Breathing of Humans and Its Simulation

Breathing of Humans and its Simulation

Mina Nishi

LSTM-Erlangen Institute of Fluid Mechanics Friedlich-Alexander-University Erlangen-Nuremberg Cauerstr.4, D-91058 Erlangen

June 14, 2004 Abstract

In this thesis, a breathing flow rate monitoring system and a mechanical breathing simulator are developed, constructed and tested for the experimental investigation of human breathing. Human breathing is a combination of three lung functions, ventilation, diffusion and circulation. In the present thesis, ventilation functioning is focused for the measurment and simulation. One of the most interesting features of ventilation functioning is its time varying volume flow rate. To measure this, the breathing mask which covers nose and mouth are used with cooperating with the thermal sensor. The sensor is called Time of Flight sensor, which is environmental condition, like temperature or humidity, independent and direction sensitive. The sensor gives two different information, one is the direction signal and the other signal is proportional to the mass flow rate. With this system, the ventilation volume flow rate can be precisely measured so that the exact human ventilation simulation will be realized. The sampled raw data of human ventilation will be analyzed to obtain the typical ventilation curve which is used for diagnosis of lung functioning defection. The second important part of this thesis is to simulate human ventilation with certain equipment which can reproduce any kind of ventilation curve. The simulation system is constructed with the mass flow contoroller which is applied for the exhalation simulation and for the inhalation simulation, volume flow controller, a proportional valve which is operated with vacuum pump and chamber. The whole ventilation simulation system is constructed and the result of the simulation is presented in this thesis. This work need to be developed further to make the breathing dummy or precise model of the human oropharynx so that it will provide the various possi- bilities, for example, to examine the particle deposition inside the human trachea etc. Contents

1 Introduction 2

2 A Brief Literature Survey 4 2.1 Breathing System of human being ...... 5 2.2 Measurement of the Human Breathing ...... 7 2.2.1 Parameters of Ventilation functioning tests ...... 9 2.2.2 Measurement Techniques of the Human Ventilation . . . . 11 2.2.3 Analyzing Technique of the Human Ventilation ...... 14 2.3 Breathing Simulator ...... 16

3 Development of a Breathing Measurement System 23 3.1 Construction and Equipment for Breathing Flow Rate Measurements 23 3.1.1 Geometry of the breathing Mask ...... 23 3.1.2 Incorporation of Flow Sensors ...... 24 3.1.3 Calibration and Time response of the Sensor ...... 30 3.1.4 Signal Processing ...... 35 3.2 Final Measurements ...... 35

4 Realization of a Ventilation Simulator 39 4.1 Construction of ventilation Simulator ...... 39 4.1.1 Instrumentations ...... 39 4.1.2 Volume Flow Control System for Exhalation ...... 41 4.1.3 Volume Flow Control System for Inhalation ...... 42 4.2 Calibration of Combined Values ...... 43 4.3 Veriﬁcation Test of the Simulator ...... 45 4.4 Application of mass ﬂow rate control system as an exhalation unit 45

5 Conclusions, Final Remarks and Outlook 47 CONTENTS ii

A numerical calculation of the three time components of the time of ﬂight sensor 50 A.1 principle of Operation ...... 50 A.1.1 Response of the sending wire ...... 50 A.1.2 Time-of-ﬂight calculations ...... 53 A.1.3 Response of the receiving wire ...... 58 A.2 Discussion of Responses of Sending and Receiving Wires . . . . . 60 List of Figures

2.1 Respiratory System ...... 5 2.2 Schematic Representation of Lung volumes ...... 10 2.3 Volume-Displacement Spirometer ...... 12 2.4 Various Spirometers ...... 13 2.5 Flow Volume Loop ...... 15 2.6 Classification of Abnormal Ventilation Functioning ...... 16 2.7 Mechanical Ventilator ...... 17 2.8 Digital Image of Active Servo Lung 5000 ...... 18 2.9 Experimental setup of the flow field in Humans’ Oropharynx . . . 20 2.10 Idealized Model geometry of human oropharynx ...... 20 2.11 Schematic aerosol experimental setup with Humans’ Inhaler . . . 21 2.12 3-D views of the oral airway model and bifurcation airway model . 22 2.13 Velocity and Non-dimensional temperature profiles ...... 22

3.1 Digital image and Schematic Figure of the mask with the sensor . 25 3.2 CTA Ventilation measurement ...... 27 3.3 Configuration of the Time of Flight Sensor ...... 28 3.4 Digital Image of the Time of Flight Sensor ...... 29 3.5 Schematic description of Time of Flight Sensor ...... 30 3.6 Measurement of time difference ...... 31 3.7 Time difference and the summation versus the flow velocity . . . 31 3.8 Calibration set up of the sensor for high velocity flow ...... 32 3.9 Calibration set up of the sensor for Low velocity flow ...... 33 3.10 Calibration curve of the extreme low velocity region ...... 33 3.11 Calibration curve of the Time of Flight Sensor ...... 34 3.12 Frequency response of the Time-of-Flight sensor ...... 36 3.13 Human Ventilation measurement with Time-of-Flight sensor . . . 38 LIST OF FIGURES 1

4.1 Conﬁguration of the ventilation simulation system ...... 40 4.2 Digital image of the proportional valve ...... 41 4.3 Calibration Curve for the Exhalation Simulation ...... 42 4.4 Calibration Curve for the Inhalation Simulation ...... 43 4.5 Averaged Calibration Curve for Combined Condition ...... 44 4.6 Simulation of the Human Ventilation ...... 46 4.7 Simulation of the Human Ventilation with Mass Flow Controller . 46

A.1 Sketch of the time of flight wires of sensor ...... 51 A.2 Theoretical prediction of sending wire time constant ...... 54 A.3 Theoretical prediction of fluid time of flight ...... 56 A.4 Fluid time of flight plotted on log scales ...... 57 A.5 Theoretical prediction of fluid time of flight as a function of Peclet number ...... 57 A.6 Detected time of flight versus the flow velocity ...... 58 A.7 Theoretical prediction of receiving wire time constant ...... 59 Chapter 1

Introduction

In various fields of medicine like physiology or Aerosol medicine, investigations related to the breathing of human beings have gained an increasing interest. Mainly this work is concentrated on the instantaneous volume flow rate through the mouth and nose of different individuals. Breathing is a physiological function which is a combination of three functions, ventilation, perfusion (diffusion) and circulation. For this thesis work, the ventilation function is the target of the monitoring and simulation. The monitoring ventilation is interesting especially for the people who work in medical field to diagnose the lung disease etc. as well as the people who try to simulate the human ventilation mechanically or numerically. There are two different kinds of Human Breathing simulator; one is used for the patients who have the breathing problem, this can be called mechanical ventilator (Machine aided breathing system) and the other is the pure breathing simulator for the measurements in e.g., Human Toxicology field. Some researchers[13] have already developed the mechanical model of human oropharynx to investigate the deposition of the particulate matters on the wall of it. Once one develops the mechanical ventilation system and it is possible to cooporate with such oropharynx system so that one can examine the particle deposition. In Chapter 2, the measurement of the breathing in the clinics or medical laboratory is mainly discussed. The purpose of the measurement for the medical doctors is, for example, diagnosis of the disease. In the first section of this chapter, the breathing system of humans is briefly explained and in the second section, the measurement technique for the Human breathing, how to analyze the result of the measurement and the parameter of them are introduced. The human breathing simulator which is available in the world is introduced in the 3 last section. In chapter 3, the monitoring system of the human ventilation volume flow rate is discussed. The monitoring system including the breathing mask with mass flow rate sensor is developed so that time varying human ventilation of different individuals will be accurately sampled. For the sampling, firstly CTA is applied, however, the result has considerable error thus the time of flight sensor is applied for the necessity since it is not sensitive of the environmental condition like temperature and humidity of the exhaled air. In chapter 4, the experimental investigation of a mechanical ventilation simulator is described. Firstly, two proportional valves, which are incorporated either with vacuum chamber for the inhalation simulation or with pressurized air for the exhalation simulation, are operated by the program of the soft ware Lab view with data acquisition card to simulate the human ventilation. However, the exhalation simulation does not suit the original ventilation curve because the ventilation is time varying flow and simple proportional valve is not suitable for that simulation. Thus a mass flow controller with pressure transducer is applied for the ventilation simulation. The data line of real human ventilation curve is applied for this mechanical simulation. The whole simulation system and the result are presented in this chapter. The conclusions and final remarks are written in chapter 5. Chapter 2

A Brief Literature Survey

In this chapter, the work which is relevant to the breathing monitoring and simulation, is briefly explained in three sections as human breathing system, the measurement of the human ventilation and the human breathing simulator. Human breathing is a combination of the lung functions of ventilation, perfusion and circulation. There are many kinds of breathing functioning test, however, one of the test, ventilation functioning test is a great interest for the medical doctors and researchers since it gives the direct diagnosis of the lung disease. In the second section of this chapter, the measurement technique for the ventilation function which is mainly used in the clinics are referred and anlysing technique of the sampled data are briefly explained. In the third section, the breathing simulators are introduced. The fields of interest in developing a breathing simulator are various. Particularly to develop the breathing support machine(Mechanical Ventilator) is required for the patients who are suffered from various respiration diseases. Not only for the patients, but also once the breathing simulator is developed, it will be easy to make bench test of the breathing mask filter etc. For example, influence of the contamination of the environment for humans, namely the deposition of the particulate matter in the oropharynx, which field is called Human Toxicology (inhalation toxicology of air pollution) is one of the most promising fields with developing the breathing simulator. 2.1 Breathing System of human being 5

Figure 2.1: Respiratory System [5]

2.1 Breathing System of human being

Humans are the only mammal which breathes not only with the nose but also with the mouth. Normally humans breathe in through the nose because it allows humans to chew food and breathe at the same time since the nose is separated from the mouth by a bone called palate. And the other reason is that the nose works as a biological air conditioning unit and also it contains hairs which traps large dust particles so that if there is a lot of dust in the air one may also sneeze to remove it from the nostrils. In Fig.2.1 the human respiratory system is shown. After taking the air through nose or mouth then it passes into the throat and down the windpipe(trachea). The entrance of the trachea is protected by a valve, the epiglottis, which closes when one swallows food or drink. And then the air goes to the lungs. The lungs are found inside humans’ chest or thorax surrounded by the rib cage which protects them. The ribs also support the lungs and help to pump air in and out when humans breathe. This function is called ventilation which ﬂow is monitored and simulated in this thesis. The other part of the thorax (chest) which helps to pump air in and out is the diaphragm. The diaphragm is a sheet of ﬁber and muscle which rises and falls as 2.1 Breathing System of human being 6

Gas Inspired air (% ) Expired air (% ) Nitrogen 78 78 Oxygen 21 16 Carbon Dioxide 0.03 5 Water Vapor varies saturated

Table 2.1: Contents of the air of inhalation and exhalation

Temperature (◦C) Inspired air Expired air −70 +37 0 +37 +50 +37

Table 2.2: Temperature of the air of inhalation and exhalation[1] humans breathe. During breathing in (inhalation), skeletal muscles such as the diaphragm and external intercostals contract thereby increasing volume within the thorax and lungs. As volume within the air spaces of the lung (intrapulmonic volume) increases, air pressure within the lung (intrapulmonic pressure) falls below atmospheric pressure and air rushes into the lung. During breathing out (exhalation), the inspiratory muscles relax causing the volume of the thorax and lungs to be reduced. The reduction in intrapulmonic volume is accompanied by an increase in intrapulmonic pressure above atmospheric pressure, forcing pulmonary gas back into the atmosphere. Normally, unlabored expiration at rest is a passive event resulting from relaxation of inspiratory muscles. When an increase in pulmonary ventilation is required, such as during exercise, expiration becomes an active event dependent upon contraction of expiratory muscles that pull down the rib cage and compress the lungs. On average an adult human inspires and expires 10 to 20 cycle/min (the breathing frequencies or respiratory rate is 0.17 to 0.33 Hz) during normal quiet breathing (eupnea). This can increase to 25 cycle/min ( 0.42Hz ) during heavy exercise. Each time humans breathe the air 5 to 7 L/min which is inspired and expired, about 0.5 L of air moves into and out of the respiratory system. This volume is known as tidal volume (cf. 2.1.2). The product of tidal volume and respiratory rate is equal to the rate of 2.2 Measurement of the Human Breathing 7 pulmonary ventilation, also known as minute respiratory volume. A value within normal range is 7.5 L/min. This, however, is when humans are resting. If one begins to exercise, not only one breathes faster but also breathes deeper. An adult human has an extra 2.5 L of breath to call upon if needed. When taking heavy exercise a man could be breathing the air in and out up to 120 L/min. The air that one inspires and expires is a mixture of gases as it is shown in Table2.1. The most important of these are nitrogen, oxygen, carbon dioxide and water vapor. The air that one expires is not the same as the air of atmosphere as the water vapor in the atmosphere varies a lot depending upon the weather, for example, the air is saturated with water vapor if it is raining, instead, the air that one expires is always saturated with water vapor. The temperature of the air of the humans’ inhalation and exhalation may also change as it is shown in Table2.2. One breathes in cold air, the air is warmed up to body temperature by the blood in the many capillaries which are found close to the walls of the nasal cavity. These blood vessels also provide water which humidiﬁes the air if it is too dry so that it does not harm the lungs.

2.2 Measurement of the Human Breathing

In this section, the measurement of the breathing in the clinics or medical laboratory is mainly discussed. Medical doctors and researchers test the breathing functions for the following purposes:

1. Diagnosis of known or suspected lung disease

2. Treatment of lung disease, monitoring the eﬀect of preventive measures or diagnostic procedures

3. Establishing a prognosis

4. Pre-operative assessments

5. Evaluation of pulmonary disablement

6. Monitoring the respiratory health of populations

7. Interpretation of other volume dependent lung function tests 2.2 Measurement of the Human Breathing 8

Breathing is a physiological function which is a combination of three functions, ventilation, perfusion (diﬀusion) and circulation. The breathing functioning test can be categorized into 10 diﬀerent tests [2]:

1. Ventilation functioning tests e.g., Lung Volume test, Flow Volume curve analysis, Residual Volume Mea- surement, Air way resistance test, Lung Compliance test

2. Exercise load test e.g., Tredmill stress test

3. Sleeping respiration test e.g., Polysomnography

4. Air way sensitive test e.g., Astograph method, Body Plestymograph

5. Blood gas Analysis e.g., Artery blood test, Mixed blood test

6. Lung diﬀusion test e.g., DLCO (Diﬀusing Capacity for Carbon Monoxide Method)

7. Alveoli Gas diﬀusion test e.g., Gas Dilution method, Closing Volume method

8. Respiration regulation test, Ventilation response test e.g., CO2 ventilation response test, P0.1(Occlusion pressure test)

9. Circulation test

10. Others

In all these ten different kinds of breathing functioning test, the first three tests are most relevant topic for this thesis work and especially the first one, ventilation tests are most commonly used method in the clinics to detect different kinds of diseases. Thus, the Ventilation functioning tests is mainly discussed in the following. 2.2 Measurement of the Human Breathing 9

2.2.1 Parameters of Ventilation functioning tests

In Ventilation functioning tests, there are for example, airway resistance test and lung compliance test. The former measures the pressure difference developed per unit flow, measured as the difference in pressure between the mouth and that in alveoli. The latter measures the lung volume change per unit of pressure change. Since both are less related to the present thesis work no more details is given in this thesis. There are many parameters for the Lung Volume Test which can be divided in two parts, one is the volume of air when humans breathe in relaxed manner (unlabored respiration) and the other is the volume of the air of Labored respiration. All of them are recorded in liters and reported at Body Temperature, Pressure, and Saturated with water vapor (BTPS). Lung Volume of Unlabored Respiration The volume parameters of unlabored respiration, which is performed in a relaxed manner without haste or deliberately holding back is shown in Fig.2.2. The curve in that Figure is called Spirogram which presents a graphic display of inspired and expired air volume against time. Lung Volume of labored Respiration Secondly the volume parameters of labored respiration which is performed when humans respirate as forcefully and rapidly as possible. These parameters are important for the volume flow loop analysis which is discussed in section2.2.3.

Forced Vital Capacity (FVC) The maximum volume of gas that can be expired, after a maximal inspiration to total lung capacity.

forced inspiratory vital capacity (FIVC) A maneuver performed similarly beginning at maximal expiration and in- spiring.

Forced Expiratory Volume (FEVT ) The volume of gas expired during a given time interval (T second) from the beginning of the FVC maneuver. Of the various FEVT measurements the FEV1 is the most widely used.

Forced Expiratory Flowx-y (FEFx−y) The average ﬂow rate during a given interval (percent) of the FVC maneuver. The index x − y is used to denote the portion of the FVC for which 2.2 Measurement of the Human Breathing 10

Abbr. Full name Short description of the volume of the gas VC Vital Capacity full inspiration after a maximal expiration FRC Functional Residual Capacity remained in the lungs at the average the FRC level RV Residual Volume present in the lung at the end of a full expiration ERV Expiratory Reserve Volume maximally expired from the level of the FRC level TV Tidal Volume inspired or expired during a normal respiratory cycle IRV Inspiratory Reserve Volume inspired from the FRC level IC Inspiratory Capacity maximal volume which is inspired from the FRC level TLC Total Lung Capacity present in the lung at the end of a full inspiration

Figure 2.2: Schematic Representation of Lung volumes [3] 2.2 Measurement of the Human Breathing 11

this average flow is measured (mostly used as FEF25%-75%: the average flow rate for the liter of gas expired after the first 25% of FVC during an FVC maneuver).

Forced Inspiratory Flow (FIFx−y) The average ﬂow rate during a given interval (volume) of the FIVC maneuver.

Maximum Voluntary Ventilation (MVV) The largest volume that can be breathed during a 10- to 15- second interval with voluntary eﬀort. Normal values of healthy young men average between 150 to 200 L/min. (slightly lower in healthy women) and decreases with age in both men and women.

Peak Expiratory Flow Rate (PEFR) The maximum ﬂow rate attained during an FVC maneuver. Normal values for healthy young adults may exceed 600 L/min.

2.2.2 Measurement Techniques of the Human Ventilation

For the measurement of human ventilation functioning, spirometer is most commonly used in medical ﬁeld. As it is shown in Fig.2.3, Usually nose clip and mouthpiece are used for this measurement. There are various spirometers which can be divided in two groups. One is volume displacement spirometers and the other one is ﬂow-sensing spirometers. The Volume-Displacement spirometers provide a direct measure of respired volume for example, displacement of a bell, piston or bellows spirometer. Fig.2.3 is an example of the spirometer with displacement of a bell.

They are recorded in the spirogram (cf, Fig.2.2) and the parameters like FEV1, FVC and VC are calculated including correction to BTPS which is necessary for the accurate measurement since Expired air is at body temperature and saturated with water vapor but the air cools down in the spirometer. The problem of the Volume-Displacement spirometers is the poor dynamic characteristics. The response characteristics of them is faithful only for the recording of events occurring over seconds (FVC, FEV1) and they are not usually suﬃciently fast to accurately record rapid events (e.g. PEF measurements). On the other hand, ﬂow-sensing spirometers generally utilize a sensor that measures 2.2 Measurement of the Human Breathing 12

Figure 2.3: Volume-Displacement Spirometer [8]

flow as the primary signal and calculate volume by electronic (analog) or numerical (digital) integration of the flow signal. The most commonly used flow-sensing spirometers are with:

1. Pneumotachmeter,

2. Hot Wire Anemometer or

3. turbine blade as shown in Fig.2.4. However, the accuracy of each new sensor may need to be established. Accuracy and reproducibility depend on the stability and calibration of the electronic circuitry and appropriate correction of ﬂow and volume to BTPS conditions. For example, a small error when detecting 0 ﬂow rate can cause these devices to produce large errors in the measurement of FVC, as the error is con- tinually added during the time needed to complete the exhalation. With heavy use, the sensor may also change its calibration due to the condensation of water vapor. 2.2 Measurement of the Human Breathing 13

Figure 2.4: Various Spirometers[7] upper:FleischPneumotachometer, middle:Hot wire spirometer, bottom:Turbine spirometer 2.2 Measurement of the Human Breathing 14

The pneumotachograph derives the volume flow rate from the measurement of pressure drop over a fixed resistance, consisting of a bundle of parallel capillary tubes (Fleisch type pneumotachometer). The apparatus is designed in such a way that the air flowing through the resistance has a laminar profile, ensuring a direct proportionality between pressure drop over the resistance and flow. This condition is met only within a given range of flows. When this range is exceeded, the relationship between pressure drop and flow becomes nonlinear in the sense that the pressure drop increases progressively more for a given increase in flow. The limits of linearity should be known. Volume is obtained from analog or digital integration of the flow signal. It has its own error as it can be explained with the acceleration. Since the calibration is made under steady conditions, whereas ventilation is a time varying Pulsating flow. This will cause also the decelerations from the actual values especially for fast breathing measurement. The ventilation measurement with constant temperature anemometry his also inaccurate as the human ventilation is temperature varying and saturated with water vapor. This problem is discussed in detail in Section 3.3 with the actual ventilation measurement with CTA. The turbine spirometer measures inaccurately the flow rate of time varying Pulsating flow because of its inertia.

2.2.3 Analyzing Technique of the Human Ventilation

A hard copy of the spirogram(e.g. Fig.2.2) or ﬂow volume curve (Fig.2.5) gives valuable information of the ventilation functions. The factors which determine the size of normal lungs are: age, height, weight, stature, gender, posture, habits, ethnic group, reﬂex factors and daily activity pattern. The evaluation is, for example, predicted vital capacity which is calculated by the subject’s age, height, weight etc. is compared to the measured vital capacity. This is an example equation [4] of the predicted vital capacity:

Male: (27.63 − 0.112 ∗ age)∗height (ml) Female: (21.78 − 0.101 ∗ age)∗height (ml) But only for 17 < age < 70

Reduction in VC (e.g., less than 80%) can be caused by a loss of lung tissue. In general this may be the result of tissue destruction or resections (lobec- tomy), space-occupying lesions (tumors), or changes in the composition of the 2.2 Measurement of the Human Breathing 15

Figure 2.5: Flow Volume Loop [3] parenchyma itself (fibrosis). The VC is often reduced in obstructive lung disease. Other causes of a decreased VC can also be: depression of the respiratory centers or neuromuscular diseases, reduction of available thoracic space (pneumothorax, cardiac enlargement) and limitations of thoracic (kyphoscoliosis) or diaphrag- matic (pregnancy, ascites) movement, brain obstacle and the deformation of the thorax. The Volume Flow Loop (Fig.2.5) is a graphic analysis of the flow generated during the FVC maneuver plotted against volume change (maximal expiratory flow-volume MEFV) and is usually followed by the FIV maneuver, plotted similarly (maximal inspiratory flow volume MIFV). In a volume Flow Loop instantaneous flow at any lung volume over the VC can be read directly from its tracing.Flows at 75%, 50% and 25% of the VC are commonly reported as the V’max75, V’max50, and V’max25 respectively (the subscript referring to the per- centage of the lung volume (VC) remaining). Flow is also reported as FEF25%, FEF50%, and FEF75% (the subscript referring to the portion of the lung volume 2.3 Breathing Simulator 16

a: Normal subjects

b: Obstructive Ventilatory defect

c: Asthma

d: Restrictive Ventilatory Defect

e: Various Restrictive Ventilatory Defects

Figure 2.6: Classiﬁcation of Abnormal Ventilation Functioning [6]

(VC) that has been exhaled). If automatic timing is available the FEVT and

FEVT % can be determined for speciﬁc intervals. There are many interpretations from the shape of the curve as it is shown in Fig.2.6.

2.3 Breathing Simulator

There are two diﬀerent kinds of Human Breathing simulator; one is used for the patients who have the breathing problem, this can be called mechanical ventilator (Machine aided breathing system) and the other is the pure breathing simulator for the measurements in e.g., Human Toxicology ﬁeld. There are various breathing support system or mechanical ventilator available 2.3 Breathing Simulator 17

Figure 2.7: Mechanical Ventilator[22] in the market which works in the way that a Patient is connected to the ventilator by a endotracheal tube passed through the nose or mouth into the trachea. The mechanical ventilator delivers inspiratory gases directly into the person’s airway. Fig.2.7 is an example of mechanical ventilator. The other type of simulator ”Active Servo Lung 5000”[12] shown in Fig.2.8 is an example. This can not be connected to the patients as mechanical ventilator but it is used for the education of the medical students etc. Similar mechanism has the ventilation simulators are used by the researchers who study about the human toxicology. For example, Dr. Heenan et. al have constructed very precise human oropharynx model which is connected to the ventilation simulator[13] (Fig.2.9, Fig2.10 to study particle deposition. Dr. Matida et al constructed the 2.3 Breathing Simulator 18

Figure 2.8: Digital Image and Schematic description of Active Servo Lung 5000 2.3 Breathing Simulator 19 experimental setup to test the eﬃciency of aerosol deposition together with a commercial dry powder inhaler as it is shown in Fig.2.11 It is also interesting to simulate the particle deposition, or mass transfer in the human oropharynx. Sev- eral reserches[18][19][20] have made the models (Fig.2.12,Fig.2.13) and obtained interesting results. 2.3 Breathing Simulator 20

Figure 2.9: Schematic experimental setup of the ﬂow ﬁeld in Humans’ Oropharynx[13]

Figure 2.10: Idealized Model geometry of human oropharynx[13] 2.3 Breathing Simulator 21

Figure 2.11: Schematic aerosol experimental setup with Humans’ Inhaler[21] 2.3 Breathing Simulator 22

Figure 2.12: 3-D views of the oral airway model and bifurcation airway model[18]

Figure 2.13: Velocity and Non-dimensional temperature proﬁles[18] Chapter 3

Development of a Breathing Measurement System

In this chapter, the human ventilation measurement system which is cooperated with the time of flight sensor is described. The geometry of the designed measurement mask is shown in the first section and in the second section, the principle of the measurement sensor, time-of-flight sensor is briefly explained. In the third section, some verification experiments are shown and in the last section, the final measurement and the results are presented.

3.1 Construction and Equipment for Breathing Flow Rate Measurements

3.1.1 Geometry of the breathing Mask

It is necessary to construct the breathing measurement mask carefully to measure the volume flow rate of human ventilation accurately. There are two types of masks which are available in the market such as nose mask and the mask for mouth and nose. Human beings breath usually with nose, however, it is also true that it is the only mammal which breaths not only with the nose but also with the mouth because it has the ability of speaking. Thus it is required to use the mask which covers both properly. Medical researchers use commonly the equipment to measure the functioning of lung, such as spirometer (cf, chapter 2), which requires to use nose clips and subjects breathe only with mouth. In this thesis work, the mask which covers nose and mouth is selected to make 3.1 Construction and Equipment for Breathing Flow Rate Measurements 24 it sure the natural human ventilation will occur during the measurement, unlike the conventional spirometry. The mask is incorporated with the time of flight sensor, whose functioning principle explained in the next subsection. The breathing mask and measuring set up is described in Fig.3.1. To connect the breathing mask to the sensor, glass nozzle with the angle of 7◦ is applied to avoid the flow separation during the respiration. To homogenize the incoming flow and to protect the sensor wires from large aerosols which can cause measurement errors and even can destruct the wires, flow straightening mesh is placed at the exit of the breathing mask (the point A) and at the both entrance of the sensor (B and C). The volume flow rate is calculated based on that the cross sectional area where the thermal sensors are located and the velocity profile is 90% flat [9].

3.1.2 Incorporation of Flow Sensors

In this section, the incorporation of the sensor with the ventilation measurement is described. First sub section shows the measurement of the human ventilation with conventional Constant Temperature hot wire anemometry(CTA) is applied. The result shows the difference between the sums of the air volume of inhalation and exhalation in 5min-long measurement more than 10%, this difference is the measurement error because of the exhaled air variation in temperature and humidity. Thus, it is concluded that the new sensor must be used for the measurement of human ventilation. The second sub section will briefly explain about the principle of the time-of flight sensor and some verification experiments are described.

3.1.2.1 Human ventilation Measurement with CTA

The ﬁrst measurement of the human ventilation is done with CTA sensor. The result of the human ventilation measurement with the CTA sensors shown in Fig.3.2. The duration of the inhalation and the breathing frequency is correctly measured, however, the summation of the air volume of the inhalation and exhalation in 5min measurement contains more than 10% diﬀerence such as the inhalation is always more than that of exhalation due to the CTA sensor’s de- pendency on the temperature. Since the conventional Constant Temperature Hot Wire Anemometry (CTA) or Constant Current Hot Wire Anemometry (CCA) [10] are the measurement technique which is based on using the heat loss from 3.1 Construction and Equipment for Breathing Flow Rate Measurements 25

Figure 3.1: Digital image and Schematic Figure of the mask with the sensor 3.1 Construction and Equipment for Breathing Flow Rate Measurements 26

Sensor parameter Value

Wire diameterdw 12.5µm

Wire lengthlw 5mm Wire spacing∆x 1.5mm Excitation frequencyf 30Hz

Table 3.1: The parameter of the time of flight sensor the wire for the velocity calculation thus their accuracy is highly sensitive to the variation of the flow temperature. It gives less output signal if the temperature of the measured material is increased even though one calibrates the output signal of the CTA sensor with the temperature correction factor. This error is not only because of the temperature varying but also of the humidity in the flow. The exhaled air is saturated with water vapor since the heat transfer of the hot wire increases with increasing humidity[11]. Since the conventional hot wire anemometry does not measure the ventilation accurately, a new sensor had to be utilized instead of CTA sensor. One needs a sensor which is temperature independent and sensitive to the direction of the flow since breathing has basically tow directions. According to the principle of the time-of-flight sensor, the atmospheric temperature and the humidity do not effect on the accuracy of the measurement [9]. In the next sub section, the principle of time-of-flight is briefly explained.

3.1.2.2 The principle of Time-of-Flight sensor

The thermal sensor is chosen for the measurement because of its temperature independence and its directional sensitivity. (Figure 3.3) There are three parallel wires which are placed in the throat area. The middle one is the sending wire which is heated by an oscillating current at 30Hz frequency. The rest two wires are receiving wires, which detect the temperature variation in the wake of the sending wire, are located at a distance 1.5mm each from the sending wire. The length of all these heated wires, which are made of platinum, is 5mm and its diameter is 12.5µm. The sensor geometry is designed by the company Draeger[14] so that the form of the velocity profile is formed always turbulent velocity profile. Fig.3.3 depicts the configuration of the sensor. The throat inner diameter is 12.5mm and the volumetric flow rate can be calculated with the cross sectional 3.1 Construction and Equipment for Breathing Flow Rate Measurements 27

- Inhalation Exhalation 1 0.423 0.328 2 0.539 0.342 3 0.461 0.440 3 0.398 0.279 4 0.499 0.347 5 0.424 0.372 duration Sum of Inhaled air Sum of Exhaled air error% 18sec 2.74 2.10 23.2 60sec 6.4 5.4 15.6 280sec 30 24.8 17.3

Figure 3.2: CTA Ventilation measurement area and atmospheric temperature. The cross section, where the thermal sensor is located is slightly thinner than the opening of the sensor and the angle is 7◦. Since the breathing measurement will be two directional measurements, the geometry of the sensor must be symmetry. The principle of the sensor function is the following. For simplicity, only one directional sensor (two wire sensor) is discussed. In Fig.3.5 it is described two wires mounted perpendicular to the ﬂow to carry out time of ﬂight measurements which yield velocity information. The wire located in the upstream (wire A) 3.1 Construction and Equipment for Breathing Flow Rate Measurements 28

Figure 3.3: Configuration of the Time of Flight Sensor is electrically heated device providing time varying thermal signal to the flow. This resultant thermal signal is flown downstream to the receiving wire (wire B) which operates as a resistant thermometer, and detects the delayed arrival of the thermal signal. The measured time of flight and known distance between the sending and receiving wires permit the flow velocity to be calculated with the following equation.

∆x 4tf = U

Where ∆x is the distance between the hot wires and U is the flow velocity. Fig.3.6 shows the example of the time difference which are obtained from the sending wire and receiving wire signal. The signal which is given to the sending wire is sinusoidal varying electrical current and the receiving wire detects the temperature oscillation. This total time difference contains three different components, 1. the time of flight(convection by the fluid in the wake of the sending wire)

2. the thermal lag of the receiving wire 3.1 Construction and Equipment for Breathing Flow Rate Measurements 29

Figure 3.4: Digital Image of the Time of Flight Sensor 3.1 Construction and Equipment for Breathing Flow Rate Measurements 30

Figure 3.5: Schematic description of Time of Flight Sensor

3. the thermal lag of the sending wire

All time components can be numerically calculated as it is described in the Appendix[9]. Although there are three diﬀerent components, Fig.3.7 shows that in the low velocity range, the range of human ventilation measurement (0.15m/s to 2m/s), the thermal lag of the wires are negligible and only time of ﬂight is dominant.

3.1.3 Calibration and Time response of the Sensor

3.1.3.1 Calibration of the thermal sensor

For high volume flow rate such as more than 10L/min, Mass flow controller has been used and for the low volume flow rate such as less than 10L/min the calibration is done with the water chamber calibration since Mass flow controller has its own error if the volume flow rate is too less. The calibration of the sensor for high volume flow rate is done with the experimental set up which is shown in Fig.3.8. It is connected to the mass flow controller[15] with 6m pipe and connector so that the flow will be fully developed. In the connector the mesh is equipped thus the velocity profile of the cross section of the measuring point in the sensor will be turbulent (90%flat). The 3.1 Construction and Equipment for Breathing Flow Rate Measurements 31

Figure 3.6: Measurement of time diﬀerence[9]

Figure 3.7: The three components of the time diﬀerence and their summation versus the ﬂow velocity [9] 3.1 Construction and Equipment for Breathing Flow Rate Measurements 32

Figure 3.8: Calibration set up of the sensor for high velocity signal will be transferred from the computer to the Mass flow controller through Data Acquisition (DAQ) card and the signal from the sensor is acquired and stored in the computer through the DAQ card. As it is described in the Fig.3.9, the low volume flow rate calibration is done by water chamber. The way of calibration is the following. There is a water chamber with no leakage, except the upper part, where the sensor is connected. When the valve located the bottom of the chamber is opened, water comes out from the outlet and the surrounding air which volume is same as water, comes into the chamber from the upper side through the sensor. The procedure of the calibration is; firstly open the valve, take the water from the valve outlet of the chamber and measure the mass of the water. Simultaneously the duration time is also measured with stopwatch so that one can obtain the mean mass flow rate of the water. The atmospheric pressure and temperature are measured by the pressure gauge and thermocouple respectively for the calculation of the density of the air and finally the mass flow rate of the air is obtained. The lowest velocity less than 0.017m/s can be realized with this test rig, however, it is found that as it is shown in Fig.3.10 the thermal sensor has free convection problem, it can not measure the velocity less than 0.15m/s. The calibration curve for the thermal sensor is shown in Fig.3.11. The Calibration is done totally two times in different days on which temperature difference is 3 degree centigrade. Since the thermal sensor is atmospheric temperature insensitive, the calibration curves are 3.1 Construction and Equipment for Breathing Flow Rate Measurements 33

Figure 3.9: Calibration set up of the sensor for Low velocity ﬂow

Figure 3.10: Calibration curve of the extreme low velocity region 3.1 Construction and Equipment for Breathing Flow Rate Measurements 34

Figure 3.11: Calibration curve of the Time of Flight Sensor obtained the diﬀerence between two calibrations is less than 5 %.

3.1.3.2 Frequency response of the sensor

Human breathing is two directional pulsating flow whose frequency ranges approximately from 0.17Hz to 0.33Hz in normal condition and can reach more 3.2 Final Measurements 35 than 0.42Hz after a heavy exercise. The frequency response test is proceeded with such experimental set up as the combination of the signal generator and mass flow controller connected with the TOF sensor for both direction. The sinusoidal signal is given to the mass flow controller from the signal generator so that it can produce the sinusoidal time varying volume flow rate with different frequencies but only one direction. The result of the frequency response is shown in fig.3.12 as the given signal is the signal given to the mass flow controller and detected signal is the acquired from the measurement electronics of the TOF sensor. It is in principle same time responce characteristic is observed for both direction, he is shown only for one directional frequency responce test results with different frequencies. There is a time lag of 0.05sec in each frequency test. This is due to the response of the mass flow controller, however, it is sufficiently responding for the measurement of the Human ventilation.

3.1.4 Signal Processing

In the measurement, two signals from the measurement electronics of the sensor are obtained; one corresponds to the mass flow rate and the other corresponds to the flow direction. The signal for the mass flow rate is represented from 0 to 10 volt, on the other hand, signal for the direction is represented 0 or 5 volt. In the actual measurement, 0 volt for the direction signal represents inhalation and 5 volt does exhalation. According to the directional signal, inhalation and exhalation is differentiated as inhalation is described negative volume flow rate and exhalation is positive volume flow rate by the calculation with FORTRAN program whose scheme is the following; firstly the noise signal like too high volume flow rate signal is cut off since the normal quiet breathing does not reach more than 35L/min and also the signal of the free convection range of the sensor is replaced 0L/min since the sensor cannot measure less than 1.17L/min. After cutting the noises, the signal is converted into the volume flow rate according to the direction signal.

3.2 Final Measurements

The ventilation curve is sampled by the system which is described in Fig.3.1. Fig.3.13 is the typical ventilation curve in normal quiet condition. This ventilation measurement is done with 5 diﬀerent individuals (diﬀerent height, weight, 3.2 Final Measurements 36

Figure 3.12: Frequency response of the Time-of-Flight sensor upper 0.1Hz middle 0.5Hz below 1Hz 3.2 Final Measurements 37 age and sex) taking summation of the volume of inhalation and exhalation respectively for 5min normal quiet breathing, the volume diﬀerence between sum of the in- and exhalation is always less than 2% whereas with the CTA sensor measurement can not reach less than 10%. 3.2 Final Measurements 38

- Exhalation Inhalation 1 0.328 0.423 2 0.342 0.539 3 0.440 0.461 4 0.279 0.398 5 0.347 0.499 6 0.373 0.425

duration sum of exhaled air sum of inhaled air error% 18sec 2.11 2.75 30.2 60sec 6.59 6.38 3 120sec 12.65 13.47 6.5 180sec 19.12 19.56 2.3 240sec 24.38 24.60 0.9 280sec 28.70 28.57 0.4

Figure 3.13: Human ventilation measurement with Time-of-Flight sensor Chapter 4

Realization of a Ventilation Simulator

In this chapter, the realization of a breathing simulation system is described. There is a brief explanation of the volume flow control system in the first two sections. In the third section, the final ventilation simulation result is shown.

4.1 Construction of ventilation Simulator

In this section, the way how to construct the ventilation simulator is described. The proportional volume control valve is selected to simulate the human ventilation and the application for the valves is described in the following subsections.

4.1.1 Instrumentations

The configuration of the ventilation simulation system is shown in Fig.4.1. The pressurized air is supplied up to 6bar. The vacuum chamber which capacity is more than 80m3 is connected to the vacuum pump manufactured by the company Busch[?]. The vacuum pump type is GRV2000 and has the vacuuming ability of 2000m3/h. For volume flow rate controlling, two proportional valves with measurement electronics which are manufactured by the company Buerkert[?] (Fig.4.2) are used. The proportional valves change the opening (cross sectional area) according to the electrical signal which ranges from 0 to 10 volt so that it controls the volume flow rate. The proportional valve of type 6021 for the exhalation simulation, 4.1 Construction of ventilation Simulator 40

Figure 4.1: Conﬁguration of the ventilation simulation system 4.1 Construction of ventilation Simulator 41

Figure 4.2: Degital image of the proportional valve

Type 6022 for the inhalation simulation and type 1094 for the measurement electronics are used. The norminal width of the opening of the type 6021 valve is maximum 1.6mm and that of type 6022, 4mm. To use the small opening valve, the controlling capacity is bigger, however, it is necessary to employ the bigger opening valve especially for the inhalation simulation because the pressure difference can not reach more than 1bar as it is operated with negative pressure with vacuum chamber and it can not give the sufficient amount of volume flow rate for the inhalation simulation. The frequency response of the valve is set to 1000Hz in the measurement electronics. The computer gives the ventilation curve to the data acquisition card (DAQ), which is sampled from different individuals (cf. chapter 3) and DAQ card gives the signal for opening and closing to the proportional valves and additionally, obtaining the velocity and the flow direction signal from the TOF sensor simultaneously.

4.1.2 Volume Flow Control System for Exhalation

For the simulation of exhalation, the proportional valve is connected to the pressurized air supply. Since the volume ﬂow rate depends not only on the electrical signal but also on the pressure of the high-pressure side, it is necessary to calibrate the valve with ﬁxed inlet pressure. 4.1 Construction of ventilation Simulator 42

Figure 4.3: Calibration Curve for the Exhalation Simulation with opening and closing

The calibration curve of the proportional valve with pressurized air is taken for opening and closing of the valve in steady condition shown in ﬁg.4.3. There is output strain between opening and closing of the valve thus, for the ventilation simulation, the averaged curve is taken as it is described in the next section.

4.1.3 Volume Flow Control System for Inhalation

For the simulation of inhalation, the same type of the proportional valve as for simulation of exhalation is used with sub-pressure operation. Since the volume flow rate is not sufficient with the opening size of the proportional valve operated by the pressure difference between vacuum chamber and the atmospheric pressure unlike the system with pressurized air. Hence a bigger opening proportional valve is used. This valve is connected to the vacuum chamber which is vacuumed by the pumps up to 0.04bar. The high-pressure side of the system of this simulation is atmospheric pressure which is different from the system of exhalation simulation with positive pressurized air. The atmospheric pressure remains constant and independent on the opening of the valve unlike the exhalation simulation setup. When the absolute pressure ratio between the high pressure side and low pressure side is less than 0.528, the flow velocity at the valve opening reaches sonic velocity 4.2 Calibration of Combined Values 43

Figure 4.4: Calibration Curve for the Inhalation Simulation with opening and closing then the velocity and mass flow rate will remain constant. And it is required to reach choked flow to get the constant volume flow rate. It is only possible in the vacuum atmosphere as the pressure of the higher pressure side remains constant. In this regard, since the opening of the valve does not affect the inlet pressure (atmospheric pressure), inhalation simulation system can control the volume flow rate more accurately than exhalation simulation system. The calibration curve of the proportional valve with negative pressure operation is taken for opening and closing of the valve in steady condition shown in Fig.4.4.

4.2 Calibration of Combined Values

After the connection of the two valves and completing the construction of the whole set up, the calibration curve for both proportional valves are taken since the back pressure affects the volume flow rate of the valves and the calibration curves for the single connected setup are not any more valid. The final averaged calibration curve is shown in Fig.4.5. 4.2 Calibration of Combined Values 44

Figure 4.5: Averaged Calibration Curve for Convined Condition 4.3 Veriﬁcation Test of the Simulator 45

4.3 Veriﬁcation Test of the Simulator

The ventilation simulation is realized by the system which is described in Fig.4.1. The breathing data line is firstly taken from the subjects and the noise is cut and obtained by the program and then separated into two parts, inhalation and exhalation. These signals are conveyed parallel to each valve. The two valves open and close mutually according to the signal, which is given from the computer. The end of the system is connected to the plastic bag and it expands with the inhalation simulation and shrinks with the exhalation which image is an artificial lung. Fig.4.6 is the typical curve of the volume flow rate which measures of the flow rate of whole system. It simulates the breathing for 5 minutes as the sampled ventilation curve. The negative volume flow rate is the inhalation simulation and the positive volume flow rate is the exhalation simulation. The inhalation curve fits the given signal curve relatively better than the exhalation simulation. The error is based on the functioning of the proportional valve since the high pressure side (pressurized air) does not remain constant according to the opening of the valve, unlike for the simulation of the inhalation. The solution for this problem is to corporate the mass flow controller to simulate the exhalation since the mass flow controller has its own pressure calibrator in it so that the pressure does not change according to the opening of the valve of the contoroller.

4.4 Application of mass ﬂow rate control system as an exhalation unit

Since the volume flow controller with pressurized air has less controllability because of pressure changes according to the opening and closing of the valve, the mass flow controller is applied. The simulation result is shown in Fig.4.7. In this figure, the negative volume flow rate is the inhalation and positive is the exhalation. In this simulation, the exhalation simulation suits quite well whereas the simple proportional valve can not have such controllability. 4.4 Application of mass flow rate control system as an exhalation unit 46

Figure 4.6: Simulation of the Human Ventilation

Figure 4.7: Simulation of the Human Ventilation with Mass Flow Controller Chapter 5

Conclusions, Final Remarks and Outlook

In this thesis, the measurement of the human ventilation and its mechanical simulation are presented. The time of flight sensor which is insensitive of the heat loss from the wires is applied for the measurement of the human ventilation volume flow rate then, the precise ventilation curve is obtained. The result is that the time of flight sensor measurement of the ventilation has little error like less than 5% whereas CTA sensor measurement contains always more than 10% error. For simulating the human ventilation, two volume flow controller are firstly employed. To improve the accuracy of the simulation, the proportional valve for the high pressure side is replaced to the mass flow rate controller[15] since the simple proportional valve is not suitable for the time varying flow because the inlet air pressure varies with the opening area of the valve, it causes the less controllability. The final result of the simulation is presented together with the ventilation curve which is sampled from a individual. To further development of this system, one can model the real form of human oroparynx[13]. With that system, it would be possible to model like real human ventilation and experimental tests of the deposition of particulate matters not only when an individual inhals but also he exhalas. Bibliography

[1] Paul Billiet, Shirley Burchill, Advancing in Natural Science, 1991, Paris, France

[2] Shigeru Sakurai, Respiration functioning test, 1998, Iwate, Japan

[3] John N. Rhoades. 1997. Basic Pulmonary Function Testing. http://asthma.about.com/library/weekly/aa091597.htm

[4] Baldwin, E. Deg., et al., Pulmonary insuﬃciency.I.Physiological classiﬁ- cation, clinical methods of analyses, standard values in normalsubject. Medicine 27

[5] Gary Ritchison, Human Physiology, 8th edition by Stuart Ira Fox, 2004

[6] Rob Pierce and David P. Johns, The Spirometry Handbook, 1995, National Asthma Counsil Ltd

[7] Philip H. Quanjer et al., http://www.spirxpert.com/

[8] Weinberger SE, Principles of Pulmonary Medicine, 2nd. ed. Philadelphia, W.B. Saunders Co., 1992

[9] Ahmed Al-Salaymeh, Flow Velocity and Volume Flow Rate Sensors with a Wide Band Width, Doctor thesis, 2001

[10] H.H. Brunn, Hot-wire Anemometry, 1995, Oxford University Press

[11] M. Still and F.Durst et al, Inﬂuence of humidity on the convective heat transfer from small cylinders, Experiments in Fluids

[12] IngMar Medical, Ltd. www.ingmarmed.com BIBLIOGRAPHY 49

[13] A.F.Heenan, E.Matida et al., Experimental measurements and computational modeling of the ﬂow ﬁeld in an idealized human orophjarynx, Exper- imental in Fluids 35 (2003)

[14] www.draeger.de

[15] F.Durst et al, Mass ﬂow rate control system for time-dependent laminar and turbulent ﬂow investigations, Measurement science technology 14(2003)

[16] www.buerkert.de

[17] www.buschpump.com

[18] Z. Zhang, C. Kleinstreuer, Species heat and mass transfer in a human upper airway model, International Journal of Heat and Mass Transfer, Volume 46, Issue 25, December 2003

[19] W. S. J. Uijttewaala, R. V. A. Oliemans, Particle dispersion and deposition in direct numerical and large eddy simulations of vertical pipe ﬂows, Physics of Fluids 8, October 1996

[20] M. Kojic, A. Tsuda, A simple model for gravitational deposition of non- diﬀusing particles in oscillatory laminar pipe ﬂow and its application to small airways, Aerosol Science August 2003

[21] E.A.Matida, W.H.Finlay, A new add-on spacer design concept for dry- powder inhalers, Aerosol Science January 2004

[22] http://www.ccmtutorials.com/rs/mv/ Appendix A numerical calculation of the three time components of the time of ﬂight sensor

A.1 principle of Operation

With the present thermal flow sensor, the velocity signal is obtained by heating the sending wire with a sinusoidal wave current, in this way the temperature fluctuation is detected in the heated wake by the receiving wire. The total time lag or phase shift between the current to the sending wire and the temperature of the receiving wire, which acts as a resistance thermometer, is made up of the thermal lag of the sending wire, the true time of flight (convection by the fluid in the wake of the sending wire), and the thermal lag of the receiving wire. Thus,

∆t = Msending + ∆tf + Mreceiving (A.1) M indicates the thermal time lag of the wires. The theoretical equations and the solution procedure for the three time components are explained in the following, e.g. Al-Salaymeh [3].

A.1.1 Response of the sending wire

The basic wire arrangement is sketched in Figure (A.1). The sending wire, denoted wire A, was assumed to be heated by a sinusoidal oscillating electrical current: A.1 principle of Operation 51

Figure A.1: Sketch of the time of ﬂight wires of the sensor

I(t) = I0 + ∆I · sin(2πft) (A.2) passing the wire with an electrical resistance. The wire temperature then varies according to the following diﬀerential energy equation:

2 2 ∂Tw I χw ∂ Tw 4 4 ρwcwAw = − πdwh(Tw − T∞) + kwAw 2 − πdwσ(Tw − T∞ ) ∂t Aw | {z } ∂z | {z } | {z } | {z } C | {z } E A B D (A.3)

The explanations of the each term are following,

Term A: Heat stored in the wire on changing its temperature, where ρw is the density of the wire material, cw is the specific heat of the wire material, 2 πdw Aw = 4 is the cross-sectional area of the wire, Tw is the wire temperature, and t is the time. Term B : Electrical heat-generation rate of the wire per unit length, where I is the heating current and χw is the resistivity of the wire material at the local wire temperature. Term C: The forced-convection heat transfer rate out of the heated wire to the fluid, where dw is the wire diameter,h is the coefficient of convective heat transfer, Tw is the wire temperature and T∞ is the temperature of the fluid.

Term D : The conductive heat-transfer rate, where kw is the coeﬃcient of thermal conductivity for the heated wire and z is the distance measured along the heated wire. Term E : The radiation heat-transfer rate, out of the heated wire, where σ is the A.1 principle of Operation 52

Stefan-Boltzmann constant and is the emissivity of the heated wire. Order of magnitude considerations suggest that radiation heat transfer and conduction along the wire (the last two terms) are both high order terms. Speciﬁcally, the heat radiation from the heated wire to the cooler surrounding is very low and often neglected in calculations. Under normal operating conditions, the radiation losses are much less than 0.1% of the convection losses and hence will not be considered further. The heat conduction to the support plates is also negligible especially when the length to the diameter ratio is large (wire length 5 mm, aspect ratio (l/d) 278). Thus the diﬀerential energy equation that describes the temperature of the sending wire reads as follows:

2 ∂Tw I χw ρwcwAw = − πdwh(Tw − T∞) (A.4) ∂t Aw

This energy equation for the sending wire is ﬁrst-order equation, whose coeﬃcient is not, in general, constant and can be written as the following form:

dT w + A (t)T = A (t) (A.5) dt 1 w 2

Taken into account that the resistivity of the wire material is temperature dependent:

χw = χ∞{1 + α∞(Tw − T∞)} (A.6) the following diﬀerential equation yields to describe the wire temperature:

2 2 dTw I χ∞ I χ∞α∞ πdwh = + − (Tw − T∞) (A.7) dt Aw(ρwcwAw) Aw(ρwcwAw) ρwcwAw

For the heat transfer coeﬃcient h , the following deﬁnition is used:

k h = Nu f (A.8) dw

where kf is the thermal conductivity of the ﬂuid and Nu is Nusselt number, for which Collis and Williams [61] found by experiment the relation A.1 principle of Operation 53

T 0.17 Nu = (0.24 + 0.56Re0.45) · f (A.9) T∞ where Re is the wire Reynolds number, which can be described as follows:

Ud Re = w (A.10) ν

ν is the kinematics viscosity of the ﬂuid and Tf is the ﬁlm temperature,

T + T T = w ∞ (A.11) f 2

All fluid properties are calculated at the film temperature. The equation of Collis and Williams is valid for Reynolds number up to about 45, where vortex shedding begins. With all these relationships, the final differential equation that describes the time varying temperature of the sending wire is:

2 2 dTw I χ∞ I χ∞α∞ πkf 0.45 Tf 0.17 = + − (0.24 + 0.56Re ) · ( ) ρwcwAw (Tw−T∞) dt Aw(ρwcwAw) Aw(ρwcwAw) ρwcwAw T∞ (A.12)

This diﬀerential equation needs to be solved to yield the wire temperature as a function of time for given wire property, given ﬂuid property and the time-varying electrical current.

The time constant of sending wire Msend is then represented by the reciprocal of the wire temperature coeﬃcient kf , thus the time constant of the sending wire can be written as:

πk M = f (A.13) ρwcwAw

In the Figure (A.2) shows the theoretical prediction of wire time constant for a platinum wire with a diameter of 12.5µm under normal condition:

A.1.2 Time-of-ﬂight calculations

A numerical computation was performed to estimate the temperature distribution around the heated sending wire, and especially the variation with A.1 principle of Operation 54

Figure A.2: Theoretical prediction of sending wire time constant for a platinum wire with a diameter of 18µm as a function of flow velocity downstream distance along the x-axi. In order to obtain this exact time of flight as a function of the free-stream velocity, the temperature distribution for the flow over and behind a circular cylinder should be solved. From the calculated temperature variation of the sending wire, the resultant temperature variation of the fluid at the position of the receiving wire, denoted wire B in Figure (A.1), the following two-dimensional partial differential equations (continuity, time-dependent momentum and thermal energy equations) were solved:

Continuity Equation: ∂U ∂U 1 + 2 = 0 (A.14) ∂x1 ∂x2

Momentum Equation: ∂U ∂(U U ) ∂P ∂τ ρ j + i j = − − ij , i, j = 1, 2 (A.15) ∂t ∂xi ∂xj ∂xi

Energy Equation:

∂ρT ∂(ρUiT ) ∂ ∂T cP + = k , i, j = 1, 2 (A.16) ∂t ∂xi ∂xi ∂xi

Where ρ is the density, Ui is the Cartesian velocity component, xi is the A.1 principle of Operation 55

Cartesian coordinate, t is the time, P is the pressure and τij is the molecular momentum transport term of momentum, which can be deﬁned as:

∂Uj ∂Ui τij = −µ + (A.17) ∂xi ∂xj

where µ is the dynamic viscosity, T is the temperature of the flow, cP is the specific heat at constant pressure and k is the thermal conductivity. A finite-volume computer code set up that described by Peric [?] and Lange et al [?] was extended to permit the present computations to be performed. The time derivatives in the momentum and energy equations are discretized with an implicit finite difference scheme. This discretization procedure can be found in Lange [?]. A structured mesh of quadrilateral CVs was used in the present work. All dependent variables are located at the center of each CV. The multi- grid method, which uses the idea of combining a fine grid with coarser grids, is used for efficient convergence. The effect of such a multi-grid approach is that the convergence rate becomes independent of the grid spacing and that the computational effort only increases linearly with the number of grid points. Computations with different values of Reynolds number were performed to predict the thermal time of flight. The laminar flow around a circular cylinder in the range of Reynolds number investigated (0.004 < Re < 45) has two regimes: steady flow without separation (Re < 5), steady flow with two symmetric standing vortices behind cylinder (5 < Re < 45), and our present computations below the regime of unsteady flow with vortex shedding (Re > 45). The Re of the optimised sensor at (for a wire diameter) was only about 10. A fine grid was selected around the cylinder wall to resolve the standing vortices. The surface of the cylinder was discretized with a total of 416 CVs, which the total number of CVs in the computation domain was 67584. Figure (A.3) represents the computation results of the time of flight as a function of the free-stream velocity based on a heated wire diameter. This computation was performed by Al-Salaymeh [3] to estimate the time lag between the sending temperature signal and the temperature signal at the receiving-wire position to give the time of flight. This figure shows clearly that the dynamic range of the flow velocity obtained by time of flight alone is too limited. The data in Figure (A.3) have been plotted on log scales as shown in Figure (A.4) to show the results at low flow velocity. The time delays due to the wire time constants A.1 principle of Operation 56

Figure A.3: Theoretical prediction of fluid time of flight versus the flow velocity are not included in these figures. Also, according to the numerical computation performed to estimate the temperature distribution around the heated wire, and especially the variation with downstream distance along x-axis, it was found that the solution to the two-dimensional energy equation for convection and diffusion of heat in a laminar stream is a function of the Peclet number. It is possible to interpret the Peclet number (P e = Re·P r , where Re depends on the distance ∆x ∆x2 between the two wires) as the ration between the diffusion time ( a ) and the convection time ( ∆x ), where a is the thermal diffusivity of the fluid ( a = k ). U ρcP It is found that if the Peclet number is below 50, which means a flow velocity below 0.7m/s with ∆x = 1.5mm , the diffusion effect will be noticeable, and this effect will increase rapidly when the Peclet number decreases. Figure (A.5) shows the relation between the Peclet number and the detected time of flight. As shown in this figure and in Figure (A.6), the effect of diffusion is dominant as the Peclet number becomes smaller. The time of flight will reach a constant value as the free-stream velocity decreases below a few centimetres per second. However, as the velocity increases, this situation is inverted and the diffusion effect rapidly becomes negligible compared with the convection time and the wire time constant. To simplify the whole situation, in the present case, the ∆x relation ∆tf ≈ U is used to estimate the time of flight value when needed. A.1 principle of Operation 57

Figure A.4: Theoretical prediction of fluid time of flight versus the flow velocity plotted on log scales

Figure A.5: Theoretical prediction of ﬂuid time of ﬂight as a function of Peclet number A.1 principle of Operation 58

Figure A.6: Detected time of flight versus the flow velocity for different sending- wire diameters (5, 12.5 and 100µm ), all at ∆x = 1.5mm

A.1.3 Response of the receiving wire

Given the solution for the velocity and temperature on the wake centre line at the position of the receiving wire, the variation of receiving wire temperature with time can be calculated with the same code as the sending-wire response, but with the forcing as the heat-transfer term. The ambient fluctuation temperature, which is detected in the heated wake by the receiving wire, has an approximately sinusoidal shape. The ambient temperature fluctuation, which is a function of the flow velocity, can be expressed as

Ta = Tm + ∆Tacos(ωt) (A.18)

where Tm is the mean ambient temperature at the receiving wire, ∆Ta is the amplitude of the ambient temperature fluctuation and f is the frequency of the ambient temperature fluctuation and that of the sending wire current, which is chosen as 30Hz. A very small, constant current passes through the receiving wire so that its resistance can be measured, but its heating effect can be neglected. Therefore, the thermal energy balance for the receiving wire can be written as A.1 principle of Operation 59

Figure A.7: Theoretical prediction of receiving wire time constant for a platinum wire with a diameter of 12.5µm as a function of ﬂow velocity

dTw πNukf = (Ta − Tw) (A.19) dt ρwcwAw where the Nusselt number Nu is dependent on ﬂuid temperature and is given in equation (A.9) , due to Collis and William [?], who deﬁned it. Equation (A.19) can be rewritten as

dT M w + T = T (A.20) dt w a(t) where M is the receiving wire time constant:

ρ c A M = w w w (A.21) πNukf

Figure (A.7) shows the theoretical prediction of receiving wire time constant for a platinum wire with a diameter of 12.5µm under normal condition: A.2 Discussion of Responses of Sending and Receiving Wires 60

A.2 Discussion of Responses of Sending and Re- ceiving Wires

The energy equations for the sending wire, Equation (A.12), and the receiving wire, Equation (A.19), are ﬁrst-order equations, whose coeﬃcients are not, in general, constant. So both equations can be written as the following form:

dT w + A (t)T = A (t) (A.22) dt 1 w 2

The time constant of both sending and receiving wires is represented by the 1 reciprocal of the wire temperature coeﬃcient in Equation (A.22). A1(t) can A1(t) be written for two wires in the following form: Sending wire:

0.17 2 πkf 0.45 Tf I(t) χ∞α A1(t) = (0.24 + 0.56Re ) − Aw) (A.23) ρwcwAw Ta Aw(ρwcw

Receiving wire:

0.17 πkf 0.45 Tf A1(t) = (0.24 + 0.56Re ) (A.24) ρwcwAw Ta

2 The second term ( I (t)χ∞α A ) in Equation (A.23) is very small compared with the Aw(ρwcw w first term, thus it can be neglected at very low overheat ratio and high velocity. This term does not appear in the receiving-wire equation since the receiving wire is externally heated from the flow, which carries the heat tracer from the sending wire. In the practical case, it is neglected the difference between the wire time constant of the sending wire and the receiving wire. In the following chapters, the term wire time constant always refers to the receiving wire time constant unless specifically indicated. Equation (A.22) is highly non-linear. To linearize this equation, it is possible using some appropriate mean values. The velocity, current, temperature, resistance and all variables can be expressed by time independent mean values plus time dependent fluctuation components. The time averages of the fluctuating quantities are zero. Therefore, the instantaneous change in the heat stored A.2 Discussion of Responses of Sending and Receiving Wires 61 within the wire is equal to the difference between the changes in the heat input and the heat loss. The linearized dynamic response of the sending or receiving wire can be written from equation as

d∆T M w + ∆T = f(t) (A.25) dt w where M is the wire time constant, which is equal to 1 , and f(t) is the input A1 forcing function. In this case a sinosoidal wave:

f(t) = Acos(ωt) (A.26)

This expression states that the temperature fluctuations of the sending or receiving wires respond as a first-order system with forcing functions due to the fluctuating current and velocity. The above equation can be solved to yield

1 Z t t − τ ∆Tw = exp(− )f(τ)dτ (A.27) M −∞ M

The response of the temperature ﬂuctuation ∆Tw in the frequency domain to the current ﬂuctuations, through the function f(t) is

A ∆T = (cos(ωt) + Mωsin(ω)t) (A.28) w 1 + ω2M 2

The magnitude of the temperature fluctuation of the wire is approximately the same as that of the forcing input function. For this consideration, it is clear that to achieve the potential for bandwidth enhancement offered by the present sensor, it is essential that the current frequency of the sending wire should be as small as possible. In the practical case, the sending current frequency is chosen to be 30Hz. The effects of the wire material, the geometry and the operational conditions determine the time constant. This time constant is strongly dependent on the flow velocity. It follows that the different wire materials may change the time constant by factor of about 2, with platinum giving the smallest value. The time constant is independent of the length but strongly dependent on the wire diameter. The most significant way of increasing the phase shift is to use a large A.2 Discussion of Responses of Sending and Receiving Wires 62 wire diameter and so the wire time constant will increase. In the practical case, the wire diameter is chosen to be 12.5µm. Kurzfassung

Das Ziel dieser Arbeit ist, die Beatmung des Menschens zu simulieren. Ein interessantes Feature von der Beatmungsimulation ist die genaue Messung des zeitabhngigen Volumenstroms. Weil die konventionellen Sensoren, zum Beispiel Konstant-Temperatur- Hitzdrahtanemometer, wegen ihrer Abhaengigkeit von der atmosphaerischen Temperatur und Feuchtigkeit, die Beatmung nicht so akkurat messen koennen, sollte man einen neuen Sensor anwenden, um genau zu messen. Deshalb hat die Authorin dieser Thesis einen sogenannte ”Time of Flight”-Sensor, eine Art Thermoanemometer, verwendet. Der Sensor hat drei Draehte, einer davon ist der sendende Draht und die anderen zwei sind die empfangende Draehte. Es ist eine Maske entwickelt, die Nase und Mund vollstaendig abdeckt, und die an den Sensor ber das At- mungsrohr angeschlossen ist. Das Atmungsrohr ist im wesentlichen ein Diffusor mit einem Oeffnungswinkel geringer als 7◦, damit keine Strmungsabloesung stat- tfinden kann. Nachdem der Atmungsmessung wird das Siganl in Volumenstrom umgerechnet und das hochfrequente Geraeusch wird ueber ein FORTRAN Pro- gramm gefiltert. Im zweiten Teil dieser Thesis wurde eine Versuchsvorrichtung erstellt, um den Luftstrom der Atmung nachzubilden. Die Vorrichtung ist mit einer Massen- stromregelung fr die Ausatmung und einer Volumenstromdrossel fr die Einatmung ausgestattet. Bei der Volumenstromdrossel handelt es sich um ein Proportional- ventil, das mit einer Vakuumpumpe und -kammer betrieben wird. Die Ergebnis von der Simulation ist in der Thesis praesentiert. In einem nchsten Schritt sollte die Vorrichtung in einen Dummy eingebaut werden, der wie ein Mensch atmen kann. Da einige Forscher bereits ein mecha- nisches Modell fuer den Mundrachenraum entwickelt haben, kann die vorliegende Vorrichtung mit dem Mundrachenraummodell auch kombiniert werden, um ver- schiedene toxikologische Experimente durchzufhren, wie z.B. die Untersuchung A.2 Discussion of Responses of Sending and Receiving Wires 64 von Partikelablagerungen im Mundrachenraum. Acknowledgement

It is my great pleasure to acknowledge to all people who have helped me for completing this master thesis in the Institute of Fluid Mechanics (LSTM) in Erlangen-Nuremberg university.

First of all, I am very thankful to Prof. Dr. Dr. h.c. F. Durst who is the head of the institute, since he has continuously encouraged, supported and given me proper guidances during whole my study for Master of Scinence. I am greatful to him for giving me such opprotunity to work with this interesting topic of the thesis under his supervision.

I owe special thanks to Dr. J.Jovanovic, head of turbulence group, and O. Ertunc, Ph.D student in LSTM for their guidance and supervision. I am very greatful to B. Unsal, Ph.D student in LSTM for his help to complete my thesis.

I am thankful to all of my colleagues and technicians who work in LSTM for their helpful advice, fruitful discussions and good time which we spent together.

I am greatly indebted to DAAD(German Academic Exchange Servis) for their ﬁnancial support during my study for Master of Scinence.

Finally, I thank my parents, brother and all friends who have always supported me through my stay in Germany.