Development of a Finite Element Model of an Ant Neck Joint for

Simulation of Tensile Loading

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree of Master of Science

in the Graduate School of The Ohio State University

by

Vienny N. Nguyen

Mechanical Engineering Graduate Program

The Ohio State University

2012

Thesis Committee:

Dr. Blaine Lilly, Advisor

Dr. Carlos Castro

Dr. Joseph Raczkowski

Copyright by

Vienny N. Nguyen

2012

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ABSTRACT

Insects have been optimized for form and function over millions of years. Ants in particular can lift and carry extraordinarily heavy loads in relation to their own body weight (up to 1000X their own weight). We hypothesize that the ant’s ability to carry extremely large loads relative to its body mass is the result of a highly integrated system comprised of composite materials, internal muscle mechanisms, and material microstructure. The work completed for this thesis focuses on studying the neck joint, which bears the full mechanical load, of Formica exsectoides. Through mechanical testing, the load-displacement behavior was recorded and used as a reference for a computational model of the neck joint. SEM and microCT imaging was used to supplement and create a 3-dimensional finite element model. The results from the mechanical tests and finite element model reveal that the load-displacement behavior is dependent on the direction of the applied load, and that the typical rupture location occurs at the material transition between the neck membrane and stiffer exoskeleton on the head.

This project serves as a gateway to better understanding the design of the neck joint; future work may include the characterization of the neck membrane material, a kinematic analysis of the joint including muscle and ligament contributions, and a comparison of the functional morphology between multiple species.

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This work is dedicated to my family and friends.

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ACKNOWLEDGEMENTS

I thank the National Science Foundation’s Graduate Research Fellowship Program for their support and investment in not only my research, but also the research of my peers that will contribute to our future. This work was also supported in part by The Ohio State University Institute of Materials Research and an allocation of computing time from the Ohio Supercomputer Center. I thank Dr. Richard Hart for use of the MicroCT Laboratory in the Department of Biomedical Engineering at The Ohio State University; SimpleWare for providing the necessary software for 3-D modeling; and Dr. Joe Raczkowski and Dr. John Wenzel for sharing their myrmecological expertise with the project. I owe a great deal to Dr. Blaine Lilly for his patience and willingness to support projects that are outside of the box, and to Dr. Carlos Castro for adopting me into the Nanoengineering and Biodesign Lab. For those who have helped me get to where I am today, there is not enough I can do or say to thank you for your support: Dr. Kinzel, Dr. Staab, Dr. Harper, Joe West and the rest of the mechanical engineering faculty and staff for giving me a hard time; the Robonaut Team at JSC for the privilege of learning how to apply my lessons from an amazing group of engineers; Dr. Freuler and the FEH family for setting the bar high; the Office of Minority of Affairs for making Ohio State possible; Dan McCarthy, Neil Gardner, and Dave Torick for introducing me to engineering just in time; all of my teachers in primary and secondary school for their dedication in dealing with students like me; my friends who supported me through the years and were there to remind me to have fun; my mom for being a constant worry wart; and my dad for letting me climb to the top of the jungle gym and for (usually) trusting that I would always get the job done. I also thank my husband, my partner in crime, and my rock. Thank you for loving, challenging, and believing in me. I finally thank God for all that He has given me.

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VITA

December 26, 1986………………………………………...Born – Columbus, Ohio, USA

2010……………………………B.S. Mechanical Engineering, The Ohio State University

2010-2011………………………………….University Fellow, The Ohio State University

2011-2012………………………………………..NSF Fellow, The Ohio State University

PUBLICATIONS

V.N. Nguyen, B.W. Lilly, and C.E. Castro, “Reverse Engineering the Structure and Function of the Allegheny Mound Ant Neck (Insecta, Hymenoptera, Formica exsectoides),” in ASME International Mechanical Engineering Congress and Exposition, Houston, TX, 2012.

FIELDS OF STUDY

Major Field: Mechanical Engineering

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TABLE OF CONTENTS

ABSTRACT ...... iii

ACKNOWLEDGEMENTS ...... v

VITA ...... vi

TABLE OF CONTENTS ...... vii

LIST OF FIGURES ...... x

LIST OF TABLES ...... xiv

Chapter 1. Introduction ...... 1

Chapter 2. Background ...... 4

2.1 Taxonomy ...... 4

2.2 Anatomy ...... 6

2.2.1 External Anatomy ...... 7

2.2.2 Internal Anatomy...... 7

2.3 Terminology ...... 8

Chapter 3. Literature Review ...... 9

3.1 Introduction ...... 9

3.2 Exoskeleton Material Properties ...... 9

3.3 Additional Functions of Insect Exoskeleton ...... 14

3.3.1 The Folded Cuticle of a Dragonfly Neck ...... 14

3.3.2 The Microsculpture of Fly Cuticle Armor ...... 16

3.4 Summary of Literature Review ...... 22

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Chapter 4. Experimentation ...... 23

4.1 Introduction ...... 23

4.2 Instrument Design...... 24

4.3 Methods ...... 26

4.3.1 Specimen Collection and Maintenance ...... 26

4.3.2 Experimental Protocol ...... 27

4.4 Experimental Results ...... 31

4.5 Summary of Experimentation ...... 34

Chapter 5. Imaging and Modeling ...... 36

5.1 Introduction ...... 36

5.2 MicroCT Methods ...... 36

5.3 SEM Methods and Images ...... 40

5.4 Conversion of MicroCT Data to a 3-Dimensional Mesh ...... 43

5.5 Finite Element Model ...... 50

5.5.1 Model Data, Boundary Conditions, Loading, and Parameters ...... 50

5.5.2 Material Verification ...... 51

5.5.3 Model Results ...... 53

5.6 Summary of Imaging and Modeling ...... 56

Chapter 6. Discussion and Conclusion ...... 58

6.1 Introduction ...... 58

6.2 MicroCT and SEM imaging ...... 58

6.3 Experimental and Finite Element Results Comparison ...... 59

6.4 Summary and Conclusions ...... 63

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Bibliography ...... 66

Appendix A: Glossary...... 71

Appendix B: Circuit Diagrams ...... 73

Appendix C: Arduino Source Code ...... 74

Appendix D: Mechanical Testing Protocol...... 77

Appendix E: MATLAB Image Processing m-file ...... 80

Appendix F: CT Specimen Staining and Preparation Protocol ...... 86

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LIST OF FIGURES

Figure 1: Examples of load carrying Oecophylla ants. A) O. smaragdina workers

contructing a nest [2]; B) O. Longinoda worker holding a dead baby bird [1]; and

C) O. smaragdina worker holding a weight from a glassy surface [3]...... 2

Figure 2: Arthopod Classification ...... 5

Figure 3: Ant Classification ...... 6

Figure 4: External and Internal Anatomy of the Ant [6] ...... 6

Figure 5: Anatomical Terms of Location. Photograph by Alexander Wild...... 8

Figure 6: A material property chart for natural materials, plotting Young's Modulus

against density. Guide lines identify structurally efficient materials which are

light and stiff [10]...... 10

Figure 7: Locust in the Oviposition [13]...... 11

Figure 8: SEM of neck area in damselflies. (A) Dorsal aspect with head removed of

Ischnura elegans; (B) Semi-thin cross section of the neck region of I. elegans; (C)

Dorsal aspect with head removed of Coenagrion puella; (D) Semi-thin cross

section of the neck region of C. puella. a, anterior direction; d, dorsal direction;

m, medial direction; EC, epidermal cells; ML, midline; NM, neck membrane; PN,

pronotum; SP, postcervical sclerite; TRD, dorsal trachea; TRV, ventral trachea;

TS, trichoid sensilla. Scale bars: 380 nm (A & B); 75 µm (C); 86µ (D) [11]...... 15

Figure 9: Three orders of the neck membrane profile in adult Odonata [11]...... 16

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Figure 10: Membranous cuticle in Brachycera, suborder of Diptera. MB, flexible

membrane; PT, microplates; Arrowheads indicate point of contact between

microtrichia. (A) Microplates of Statriomys chamaeleon legs (B) Membrane

showing curved, parallel microtrichia of Lucilia caesar legs; (C) Short papillae on

the prothorax-neck membrane of Tabanus bovinus; (D) membrane of the hip-leg

joint with single microtrichia of Eristalis tenax; (E) multiple microtrichia on each

micro-plate joined by flexible membrane Eristalis tenax on head-trunk

membrane; (F) mixture of papillae-like and elongated microtrichia on neck-head

membrane of Myathropa florea; (G) parallel microtrichia on microplates of side

hip joint of Eristalis tenax [12]...... 17

Figure 11: Different types of macrostructure of membranous cuticle in various Diptera

species. (A) single, short microtrichia directly connected to membrane; (B)

single, elongated microtrichia directly connected to membrane; (C) single,

elongated microtrichia on microplates; (D) groupings of microtrichia on

microplates; (E) microplates without microtrichia ...... 18

Figure 12: Possible functions of microstructure on membranous cuticle of various Diptera

species. (A-D) Fixation function; (E-F) String function; (G) Folding function. . 21

Figure 13: General layout of the centrifuge setup ...... 25

Figure 14: F. exsectoides specimen fixed to the centrifuge disk and marked with white

paint...... 28

Figure 15: Sample image from mechanical testing ...... 29

Figure 16: Sample of processed images and grayscale plots ...... 30

Figure 17: Stress-strain plot of the experimental results and stiffness regimes...... 32

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Figure 18: Comparison of quadratic fits for total and averaged data. The solid, orange line

shows a quadratic fit for the average binned points (orange circles), while the

dotted black line is a quadratic fit for the total data set (blue diamonds)...... 34

Figure 19: X-Ray image of F. exsectoides from CT scan using the first specimen

preparation protocol...... 38

Figure 20: X-Ray image of F. exsectoides from CT scan using the second specimen

preparation protocol ...... 39

Figure 21: Ventral view of the neck membrane of a F. exsectoides specimen (Specimen

1) ...... 41

Figure 22: Posterior view of a head from a ruptured specimen (Specimen 5) ...... 42

Figure 23: Ruptured exoskeleton in the neck area from Specimen 5 ...... 43

Figure 24: Cross-sectional slice of the processed CT images ...... 44

Figure 25: Segmentation in Amira. A) Cross-sectional slice; B) The position of the slice

in (A) shown in 3D; C) Full model showing the segmented body from the back

ground; D) The exoskeleton (red), tentorium (teal), nervous tissue (blue), eyes

(yellow), and esophagus (magenta) segmentations...... 45

Figure 26: SimpleWare segmentation of exoskeleton (tan), tentorium (green), and

esophagus (teal)...... 46

Figure 27: Neck joint cross-section showing the head (blue), neck membrane (purple),

esophagus (teal), and thoracic plates (orange)...... 47

Figure 28: Segmentation of cropped neck joint including the head exoskeleton and

tentorium (blue), thoracic segments (orange), neck membrane (purple), and

esophagus (teal)...... 48

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Figure 29: Abaqus mesh and applied boundary conditions (BN = back node, LN = load

node)...... 51

Figure 30: Simplified FE models to verify material behavior. A) Linear elastic model and

B) hyperelastic model...... 52

Figure 31: Material comparison of stress v. strain...... 53

Figure 32: Side-view cuts through the deformed stress contour plots of the deformed neck

joints. A) Linear elastic material definition and B) hyperelastic material

definition...... 54

Figure 33: Comparison of material definitions and node displacements...... 55

Figure 34: Load v. displacement for varying load vectors...... 56

Figure 35: Comparison of the rupture location in an SEM micrograph of F. exsectoides

and stress concentration in the FE model...... 59

Figure 36: Comparison of experimental and finite element results...... 61

Figure 37: Mounting and load angle comparisons. A) Position corresponds to a 65 degree

loading and B) corresponds to a 75 degree loading...... 62

Figure 38: Comparison of experimental and FE head orientations. Diamonds indicate

experimental data points (purple: 65 degree loading angle; red: 75 degree loading

angle) and the lines represent the FE load-displacement curves...... 63

Figure 39: Layers of Cuticle [28]...... 71

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LIST OF TABLES

Table 1: Tensile properties of arthrodial membrane cuticle and chitin [14]...... 12

Table 2: Tensile properties of solid sclerite cuticle and chitin [14]...... 13

Table 3: Quantitative comparison of the macrostructure of the armored membranes in the

head-body joints of various Diptera species [12]...... 19

Table 4: Quantitative comparison of the macrostructure of the membranes in the body-leg

joints of various Diptera species [12]...... 20

Table 5: Average Low and High Stiffness Values...... 33

Table 6: MicroCT Scanning Parameters for each Specimen Preparation Method ...... 37

Table 7: SimpleWare Mesh Generation Statistics ...... 49

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Chapter 1. Introduction

Insects have evolved over the course of millions of years to optimize form and function. Ants, in particular, have evolved into multifunctional and individually specialized machines with collective emergent behaviors from the colony. For example, in Atta (leafcutter ant) colonies, there are multiple worker castes that specialize in the cutting up of material for their fungal gardens, transporting the material back to the colony, and even body guards that ride on carriers to prevent parasitic phorid flies from ovipositing in the workers’ bodies. Another example is Oecophylla (weaver ant) workers which exhibit cooperative behavior in constructing their arboreal nests: the workers form chains with their bodies to pull together leaves and small branches, as shown in Figure

1A. This group of ants are also known for their tendency to cooperatively capture and retrieve large prey [1] and have been observed carrying large loads individually, as shown in Figure 1B and C.

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Figure 1: Examples of load carrying Oecophylla ants. A) O. smaragdina workers constructing a nest [2]; B) O. longinoda worker holding a dead baby bird [1]; and C) O. smaragdina worker holding a weight from a glassy surface [3]. The example in Figure 1B is particularly astonishing because it shows a singular ant holding up a dead baby bird approximately 1000 times its own mass [1]. This feat is equal to a 120 lb. adult holding a T-38 jet plane. Because the load is passed from the mandibles through the neck and body, and distributed to six legs attached to the substrate.

The neck joint is the smallest membranous component that bears the full load. Therefore, this project seeks to understand how the neck was designed to carry such a load.

Biological systems are complex and highly integrated, and many joints of exoskeleton systems do not have stiff connections, but rather softer material that connects stiff segments of the body. Therefore multiple methods were used to study the neck joint, with the main premise of pairing experimentation with modeling. Formica exsectoides

(Allegheny mound ant) was chosen as the initial study specimen because of its availability and size. This species is known to be territorial, hunt other insects and arthropods, and typically is found in dense unicolonial establishments [4].

The goal for the experiments was to test live ants to recreate loading conditions on the neck joint similar to what has been observed in nature. The results of the experiments

2 will be used mainly as a qualitative evaluation of the overall performance of the neck joint and as a reference for material specification in the models. A quantitative characterization of the neck membrane material will be the subject of future work.

As a direct complement to the experiments, a finite element (FE) model was created using micro-computer tomography (CT) scan data. The scans provided spatial data for exoskeleton geometry including complex folds in the softer neck membrane and the esophagus, which is lined with a material similar to the external neck membrane. The data was used to generate a 3-dimensional model and mesh of the neck joint that could then be loaded in the FE simulations. Scanning electron microscope (SEM) images were also used to study the external structure of the neck membrane and rupture locations of failed specimens. These images were compared to the geometry generated in the microCT data conversion and the results of the FE analyses.

The combination of experimentation, imaging, and modeling resulted in a model that could be used to physically simulate the force extension behavior of the neck joint and experimentally validated. This model provides a foundation for further detailed analysis including material characterization, muscle attachments and forces, kinematics, and a comparison of functional morphology between different types of joints and insect species.

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Chapter 2. Background

2.1 Taxonomy

Insects are in a class within the Arthropoda phylum. All arthropods have the following characteristics [5]:

1. Bilateral (left/right) symmetry

2. Segmented body

3. Exoskeleton

4. Jointed Legs

5. Many pairs of limbs

Examples of arthropods are crabs, spiders, millipedes, and grasshoppers. Figure 2 below shows a graphical taxonomy of arthropods. The class Hexapoda is within the phylum Arthropoda. Some examples of orders within Insecta are shown: Hymenoptera

(ants, bees, and wasps); Diptera (true flies); Coleoptera (beetles); Orthoptera (crickets and grasshoppers); Odonata (damselflies and dragonflies); Siphonaptera (fleas); and

Hemiptera (true bugs and cicadas).

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Animalia

Arthropoda

Myriapods Crustaceans Hexapods Chelicerates Trilobites

Malacostraca Arachnida

Decapoda Insecta Araneae

Hymenoptera Hemiptera

Coleoptera Odonata

Diptera Siphonaptera Orthoptera

Figure 2: Arthropod Classification The species of ant studied was Formica exsectoides, commonly known as the

Allegheny mound ant. F. exsectoides is in the order Hymenoptera, shown above, and in the Formicidae family. Figure 3 below shows the taxonomic breakdown for Formica and other ant genera: Oecophylla (weaver ants); Odontomachus (trap-jaw ants); Pheidole

(seed cracker ants); and Atta (leaf-cutter ants).

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Figure 3: Ant Classification 2.2 Anatomy

Figure 4 below shows a generalized representation of the external and internal anatomy of the ant.

Figure 4: External and Internal Anatomy of the Ant [6] 6

2.2.1 External Anatomy

All arthropods have exoskeletons that are comprised of grouped segments, known as tagmata, which perform a common function. For insects, the head is the first tagma with the mandibles and mouthparts, antennae, and eyes. The thorax is comprised of three segments from which the legs protrude. The segments between the thorax and bulbous gaster are reduced to form a waist and the beginning of the abdomen, also known as the metasoma. The neck joint is of primary interest in this project and consists of a soft membranous connection between the head and the thorax.

2.2.2 Internal Anatomy

Insects have a dorsal heart which pumps hemolymph forward to the anterior of the body and out into the upper portion of the head over the brain. The hemolymph then moves ventrally towards the back of the body and is recycled forward again. The nervous system is distributed ventrally and centered at the ganglia found in each body segment.

The two ganglia in the head are grouped into the brain and subesophageal ganglion.

The digestive system is divided into three regions: the foregut, midgut, and hindgut. The foregut consists of the digestive canal from the mouth to the crop and proventriculus and its role is to ingest, store, grind, and transport food to the midgut. The midgut’s role is to digest and absorb the food, while the hindgut’s role is to absorb water, salts, and other molecules. The foregut and hindgut have a cuticular lining similar to the exoskeleton [7].

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2.3 Terminology

To clarify the use of biological terms, the above sections can be used to reference anatomical parts of consideration in the following sections. Figure 5 shows an image of an ant and the directional terms that will be used to describe features.

Figure 5: Anatomical Terms of Location. Photograph by Alexander Wild. Finally, the glossary in Appendix 1 can be referenced for italicized terms that refer to anatomical features. Italicized terms that do not reference features indicate a genus or species of an insect.

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Chapter 3. Literature Review

3.1 Introduction

Insects as systems are highly integrated and optimized to minimize energy output while maximizing functionality. Ants achieve this by using components within the system that are multifunctional and multi-scalar. The exoskeleton provides a primary example of a complex material structure-function relation within the insect mechanical system. It is a laminar composite whose local material composition varies based on local function.

3.2 Exoskeleton Material Properties

Arthropod exoskeleton is a composite that consists primarily of chitin fibers in a matrix of protein – typically resilin [5] – and may also include a ceramic phase for added stiffness [8] as well as some metals such as zinc, manganese and iron [11]. With variations in the content of the material, the exoskeleton is able to meet a wide range of mechanical properties. This is illustrated in Figure 6.

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Figure 6: A material property chart for natural materials, plotting Young's Modulus against density. Guide lines identify structurally efficient materials which are light and stiff [9]. This figure shows that the Young’s modulus of cuticle ranges from about 1x10-6

GPA to about 50 GPA that correspond to cuticle from soft membrane to stiff wings, respectively.

In addition to the harder forms of cuticle, softer, membrane-like cuticle also performs essential functions as part of the exoskeleton. While the harder cuticles provide stiffness, protection, and wear-resistance, the softer cuticles allow for large deformations and stretching to accommodate motion and growth due to maturation and even abdominal

10 expansion during eating or reproduction. For example, Figure 7 shows a picture of a female locust in the position of laying eggs. Locusts are capable of laying their eggs up to 8 cm underground in order to allow the eggs to reach water [5]. This deformation is achieved by deformation and unfolding of soft membrane.

Figure 7: Locust in the Oviposition [13] A previous study by Hepburn and Chandler identified the differences in mechanical properties between harder cuticles and membrane-like cuticles. The study also took an additional step to correlate the difference in properties to varying contents of chitin and protein. Table 1 below tabulates the results from testing membrane-like cuticle.

The tangent modulus refers to the highest value of a slope tangent to the experimental, and non-linear, stress-strain curve and relative stiffness is the tangent modulus multiplied by the thickness of the specimen. Under each arthropod named are a series of angles that refer to the tensile direction where zero degrees refers to a direction longitudinal to the body (from head to tail) and ninety degrees refers to a direction transverse to the body

(from side to side). Also, some of the series also include an additional note indicating

11 that tensile tests were performed on the cuticle after the protein was removed and only chitin remained.

Table 1: Tensile properties of arthrodial membrane cuticle and chitin [14].

Hepburn found that exoskeleton is not an isotropic material based on its performance when tested in different directions. The results also show variability in its extensibility, with the cuticle of the female locust, shown above as Locusta, having the highest extensibility of about 2000%; while the cuticle found at the joints of crabs, shown

12 as Scylla, has the second highest extensibility with elongation between 278% and 304%.

Finally, when comparing between the whole cuticle and cuticle with the protein removed, the hardness increases in all directions and percent elongation generally decreases as illustrated by the results for shrimp cuticle, shown as Penaeus.

Table 2 below shows results from mechanical testing of hardened cuticle. Similar to Table 1, a series of angles are listed under each arthropod that refer to the tensile direction where zero degrees refers to a direction longitudinal to the body (from head to tail) and ninety degrees refers to a direction transverse to the body (from side to side), as well as a note indicating if protein was chemically removed from the cuticle.

Table 2: Tensile properties of solid sclerite cuticle and chitin [14].

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The results show that the hardened cuticles typically have higher moduli of elasticity and relative stiffness coefficients, and much lower breaking strains. When comparing between whole cuticle and cuticle with protein removed, both stiffness and the modulus of elasticity increase for membranous cuticle while there is a decrease of both properties for hardened cuticle.

From these results, it can be concluded that the mechanical properties of un- sclerotized, or un-hardened, membrane-like cuticle depends heavily on the chitin fibers, while the sclerotized cuticle depends on the protein matrix. In the case of sclerotized cuticle, it is possible that the chitin fibers play a stronger role in structural stability and fracture resistance [14].

3.3 Additional Functions of Insect Exoskeleton

Beyond the material content and mechanical properties of exoskeleton, its structure plays a major role in the function that it performs. In the previous section, it was shown that the strength and flexibility of cuticle could be determined by material content and microstructure. This section will describe the results of studies of exoskeleton that focus on the macrostructure of the cuticle and describe the possible functions these structures perform.

3.3.1 The Folded Cuticle of a Dragonfly Neck

The membrane that is found between hard plates and body sections in arthropods can be either highly extensible, as shown in Section 3.1, or folded and laminated to provide a lower degree of extensibility but higher degree of strength. To understand the shape and function of folding cuticle, a study was done in which the neck of various

14 species of dragonflies, Odonata, was examined. Figure 8 below shows sample images that were taken using SEM.

Figure 8: SEM of neck area in damselflies. (A) Dorsal aspect with head removed of Ischnura elegans; (B) Semi-thin cross section of the neck region of I. elegans; (C) Dorsal aspect with head removed of Coenagrion puella; (D) Semi-thin cross section of the neck region of C. puella. a, anterior direction; d, dorsal direction; m, medial direction; EC, epidermal cells; ML, midline; NM, neck membrane; PN, pronotum; SP, postcervical sclerite; TRD, dorsal trachea; TRV, ventral trachea; TS, trichoid sensilla. Scale bars: 380 nm (A & B); 75 µm (C); 86µ (D) [10]. The results of the study showed that there were several hierarchical orders of folds present in the neck membrane at different scales. Figure 9 below shows a visual representation of the three orders.

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Figure 9: Three orders of the neck membrane profile in adult Odonata [10]. Having this hierarchy and structure of folds allow the necks of Odonata to pitch, roll, and yaw. This set of structures also allows the cuticle itself to be stiffer than the smoother counterpart as a result of increased material and yet have a high extensibility.

In addition to these formations, the cuticle is also laminar which can allow the layers to slide relative to each other during motion.

3.3.2 The Microsculpture of Fly Cuticle Armor

The exoskeleton of many insects includes various types of membranous cuticle designed to stretch between hardened plates. In order to understand the structure of this type of membrane, a study was done to correlate the surface structure of the membrane with function. In this study, various types of flies, Diptera, were used and two different areas were examined using SEM. The first area focuses on the head-body joint, while the

16 second focuses on the body-leg joints. Figure 10 below shows examples of the structures that were observed for each joint type.

Figure 10: Membranous cuticle in Brachycera, suborder of Diptera. MB, flexible membrane; PT, microplates; Arrowheads indicate point of contact between microtrichia. (A) Microplates of Statriomys chamaeleon legs (B) Membrane showing curved, parallel microtrichia of Lucilia caesar legs; (C) Short papillae on the prothorax-neck membrane of Tabanus bovinus; (D) membrane of the hip-leg joint with single microtrichia of Eristalis tenax; (E) multiple microtrichia on each micro-plate joined by flexible membrane Eristalis tenax on head-trunk membrane; (F) mixture of papillae-like and elongated microtrichia on neck-head membrane of Myathropa florea; (G) parallel microtrichia on microplates of side hip joint of Eristalis tenax [11].

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The macrostructure of the membranes can be generalized into the following categories:

- Microplates without microtrichia

- Single, short papillae-like microtrichia directly connected to membrane

- Single, elongated microtrichia directly connected to membrane

- Single, elongated microtrichia on microplates

- Microplates that containing groupings of microtrichia

These categories are shown below in Figure 11.

Figure 11: Different types of macrostructure of membranous cuticle in various Diptera species. (A) single, short microtrichia directly connected to membrane; (B) single, elongated microtrichia directly connected to membrane; (C) single, elongated microtrichia on microplates; (D) groupings of microtrichia on microplates; (E) microplates without microtrichia

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The results from analyzing the joints between the head and body were quantified by the number of microtrichia occurring on a microplate, microplate size, and spacing between microplates. These results are tabulated below in Table 3.

Table 3: Quantitative comparison of the macrostructure of the armored membranes in the head- body joints of various Diptera species [11].

The results from analyzing the joints between the body and legs were quantified similarly to the results from the body and head joints above. The results are tabulated below in Table 4.

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Table 4: Quantitative comparison of the macrostructure of the membranes in the body-leg joints of various Diptera species [11].

From the results shown above, the membrane found in the general body to head transition tends to have only single formations of microtrichia per microplate and their lengths are sometimes longer than the distance between the microplates. Also, the transition from body to neck tends to have shorter microtrichia than in the transition from the neck to the head. In the transition from the body to the legs, there is a higher number of microtrichia and their lengths tend to be longer than the distance between the microplates.

These formations are considered to help provide structural stability of flexible membranes as well as vary the frictional forces in contact areas. Depending on the direction of deformation and shape of the macrostructures, these can increase the

20 frictional forces, providing stability of motion. Examples of the functions these frictional forces are shown below in Figure 12.

Figure 12: Possible functions of microstructure on membranous cuticle of various Diptera species. (A-D) Fixation function; (E-F) String function; (G) Folding function. These functions are grouped into three categories. The first is fixation in which the microtrichia are longer than the spacing between microplates and can interact in order to provide holding stability. The second is the string function where the microtrichia are angled parallel to the surface of the cuticle in order to provide another degree of

21 resilience to deformations in the membrane. The final function is folding in which pattern of the microtrichia provide a specific direction for the membrane to fold.

Previous research suggests that microtrichia exists to perform at least two of these functions on a membranous surface [11].

3.4 Summary of Literature Review

Exoskeleton plays an important role in the structure and protection of the insect body, but also has a wide range of localized functions. As a result, the material properties vary widely and are dependent on factors including the quantities of its constituents (e.g., chitin, resilin, metals, ceramics, and water) and the amount of polymer cross-linking

(e.g., sclerotized vs. un-sclerotized). The degree of sclerotization changes locally and gives rise to regions of hard and soft membranous cuticle. These regions can also supplement function through surface micro- and macro- structure. Folds within membrane are used to facilitate motion and extension, and surface structures on both hardened and soft cuticle can be used to change surface-to-surface interactions to maintain shape, position, and aid in motion. These multi-scale features are an example of the complexity and level of integration of the exoskeleton and should be explored and considered in the multi-scale modeling of the ant neck joint.

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Chapter 4. Experimentation

4.1 Introduction

There are many challenges associated with the mechanical testing of biological materials. Specifically, in cases where the material is soft, it is very difficult to prepare and clamp the ends of the material without permanently deforming it or isolating the far- field effects. Also, it is oftentimes necessary to consider material moisture or perform tests with the specimens submerged in solution. To reduce the complexity of the experimental setup for this project, whole live ant specimens were tested in an open centrifuge fitted with a strobe and camera.

Federle and Hölldobler used a centrifuge setup to compare the feet attachment forces of arboreal ants on smooth surfaces [12]. They used an open air drum that was mounted to the output of a centrifuge motor and performed experiments with speeds ranging from 0-6000 rpm. To record their results, they used a high-speed video camera to capture images at a rate of 200 frames per second and a stroboscope at 200 Hz. This design relied on the mass of the specimens and the centrifugal acceleration that could be controlled with the speed of the centrifuge. Though the testing of the neck joint requires at least one fixation point, we chose to follow this example to avoid having to fix the opposing end of the specimen. Centrifuges have also been used in other loading experiments at the micro-scale to evaluate cellular characteristics [13-16].

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4.2 Instrument Design

The centrifuge needed to be designed, at minimum, to meet the loading conditions observed in literature and also be capable of testing beyond those conditions. Wojtusiak recorded a weaver ant, Oecophylla longinoda, holding a 7 gram dead baby bird off the side of a table – a mass that was equal to approximately 1000x the mass of the ant specimen [1]. This reference served as a performance requirement for the design of the centrifuge. The following equations were used to determine the minimum performance speed for the centrifuge:

√ ( )( )

Where F is the desired applied load, r is the approximate radial distance of the applied load, m is the approximate mass of the body, rpm is revolutions per minute, rps is revolutions per second, and FoS is the factor of safety to ensure the device could load beyond what was observed by Wojtusiak. The values for each variable are listed below:

( ) ( [ ])

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Where the mass of the bird was obtained from Wojtusiak [1], the value of r was approximated based on the expected size of the centrifuge disk, and the mass of the ant body was approximated to be half of the total mass of O. smaragdina specimens as reported by Federle and Hölldobler [12]. Applying these values, the maximum desired rotation speed of the centrifuge was calculated to be 421 rounds per second (rps) or

25,270 rounds per minute (rpm).

To meet this requirement and eliminate the need for gearing, a commercial-off- the-shelf router was fitted on a router table with an adapter spindle to directly drive a hard drive platter. Figure 13 below is a representation of the experimental setup.

Figure 13: General layout of the centrifuge setup A variable transformer was used to vary the AC input voltage to the router, thus changing the speed of the centrifuge. A CNY70 optical sensor was used to sense transitions on a spoke pattern on the bottom of the centrifuge disk. The circuit diagram for the optical sensor can be found in Appendix B: Circuit Diagrams. The transitions

25 were counted by a control program run by an Arduino micro-controller and the instantaneous speed was calculated and displayed onto a liquid crystal display (LCD).

The full text of the program can be found in Appendix 3: Arduino Source Code. The speed output value was verified using a stroboscope to compare the rounds per second displayed on the LCD and the frequency displayed on the stroboscope. The speed was calculated and displayed after the user presses a button to initiate data capture. After the speed was displayed, a digital SLR camera took a photograph using the onboard high speed flash. The circuit diagram for the camera switch can be found in Appendix B:

Circuit Diagrams.

4.3 Methods

Because testing of the specimens was to be conducted on live ants, a laboratory nest was maintained throughout the project and a specimen preparation protocol was developed to ensure the ants were alive during testing. Following the mechanical tests, the images were processed to extract loading and displacement information. The procedures used for specimen maintenance and preparation and data processing are described in detail within this section.

4.3.1 Specimen Collection and Maintenance

Formica exsectoides workers were collected in Columbus, Ohio from a large grouping of colonies, also known as a super colony. The top square foot of a mound was extracted and placed in a plastic container in which the top two inches were coated with

Fluon®, a PTFE coating, to prevent escape. Both the original mound and collected nest material was repaired by the workers within two days. The initial collection was led by

Dr. John Wenzel, former professor of entomology at The Ohio State University, while

26 subsequent collections were completed independently. A total of 3 collections were made within an 18 month period.

The nests were stored in a lab at approximately 72 degrees Fahrenheit and 30% relative humidity. The containers were kept open to the air to prevent condensation from collecting on the Fluon® coating, which would enable the specimens to escape. Feeding took place every 1-2 days in which 5- 10 mL of honey water (50% honey, 50% water) droplets were dispensed on a petri dish placed within the foraging area. In addition to the honey water, 4-6 mealworms were cut up and placed on another petri dish. The nest soil was watered every 2 days with approximately 250 mL of water to maintain moisture and nest garbage and debris were also removed after the workers placed them in the foraging area.

4.3.2 Experimental Protocol

Live specimens were tested on the centrifuge to recreate a loading situation in which muscles could contribute to the performance of the neck joint. In order to do this, the ants were anesthetized in a 30°F freezer for 5-10 minutes until immobile. The heads were then fixed using a cyanoacrylate glue and accelerant within a labeled section on a centrifuge disk. The glue was then allowed to set for 15 minutes to reduce the possibility of a glue adhesion failure. During that time, the ant was marked along its body using white acrylic modeling paint so that displacement could be later recorded and calculated.

Figure 14 shows a photograph of a prepared specimen.

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Figure 14: F. exsectoides specimen fixed to the centrifuge disk and marked with white paint Once the specimens were ready for testing, the disk was mounted onto the centrifuge spindle adapter and the electronics were powered on. The speed was increased incrementally at a rate of about 15 rps every 12 seconds. A photograph was taken at each speed increment to record instantaneous speed and displacement. Figure 15 is an example of an image recorded during mechanical testing.

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Figure 15: Sample image from mechanical testing For a detailed protocol of the specimen preparation and mechanical testing, please see

Appendix D: Mechanical Testing Protocol.

Following mechanical testing, the image sets were uploaded to a computer and imported into MATLAB for processing. During processing, images were centered, rotated, cropped around the specimen, and the pixels were evaluated based on grayscale values to identify the white markings painted on different sections of the ant. The

MATLAB m-file that was used to process the images can be found in Appendix E:

MATLAB Image Processing m-file. Figure 16 is an example of the output, showing the

29 cropped images and the grayscale value of the pixels lying along a line that is drawn by the user.

Figure 16: Sample of processed images and grayscale plots The grayscale value plots are used to approximate the relative location of the painted areas and then used to calculate total distance and strain. Logarithmic strain, or true strain, was calculated as follows:

( )

Where Lf is the final length and Li is the initial length. Stress was calculated as follows:

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( )

Where mbody is the mass of the body measured after the experiment, rps is the recorded instantaneous speed in revolutions per second, r is the distance of the body from the center of the disk, and A is the neck cross-sectional area. The value, A, was obtained from the 3-dimensional model generated using microCT data, as discussed in Section 5.

4.4 Experimental Results

The goal of the experiments was to evaluate and record the overall tensile behavior of the neck joint. These results would be later used as a comparison to the finite element models. Figure 17 shows the stress strain relationship recorded for 12 specimens.

The relationship is non-linear, as is typical for biological materials, and seems to exhibit two stiffness regimes – a low regime in which relatively large displacements occur at low loads and a high regime in which smaller displacements were observed at relatively high loads.

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Figure 17: Stress-strain plot of the experimental results and stiffness regimes. The low and high regime consistently occurred during the first and second half of loading, respectively. A linear curve fit could then be easily applied to find the overall stiffness, which is equal to the slope of the linear fit, for each regime and the values compared. The linear fits for the low stiffness regime were set to intercept at y=0. The average was calculated from these slopes by using the following formula:

∑

Where E is the slope of the linear fit and overall stiffness of the joint, and N is the number of samples. Standard error was calculated by using the formula below:

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√∑( )

√ √

Where σsample is the standard deviation for a sample of a population. Error! Reference source not found. Table 5 reports the average stiffness values and standard error for each calculation.

Table 5: Average Low and High Stiffness Values

Low Regime [Mpa] High Regime [Mpa] Average Stiffness 19.26 233.2 Standard Error 1.804 40.53

Both values of 19.26 MPa and 233.2 MPa for the high and low stiffness regimes fall within the range of arthrodial membranes tested by Hepburn [17] and Vincent [9]. In addition to recording nominal stress and strain, an average rupture stress and load was recorded to be 36.7±13.1 MPa and 0.33±0.065 N, respectively, for n=2 specimens.

It was hypothesized that the low stiffness regime would be strongly dependent on the geometric features of the neck joint, namely the folds within the membrane.

Therefore, the average stiffness of 233.2 MPa calculated for the high regime was used in the linear elastic FE model as the material stiffness for the neck membrane and esophagus. On the other hand, experimental data input to describe the behavior of the membrane under load for the non-linear material FE model. To generate a representative set of points for the model, the experimental points were averaged within fixed size strain bins and a quadratic fit of the average data was compared to a quadratic fit of all the points. A bin size of 0.05 strain was chosen, and all points falling within the bin interval

33 were averaged and the error calculated using the equations shown above. Figure 18 shows a comparison plot of the points and fits.

Figure 18: Comparison of quadratic fits for total and averaged data. The solid, orange line shows a quadratic fit for the average binned points (orange circles), while the dotted black line is a quadratic fit for the total data set (blue diamonds). Both fit lines were constrained to y=0 intercepts with R2 values of 0.7344 for the total data set and 0.9744 for the averaged data. Because the fits are closely matched within the given strain range, the averaged data was used as the input data when defining the Neo-

Hookean hyperelastic model in the non-linear FE analysis.

4.5 Summary of Experimentation

The design and implementation of a high speed centrifuge allowed for the collection of load v. displacement data of the Formica neck joint. The results showed the

34 relationship to be non-linear, as is typical for biological materials, and were processed for use as material specifications in the finite element models. The first specification that was used was an averaged, linear stiffness of 233.2 MPa obtained from the high loading regime shown in Figure 17. The second specification was a set of averaged data points that would be used as the input into a Neo-Hookean hyperelastic material definition in

Abaqus. The results of these models will be compared and used to explore the neck joint behavior under loading.

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Chapter 5. Imaging and Modeling

5.1 Introduction

To complement the experimental work, a finite element (FE) model was developed to simulate the experimental loading conditions. To perform the FE analysis, an accurate 3-dimensional model, mesh, and boundary conditions were necessary to capture the complex non-linear behavior observed in the experiments. The 3-D model was generated using SimpleWare’s software program, ScanIP and +FE module, as a tool to convert micro-computer tomography (CT) image data to spatial and mesh data. The mesh was then imported into the finite element software Abaqus for loading simulations.

Additionally, specimens were studied using a scanning electron microscope (SEM). The images captured using SEM were used to supplement and compare the behavior of the model in the Abaqus simulations.

5.2 MicroCT Methods

Ant specimens were scanned using a SkyScan 1172 scanner equipped with a 20-

100 kV, 10W tungsten x-ray source and 11 mega-pixel CCD camera in the Biomedical

Engineering Department’s MicroCT Laboratory at The Ohio State University. The first scan was made at no charge with the support of Dr. Richard Hart of the Department of

Biomedical Engineering and subsequent scans were funded by the Institute of Materials

Research facility grant. Two methods were used to prepare specimens to optimize information collected from microCT scans.

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For the first method, an ant specimen was killed in 70% isopropyl alcohol. The specimen was then removed from the alcohol and placed on an absorbent tissue to remove excess alcohol from the body. A low viscosity cyanoacrylate glue (INSTA-

CURE® from Bob Smith Industries, Inc.) was applied to the surface of a 75 mm petri- dish and the specimen was placed upon the glue in an upright position with the abdomen contacting the surface of the dish. This was then left to dry overnight in open air. Before mounting the specimen in the CT scanner, the petri dish area directly below the specimen was removed using a hobby knife with care taken not to damage the specimen. The remaining plastic and specimen were then mounted to a specimen stud using adhesive putty. The scanner parameters used for this scan are shown in Table 6.

Table 6: MicroCT Scanning Parameters for each Specimen Preparation Method

First Protocol Second Protocol Source Voltage [kV] 34 29 Source Current [uA] 210 169 Number of Rows 1200 1200 Number of Columns 2000 2000 Number of Connected Scans 1 2 Image Pixel Size [um] 3.16 1.9 Filter No filter No filter Exposure [ms] 200 460 Rotation step [deg] 0.4 0.4 Use 360 Rotation No No Flat Field Correction On On Rotation Direction CC CC Type of Motion Step and Shoot Step and Shoot This method resulted in image data that could be processed to extract exoskeleton geometry, but it was unreliable for muscle information. A sample X-ray image from the scan is shown in Figure 19 below. There were also air gaps and cavities present in the

37 images that made it difficult to determine any significant contribution to the internal anatomy of the specimen.

Figure 19: X-Ray image of F. exsectoides from CT scan using the first specimen preparation protocol. The second method was modeled after a combination of protocol recommendations for preparing insects for micro-imaging. The specimen was placed in a killing jar with ethyl acetate. Once dead, it was placed in a 1:1 mixture of Bouin’s solution and ethanol [18] to fixate the specimen and retain tissue geometry for 24 hours

[19]. It was then transferred to 95% ethanol and then 100% ethanol for 30 minutes each

[19] [20]. The specimen was then stained in a 1% (weight/volume) Iodine solution for 22 hours and washed with ethanol as desired [20] [21]. The stain was used to increase the contrast between muscle tissue and other internal features. The specimens were then stored in ethanol until imaging. See Appendix F: CT Specimen Staining and Preparation

Protocol for more detailed protocols. The specimen was initially prepared to be imaged in

38 alcohol following Metscher’s recommendation [18], but the contrast was very poor between the specimen body and the fluid. The sample was eventually imaged in a PCR tube with the alcohol removed. The scanner parameters used for this scan are shown in

Table 6. This method resulted in images that contained more muscle detail, as shown below in Figure 20.

Figure 20: X-Ray image of F. exsectoides from CT scan using the second specimen preparation protocol Unfortunately, because the alcohol was removed immediately prior to the scan, the specimen settled and shifted during the scan, which resulted in un-usable data. The images, however, show that the fixation reduced the amount of air cavities and the staining improved muscle detail as shown by the striations in Figure 20. A modified

39 protocol for future imaging will include preparation and specimen mounting technique for imaging in air.

5.3 SEM Methods and Images

A variety of specimens were used for SEM study. Whole specimens were killed in

70% ethanol and allowed to dry overnight in a covered petri dish. Ruptured specimens were killed via tensile decapitation using fine-tipped forceps or removed from the experimental apparatus and also allowed to dry overnight in a covered petri dish. One day prior to SEM imaging, the specimens were mounted on aluminum SEM pin studs obtained from Ted Pella, Inc. (Product Number: 16111) using conductive carbon adhesive tabs (Product Number: 16084-1). The mounted specimens were then sputter coated with a conductive layer of gold-palladium. The following day, specimens were imaged using a Quanta 200 SEM operated at low vacuum, and an acceleration voltage of

15 kV with an Everhart-Thornley secondary electron detector.

Whole specimens were imaged to provide an idea of external geometry and structure of the neck joint. The neck is an exoskeleton system that has localized soft membrane to allow for range of motion. As discussed in Chapter 3, joint membranes in other insects have features such as surface structures and folds that contribute to the function of the joint (e.g., directional movement, surface stiffness/rigidity, and positioning). Figure 21 is an SEM micrograph of the ventral side of the neck of a

Formica specimen. The top of the image shows the underside of the head and the bottom right and left show the “chest plates” on the thorax; both are comprised of hard exoskeleton. In between, the membrane consists of two surface structure regions. The portion near the thorax is a field of armor-like bumps while the area near the head is

40 smooth with two series of setae. These setae are most likely used as position sensors for the head and neck joint. The dark areas to the right and left of the smooth membrane are the posterior tentorium pits.

Figure 21: Ventral view of the neck membrane of a F. exsectoides specimen (Specimen 1) It is unclear as to why there are two distinct areas of surface microstructure on the membrane. Based on the work done by Gorb, the armored area could provide friction at the interfacing surfaces between the membrane and the thoracic exoskeleton, increased stiffness, and/or a deterministic positioning and extension system. The smooth membrane could provide another degree of extension or specific region for deformation [10] [11]

[22].

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SEM images of ruptured specimens provided a sense of the failure mode for the neck joint under tensile loading. Figure 22 shows that the rupture location of the neck joint occurs at the neck-head transition in the smooth area of the membrane.

Figure 22: Posterior view of a head from a ruptured specimen (Specimen 5) Figure 23 shows the rupture surface of the exoskeleton and its laminar structure in a region of stiffer material. The speckling on the internal surfaces in Figure 23b could be ruptured cross-fibers that failed and caused delamination in that particular area.

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Figure 23: Ruptured exoskeleton in the neck area from Specimen 5 The observations made with the SEM images provided a supplement and comparison to the results of the finite element simulations of tensile loading of the neck joint.

5.4 Conversion of MicroCT Data to a 3-Dimensional Mesh

The raw microCT data comprised a series of X-Ray images taken as the specimen was rotated on a stage within the scanner. This series of images was processed using

CTAn, a software program provided by SkyScan. Within CTAn, adjustments were made to parameters for misalignment compensation, ring artifacts reduction, and beam hardening correction. CTAn then processed the raw images into a series of cross- sectional slices, a sample of which is shown in Figure 24. These slices could then be imported as a series into specialized software that provides tools for converting the 2- dimensional data into 3-dimensional models and finite element meshes.

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Figure 24: Cross-sectional slice of the processed CT images Two different software packages were used to evaluate their ease of use and effectiveness. Both packages contained their own set of tools and work flow procedure for the segmentation of the images. Each image slice was prepared at specific distances through the specimen (the same value as the pixel resolution: in this case, 3.16 um/pixel); the software assigned this value as a “thickness” for each pixel, making them volumetric pixels or voxels. Segmentation involves the labeling of these voxels as separate from the background or as different anatomical parts.

The first software that was tested was Amira Version 5.4; it was evaluated for a total of 15 days. The voxel grayscale value threshold tools could be used to separate the body of the ant from the darker background very easily. However, it was difficult to separate the exoskeleton from the body because it was done manually with a paintbrush

44 tool. Only a partial model was segmented during the 15-day trial; Figure 25 shows the results of the segmentation in Amira.

Figure 25: Segmentation in Amira. A) Cross-sectional slice; B) The position of the slice in (A) shown in 3D; C) Full model showing the segmented body from the back ground; D) The exoskeleton (red), tentorium (teal), nervous tissue (blue), eyes (yellow), and esophagus (magenta) segmentations. The second software that was tested was SimpleWare’s ScanIP with the +FE module for generating meshes, Version 4.3.5. ScanIP included a variety of imaging filters to further process the 2-dimensional slices that were imported into the program (such as pixel smoothing and binarization). There were also a greater number of segmentation tools available. The greyscale value threshold tool allowed the specification of both

45 ceiling and floor values which resulted in a smoother surface approximation for the segmentation. The exoskeleton was quickly extracted from the entire body through a series of “erosions” of the labeling to match the thickness of the exoskeleton and Boolean operations for multiple labels. The segmentations were then modified manually, layer-by- layer to ensure continuity. Figure 26 below shows the results of the initial segmentation using SimpleWare.

Figure 26: SimpleWare segmentation of exoskeleton (tan), tentorium (green), and esophagus (teal). The full model shown above was used as a visual aid for understanding the internal geometry of the neck, tentorium, and esophagus. It was also used to extract geometric measurements for calculating the nominal stress for the experiments. The esophagus was found to have an average outer diameter of 0.132mm and an average thickness of 8.94E-3mm. The neck membrane was found to have an average outer diameter of 0.257mm and an average thickness of 1.68E-2mm. These were used to approximate the structure as tubular in nature with a cross-sectional area of 1.61E-2 mm2.

Figure 27 shows a cross section of the neck and membrane thickness measurement.

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Figure 27: Neck joint cross-section showing the head (blue), neck membrane (purple), esophagus (teal), and thoracic plates (orange). The entire model could not be meshed because of computational limitations, so it was cropped to concentrate on the neck joint area. The cropped area maintained the hard exoskeleton components of the head and thorax for rigidity and the application of far- field boundary and loading conditions. The neck membrane was separated from the hard exoskeleton in the head and thoracic segments; the tentorium was labeled as a continuous structure with the head exoskeleton and the esophagus that runs through the neck. Figure

28 shows a full and cutaway view of the cropped neck joint.

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Figure 28: Segmentation of cropped neck joint including the head exoskeleton and tentorium (blue), thoracic segments (orange), neck membrane (purple), and esophagus (teal). After the completion of voxel segmentation, the data was then converted to a finite element mesh using the +FE Free and +FE Grid algorithms to compare the quality of the mesh and elements generated. The +FE Grid algorithm produces a combination of tetrahedral (C3D4H in Abaqus) and hexahedral (C3D8H in Abaqus) linear hybrid elements with options for surface smoothing and mesh refinement. The +FE Free algorithm begins with the +FE Grid algorithm to generate a surface that is extracted for re-meshing using only tetrahedral elements and a Delaunay/Advancing Front method to mesh the interior volume. The result from the +FE Free algorithm using an overall coarseness parameter and localized refinement around the neck was a smoother model and fewer elements than the +FE Grid algorithm. However, +FE Free also generated more than 1000 elements with relatively small volumes, causing an error to occur in the finite element program, Abaqus, when running an element check. As a result, the mesh

48 generated with +FE Grid was used for the final FE model. ScanIP+FE exported the mesh as an Abaqus input file, which was then imported into Abaqus CAE. The mesh statistics are shown in Table 7.

Table 7: SimpleWare Mesh Generation Statistics

6594672 Number of Volume Elements 5350843 Number of Tetrahedral Elements 1243829 Number of Hexahedral Elements 0.797975 Total Volume of Elements [mm^2] 0.142855 Total Volume of Tetrahedral Elements [mm^2] 0.65512 Total Volume of Hexhedral Elements [mm^2] 648489 Number of Nodes 0.724786 Mean in-out Aspect Ratio 0.0330834 Worst in-out Aspect Ratio 1 (0.0000%) Number of Elements with in-out Aspect Ratio less than 0.1 1.92498 Mean Edge Length Aspect Ratio 27.9297 Max Edge Length Aspect Ratio 7082 (0.1074%) Number of Elements with Edge Length Greater than 10 0.395187 Mean Angular Skew 0.964272 Max Angular Skew 0.422979 Mean Tetrahedral Volume Skew 0.995935 Max Tetrahedral Volume Skew The statistics that indicate the quality of the mesh are the in-out and edge length aspect ratios. The edge length aspect ratio is a comparison between the lengths of longest edge of the element and its shortest edge. SimpleWare recommends this ratio to be less than 10. However, Dompierre, et. al., suggests that this measure should not apply to 3- dimensional shapes because it fails to detect nearly planar elements [23]. The in-out aspect ratio is a comparison of the radius of a sphere inscribed within the element and a sphere circumscribed around it. SimpleWare calculates the inverted in-out aspect ratio as follows:

49

It is recommended that the in-out aspect ratio be greater than 0.1, but a value of 0.05 is expected to be above the quality at which FE software would issue an error in the element check [24]. This mesh contained only one element that had an in-out aspect ratio lower than 0.1 and Abaqus did not issue an error during the element check.

5.5 Finite Element Model

The input file generated by ScanIP was imported into a model database in Abaqus

CAE. The file included the mesh, element sets for each anatomical body (head, neck membrane, esophagus, and thorax), and empty material properties specifications, boundary conditions, constraints, and loads. The empty sets were defined within the

Abaqus CAE environment and are described in detail in the following subsection.

5.5.1 Model Data, Boundary Conditions, Loading, and Parameters

The material properties for each element set were based on either the experimental results or values from literature. The thorax and head were assigned a stiffness of 2668 N/mm^2 based on the average stiffness of locust sclerotized exoskeleton as reported by Hepburn [17]. Two material models were used to define the neck membrane and the results were evaluated against the experimental values. In the first model, the esophagus and neck membrane were assigned the same linear elastic stiffness of 233.24 MPa based on the average stiffness found from the high stiffness regime of the experiments and a Poisson’s ratio of 0.4. In the second model, the membranes were described as hyperelastic materials using the Neo-Hookean model and determined from the averaged experimental data as discussed in Chapter 4.4: Experimental Results. For all cases, a 0.2N reference load was applied to a single node at the back vertex of the esophagus along a defined vector. The head was fixed by constraining the nodes on the

50 front surface of the head and esophagus to zero displacement and rotation. The nodes on the back and bottom surfaces (on the x-y and x-z planes) of the thorax and esophagus were rigidly tied to the displacement of the load node. Figure 29 below shows the configuration of the boundary conditions on the mesh.

Figure 29: Abaqus mesh and applied boundary conditions (BN = back node, LN = load node). The load of 0.2N was applied as a linear ramp over a time step of one second. The models were configured such that geometric non-linearity and large displacement would be accounted for, and Abaqus would automatically select the size of the time and load increments to optimize convergence times.

5.5.2 Material Verification

To verify the performance of the material definitions, a simplified finite element model was created to record corresponding stress and strain. The model was a rectangular

51 prism with the same cross-sectional area as the neck joint and meshed using linear hybrid tetrahedral elements (C3D4 in Abaqus). One end of the bar was constrained to zero displacement and rotation while a pressure load totaling 0.2N was applied to the opposing surface. The material properties were specified as described in the previous section: the first with the linear elastic definition, and the second with the hyperelastic definition.

Figure 30 shows the deformed stress contour plots for each model. The hyperelastic model shows a significant amount of deformation compared with the linear elastic model.

Figure 30: Simplified FE models to verify material behavior. A) Linear elastic model and B) hyperelastic model. The models were directly compared to the experimental data using displacement data recorded during the simulation and calculating the nominal stress on the cross- section of the bar. The results were plotted directly with the averaged data in Figure 31.

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Figure 31: Material comparison of stress v. strain. The plot shows that the linear elastic model performs as expected based on the high stiffness material definition. The hyperelastic model does not agree as well with the averaged data that was used in the material definition. It should be noted, however, that the experimental data does not isolate the material behavior, but also includes geometric mechanical behavior such as the unfolding of the membrane. Therefore, the results of the hyperelastic model seem to reasonably approximate the material behavior.

5.5.3 Model Results

To compare the material definitions, the load was applied along a 45 degree vector and the displacement of the load node and a node on the back of the thoracic exoskeleton was recorded at each time increment during the step. The deformed stress

53 contour plots were also used to evaluate the geometric behavior as a result of the material definition, as shown in Figure 32.

Figure 32: Side-view cuts through the deformed stress contour plots of the deformed neck joints. A) Linear elastic material definition and B) hyperelastic material definition. The deformed contour plot shows that the application of the linear elastic material definition results in a relatively stiff neck membrane that does not deform significantly under loading. On the other hand, the hyperelastic model deforms significantly such that the membrane folds are unfolded and fully extended. Both models indicate a stress concentration at the material transition between the neck membrane and head exoskeleton.

The node displacement output from the model reflects the visual representation of the deformed stress contour plots. Figure 33 shows a plot of the displacement recorded at each node over the loading step.

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Figure 33: Comparison of material definitions and node displacements. The displacement was calculated along the load vector using the following equation:

̅ ̅ ̅ ̅ | ̅| ( ) | ̅| ( ) ( ) | ̅|| |̅ | |̅

Where ̅ is the displacement vector, ̅ is the load vector, and θ is the angle between the displacement and load vectors. The plot shows that the difference between the displacement recorded at the load and back nodes is small and that the non-linear material model achieves a greater displacement profile than the linear model. As a result, the displacement at the back node was recorded to mirror experimental procedures, and the non-linear material model was used for subsequent simulations.

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The subsequent simulations were used to determine the displacement profile as a function of loading direction and an approximate envelope of performance. Simulations were run with the load applied at 45, 60, 70, 75, 80, and 90 degrees. The plot in Figure 34 shows that the initial stiffness is strongly dependent on the loading angle in the low load regime, while it is similar in the high regime for all load cases.

Figure 34: Load v. displacement for varying load vectors. 5.6 Summary of Imaging and Modeling

The use of microCT and SEM imaging contributes to the understanding of the neck joint structure and failure mechanisms. Without the conversion of the microCT data to 3-dimensional models and meshes, the geometry of the neck membrane folds would not have been captured and modeled in the FE simulations. The protocol used to prepare the specimens for microCT scanning determines the amount of detail that can be shown

56 in the internal anatomy and, as a result, has limited the model used for this project to just the exoskeleton and esophageal membrane. SEM images were used to identify membranous areas around the neck joint and typical rupture locations at the neck-head transition.

The mesh that was generated from the microCT data was imported into FE software and the initial simulations were used to determine an appropriate material definition for the model. The results showed that the hyperelastic definition better approximated the behavior observed in the experiments and that the model behavior was dependent on the applied loading angle. The overall stiffness of the joint seemed to remain constant at higher loads, while there was a marked decrease in stiffness (or increase in displacement) at lower loads as the loading angle was increased. This behavior is consistent with the known geometry of the neck joint and may be the result of folds in the membrane that behave differently at various loading angles.

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Chapter 6. Discussion and Conclusion

6.1 Introduction

Using multiple tools to study the neck joint allows for the direct comparison and verification of results from modeling and experimental validation. The SEM micrographs of the rupture locations can also be used to compare to the stress-contour plots of the finite element model. The results from the mechanical testing and computational models show that the non-linear load-extension behavior of the neck joint is dependent on both the material specifications and geometric features of the membrane folds. These comparisons are discussed in the following sections with suggestions for future work that can build and expand upon the results obtained for this project.

6.2 MicroCT and SEM imaging

The images obtained using the SEM were useful in studying the neck joint surface structure and rupture locations. The images of the membrane surface revealed two regions of varying microstructure that could play a role in the operation of the joint. The region in the head-neck transition was smooth with a series of setae that are most likely used for position feedback, while the membrane at the thorax-neck transition contained armor-like plates on the surface. The plate structures could serve as both a local stiffener and provide a deterministic set of folding paths for the membrane. For the ruptured specimens, the SEM micrographs revealed that the failure location was at the neck-head

58 transition. This corroborates the stress concentration observed at the neck-head material transition in the finite element model results, as shown in Figure 36.

Figure 35: Comparison of the rupture location in an SEM micrograph of F. exsectoides and stress concentration in the FE model. The microCT data that was obtained was essential in the development of the 3- dimensional mesh for finite element analysis. Through the testing of two separate protocols for specimen preparation, one dataset was successfully produced that contained enough information to create a model of the exoskeleton and esophagus. The second protocol included fixation and tissue staining produced promising results for also obtaining muscle and ligament details, as shown in Figure 20. Unfortunately, the specimen moved during the scan, resulting in unusable data. In order to obtain muscle and ligament data for future models, a modified protocol will be developed to include the fixation and staining, and ensure the specimen does not move during scanning.

6.3 Experimental and Finite Element Results Comparison

The experimental results showed that the neck joint behavior had a non-linear relationship between load and displacement. It was originally hypothesized that the non-

59 linearity was mostly the result of the geometric effects of the membrane folds within the neck joint. To test this hypothesis, an average high stiffness value was applied to the neck region of the FE model. The results of this analysis showed that this assumption did not allow the neck to deform as expected and that the overall displacement of the body was very low and nearly linear compared to the experimental results, as shown in the load v. displacement plot in Figure 33. However, applying a hyperelastic material model to the neck membrane did result in significant membrane deformation, as expected, and an overall displacement that was on the same order of magnitude as the experimental results.

The results of the initial hyperelastic material model did not closely match the experimental data. As a result, multiple boundary conditions were tested to find one that best matched the results. In each variation of the boundary conditions, only the load direction was changed while maintaining all other conditions. The results of these iterations are plotted with the experimental data points in Figure 36. The plot shows a correlation between the loading direction and resulting displacement behavior. The differences in initial displacements indicate that the geometry of the folds is more dominant at higher loading angles. It also suggests that the majority of the experiments were conducted with an applied loading direction between 70 and 80 degrees – a less than optimal orientation for axial loading of the joint. The magnitude of the deformation in the initial low stiffness regime is highly sensitive to loading angle.

60

Figure 36: Comparison of experimental and finite element results. To confirm this, photographs were taken of two mounted specimens that were used in the experiments and directly compared to the orientation of the 3-dimensional models. Figure 37 shows both the original photographs and an overlay of the 3- dimensional model. The orientation of the heads in Figure 37A and Figure 37B correspond to a loading angles of 65 and 75 degrees, respectively. Both of these values fall within the ranges identified in the experimental and FE data comparison in Figure 36.

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Figure 37: Mounting and load angle comparisons. A) Position corresponds to a 65 degree loading and B) corresponds to a 75 degree loading. Furthermore, the experimental data corresponding to these specimens was directly compared to the FE load-displacement curves, as shown in Figure 38. The points do not closely align with the FE curves based on the loading angle orientation, but do indicate a similar relationship between the loading angle and initial stiffness – that is, the higher the loading angle, the higher the displacement, or lower stiffness, at low loads.

62

Figure 38: Comparison of experimental and FE head orientations. Diamonds indicate experimental data points (purple: 65 degree loading angle; red: 75 degree loading angle) and the lines represent the FE load-displacement curves. These results account for the range of the behavior envelope for the experimental data points and show that the mounting orientation strongly affects the displacement behavior at low loads. Future work with the centrifuge, or new device designs, should ensure a more consistent mounting position for the head or the experimental protocol should include the detailed recording of the position of each specimen.

6.4 Summary and Conclusions

The combination of experimentation, imaging, and modeling works well to create a better understanding of the neck joint as a system. The SEM images provided a reference for the external structure and failure locations of the neck joint; the microCT

63 scans were a foundation for the geometric internal and external features of the joint and finite element mesh; and the experiments provide a baseline and verification for the finite element model behavior. The comparison of the experimental and FE results indicate that the material itself has some degree of non-linearity and that the loading conditions play an important role in the overall deformation. Though the contribution of each facet was important, or even essential, the knowledge of the neck joint system as a whole is not complete and this project should serve as a spring board for future work.

For example, the experimental results give the load v. displacement data for the entire neck: including not just the neck membrane material, but the geometric folds and their potential surface structure behavior, muscles and ligaments, and esophagus.

However, the material specification that was used for the finite element model was based on the experimental data. Though the results for the FE model do show a correlation between the membrane geometry behavior and load direction, more work should be done to isolate the membrane material and characterize its properties – such as anisotropy,

Poisson’s ratio, and viscoelasticity/plasticity. Anisotropy would arise from the composite nature of the exoskeleton material in which chitin fibers could be preferentially aligned based on function [17]; the Poisson’s ratio for biological materials is not constant and changes significant over high strains [25]; and the viscoelasticity of the material will depend strongly on the degree of hydration of the material [10] [17] [25]. These properties could then be applied to the model and compared with experimental data collected from the joint. The difference could then be used to quantify the contribution of the internal anatomy to the strength of the joint. Finally, additional CT scans can be conducted to obtain muscle and ligament information that could be added to the finite

64 element model or to a kinematic model to extract information such as range of motion and directional strength.

The neck joint is a complex and highly integrated mechanical system. Efforts to understand the structure-function relationship in this system will contribute to the understanding of the design paradigms for optimized exoskeleton mechanisms. As we look to the future of human-assistive devices and ultra-light robotics, the development of

3-dimensional models for visual analysis and loading and kinematic simulation will also serve as tools for evaluating and comparing the functional morphology of multiple species and types of joints.

65

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70

Appendix A: Glossary

The following listing of terms is used to describe the exoskeleton and its features

[7] [26]:

Abdomen: The third, tail-end section of insects.

Abduction: the motion of moving away from the body.

Adduction: the motion of bringing closer to the body.

Arthrodial Membrane: Soft, stretchable cuticle found in larvae and between segments.

Chitin: a fibrous polymeric sugar that is the most commonly used tensile material in animals [5]. In exoskeleton, chitin exists as the fibrous phase within a protein matrix, whose increased content can also serve to increase the strength of the cuticle. Chitin fibers are typically the same size and length with diameters of about 2.8 nm [6] and about 0.4 µm long [7].

Cuticle: The external skeletal structure, secreted by the epidermis, composed of chitin and protein. The cuticle consists of several layers: the epicuticle, exocuticle, and endocuticle.

Figure 39: Layers of Cuticle [27] Desiccation: The process of removing water.

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Epidermis: The unicellular layer of exodermally derived integument that secretes the cuticle.

Ganglion: Grouping of nervous tissue.

Hemolymph: Circulatory fluid in arthropods.

In Vivo: Experimentation with a living specimen.

Larva: An immature insect after emerging from the egg.

Mandible: The jaws that can be jaw-like in shape for biting and chewing, or as stylets for piercing and sucking.

Microplate: A small hardened plate found on insect cuticle, typically on membranous cuticle [23].

Microtrichia: Subcellular cuticular hairs with several to many extensions per cell.

Resilin: a rubber-like protein whose name comes from the term resilience. This is because it is considered to return the largest amount of work that is imposed on it after the removal of the acting stress. In pure forms, it is used at the base of the legs of jumping insects and at wing hinges for flying insects for the storage of energy [5].

Sclerite: A plate on the body wall surrounded by membrane [4].

Sclerotization: Stiffening of the cuticle by cross linkage of proteins. An irreversible process that visibly darkens the exocuticle.

Setae: Hair-like structures that protrude from the cuticle.

Tagmata: A group of specialized segments in arthropods such as the head, thorax, and abdomen.

Tentorium: A set of internal struts within the head of insects. It is formed from the exoskeleton and the external formation points can be found at the anterior and posterior tentorium pits.

Thorax: The mid-section of insects.

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Appendix B: Circuit Diagrams

CNY70 Optosensor Circuit

Camera Switch Circuit

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Appendix C: Arduino Source Code

// Vienny Nguyen // 5/10/2012 - last update // Code to use feedback from strobe/break beam sensor to trigger a Sony SLR camera. // The camera can be triggered remotely by shorting out a set of contacts on the trigger port. // Shorting one set enables auto focus/half trigger, shorting the first set to the third contact // actuates the shutter/full trigger.

// The following was written with reference to Maurice Ribble's code to trigger a Canon SLR camera // using keyboard commands. http://www.glacialwanderer.com/hobbyrobotics // The tachometer readout was written with reference to: http://www.arduino.cc/playground/Learning/Tachometer

#include // User defined serial library

#define txPin 2 // User defined serial transmit pin #define focus_pin 6 // Pin used to switch focus #define shutter_pin 7 // Pin used to switch shutter #define opto_pin 5 // Pin used to read strobes #define click_pin 8 // Pin used to read for shutter "go" (normally LOW) #define strobe_pin 4 // Pin used to actuate strobe int opto_val = 0; // variable to store the strobe value int opto_val2 = 0; // Variable to compare change in state int click_val; // Variable to check clicker state const double t_sample = 2000; // Sample time for tachometer (increase this to increase accuracy) [ms] int camera_delay = 80; // Shutter release delay, [ms] unsigned long time_ref; // time holder to calc speed int pic_num = 1; int pic_count; double rpm; // Variable for speed [rpm] double rps; // Variable for speed [rps] long click_delay = 1000; // Minimum time between camera clicks [ms]

SoftwareSerial LCD = SoftwareSerial(13, txPin); // Setup new serial port void setup() { // Serial pin setup pinMode(txPin, OUTPUT); // Define transmit pin as output pinMode(13, INPUT); LCD.begin(9600); // Set the baud rate (9600 is max) clearLCD(); // LCD.print(0xFE, BYTE); //command flag // LCD.print(0x01, BYTE); //clear command. LCD.print("Setup");

// Camera pin setup pinMode(focus_pin, OUTPUT); digitalWrite(focus_pin, LOW); //High = camera focuses pinMode(shutter_pin, OUTPUT); digitalWrite(shutter_pin, LOW); //High = take a picture // Strobe/Centrifuge feedback setup pinMode(opto_pin, INPUT); pinMode(click_pin, INPUT); digitalWrite(click_pin, HIGH); pinMode(strobe_pin, OUTPUT); digitalWrite(strobe_pin, LOW);

//fix LCD: // while(1) // { // LCD.print(18, BYTE); // Reset to 9600 Baud // LCD.print(6, BYTE); //Reset character for 2 Lines on LCD // delay(50); // }

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} //////////////////////////////////////////////////////////////////////////////////////////////////// // End of SETUP //////////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////////////////////////// void loop() { // Initialize and check values throughout click_val = digitalRead(click_pin); opto_val = digitalRead(opto_pin); while(click_val == 1) // The approval button has not been pressed { clearLCD(); LCD.print("Wait for Button"); // digitalWrite(focus_pin, LOW); // digitalWrite(shutter_pin, LOW); click_val = digitalRead(click_pin); delay(50); } Tach(); // The approval button has been pressed (centrifuge up to speed) } //////////////////////////////////////////////////////////////////////////////////////////////// // End of LOOP ///////////////////////////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////////////////////////////

///////////////////////////////////////////////////////////////////////////////////////////////// // Tach() Function ///////////////////////////////////////////////////////////////////////////////////////////////// //void camera_snap() //{ // delay(rpm*60/1000-camera_delay); // Syncing factor // digitalWrite(focus_pin, HIGH); // digitalWrite(shutter_pin, HIGH); // delay(500); // Keep the signal on for a time // digitalWrite(focus_pin, LOW); // digitalWrite(shutter_pin, LOW); // delay(click_delay); // Wait a bit before starting over // pic_count++; // clearLCD(); // selectLineOne(); // LCD.print("Snap!"); //} void Tach() { int c = 0; //generic counter double count = 0; // counter to calc speed // if (click_val == 0) // "Approve" button to take pictures during speed increment clearLCD(); //clear LCD LCD.print("Click!"); //acknowledge click delay(500); //temporary delay for debugging

// First calculate the speed: time_ref = millis(); while((millis()-time_ref) < t_sample) { if(opto_val2 != opto_val) { count++; opto_val2 = opto_val; } opto_val = digitalRead(opto_pin); } rps = (count/24.0)/((t_sample)/1000); rpm = ((count)/24.0)/((t_sample)/1000.0)*60; clearLCD(); selectLineOne; LCD.print("RPS: "); LCD.print((int)rps); selectLineTwo(); LCD.print("RPM: "); LCD.print((int)rpm); delay(500);

// Then initiate camera clicking pic_count = 0; while(pic_count < pic_num) {

75

opto_val = digitalRead(opto_pin); if (opto_val != 0) //if it’s on the black, do this stuff { pic_count++; selectLineTwo(); LCD.print("Picture: "); LCD.print(pic_count); digitalWrite(focus_pin, HIGH); digitalWrite(shutter_pin, HIGH); delay(1000); // Keep the signal on for a time digitalWrite(focus_pin, LOW); digitalWrite(shutter_pin, LOW); delay(1000); // Wait a bit before starting over } else { digitalWrite(focus_pin, LOW); digitalWrite(shutter_pin, LOW); selectLineTwo(); LCD.print("Waiting"); } }

}

///////////////////////////////////////////////////////////////////////////////////////////////// // SerialLCD Functions based on the code from: // http://www.arduino.cc/playground/Learning/SparkFunSerLCD ///////////////////////////////////////////////////////////////////////////////////////////////// void selectLineOne(){ //puts the cursor at line 0 char 0. LCD.write(0xFE); //command flag LCD.write(128); //position } void clearLCD(){ LCD.write(0xFE); //command flag LCD.write(0x01); //clear command. selectLineOne(); } void selectLineTwo(){ //puts the cursor at line 2 char 0. LCD.write(0xFE); //command flag LCD.write(192); //position } void selectLineThree(){ //puts the cursor at line 3 char 0. LCD.write(0xFE); //command flag LCD.write(148); //position } void selectLineFour(){ //puts the cursor at line 4 char 0. LCD.write(0xFE); //command flag LCD.write(212); //position } void goTo(int position) { //position = line 1: 0-19, line 2: 20-39, etc, 79+ defaults back to 0 if (position<20){ LCD.write(0xFE); //command flag LCD.write((position+128)); //position }else if (position<40){LCD.write(0xFE); //command flag LCD.write((position+128+64-20)); //position }else if (position<60){LCD.write(0xFE); //command flag LCD.write((position+128+20-40)); //position }else if (position<80){LCD.write(0xFE); //command flag LCD.write((position+128+84-60)); //position } else { goTo(0); } } void backlightOn(){ //turns on the backlight LCD.write(0x7C); //command flag for backlight stuff LCD.write(157); //light level. } void backlightOff(){ //turns off the backlight LCD.write(0x7C); //command flag for backlight stuff LCD.write(128); //light level for off. } void backlight50(){ //sets the backlight at 50% brightness LCD.write(0x7C); //command flag for backlight stuff LCD.write(143); //light level for off. } void serCommand(){ //a general function to call the command flag for issuing all other commands LCD.write(0xFE); } /////////////////////////////////////////////////////////////////////////////////////////////////

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Appendix D: Mechanical Testing Protocol

1. Power on the Arduino and ensure that all the electronics are working.

2. Adjust camera settings and ensure correct position and focus.

3. Collect ant(s) from the nest using featherweight tweezers to reduce likelihood of

damage. (It may be more economical to test more than one ant at a time. Details

below.)

4. Weigh the ant(s) using a high precision scale to record the initial body weight.

5. Anesthetize the ant(s) for at least 5 minutes and no more than 10 minutes to ensure

that the specimen remains alive.

6. 1 minute prior to removing the specimen from the freezer, apply a drop of accelerant

onto the labeled area on the disk.

7. At the end of 5 minutes, remove the specimen from the freezer, reset the time for 15

minutes, and fix to the disk using cyanoacrylate glue:

a. Apply a drop of gap-filling, 5-15 second cyanoacrylate glue (INSTA-CURE+

from Bob Smith Industries, Inc.) to the disk.

b. Position the head, mandibles facing down into the glue, as upright as possible.

Position the body radially on the disk and maintain position until the glue has

set, about 15-20 seconds.

77

c. Using forceps, lift up the body away from the disk to expose the underside of

the head in the glue area. Apply a smaller drop of the same glue to a needle

point and apply to the underside of the head area, keeping clear of the neck.

d. Repeat steps 7a-7c if using multiple specimens.

8. Apply markers along the dorsal side of the body using water based acrylic paint.

a. Wet/prime a #003 paintbrush with water and remove excess water with a

tissue or paper towel.

b. Use the brush tip to collect a drop of white paint and apply to the:

i. Head (1x)

ii. Thorax (2x)

iii. Abdomen (1x)

c. Re-apply as necessary. Be sure to clean the brush after each use to maintain

integrity.

9. Install the disk onto the centrifuge using 6 3-48-3/16” cap head screws. Be sure to use

a cross pattern to ensure even tightening.

10. Record the state of the specimen (whether or not it is alive) and wait for the end of the

15 minute time period.

11. Begin the tensile test:

a. Set, but do not start a timer for 10 seconds.

b. For the incremental/hysteresis speed test:

i. Begin at variac setting 25 and start the timer

ii. At the end of the timer, initiate photo capture

iii. After the photo has been taken, advance the variac setting by 2.5

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iv. Repeat up to 52.5 and back down to 25. At the end, reduce the variac

back down to 0.

v. There will be a total of 23 photos captured.

c. For the constant speed test:

i. Begin at variac setting 25 and start the timer

ii. At the end of the timer, initiate photo capture

iii. After the photo has been taken, advance the variac setting by 5

iv. Repeat up to 45.

v. Maintain the variac setting at 45 and take a picture every 10 seconds.

vi. Repeat 18 times and reduce variac back down to 0.

12. At the end of each test, record the state of each specimen (whether or not it is alive)

and failure mode (if any).

13. Collect body parts if rupture occurred and weigh. If rupture did not occur, remove the

body and weigh.

14. Remove the disk from the apparatus and repeat as necessary.

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Appendix E: MATLAB Image Processing m-file

% Centrifuge Microscope Image analysis. % Written and modified by Vienny Nguyen and Carlos Castro. % Last modified 5/16/2012

% This program reads in a base image, rotates it to a set position using % user input, crops the image, creates line of interest with user input. % This base information is then used on all following images that are first % rotated to match the base image position.

%% Base image processing: clc, clear all, close all

% The following can change per run: ------% Define disk # disk = '5'; % Define test specimen test = 'D'; % Define number of images in test Ni = 9; % Define pixel location of center of rotation xm=1473; ym=2986; % ------% The following sets up the file name format and prompts user to select % first image in sequence. % Base name: prefix = ['Disk' disk 'Test' test ' '];

% Read in the base photo % by selecting, opening, and displaying original image [fn_1 pn_1]=uigetfile('.JPG','Select image file:'); filename = fullfile(pn_1,fn_1); A_1=imread(filename); figure(1) imshow(A_1),hold on % ------% Define number of control points for transformation. % Use corners of light colored spoke. ncp = 2; % Select the base control points % base_points = ginput(ncp); [sa sb sc]=size(A_1); % ------% Image rotating and cropping: r1=1099; r2=1440; % max radius of interest A_Xmin=ym-r2; A_Xmax=ym+r2; % X limits for reducing image to platform A_Ymin=xm-r2; A_Ymax=xm+r2; % Y limits for reducing image to platform A(:,:,:)=A_1(A_Xmin:A_Xmax,A_Ymin:A_Ymax,:); % cropping image to platform figure(2) imshow(A),hold on

80 xmA=xm-(A_Ymin-1); % shifting middle point to center of cropped image ymA=ym-(A_Xmin-1); % shifting middle point to center of cropped image theta=0:0.01:2*pi; xp1=r1*cos(theta)+xmA; % plotting circle with radius r1 yp1=r1*sin(theta)+ymA; plot(xp1,yp1,'r','linewidth',2) xp2=r2*cos(theta)+xmA; % plotting circle with radius r2 yp2=r2*sin(theta)+ymA; plot(xp2,yp2,'r','linewidth',2) plot(xmA,ymA,'ro','MarkerSize',12,'Linewidth',2)

% Reducing image to radial section [sa sb sc]=size(A);

B1=zeros(size(A)); B1(:,:,3)=10; figure(3) imshow(B1) for i=1:sa xd=i; yd=1:sb; Atemp=A(1,:,:); Atemp1=A(i,:,1); Atemp2=A(i,:,2); Atemp3=A(i,:,3); di=sqrt((yd-xmA).^2+(xd-ymA).^2); Atemp1(di>r2)=0; Atemp2(di>r2)=0; Atemp3(di>r2)=0; Atemp(1,:,1)=Atemp1; Atemp(1,:,2)=Atemp2; Atemp(1,:,3)=Atemp3; B1(i,:,:)=Atemp; clc clear Atemp Atemp1 Atemp2 Atemp3 di end

B1=uint8(B1); % converting image back to integer grayscale values figure(3) imshow(B1),hold on plot(xmA,ymA,'ro','MarkerSize',14,'Linewidth',2) [xR yR]=ginput(1); plot(xR,yR,'ro','MarkerSize',14,'Linewidth',2)

% rotate image so ant is at the bottom % first calculate angle of rotation using selected point and mid-point theta=atan((xR-xmA)/(yR-ymA))*180/pi; BR1=imrotate(B1,-1*theta,'bilinear'); if yR

% cropping rotated image to original size [saR sbR scR]=size(BR1); xmR=ceil(saR/2); ymR=ceil(sbR/2); plot(xmR,ymR,'ro','MarkerSize',12,'Linewidth',2)

Bmin=xmR-r2; Bmax=ymR+r2; 81

% BgSR is rotated image of the same size as B1 where ant is located at bottom BR=BR1(Bmin:Bmax,Bmin:Bmax,:); figure(6) imshow(BR),hold on plot(xmA,ymA,'ro','MarkerSize',14,'Linewidth',2)

% Now let's pick out just the portion of the image where the ant is sAx=400; sAy=600; Im_ant=BR((2*r2-sAy):(2*r2),(xmA-sAx/2):(xmA+sAx/2),:); % Converting to grayscale Im_gs=.2989*Im_ant(:,:,1)+.5870*Im_ant(:,:,2)+.1140*Im_ant(:,:,3); figure(7) imshow(Im_gs), hold on set(gcf,'Color',[1 1 1]) close all; k=1; scrsz = get(0,'ScreenSize'); % ------

%% Following images while k<=Ni % ------% selecting, opening, and displaying original image % [fn_1 pn_1]=uigetfile('.JPG','Select image file:'); filenum = int2str(k); fn_2 = [prefix filenum '.JPG']; filename2 = fullfile(pn_1,fn_2); A_2=imread(filename2); figure(1) imshow(A_2),hold on

[sa sb sc]=size(A_2); A_Xmin=ym-r2; A_Xmax=ym+r2; % X limits for reducing image to platform A_Ymin=xm-r2; A_Ymax=xm+r2; % Y limits for reducing image to platform A(:,:,:)=A_2(A_Xmin:A_Xmax,A_Ymin:A_Ymax,:); % cropping image to view only platform

xmA=xm-(A_Ymin-1); % shifting middle point to center of cropped image ymA=ym-(A_Xmin-1); % shifting middle point to center of cropped image theta=0:0.01:2*pi; xp1=r1*cos(theta)+xmA; % plotting circle with radius r1 yp1=r1*sin(theta)+ymA; xp2=r2*cos(theta)+xmA; % plotting circle with radius r2 yp2=r2*sin(theta)+ymA;

[sa sb sc]=size(A);

B1=zeros(size(A)); B1(:,:,3)=10; figure(3) imshow(B1)

for i=1:sa xd=i; yd=1:sb; Atemp=A(1,:,:); Atemp1=A(i,:,1);

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Atemp2=A(i,:,2); Atemp3=A(i,:,3); di=sqrt((yd-xmA).^2+(xd-ymA).^2); Atemp1(di>r2)=0; Atemp2(di>r2)=0; Atemp3(di>r2)=0; Atemp(1,:,1)=Atemp1; Atemp(1,:,2)=Atemp2; Atemp(1,:,3)=Atemp3; B1(i,:,:)=Atemp; clc clear Atemp Atemp1 Atemp2 Atemp3 di end

B1=uint8(B1); % converting image back to integer grayscale values figure(3) imshow(B1),hold on plot(xmA,ymA,'ro','MarkerSize',14,'Linewidth',2) [xR yR]=ginput(1); plot(xR,yR,'ro','MarkerSize',14,'Linewidth',2)

% rotate image so ant is at the bottom % first calculate angle of rotation using selected point and mid-point theta=atan((xR-xmA)/(yR-ymA))*180/pi; BR1=imrotate(B1,-1*theta,'bilinear'); if yR

% cropping rotated image to original size [saR sbR scR]=size(BR1); xmR=ceil(saR/2); ymR=ceil(sbR/2); plot(xmR,ymR,'ro','MarkerSize',12,'Linewidth',2)

Bmin=xmR-r2; Bmax=ymR+r2;

% BR is rotated image of the same size as B1 where ant is located at bottom BR=BR1(Bmin:Bmax,Bmin:Bmax,:); figure(6) imshow(BR),hold on plot(xmA,ymA,'ro','MarkerSize',14,'Linewidth',2)

% ------%% Now let's pick out just the portion of the image where the ant is and % plot in pre-sized windows % sAx and sAy define the size of the cropped image of the ant sAx=400; sAy=600; Im_ant=BR((2*r2-sAy):(2*r2),(xmA-sAx/2):(xmA+sAx/2),:);

% Converting to grayscale Im_gs=.2989*Im_ant(:,:,1)+.5870*Im_ant(:,:,2)+.1140*Im_ant(:,:,3);

if k<=6 clips = figure(7); set(gcf,'OuterPosition',[10 10 0.9*scrsz(3) 0.45*scrsz(4)]) subplot(1,6,k) imshow(Im_gs), hold on set(gcf,'Color',[1 1 1])

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elseif k>6 && k<=12 clips = figure(9); set(gcf,'OuterPosition',[10 10 0.9*scrsz(3) 0.45*scrsz(4)]) subplot(1,6,k-6) imshow(Im_gs), hold on set(gcf,'Color',[1 1 1])

elseif k>12 && k<=18 clips = figure(11); set(gcf,'OuterPosition',[10 10 0.9*scrsz(3) 0.45*scrsz(4)]) subplot(1,6,k-12) imshow(Im_gs), hold on set(gcf,'Color',[1 1 1])

else clips = figure(13); set(gcf,'OuterPosition',[10 10 0.9*scrsz(3) 0.45*scrsz(4)]) subplot(1,6,k-18) imshow(Im_gs), hold on set(gcf,'Color',[1 1 1])

end

% Rotating points picked earlier to define ant profile % Rearranging picked spots in terms of distance from center(so it doesn't % matter what order spots are picked) [xL yL]=ginput(2); dxL=sqrt((xL-xmA).^2+(yL-ymA).^2); [md id]=max(dxL); if id==1 xa1=xL(1); ya1=yL(1); xa2=xL(2); ya2=yL(2); else xa1=xL(2); ya1=yL(2); xa2=xL(1); ya2=yL(1); end

R = sqrt((xa1-xa2)^2+(ya1-ya2)^2); Im_top=2*r2-sAy; plot(xa1,ya1,'ro','MarkerSize',12,'Linewidth',1) plot(xa2,ya2,'ro','MarkerSize',12,'Linewidth',1) xx=[xa1 xa2]; yy=[ya1 ya2]; c=polyfit(yy,xx,1); yp=min(yy):(max(yy)-min(yy))/R:max(yy); xp=yp*c(1)+c(2); plot(xp,yp,'r','linewidth',1)

% ------%% Print to clips to separate files:

if k == 6 || (k == Ni && k<6) clipsname = ['clips_d' disk '_s' test '1.fig']; saveas(gcf,clipsname) elseif k == 12 || (k == Ni && k<12) clipsname = ['clips_d' disk '_s' test '2.fig']; saveas(gcf,clipsname) elseif k == 18 || (k == Ni && k<18) clipsname = ['clips_d' disk '_s' test '3.fig']; 84

saveas(gcf,clipsname) elseif k == 24 || (k == Ni && k<24) clipsname = ['clips_d' disk '_s' test '4.fig']; saveas(gcf,clipsname) end

% ------%% Determining grayscale profile of ant and plotting in presized windows gs_ant=zeros(size(xp)); for i=1:length(xp) gs_ant(i)=Im_gs(floor(yp(i)),floor(xp(i))); end

if k<=6 gs = figure(8); set(gcf,'OuterPosition',[10 scrsz(4)/2 0.9*scrsz(3) 0.45*scrsz(4)]) subplot(1,6,k) plot(1:length(xp),gs_ant,'k','Linewidth',2) ylabel('Grayscale Values','FontSize',16) set(gcf,'Color',[1 1 1]) if k == 6 || k == Ni gsname = ['gs_d' disk '_s' test '1.fig']; saveas(gcf,gsname) end elseif k>6 && k<=12 gs = figure(10); set(gcf,'OuterPosition',[10 scrsz(4)/2 0.9*scrsz(3) 0.45*scrsz(4)]) subplot(1,6,k-6) plot(1:length(xp),gs_ant,'k','Linewidth',2) ylabel('Grayscale Values','FontSize',16) set(gcf,'Color',[1 1 1]) if k == 12 || k == Ni gsname = ['gs_d' disk '_s' test '2.fig']; saveas(gcf,gsname) end elseif k>12 && k<=18 gs = figure(12); set(gcf,'OuterPosition',[10 scrsz(4)/2 0.9*scrsz(3) 0.45*scrsz(4)]) subplot(1,6,k-12) plot(1:length(xp),gs_ant,'k','Linewidth',2) ylabel('Grayscale Values','FontSize',16) set(gcf,'Color',[1 1 1]) if k == 18 || k == Ni gsname = ['gs_d' disk '_s' test '3.fig']; saveas(gcf,gsname) end else gs = figure(14); set(gcf,'OuterPosition',[10 scrsz(4)/2 0.9*scrsz(3) 0.45*scrsz(4)]) subplot(1,6,k-18) plot(1:length(xp),gs_ant,'k','Linewidth',2) ylabel('Grayscale Values','FontSize',16) set(gcf,'Color',[1 1 1]) if k == Ni || k == Ni gsname = ['gs_d' disk '_s' test '4.fig']; saveas(gcf,gsname) end end

k=k+1; % ------end

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Appendix F: CT Specimen Staining and Preparation Protocol

Procedure Materials

Anesthetization 1) Drop specimen into insect saline (6- 1) 6-8 g NaCl/liter H2O (Optional) 8grams NaCl/liter of water) for at least 30 minutes or until insect stops struggling [19] 2) Place in refrigerator for about 15 minutes until no movement Killing 1) Place specimen in killing jar and wait 1) A couple of teaspoons of until dead ethyl acetate or acetone 2) Try to minimize time between death and free nail polish remover next step Fixation 1) Transfer specimen to container with 1) 20x volume of specimen fixation mixture as specified of fixation mixture [19] 2) Fix for 1-3 days [19] 2) 1:1 ratio of Bouin’s with 3) Transfer directly to 95% ethanol and 100% ethanol [21] keep for at least 30 minutes [19] [20] 3) 95% ethanol Wash/detracting 1) Transfer to 100% ethanol for 30 minutes 1) 100% ethanol water [20] 2) May repeat if desired to remove yellow pigment from leftover Bouin’s, but not necessary [19] [20] Staining 1) Dissolve I2 in absolute ethanol or 1) 1g Iodine (I2 ) methanol. [18] 2) 100 mL absolute ethanol 2) Transfer specimen to staining fluid for 22 hours [20] 3) Wash with 100% ethanol as desired, but 3) Absolute Ethanol for not necessary [21] washing Mounting [18] 1) If using pipette tips, heat seal one of 1) 2 PCR tubes or pipette them – this will be the container side. tips (0.2mL suggested?) 2) Cut the other tube/tip so that the contain 2) Absolute Ethanol fits within. 3) Using sticky tack, mount one tip/tube within another inverted tip/tube. The inverted tip/tube will act as the base that will mount within the CT machine. 4) Fill the top tube/tip with ethanol and transfer the specimen to this container. 5) Arrange the specimen within the conical tip to release air bubbles and minimize movement during the scan.

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