putnam and Littell (2019), the present study sought to tackle similar concerns regarding the development of structural systems capable of sustaining low levels of occupant injury even on critical conditions. Taking a more conceptual and general approach, the study here reported differs from the previous fundamentally by enabling the investigation of a larger set of different structural aspects using a simplified model to achieve that.

21 CHAPTER 3

METHODOLOGY

3.1 General Research Methodology

The starting point of this study has been based on identifying the main research goals to be pursued considering the existing research gaps in the literature and the execution steps required to develop a study that is able to achieve that. With the objectives defined, the methodology to investigate the main research points is presented. The next phase focused on developing and validating the multibody model to be used in the principal study by using previous research and experimental tests to obtain a representative model of the phenomena of interest. Once this phase is completed, a parametric study aiming to address the research questions has been conducted, followed by the analysis of the obtained results. In Figure 3.1 the unfolding of these steps is summarized with a flowchart. During the model development and validation phase, two steps with increasing complexity are considered. First, a simple FAA Test 1 procedure model is produced, and its results are compared with test data to ensure proper similarity. Next, a published study reporting a vertical drop test and simulation is used as a reference to model the event and assess the similarity of the produced model, which is intended to describe the occupant injury in the event of a vertical impact scenario. These two steps are taken with the intent to obtain a simplified yet predictive tool to investigate the proposed hypothesis. With the validation steps completed, a model to describe the specific case of interest is produced. Two separate case studies are then evaluated, where the first makes use of a linear stiffness behavior to characterize the stiffness of the structural components, while the second takes into account the failure of the structural systems by using a non-linear stiffness curve. Once more, a two step process with increasing complexity is employed so that the analysis of the simpler case can yield a further understanding of the more complex case. This study focuses on evaluating preliminary design parameters on passenger injury severity during an emergency landing condition for vertical take-off and landing aircraft. Mak-

22 Figure 3.1: Sequence of the research methodology ing use of a hybrid model composed of lumped mass elements and multibody dynamics, the primary investigation aims to identify the sensitivity and possible best parameters to maximize the chance of survivability of a passenger in the considered scenario. The parameters being analyzed are the mass, stiffness, and damping of the main structural systems contributing to the energy transfer and absorption during the crash event. Based on the vehicle impact dynamics discussion, the emergency landing condition of interest is the vertical drop in level ﬂight on terrain prepared for aircraft landing. In addition to the design variables, three different drop velocities are considered to account for the possibility of different landing scenarios and also the application of methods to reduce the impact velocity, such as parachute or retro-rockets systems.

23 3.2 Objectives

With the intent to broaden the knowledge of the scientiﬁc community, particularly regarding aircraft crashworthiness, this research is aimed at investigating a hypothesis with rele- vance to the current time and state of the art. The main hypothesis to be tested is: ”The occurrence of an emergency landing condition during the take-off or landing phases of a VTOL aircraft, in the context of urban air mobility, is critically injurious when designing an aircraft for the current airworthiness regulations and the applied methods of construction used in the aeronautical industry.”

With such a hypothesis as guidance, the following objectives have been identiﬁed to be achieved by this research:

• To develop and validate a representative model of a VTOL aircraft vertical drop crash;

• To predict and understand the injury levels corresponding to the considered crash scenario for different drop velocities;

• To investigate the need for emergency landing safety systems that reduce the aircraft impact velocity;

• To evaluate the injury mitigation capable of being identiﬁed with the methodology employed in this study;

• To develop a general understanding of the driving structural parameters to serve as a guidance for the design of safety systems in VTOL aircraft;

• To identify the need for an integrated safety design approach to reach minimum levels of safety;

• To assess if the current airworthiness regulations are ﬁtting for certifying safe aircraft for urban VTOL operation.

24 3.3 Modeling Methodology

The automation and speed provided by computational systems have enabled the use of tools in engineering that have changed the way the profession is performed by itself. With the introduction of CAE tools, engineers can focus more heavily on the application rather than the method of the numerical solution to be employed. For such reasons and to aid the development of this study, a few engineering software were used to solve different aspects of the problem, manage and integrate automatized processes, and reduce and prepare the results. MADYMO is a software developed by the Netherlands Organization for Applied Scien- tific Research (TNO) and today is owned and distributed by Siemens Software. MAthematical DYnamic MOdelling (MADYMO) provides numerical solvers, dummies, and human models that are used to solve problems in crash engineering applications (TASS International Software, 2017). Being a tool capable of dealing with multibody mechanics and finite element models, MADYMO is a versatile tool widely used on occupant protection problems in the automotive and aerospace industries. The library of dummies and human models that comes with MADYMO includes various models that represent the actual dummies used for crash testing. The dummy models available are either modeled using ellipsoids or facets. The models are calibrated and validated to behave just as their physical twin, providing readings from the same sensors and load cells. As seen in Figure 3.2, a range of different dummy models are available, which are commonly used for crash test certification in the automotive and aerospace industries. Due to its versatility and availability of validated dummy models, MADYMO has been chosen as the primary CAE tool for evaluating the occupant injury during the studied crash events. Also, its format of input and output files makes it an easy process to integrate with other applications. Moreover, its capabilities enable the improvement or further detailing of the basic model for more complex studies. Both the validation models and the study model have been created and computed using MADYMO. Since a more detailed description of each model shall be provided in the respective chapters, a broader overview of the modeling methodology is presented.

25 Figure 3.2: Crash test dummies available in MADYMO

The essential constituent elements that form the constructed models can be seen in Figure 3.3. The ﬁnite elements are used only to model the occupant seat belt, which is preferred over rigid bodies as the discretization of it by shell elements produces better contact interactions and represents more accurately its physical behavior.

Figure 3.3: Constituent elements of the MADYMO models prepared

On MADYMO, rigid bodies can be represented as planes, cylinders, or ellipsoids. These bodies may interact with other rigid bodies or ﬁnite elements by using kinematic joints and/or contacts. With the use of kinematic joints, mechanical restraints can be further added to model resistive and/or dissipative behavior for the interaction of the bodies in a kinematic joint. One of the restraints available on MADYMO is the Kelvin restraint, a massless element composed of a spring and a damper coupled in parallel that produces forces uni-axially as the attached bodies move relative to its end points. In accordance with what was discussed in subsection 2.1.2, the ATD model used for this study was the male FAA Hybrid III 50th percentile, shown in Figure 3.2. The MADYMO dummy model of this ATD is a representation of such, consisted of 49 ellipsoidal bodies, and

26 including the standard instrumentation, which consists of the sternum deﬂection sensor, the accelerometers on the head, upper torso, lower torso, spine and pelvis, and the load cells on the neck, lumbar spine, femur, and tibia. The validation of the ATD model has been executed under component level tests and full ATD tests by TASS International, as seen in Figure 3.4. Further details of the model deﬁnitions can be found on the MADYMO Model Manual (TASS International Software, 2017).

Figure 3.4: Experimental validation for the chest and the full dummy under vertical loads for the FAA Hybrid III ATD (TASS International Software, 2017)

Throughout this study, two arrangements of seat belts were employed: a two-point lap belt and a four-point with lap belt and shoulder harness connected in a single point, showed in Figure 3.5. The two-point belt has been used only for the FAA test 1 validations, while the other configuration is used in all other cases. The belt straps are modeled using two different types of elements. One-dimensional elements form the belt segments used to connect the seat belt attachment on the structure to the main strap parts. These main straps are created using 2D triangular elements, which are preferred over the 1D elements for better contact interaction. In the four-point belt configuration, an MB ellipsoid is modeled as the belt buckle. The straps of the seat belts are fitted against the dummy using the belt fitting tool native from MADYMO. In addition to that, a pretensioner was created on the belt segments to guarantee that the straps are firmly secured against the dummy with no loose spots. For that, a linear payin curve was added, with maximum payin reaching 10 mm at 10 ms in the simulation. With the joint positioning tool native from MADYMO, the dummy model could be appropriately positioned. The positioning varied depending on the model characteristics, such

27 Figure 3.5: Seat belt arrangements used on the MADYMO models as the seat angle and the seat’s height, but in all cases, the dummy was placed as close as possible to the surrounding surfaces, avoiding any initial penetration. The joints were moved as little as possible from the default position, except for the arms and hands, which were always positioned so the dummy would have its hands laying on its lap. In the MADYMO environment, three types of contacts can be used, which are: (a) MB to MB, (b) MB to FE, and (c) FE to FE. Three groups of contact definitions were set on each of the models, when applicable, and these are: (a) dummy to seat, (b) dummy to floor, and (c) dummy to belt. The first two are MB to MB type, and the third is an MB to FE type. Fol- lowing MADYMO’s recommendations (TASS International Software, 2017), the MB contacts interfacing with a rigid surface were set with the parameters listed in Table 3.1. In addition, the characteristic force type was selected as SLAVE, which means that the contact behavior of the interaction corresponds to the contact characteristics defined on the slave surface. The master and slave groups selected for the MB to MB contacts are presented in Figure 3.6. The contact definitions regarding the seat back, the seat cushion, the floor, and the belt buckle all received a MB to MB configuration. For the belt strap contacts, each main strap had a separate contact with the selected MB surfaces. In the four-point belt configuration, further subdivisions in the contacts were

28 Table 3.1: Parameter values used for the MB to MB contact deﬁnitions

Parameter Value DAMP COEF 600.0 N.s/m FRIC COEF 0.4 BOUNDARY WIDTH 0.002 m

Figure 3.6: MB to MB contact definitions (surfaces in red are master and in blue are slave) defined in order to improve the contact evaluation between the various surrounding surfaces. These MB to FE contact definitions were created with the characteristic force type as MASTER, since the slave surface was defined as belt straps. Different friction coefficients were added for the longitudinal and the transverse direction of the belt straps, with 0.6 for the longitudinal direction and 0.3 for the transverse direction. To provide movement between distinct connected bodies, mechanical joints were employed. The body in the model with no relative movement to the reference was connected with

29 Figure 3.7: MB to FE contact definitions for the left side belt straps (surfaces in red are master and in blue are slave) a joint locked in all degrees of freedom. The bodies with some relative movement with respect to others were connected with a translational joint, which also included a Kelvin restraint when resistive/dissipative behavior was desired. On the other hand, the dummy had interactions only by the contact definitions; no joint was directly attached to the dummy. The Kelvin restraints used on the models of the present study are defined by a constant viscous damping coefficient and a constant stiffness coefficient. When specified, however, a non-linear stiffness behavior is added to the definition in order to represent the effect of the structural failure of the represented component. This is achieved by defining a characteristic curve for the stiffness in which the control points on the curve define the expected failure behavior. Also, no initial strain or initial length to account for slack or pre-tension was added to the applied restraints. For the execution of the simulation, the Euler integration method was chosen to solve the multibody equations of motion. Due to the limitation of the minimum timestep of the ATD model, a time step of 1 × 10−5 s was utilized, with a total run time depending on the case, since the physical phenomena of interest can develop in different time durations. The MADYMO solver from version 7.7 of the software was used for the computations.

30 3.4 Parametric Study

The preliminary design phase of a project is usually a step where a large number of designs are still in consideration. For that reason, using computationally expensive methods to evaluate all of them is often impractical. The choice to be made is to consider only a few potential candidates using the expensive methods or consider a more extensive set of designs by employing a simpliﬁed model for the analysis. Considering the latter approach that this study is based on, mostly because with the methodology applied, it is possible to improve parts or the whole model for more detailed analysis in case necessary.

3.4.1 Deﬁnition of the Model Parameters

As the starting point of most studies, the less complex case is ﬁrst chosen, so a more comprehensive understanding of the problem fundamentals can be developed. With this in mind, the chosen aircraft to be considered for the current study, seen in Figure 3.8, was the single passenger aircraft concept previously presented in section 2.3, which is one of the potential types of aircraft to be used in UAM according to NASA (Johnson, Silva, and Solis, 2018).

Figure 3.8: Representation of the single passenger eVTOL aircraft concept (Johnson, Silva, and Solis, 2018)

This speciﬁc aircraft concept was designed to achieve a range of 50 nautical miles with a cruise speed of 70 knots. With such limited capabilities, this single-occupant vehicle is expected to be piloted or autonomously controlled in intracity routes for quick short-distance trips. The propulsion system consists of four electric engines that are powered by rechargeable batteries, so no fuel or tanks are necessary.

31 A mass distribution analysis was conducted in the referenced concept vehicle study to determine the aircraft feasibility and its ﬂight characteristics. Based on the mission characteristics deﬁned and the payload of 250 lb for one passenger, this analysis yielded the mass distribution by components as presented in Table 3.2.

Table 3.2: Aircraft mass (Johnson, Silva, and Solis, 2018)

Component Mass [lb] Mass [kg] Structure 348 158 Propulsion 385 175 Flight Controls 58 26 Systems 211 96 Total 1002 455

It is inherent to any analysis and even more critical to preliminary design ones that only a number of key aspects of the problem are chosen to be considered at a time. For the matter of crashworthiness, the most important aspects considered in a model are the structure’s response, and ultimately, the occupant level of injury. Therefore, non-structural elements and associated systems are not of concern to this type of analysis and are thus solely interpreted with the characteristics that play a role in the key aspects of interest. Considering the type of aircraft shown in Figure 3.9a, the structural components considered relevant for the intended occupant injury severity analysis were each interpreted as a mass-spring-damper system, as seen in Figure 3.9b. The structural systems chosen for the structural model were: (a) the seat systems, (b) the subfloor structure, and (c) the landing skid. As seen in Figure 3.9b, the seat surfaces are defined as rigid and not considered part of the seat system since these serve the only purpose of distributing the loads between the occupant and the structural systems through contact. Within these three modeled systems of interest, their structural characteristics are described by the mass, the damping, and the stiffness of the overall system. These characteristics are the parameters that define a design and thus are varied during the parametric study to evaluate the occupant injury severity. In total, this sums up to the requirement of 9 variables to define a given design. However, considering the known information about the aircraft mass, the mass of the system will be predefined according to the expected mass for each system. The considered mass distribution for the systems is presented in the Table 3.3.

32 (a) Typical single passenger VTOL aircraft. (b) Simpliﬁed structural model Adapted from Johnson, Silva, and Solis (2018)

Figure 3.9: Interpretation of the structural systems

Table 3.3: Mass distributed for each system

Component Mass [lb] Mass [kg] Seat System 33 15 Subﬂoor System 903 410 Skid System 66 30 Total 1002 455

Of the total 348 lb of structural mass reported on Johnson, Silva, and Solis (2018), 137 lb are considered for the rotor group structure and 108 lb for the fuselage, leaving 103 lb for the remaining of the supporting structures. From this remaining value, a portion of it is considered for the seat structure and another portion for the landing skid structure. A typical aircraft seat generally weighs around 20 lb per passenger but considering a more significant margin for needed energy absorption systems, a value of 33 lb was defined. The landing skid mass for a rotorcraft can vary considerably depending on the Maximum Take-Off Weight (MTOW) of the aircraft and other design requirements, but for the purpose of this study, a total of 66 lb was assigned to the skid system, which is almost 65% of the weight of the supporting structure. All the rest of the aircraft’s structure and systems weight was defined under the subfloor system mass since the inertia effect of those components shall be transferred by this system.

33 An essential part of this study relates to the definition of the input variables bounds, which are the damping and stiffness limits for each system. For significance, the range of the structural parameters investigated has to be realistic when considering the possible range of these characteristics found on typical aircraft structures. Since the specific construction and design features can considerably change the characteristics of a given system, general characteristics are considered to define a possible working range for the variables of interest. To aid in this process, the typical subcomponent structures found in rotorcraft were considered, as seen in Figure 3.10.

Figure 3.10: Typical subcomponent structure found in rotorcraft. Adapted from Bisagni (2002), Farahmand, Ganji, and Sajadi (2019), and G. J. Hiemenz, W. Hu, and Wereley (2008)

The definition of the stiffness limits for the systems considers the structural behavior of a bar in compression to aid in the computation of the estimated limiting range values. Using the axial loading model presented in Figure 3.11, the expression in Equation 3.3 can be used to describe the overall component stiffness by its structural properties given by the component length L, the effective cross-sectional area A and the material stiffness E. Once the limits for each of these characteristics are defined for each one of the structural systems, the stiffness range for the parametric study is set. The expression shown in Equation 3.1 describes the displacement u of a loaded bar, under tension or compression, characterized by the applied force F , the total bar length L, the bar stiffness E and the bar area A. This expression can be rearranged in the form of Equation 3.2, which highlights the form of the linear stiffness K for such a case. Therefore, the linear stiffness for the considered problem can be defined as presented in Equation 3.3.

34 FL u = (3.1) EA

uL F = = Ku (3.2) EA

L K = (3.3) EA Figure 3.11: Axial loading in a structural element In aeronautical structures, the most commonly used materials are aluminum and carbon fiber, but steel or titanium can also be employed in some cases. For this range of materials, the Young’s modulus can vary from 70 GPa for aluminum up to around 250 GPa for high- performance steel alloys or carbon fiber composites. The total vertical length of the structural systems was defined around a broad range since the actual values for the considered concept aircraft are unknown, nevertheless, these values were based from studies like Bisagni (2002), Farahmand, Ganji, and Sajadi (2019), and G. J. Hiemenz, W. Hu, and Wereley (2008), and general research across the internet. However, considering existing rotorcraft, the range of dimensions presented in Table 3.4 can be verified. With respect to the consideration for the effective cross-sectional area, a rough estima- tion of the magnitudes was conducted, taking into account each separate system. For the seat system, a structure based on four legs was considered, which is typical for aeronautical seats. Each leg area was allowed to vary from a leg cross-section of 10x10 mm2 to 20x30 mm2, yield- ing the values seen in Table 3.4. The skid system followed a similar approach, for which the area was allowed to vary between 20x20 mm2 to 60x60 mm2. For the subfloor structure system, an area close to the seat measuring 75x75 cm2 was considered to act as the primary source of structural rigidity from this system. Of this total area, a given percentage range of material was estimated to compose the effective structure cross- section, which ranged from 10% to 25% of the defined region around the occupant seat. The resulting area ranges for each system is seen in Table 3.4 along with the final stiffness range calculated based in Equation 3.3.

35 Table 3.4: Computation of the stiffness ranges for each structural system

Structural L [in] E [GPa] A [m2] K [N/m] System Min Max Min Max Min Max Min Max Seat System 5 15 70 250 4.00E-4 2.4E-3 1.42E+05 1.02E+06 Subﬂoor System 5 20 70 250 5.63E-2 1.41E-1 2.00E+07 4.46E+07 Skid System 15 35 70 250 1.60E-3 1.44E-2 1.90E+05 2.61E+06

The damping of a system is usually described by its damping ratio ζ, as presented in Equation 2.4. For undamped structures, this ratio generally stays below 5%, whereas for cases where damping is of considerable importance, it can reach much higher levels, but with the expense of additional mass. Considering this expected trade-off and the higher level of damping necessary for the systems as a whole, the minimum and maximum limits for the damping ratios of each system is deﬁned as shown in Table 3.5. With the damping ratios and the stiffness of the systems, the range of damping for each system can be computed using Equation 2.5, which is also shown in Table 3.5.

Table 3.5: Computation of the damping ranges for each structural system

Structural Damping Factor [%] Damping [N.s/m] System Min Max Min Max Seat System 5 20 1.46E+02 1.56E+03 Subﬂoor System 1 12 1.85E+03 3.31E+04 Skid System 5 20 1.95E+02 2.89E+03

For the study where the system failure behavior is considered, the failure parameters need to be defined. The strain for each system’s elastic limit was left to be varied since the energy absorption capabilities are well related to this characteristic. The elastic failure was set in the range from 0.01 % to 0.20% for each of the structural systems. On the other hand, the strain limit for the bottoming behavior was defined constant, but differently for each system, since the maximum relative crush distance is expected to be respectively different. The information for the failure parameters is presented in Table 3.6. The total considered simulation time was initially established at 150 ms to match the validation model, but with some test runs it was observed that a simulation time of 100 ms would be enough to capture the first impact peak, this way reducing the total Design of Exper- iments (DOE) running time. The initial conditions applied to the model are also a key part of

36 Table 3.6: Deﬁnition of the failure parameter ranges for each structural system

Structural Elastic Limit Strain [%] Strain Limit System Min Max for Bottoming [%] Seat System 0.01 0.20 50 Subfloor System 0.01 0.20 30 Skid System 0.01 0.20 70 the analysis and its outcomes. The ground to aircraft interface was simplified in such a way that one end of the landing skid is considered to be constrained entirely to the ground. This is considered to be a reasonable simplification since an efficient impacting structure should not present any rebound behavior. The start condition for the simulation represents the moment at which the aircraft touches the ground, initiating the impact event. For this reason, the entirety of the model has an initial velocity, which corresponds to the impact velocity. The specification of the impact velocity for the simulation considered the record of accidents discussed in subsection 2.2.2, which resulted in a baseline velocity of 30 ft/s and two other levels at 15 ft/s and 45 ft/s. The chosen range was adopted to allow for an evaluation of both what is already required by regulations and additional possible extreme cases. The principal metric to be compared along the different designs is the lumbar spine load, which is usually a restricting injury criterion for vertical load cases. The output of this variable provided by MADYMO already applies a filter CFC1000 so no further filtering was utilized to process the outputs. Two essential computational tools selected to aid this analysis were MADYMO and modeFrontier. As seen in the previous sections, MADYMO handles the computation of the multibody model, and the additional steps to those presented in section 3.3 is described in the very next section. To create and manage all the DOE and optimization processes, a workflow on modeFrontier was created. The workflow configuration that permitted this study to be executed is then detailed next.

37 3.4.2 Case Study I: Linear Structural Behavior

With the objective to first understand the overall behavior of the system and the general effect of each factor, a case with linear structural behavior was first studied. Considering a simpler model, where no failure parameters need to be controlled and analyzed, it helps to end up with a more manageable amount of results that can be processed and understood. For this case study, the structural characteristic of each structural system follows the definition seen in Figure 3.12. The stiffness value defined by the DOE for each system is assigned in a characteristic curve as the kspring, and since no failure parameters are defined for this case, no additional characteristics are added to the structural model. The tension and compression characteristics are considered to be equivalent.

Figure 3.12: Deﬁnition of the linear characteristic for each structural system

Since no failure behavior is defined, it is expected that for low stiffness values and high energy impact levels, the relative structural system elongation might surpass 100%, which means that the component deformed a value over its own length, which is not a physical behavior. For this reason, a constraint in the system is defined to consider valid cases only those that do not reach or exceed 100% of relative elongation. As discussed in subsection 2.1.2, according to the existing airworthiness regulations, the maximum allowed lumbar load is 6675 N. Although this is a critical value to be considered, the interest of this first study is to understand the overall response of the systems and their interactions; thus, the designs that result in loads higher than the maximum allowed will not be considered unfeasible or invalid.

38 With those considerations, the input and output variables examined for this case study are defined, as presented in Figure 3.13. Two variables for each system are varied to define the structural design characteristic: damping and stiffness; resulting in 9 input variables. For the outputs, along with the maximum lumbar load experienced by the ATD during the impact event, the elongation of each structural system was recorded to identify the invalid cases and help on the analysis of the results for the identification of trends.

Figure 3.13: Identiﬁcation of the input and output variables for the case study I

Since it is not feasible to show the response of many designs, sample results are presented with the intent to help on the overall analysis and also to provide the reader visual representation of the typical results achieved with the applied methodology. In addition to the presentation of the resulting kinematics, the time history responses for the lumbar load, the head acceleration and the chest acceleration are also reported. Once all the results were gathered, the error and invalid designs were removed so only meaningful results would be part of the analysis. Following, a sensitivity analysis using the ANOVA methodology was conducted, where the driving factors for the response could be iden- tiﬁed. To guarantee that the ANOVA analysis was valid, the R2 ﬁtting factor was checked where only values over 0.7 were accepted.

39 3.4.3 Case Study II: Non-linear Structural Behavior

The deﬁnition of the stiffness characteristic on case study I is known to not accurately represent the physical response of real structure under the loads experienced for the problem considered. This case study II aimed to add a non-linear aspect to represent the plastic failure of the considered structural systems, as presented in Figure 3.14. To achieve that, a parameter

εfailure was added to each of the systems to control the elastic strain limit. After this strain value is reached, the force to deform the structure remains constant up to the point when it reaches εmax, where no additional deformation is allowed, which models the bottoming of the loaded member, when no more deformation is given by the structure.

Figure 3.14: Deﬁnition of the non-linear characteristic for each structural system

With the addition of this new failure parameter, the total number of input variables to define a design increased to 9, as presented in Figure 3.15. The output variables were kept the same, however, in this case the monitoring of the relative elongation of each system is of critical importance in order to understand if a structure exceeded the elastic limit or not in a certain condition. Furthermore, identifying if a system reached the bottoming strain limit can tell if that design didn’t have an efficient configuration for energy absorption, which can lead to higher values in lumbar load. For this study the non-linear definition used for the structure characteristic allows the own system to eliminate the need to invalidate any design for exceeding the component length in deformation. When all evaluations are finished, only a small number of error designs should be expected to be eliminated from the analysis.

40 Figure 3.15: Identiﬁcation of the input and output variables for the case study II

Following the same approach taken on study I to compare a few sample cases, such analysis was also employed for the understanding of this second study. In this case, the addition of input variables naturally modiﬁes the system, but maintaining the values of the variables kept in the model should provide a clear distinction regarding the effects of each considered structural model. Regarding data post-processing, the same methodology employed in study I should be used to analyze this study. Doing so, not only aids the data processing but also allows easier comparison of the different studies.

3.4.4 MADYMO Model of the ATD and eVTOL Aircraft

Based on the methodology described to build the validation models in chapter 4, the parametric study model was defined. A representation of this model can be seen in Figure 3.16a. The components showed for the structural systems do not have any interaction defined in the model; they serve the only purpose of visualization. The kinematic joints that connect these systems presented in Figure 3.16b, are the elements that provide the structural characteristics. These joints allow only the vertical translation movement and have Kelvin restraints defined to provide the desired structural behavior.

41 (a) MADYMO representation of the model (b) Conﬁguration of the kinematic joints

Figure 3.16: Interpretation of the kinematic relationship

The choices made for the model simpliﬁcation along with the limited capacities due to the method of solution employed generate a number of limitations for this analysis that are important to be described. The identiﬁed limitations include:

• The translational kinematic joints deﬁned to connect the structural systems imply that all the load is transmitted unidirectionally and in its entirety along with these systems;

• Since one end of the landing skid is considered to be constrained to the ground, no rebound behavior can be properly considered through this analysis;

• The seat in contact with the ATD does not have any design input parameter to evaluate the effect of different cushion materials;

• There are no hysteresis or speciﬁc unloading curves deﬁned for the structural systems.

3.4.5 DOE Investigation Using modeFrontier

Developed and distributed by ESTECO, modeFrontier is a modular environment capable of providing process automation and optimization in the engineering design process. With a set of DOE and optimization algorithms, modeFrontier is most often used to aid in the design process by reducing the amount of design evaluations and by obtaining the best performing

42 candidate. The facilitated integration of a number of engineering tools, as seen in Figure 3.17, greatly contributes to manage and exchange information between processes.

Figure 3.17: Integration nodes available on modeFrontier

In virtue of its flexibility, many applications develop workflows to deal with multidisciplinary problems, as optimizing for one domain of expertise is not enough to reach the best possible performance overall. The statistical approach towards the input and output variables provides the capability to explore the design space considering variations inherent to the processes while maximizing its reliability. On top of that, the post-processing tools enable the analysis of a significant number of variables at once, helping on the decision making step. In the context of this study, modeFrontier is a key tool used to integrate the design generator, the simulation process, constraint satisfaction, and data management. The whole process regarding the simulation procedures is done on modeFrontier, since choosing the input parameters, defining the search strategy, extracting the outputs, and processing the information. Among the DOE algorithms available on modeFrontier, the case study I used a full factorial DOE approach since the reduced number of variables allowed for a reasonable number of runs to evaluate for a three factor level DOE. For the case study II, the Uniform Latin Hy- percube (ULH) DOE method was chosen to be used. This algorithm produces very efficient DOEs since it seeks to minimize the correlation between inputs while maximizing the distance between the design point to distribute them uniformly across the design space.

43 The basic workflow built on modeFrontier, seen in Figure 3.18, was based around the MADYMO execution node. This node is able to gather all the design inputs, write a new input file, run the MADYMO simulation, and extract the outputs from the formatted output files. For the input parameters, 13 design variable nodes are employed, where 12 control the characteristic of the design, and one controls the initial velocity condition, which is maintained constant along one design evaluation. Among the 12 variables, three define the strain failure for each system, which is kept constant at 1 for cases where failure is not being considered.

Figure 3.18: modeFrontier workﬂow developed to run the study

44 CHAPTER 4

MODEL VALIDATION

4.1 Validation Methodology

The credibility of scientific discoveries is directly tied to the methodologies used in a given study as it seeks to uncover and compare new findings to the related state of the art. Within the methodology employed, validation steps are performed to show accordance with the mathematical and physical behavior of the phenomena considered. According to Schwer (2009), verification is ”the process of determining that a computational model accurately represents the underlying mathematical model and its solution”. On the other hand, Schwer (2009) defines validation as ”the process of determining the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model”. In a simplified manner, it can be said that verification is in the domain of mathematics and validation in the domain of physics. To be able to derive or infer any meaningful conclusions from the results of a model, these steps need first to be executed. As stated by EASA (2020), in the context of complex models, it is often adopted the concept of the building block approach, where increasing levels of detail are used to verify and validate a model. For the present study, two validation processes are undertaken. It has been chosen to not pursue a verification process since the use of widely employed computational tools around the industry gives enough credibility to consider skipping this step. Furthermore, by successfully validating the model, the verification is automatically guaranteed. With the validation processes conducted, the specific physics involved with the intended application was validated in two steps: (a) using a simple model to compare with the standardized FAA Test 1 certification procedure, and (b) a drop test and simulation documented on the publication produced by D. Y. Hu, Yang, and M. H. Hu (2009).

45 4.1.1 FAA Test 1 Validation

In the context of the present study, the data gathered from the ATD model is of great importance for the injury analysis. Thus, it is necessary to guarantee that the ATD model can produce reliable results for the intended application and range of considered conditions. As previously shown in Table 2.2 and in Figure 2.9, the FAA requires that OEMs execute both the dynamic experimental tests for compliance. Since this study is more focused on vertical load events, the FAA Test 1 has been used as the test condition that provides the loading of the ATD lumbar spine, when compared to the FAA Test 2 procedure. The AVET lab from NIAR has generously made available for this validation process the data for one of the Test 1 procedures executed on their dynamic testing facility. Along with the video with the kinematics, data for the head and pelvis’ Center of Gravity (CG) locations and the load from the lumbar spine load cell were provided. As seen in Figure 4.1, no backrest or bottom cushions were installed in this test, and the seat used was a robust steel frame, designed to act as a rigid structure for the range of loads experienced during the test.

Figure 4.1: Setup for the FAA test 1 procedure at the NIAR facility

The MADYMO model used for this validation used the same methodology as described in section 3.3 with additional conﬁgurations that are presented next. In Figure 4.2a is presented the model used for this validation. Figure 4.2b presents the acceleration proﬁle requested by

46 the regulations and the actual acceleration measured from the sled during the test execution. The seat dimensions were added according to the actual rigid seat used on the NIAR sled test. The input acceleration generated by the sled during the test and the material properties of the seat belt were also available to be added to the model definition. As used on the test, the seat belt configuration is a 2-point lap belt fitted around the abdomen of the dummy.

(a) Model for the FAA Test 1 validation (b) Acceleration pulse

Figure 4.2: Inputs for the FAA Test 1 simulation

To compare the results from the test with the simulation, the Sprague and Geers (S&G) method, as described in Sprague and Geers (2003), shall be used. This method computes two measures of error, a phase, and a magnitude error. To ﬁnd the results in an acceptable range of validation, it is expected that the percent relative error to be within a ±10% range of the ideal S&G metrics since the model and test are of simple nature.

4.1.2 Drop Tower Test Validation

The load condition experienced by the ATD on the FAA Test 1 procedure generates some vertical loads on the occupant (considering the ATD local reference). However, there is still a considerable horizontal acceleration component that affects the potential injury mechanisms that arise from such conditions. The main focus of this study considers the emergency landing case where the aircraft is essentially dropped from a height with an initial velocity, and the FAA Test 1 procedure does not represent this condition adequately. Thus an additional validation procedure focused on a pure vertical crash landing was found necessary.

47 In the study published by D. Y. Hu, Yang, and M. H. Hu (2009) a full-scale vertical drop test procedure of a crashworthy helicopter seat was conducted and reported. The conﬁguration of this test can be seen in Figure 4.3. On the actual test, the carriage with the ATD and the seat was dropped from a height of 8.36 m and then stopped by a cylindrical pool ﬁlled with water at the bottom of the tower well.

(a) Schematic diagram of the test facility: 1-release (b) Picture of the actual test conﬁguration hook, 2-rails, 3-carriage, 4-plunger, 5-cylinder pool, (D. Y. Hu, Yang, and M. H. Hu, 2009) 6-seat, 7-ATD. Adapted from D. Y. Hu, Yang, and M. H. Hu (2009)

Figure 4.3: Conﬁguration of the test conducted by D. Y. Hu, Yang, and M. H. Hu (2009)

Along with the test, a model on MADYMO was developed to mimic the results achieved through testing. An approach using simpliﬁed structures was employed on the MADYMO model, where only the energy absorbing tubes present on the seat were deﬁned for the seat structure. In addition to the kinematics seen in Figure 4.4, results for injury metrics from the ATD and also data from sensors on the structure (seen in section 4.3) were used to compare the similarity and accuracy on the prediction of the phenomena by the simulation model. For this validation, a model using the same methodology to be used on the parametric study was employed. The setup can be seen in Figure 4.5, where in Figure 4.5a the validation model is shown and in Figure 4.5b the input acceleration for the model is presented, which is the measured response generated by the carriage impact on the test.

48 Figure 4.4: Comparison between kinematics obtained from the simulation and test presented by D. Y. Hu, Yang, and M. H. Hu (2009)

To validate this model, the results expected must be of close similarity when compared to the results obtained through the simulation documented by D. Y. Hu, Yang, and M. H. Hu (2009). Since the same basic methodology is being used, the behavior is expected to be equivalent. Due to the increased complexity of the physical phenomena being modeled, a more comprehensive range of results shall be accepted, but engineering judgment of the achieved result’s applicability should also play an essential role in the validation decision. To assess the similarity between the reference and the current study, the S&G methodology was employed.

4.2 FAA Test 1 Validation Results

Once the simulation was completed, the results were processed on Altair’s Hyperview, where the kinematics of the simulation and the test could be analyzed together. The resulting analysis is seen in Figure 4.6. The comparison of the kinematic frames shows good agreement of results, being nearly indistinguishable the visual differences between the model and the actual ATD motion from the sled test.

49 (a) Model for the drop test validation (b) Acceleration pulse

Figure 4.5: Inputs for the drop tower test simulation

Figure 4.6: Comparison of the kinematics between test and simulation

The data provided by NIAR for the ATD sensors were recorded at a frequency of 10 kHz, and no data-filtering was applied during the data extraction or the post-processing. The simulation output was set at the same rate of 10 kHz, and the default filter applied by MADYMO was turned off. In Figure 4.7, the results for both the test and the simulation are presented, with the S&G analysis highlighted on the bottom right corner. The attached notes on the plots show the values obtained from the S&G methodology for error quantification (Sprague and Geers, 2003). The results obtained for the head and pelvis accelerations presented values for the S&G metric that satisfy the required values to consider the validation a success. For the lumbar load results, however, an evaluation of the S&G met-

50 Figure 4.7: Comparison of results from test and simulation

51 rics for the entire simulation period presents values that would not be accepted according to the specified validation criteria. Though, when assessing these metrics for the first 150 ms of simulation, which well comprises the behavior of interest, the obtained error metric values are found to satisfy the validation criteria as the combined metric reaches a value of 0.95. These values obtained are considered under the acceptable margin, which signals that the model is in good agreement with the test. In addition to the error comparison method, an analysis of the shape of the curves is often necessary. For that, the overall deviation between the compared results is analyzed and the occurrence of characteristics on the data that are key to describing the phenomena considered. The peaks and valleys of both curves presented on the results comparison match well, considering a small allowable deviation. The deviation seen is considered not to demonstrate a divergence on the expected behavior and thus is considered acceptable. A general look over the shape of the curves presented in Figure 4.7 demonstrates a small deviation along time. Although, the results presented for the lumbar load start to deviate significantly after 150 ms, while the other results do not. The behavior seen due to this dis- parity translates to the fact that the ATD on the test experiences a tension load on his lumbar spine, while the ATD from the model does not. Since this behavior happens after the main loading phase and does not present a magnitude that would lead to erroneous conclusions, that difference was deemed acceptable. With the presentation and comparison of these results, it can be considered that the methodology employed is adequate to generate meaningful and satisfactory outputs. More importantly, the realization that the virtual ATD produces reliable and realistic behavior when loaded with vertical forces gives the confidence to continue the present work with the knowledge to consider its possible limitations.

4.3 Drop Tower Test Validation Results

With the information provided in the study D. Y. Hu, Yang, and M. H. Hu (2009), the multibody model representing the executed test could be built. Along with the carriage measured acceleration, presented in Figure 4.5b, the article also provided curves for the load

52 characteristic of the energy-absorbing elements, the belt material behavior, and the interface contact characteristic between the ATD and the seat cushion. These curves used as input for the model are presented in Figure 4.8.

Figure 4.8: Characteristic curves used for the model in D. Y. Hu, Yang, and M. H. Hu (2009)

Although extensive information about the MADYMO model’s characteristics was reported on the reference study, a few input parameters had to be defined using methods like engineering judgment, indirect estimate using the given information, and trial and error. A few parameters that were defined in such a way were: (a) the precise positioning of the ATD, (b) the correct value for the seat backrest inclination, (c) the distance between the seat and the floor, and (d) the belt position and pretension characteristics. The reference study provided the kinematic frames for both the test and the simulation, allowing the comparison of the developed model with both approaches, which is presented in Figure 4.9. In Figure 4.9a and Figure 4.9b are the comparison between this study’s simulation and the test executed by the reference study. Next, both simulations, this study’s and from reference study, are examined for correlation.

53 (a) Kinematics comparison with test 0-126 ms

(b) Kinematics comparison with test 156-267 ms

Figure 4.9: Kinematic frames comparison. Adapted from D. Y. Hu, Yang, and M. H. Hu (2009)

54 The kinematic frames of the drop test provided by the reference study are not very clear and sharp, but the general position of the ATD can be identified. Considering that, the motion of the ATD from the simulation shows evident similarity with the motion seen on the test. The last kinematic frame, correspondent to 267 ms in time, presents some differences that can be noticed in the simulation from the backward movement of the ATD head and the sliding of the legs. This difference is expected to be caused due to some unidentified difference regarding the ATD position, the belt position, or some other aspect of the belt definition as pretensioners and retractors, which were not reported on the reference study. The visual analysis of the correspondence between the two simulation models shown in Figure 4.9c yields closely matching motion. As seen in comparison with the kinematic frames from the test, the simulation analysis also differs on the last kinematic frame, which in this case, represents time 290 ms. On the results presented for the developed model, the penetration of the ATD with the seat and even with the ground can be observed to be significantly higher than that experienced by the reference simulation. Several approaches to improve this behavior were attempted, but no better result could be achieved, which indicates to be limited due to missing information about the reference model. The quantitative evaluation of the model validity is done by assessing the similarity of the available results, which are related either to injury parameters or to the structure behavior. For the purpose of this study, the outputs regarding injury assessment are of greater importance and thus were sought to show closer agreement in the results. In Figure 4.10, the head acceleration results are presented with the S&G similarity metrics. For the comparison of the results for this validation, since there are two sets of data that can be used to assess response similarity, an S&G evaluation was conducted amongst them all, resulting in the following comparisons:

1. Test reference against simulation reference;

2. Simulation reference against the simulation of the present study;

3. Test reference against the simulation of the present study.

55 Figure 4.10: Response and evaluation of the head acceleration results

The first S&G evaluation is the primary reference, which shows the level of that the reference study was able to achieve. The two other analyses show the correlation of the present study results compared to both the reference data. The results obtained for the head acceleration agree well with both the test and simulation, showing an intermediate response in the significant part of the simulation time. The similarity metrics found to present an excellent quantitative agreement between the developed simulation and the reference data. The analysis for the chest acceleration responses is found in Figure 4.11. The time history plot presents a nearly ideal similarity for the developed model results when considering the first 150 ms of run time. Overall the S&G metrics show the same or better level of error obtained for the reference study than both approaches.

Figure 4.11: Response and evaluation of the chest acceleration results

56 The results and analysis for the single most important response in this study, the lumbar load, is presented in Figure 4.12. By the evaluation of the ﬁrst major peak in the response, it can be noticed that the peak magnitude of the lumbar load for the present study’s model is slightly higher than both of the reference data. Up to the ﬁrst 150 ms point, the visual agreement amongst the curves shows a satisfactory correspondence, and the quantitative analysis presents a similar level of error when compared to the reference study.

Figure 4.12: Response and evaluation of the lumbar load results

In addition to the analyzed injury parameters, the agreement of the results was also being evaluated by comparing the data available for the force in the inversion tubes and the seat stroke. The quantitative curve relationship analysis was not conducted since these responses are not as important as the previously presented results. However, the proximity of the responses for the period of interest corroborates the acceptance of the validation process.

Figure 4.13: Structural behavior results

57 In summary, it can be safely said that the developed simulation model well represents the physical phenomena of interest, and it was able to achieve the same or better level of error when comparing the different employed approaches. Considering that, the developed model can be considered successfully validated for the response prediction of the ﬁrst 150 ms, which comprises the occurrence of the main load transferred to the ATD, being this the most likely period in the crash event to develop the most critical injurious conditions.

58 CHAPTER 5

PARAMETRIC STUDY

5.1 Case Study I: Linear Structural Behavior

Based on a Full Factorial DOE with 7 factors and 3-factor levels, this case study I comprised of a total of 2187 designs that were separated for analysis into three categories for each of the considered impact velocities. The full DOE took a total of 20 hours and 14 minutes to complete, which was run with the parallel processing of 4 designs at a time, using each 2 Intel Xenon 2.30 GHz processors.

5.1.1 Overview

With the results in hands, the valid designs needed to be ﬁltered from invalid and error designs, as described in subsection 3.4.2 and presented in Figure 5.1. From the total of 2187 designs evaluated, a portion corresponding to 22% of the designs was deemed invalid and thus left out of any further analysis. Additionally, 2% of the DOE designs yielded an error during the simulation and could not be completed by the MADYMO solver, being also disregarded since no result was extracted.

Figure 5.1: Identiﬁcation of error and invalid designs from the analysis for study I

A further look into the designs that the solver could not complete and thus resulted in error showed that this outcome was obtained for a couple of reasons. The most frequent root

59 cause for the error was generated due to excessive movement of the ATD joints, which happens when excessive force or acceleration is applied to one or both bodies in a joint, causing the joint to collapse due to exceeded joint limits. Another error case was identiﬁed to be related to the belt anchor points, where the solver would collapse when both the ends of one of the belts’ one-dimensional elements reached the same position, causing a solver singularity. Since the occurrence of these error designs was low and seen only on the higher energy case, where these kinds of issues are more likely to occur, the removal of these designs was considered enough to proceed with the analysis. An overall check of results and trends can be achieved by analyzing a chart like the one seen in Figure 5.2, where the distribution and linear correlation between the variables can be easily seen in a matrix format. For the ease of the reader that might not recognize this visual, on this chart, the diagonal cells show a histogram with the distribution of values according to the frequency of the obtained value for each variable. The upper matrix triangle area shows the distribution of values in an XY plot type, where each variable in the rows and columns are plotted to have their distribution shown. On the lower matrix area, though, the values shown represent the coefﬁcient of linear regression for the relationship of the matching variables, where 0 means no relationship, and 1 or -1 would mean a direct linear correlation.

Figure 5.2: Distribution and correlation matrix of the results for study I

60 To check if the inputs were generated and filtered correctly according to a full factorial DOE, one can look for close to zero correlation between the input variables and sparsely separated values in the scatter plot. Along with that, the diagonal plots should show a clear separation between the number of levels defined for the DOE. In the case of Figure 5.2, the only output plotted corresponds to the last row and column of the matrix, so all the other variables should be completely independent of each other. However, when the correlation factor between the variables K SKID SYS and INIT JNT VEL is noticed, a considerable correlation value is seen. This is due to the fact that from the invalid and error designs filtered, a considerable number of them had an occurrence when both these variables were at their low values (high energy level for the initial velocity), which then favored the distribution to show some correlation falsely. The fact that these two variables had a considerable number of designs removed when found on their lower levels should be taken into account in any case. The row and column relative to the Max Lumbar Load output, the distribution, and relationships between each separate input and this output can be observed. On the correlation part, a value of -0.898 is seen between the INIT JNT VEL and the output, which indicates a strong inverse linear correlation. Ultimately, this means that for higher values of impact velocity (lower energy levels, since for the simulation, the velocities are in the negative direction), the lower the lumbar load will be, which is the expected behavior to see for these two variables. In addition to that, a small correlation is seen for the inputs D SKID SYS and K SKID SYS, which could indicate that the variables related to the skid system have a more significant effect on the lumbar load result, but the correlation values are too small to be able to state that. Next, a closer look at the lumbar load distribution is taken, as seen in Figure 5.3. When categorized by the impact velocity, it is clear to see the results’ distinction depending on this initial condition. From this result, it can be stated that the higher the initial velocity, the higher the mean and standard deviation of the lumbar load will be. For the purpose of later comparison, the lumbar load criteria was considered so that the number of feasible designs obtained from the design evaluations could be examined, as shown in Figure 5.4. Overall, only 40% of all the valid designs could pass the lumbar load criteria; however, these feasible cases were only found for the lower impact energy level.

61 Figure 5.3: Lumbar load distribution by energy level for study I

Figure 5.4: Feasible designs for study I

This overview of results provided a general look into them, which gave some initial insights and the check that the DOE was executed as expected, and the results obtained do not show any concerning anomaly.

5.1.2 Sample Responses

With a large number of designs to be evaluated, the analysis of results is mostly conducted by comparing critical outputs and indicators. However, when possible, a visual and more in-depth investigation of a few cases is always advised since unexpected problems can occur that do not translate into data outliers. Considering that, and also to give the reader a better understanding of the observed behavior, a few sample responses are presented next.

62 Since the main objective of this study I is to successfully run and understand a simple case that can get much more complex, no specific or extreme results were chosen to be presented. The following results are derived from the central value of each input variable for each of the impact velocities, which means that the structural systems being compared are the same, and only the initial condition is varied for this specific analysis. In Figure 5.5, the kinematics of a few timeframes can be visualized. Observe that the visualization was simplified (visual only elements like the aircraft fuselage were removed) to improve the observation of the ATD and structure behavior. Also, take into account that the lower portion of the skid system is directly constrained to the ground, which means that no visual displacement of the skid will be apparent. However, the forces concerning this system are being captured since the relative displacement between systems is the fundamental aspect concerning that computation.

Figure 5.5: Typical kinematics for the three energy levels for study I

The increase in the impact velocity shows an effect right in the ﬁrst kinematic frame compared in Figure 5.5, representing 25 ms in the simulation time. For the same structural system, with the increase in impact velocity, the displacement of the ATD at 25 ms is noticeably increased too, since more energy needs to be dissipated by the structure. Following the next timeframes, it is observed that the structural systems are not capable of dissipating enough energy as the impact velocity is increased, generating greater reaction forces in the ATD, which is then violently expelled from the seat in the condition with greater impact energy, as observed on the last timeframe shown.

63 The behavior of the structure can be observed by accounting for the displacement of the subfloor structure element. Since this system concentrates a more significant amount of mass, the inertial effects play a prominent role, which can be noticed since the displacement between the seat elements and the subfloor can hardly be visualized. The dissimilarity of the structural behavior between the subfloor and seat systems is apparent due to the movement of the legs, which are evidently affected by the relative movement between them, causing an extreme force that can lead to the impact of the legs to the head, as seen on the 45 ft/s kinematics. For the first impact velocity response presented in Figure 5.5, the seat belt is capable of holding the occupant close to a vertical position, which is desirable in such loading conditions. However, for the other cases, there is a clear movement of the ATD torso forwards, bringing its spine to a curved condition, being detrimental to the passenger’s chances of survival. The failure of the seat belt to provide a safer erect position to the ATD can be caused by several reasons, which include the property of the seat belt material, the anchoring and retracting characteristics defined, and the belt pretension load. An important aspect to bring to the reader’s attention is that the apparent excessive penetration of the ATD into the seat and remaining components is caused due to a few aspects. First, the characteristic of the validation model used as a foundation to build this parametric model had the same excessive penetration observed, meaning that by the nature of the model configuration, a certain level of penetration is expected. Besides, since the energy levels are higher in some cases compared to the validated model, an increase in penetration is likely to occur. Lastly, when considered that a cushion component was not defined to serve as a deformable element and the penetration is required to happen due to the multibody contacts’ nature, such visualization effects are bound to occur and thus expected. A few occupant responses are plotted along time to be analyzed, as shown in Figure 5.6. The profile of the responses are very similar, but the peak magnitude and time to peak vary according to the initial impact velocity. The survivable limit of 6675 N, as stated by the airworthiness regulations, is delimited in the lumbar load plot to indicate if a case would pass in this criteria. For the three conditions being analyzed, only the lower impact energy case would not result in the failure of such criteria. As noted in previous results, all the injury responses can

64 be seen to worsen as the impact energy is increased. Especially on the lumbar load plot, it is evident the change in the load time exposure, which as Eiband (1959) described, is an essential factor for the analysis of occupant injury, but a factor disregarded for the lumbar load criteria.

Figure 5.6: ATD response for the three injury levels for study I

On the head acceleration plot for the impact velocity of 45 ft/s, a sudden spike in the acceleration is seen around 56 ms. This rapid increase in head acceleration is caused by the impact of the ATD head against its legs. The monitoring and analysis of such output are not of the direct focus of this study, but this response indicates that such type of impact with the head should be avoided since the load caused by this condition would undoubtedly make the occupant unconscious, if not leading to his death. The chest acceleration response agrees well with the kinematics results since, with the increasing impact energy, the seat belt became less effective, leading to the rotation of the ATD torso. This characteristic is evidenced by the faster rise in acceleration and maintained a level of load along time for higher impact velocities.

65 5.1.3 Sensitivity Analysis and General Trends

The analysis of the factor sensitivity to the response was conducted using the ANOVA method. For each of the energy levels, a separate ANOVA was computed with the objective to possibly identify a shift in factor significance for the different initial conditions. The residuals and R2 coefficient of fit goodness were checked, and all the ANOVA computed yielded a R2 of at least 0.72, which can be considered acceptable to proceed with the analysis. The results of the ANOVA for study I are presented in Figure 5.7.

Figure 5.7: Comparison of the sensitivity analysis for the different energy levels for study I

According to the ANOVA results, the input D SKID SYS presents a significant dominance in the lumbar load response compared to the other factors in any energy levels. At the lowest energy level, though, the K SKID SYS also presents a significant contribution to the lumbar load response, which is not seen for the other energy levels. This is likely the case for the K SKID SYS since many designs for the mid and high energy levels had to be removed, as discussed in subsection 5.1.1. Another relevant trend is the increasing significance of the K SEAT SYS as the impact velocity was increased. In addition, it is noticeable that no variable related to the subfloor system showed relevant significance in any of the energy levels, resulting from the high inertial effect from this system, leading to small energy dissipation regardless of the factor levels.

66 With the employment of the modeFrontier data clustering tool, designs with relative similarity were identified and grouped in order to find other factor relationships. The visualization tool chosen to present this data clustering is the parallel coordinate plot, exemplified in Figure 5.8. On this chart, each horizontal line represents a single design, and each existing vertical axis represents the design space for each variable, which can be filtered independently to highlight regions of interest along with the design space.

Figure 5.8: Design relationship visualization through the parallel coordinates plot

The resulting data clustering for the impact velocity of 15 ft/s is presented in Figure 5.9. This clustering process is entirely unsupervised, which means that the outcomes solely depend on the close similarity of the clustered designs. Even so, a clear distinction between clusters that resulted in higher lumbar loads and lower lumbar loads can be identiﬁed.

Figure 5.9: Identiﬁcation of data clusters for the velocity of 15 ft/s for study I

67 For all three levels of impact velocity, the same clustering process was executed. Similar trends for the clustering of designs with high or low lumbar loads were observed. These results with the highlight of clear trends are presented in Figure 5.10.

(a) Impact velocity: 15 ft/s

(b) Impact velocity: 30 ft/s

68 Overall the trend observed across the data clusters for the different energy levels shows a commonality on the response outcome concerning the variable D SKID SYS, where higher values of skid damping, the lowest values for lumbar loads were found, and vice-versa. This ﬁnding from the clustering process results converges with the outcomes of other discussed analyses and presented data, reinforcing the importance of this parameter. For the impact velocity of 30 ft/s, clusters found on the very low end of the lumbar load results present a tendency for lower stiffness values for both the subﬂoor and the seat systems. That trend was not seen for the other impact velocity cases, however.

5.2 Case Study II: Non-linear Structural Behavior

5.2.1 Overview

From the 7500 designs evaluated, 114 designs could not generate outputs due to errors along with the MADYMO execution, which yielded 98.5% of valid designs, as presented in Figure 5.11. In this case, there are no invalid designs to be considered since the purpose of the previous ﬁltering was intended to remove designs that were identiﬁed to not contribute to the analysis since there was no physical meaning of the results. Looking separately by energy levels, there is a slight increase in the frequency of error designs as the energy is increased, which is an expected outcome.

Figure 5.11: Identiﬁcation of error designs from the analysis for study II

69 The chart shown in Figure 5.12 highlights the distribution of inputs and the relationship with the main output. Unlike seen in Figure 5.2, here, the input distribution is seen continuous and uniform as it is not uniquely evaluated in given parameter levels, with the exception of the initial impact velocity, which is evaluated in three levels. The distribution of designs seen in the input pairs’ scatter plot underlines a good coverage of the design space, and the lack of correlation between the inputs emphasizes the proper generation of points by the ULH algorithm in the sense of selecting sparsely located designs.

Figure 5.12: Distribution and correlation matrix of the results for study II

The only relevant correlation seen for the presented parameters is between the initial velocity and the maximum lumbar load, which is expected. The scatter plots with the output parameter do not show any clear trend, and the correlation factors are equally indeﬁnite. The distribution of results for the lumbar load is similar to that seen for the case study I, but a closer look into it might tell otherwise, as seen next. In Figure 5.13, the frequency of lumbar load results is seen categorized by energy level. For the case study I, this same visualization, presented in Figure 5.3, was able to highlight a greater frequency of results on higher loads for the higher energy designs. However, this is not the case for the current study, which shows an overlapping distribution for the two higher energy levels. Since this is not the anticipated outcome, a further investigation and discussion on the reasons for such behavior are brought in subsection 5.2.3.

70 Figure 5.13: Lumbar load distribution by energy level for study II

With the addition of the failure parameters, a consistent decrease in the mean values was found for the lumbar load distribution in all impact conditions, where a reduction of at least 10% was observed. Now, when taking into consideration the lumbar load criteria of 6675 N for the survivable limit, only a portion of the valid designs could be identiﬁed as feasible, as seen in Figure 5.14. From the gathered feasible designs, it can be noted that even with the addition of energy-absorbing mechanisms by the failure model, no signiﬁcant improvement in the relative number of feasible designs could be achieved.

Figure 5.14: Feasible designs for study II

71 5.2.2 Sample Responses

Similarly to the analysis done in subsection 5.1.2, one design per energy level was evaluated for analysis, shown in Figure 5.15. For ease of comparison, the design used follows the same characteristics as the previous analysis, with the exception of the addition of the parameters that characterize this case study. Just as for the other parameters, the add elastic limit variables had their values deﬁned as the central value in the parameter range.

Figure 5.15: Typical kinematics for the three energy levels for study II

Once again, the first time frame for each energy level shows an increasing amount of displacement as the initial velocity increased. Comparing to the study I kinematics, the response for 15 ft/s shows a remarkable similarity, which is likely due to the low impact energy defined for this case. However, as the energy increased, the responses start to show more noticeable differences since the added parameters begin to play a role. For the case with 30 ft/s of initial velocity, when compared to the study I case, the difference between the response of the floor and the seat appears to have been lessened since the rebound of the legs is not so prominent. On the other hand, the case with 45 ft/s presented a worse response when making the same comparison. This difference was seen because the latter case had both the seat and the skid systems to bottom out, which causes an excessive reaction force to develop, even raising the subfloor system considerably, as seen in the third timeframe. The responses from the ATD, seen in Figure 5.16, can add to the findings observed on the kinematics with respect to the large distinction observed across the energy levels. The

72 reported results in Figure 5.16 show a mismatch between the responses of the ﬁrst two energy levels with the last, almost resembling a comparison of largely distinct structural designs. Just like from the analysis of the kinematics seen for 45 ft/s, the ATD injury results indicate a highly injurious condition, while that is not the case when evaluating the two other cases. These observations corroborate the previous conclusion that the bottoming of the structural systems on the highest energy case is the key factor contributing to such disparate outcomes.

Figure 5.16: ATD response for the three injury levels for study II

Considering the time histories for the two lower energy levels, for the lumbar load, both cases were able to manage the impact energy so that the maximum lumbar load stayed below the threshold considered for survivable limit. In addition to that, these two responses look very similar when comparing all the three injury parameters, where the magnitude for those are found relatively close, and the shape and phase of the curves agree well for the ﬁrst half of the event. The differences between the results for the impact velocities of 15 and 30 ft/s are presented mostly along time, where the responses clearly show that the latter case has more kinetic energy to be managed, which requires additional time to be dissipated.

73 5.2.3 Analysis of the Results

The post-processing and analysis of the results obtained from this study proved to be much more challenging than the previous in terms of finding trends to help with the design process. The increase in the number of variables is alone a factor contributing to this fact, but most importantly, the intricate behavior of some non-linear combined effects from the input variables transforms the trend and sensitivity analysis a tough task in the design space level. For such reasons, the same tools and methodology used to analyze study I could not be in the same manner employed since the linear regressions for the sensitivity analysis yielded fitting factors too low to be considered, and the clustering process could not deliver design clusters that could show a clear trend. Regarding the non-linear combined effects mentioned, that is first related to the addition of the elastic limit as a variable, since now the energy absorption obtained from the stiffness behavior depends on two linked variables. Another aspect to consider is that now that the stiffness behavior of the structure can provide significant energy absorption during the impact event, clear trends on the mechanisms allowing for energy dissipation were compromised since the damping parameters also influence this factor. In the attempt to find more meaningful data that could lead to the understanding of the issue discussed around the overlapping lumbar load distribution for the two highest impact velocities, an analysis considering the energy dissipation contribution of each structural system was executed. In the process of doing so, it was essential to keep in mind the different mechanisms for which the energy is dissipated through the change in stiffness, seen in Figure 5.17, along with the affecting variables, as presented in Equation 5.1, Equation 5.2 and Equation 5.3. Although the stiffness behavior definition for this case shows a constant force required to reach both εfailure and εmax as the same, that does not imply that once this force is reached, the structure would instantly deform the amount relative to this gap. In the same lines, as this instant deformation does not occur, the energy dissipation is at the same pace not suddenly increased. In reality, the physical response needs time to deform and have the energy dissipated, being this is a key factor when considering the important aspects to reduce occupant injury.

74 1 E = k · ε (5.1) elastic 2 spring failure

Eplastic = kspring · εfailure·

(εdeformed − εfailure) (5.2)

T otalEnergy = Eelastic + Eplastic (5.3)

Figure 5.17: Structural energy absorption

In Figure 5.18a, a monotonically increasing amount of energy is seen to be dissipated by the seat system as the initial impact velocity increases. That can be especially noted when considering the shift of the displayed densest half of occurrences. This trend is in the same manner seen when looking at the contribution resulted from the subﬂoor system, which has not been displayed for simplicity. On the other hand, the plot showed in Figure 5.18b presents a diverging trend when considering the densest half of designs.

(a) Energy absorption contribution by the seat (b) Energy absorption contribution by the skid system for study II system for study II

Figure 5.18: Analysis of the energy absorption contribution by system

75 From the information displayed in Figure 5.18b and referring to the discussion about the time taken for energy dissipation, a few inferences can be made. The fact that the densest half of results is located around the upper half of the result range for the 30 ft/s impact condition, and also considering that the variation between the third quartile and the maximum value is relatively small, these imply that for the evaluated designs, the energy absorption capabilities were basically maxed out at that impact energy level. With similar considerations, it can be observed that the densest half of results for the 45 ft/s condition presents a lower energy dissipation than the designs evaluated for the 30 ft/s condition. Accounting for that, it can be safely said that in the higher impact velocity case, the skid system did not have enough time or deformation to dissipate the energy generated during the impact. As a result of that, the contact between the seat and the ATD was not capable of developing higher forces for the lumbar spine, while the 30 ft/s case might not be efﬁciently diverting the loads throughout the structure. Hence the lumbar load distribution overlap noticed in Figure 5.13. Since this study focused on analyzing the ﬁrst loading during the impact event, effects that would take place in a later stage are not being considered. That is the case for a second impact, for example, which is likely to occur for many designs in the higher spectrum of impact velocities, a condition where the lumbar load and other injury parameters would show values over the survivable limits.

76 CHAPTER 6

CONCLUSIONS AND RECOMMENDATIONS

6.1 Conclusions

The main goal of this study was to investigate the driving factors in structural design that can lead to improved survivability in the case of an emergency landing condition for a VTOL aircraft. To achieve that, a representative model of the impact event was developed and validated using different tests and simulation studies previously conducted to serve as a reference for this validation process. With the validated model, two case studies were executed to explore the effects of the structural parameters in models with different levels of complexity. The process of model validation was executed in two steps, where ﬁrst, the intended outcome was to guarantee that the ATD model and its responses were capable of replicating the test results for a regulated test condition. Along this process, learnings regarding the proper model execution and initial setup were acquired. The results could be validated with a high degree of similarity. The second validation step focused on achieving valid results for the pure vertical loading condition. The reference study used to develop this validation was of great help on this process since the reference publication reported not only the drop test executed in a test facility but also the development and achieved results obtained with the described MADYMO model. A great deal of detail and information presented on the paper regarding the model conditions were crucial to achieving good validation results for the model developed in this study. Even with that, several important and sensitive information could not be extracted from the released information, which led to a process of adjustment where these unknown characteristics were varied to achieve a solution as close to the reference as possible. The validated model achieved with this process could accurately replicate the reference results for the interest analysis range. The case study with lower complexity was analyzed ﬁrst to take more informed conclusions from the case with additional parameters. This initial study could show that the model be- haved as expected, especially when considering the obtained kinematics, the injury responses,

77 and the overall distribution of results. The in-depth analysis of the contribution of the input parameters was capable of presenting clear trends highlighting the dominance of the skid parameters, especially for damping ratios exceeding 15%. The results obtained for the second case study initially seemed to represent the outcome of an inadequate analysis. However, the methodology employed where increasing complexity was added at each step gave the confidence to look at the results with an inquisitive perspective rather than denial. The incapacity of finding clear trends for the contribution of the variables led to using a different set of tools and analysis methods to uncover the hidden patterns across the data. The modified approach was then capable of providing meaningful insights regarding the understanding of the data initially thought to be erroneous. The first parametric study could only yield feasible designs, those below the lumbar load limit, for the lower impact energy velocity. On the other hand, with the addition of failure parameters in the second study, feasible results could be achieved for the first two impact energy levels, even with a lower number of designs. Furthermore, the mean and minimum lumbar load values were lowered for all the impact cases in the second study, where the mean values improved by at least 10%. The difference in the addition of the failure parameters can be clearly noticed when looking at the injury response plots for the sample responses, where the time for the peak load and its magnitude could be improved significantly for the first two impact velocity conditions. The unexpected results obtained for study II showed that the interaction between the systems became much more important as the complexity increased. Using the analysis for the contribution of each system in the energy absorption, it was clear that in this case, one system only drove the response that yielded injury values over the survivable range. With such limited space due to the proximity to the ground, the design of the structural systems for VTOL aircraft that meets the survivable limits becomes very challenging. The independent design of the structural systems may end up in worse performance as these systems are put together. For that reason, the consideration of integrated design from the start of the process can produce more effective and thus safer aircraft.

78 6.2 Future Work

As discussed in the literature review section, the research on the area of crashworthiness for VTOL aircraft operating in urbanized areas has just begun. With the large variety of aircraft concepts, several aspects concern the area of crashworthiness that can be studied to help on the path of achieving safe operation for this market. Here, the emergency landing condition of pure vertical loading was studied; however, the novelty of such concepts should require a look into failure modes occurring in different ﬂight phases, such as in the transition or cruising phases. Precisely to what this study covered, additional efforts can be taken to improve on the limitations discussed in subsection 3.4.4. Additionally, increasing complexity levels can be considered in this model to represent an additional component or material characteristics, such as an independent seat cushion or the consideration of hysteresis and unloading material curves. For simplicity and the lack of enough information, the contact at the impact instant was disregarded for the developed model. A study on the characterization of such interaction could enable the analysis of different aircraft attitudes since external effects like wind, wildlife, and unexpected malfunction can lead to uncontrolled landing conditions. Furthermore, as different concepts are considered, depending on the aircraft’s size, distinct levels of occupation can shift the vehicleCG, which can change the impact dynamics considerably, being this a candidate for future research.

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