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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 investiga-

tion 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 con-

dition, 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 con-

troller, 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 me-

chanical 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 orophar-

ynx 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 simu-

lator 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, per-

fusion and circulation. There are many kinds of breathing functioning test, how-

ever, 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 lab-

oratory 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


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.


2.2.1 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 res-

piration. 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 inspira-

tion 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 maneu-

ver. The index x − y is used to denote the portion of the FVC for which


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]


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 maneu-

ver.

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 com-

monly 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


Figure 2.3: Volume-Displacement Spirometer [8]

flow as the primary signal and calculate volume by electronic (analog) or numeri-

cal (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 con-

ditions. 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.


Figure 2.4: Various Spirometers[7] upper:FleischPneumotachometer, middle:Hot

wire spirometer, bottom:Turbine spirometer


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 tis-

sue. 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


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 sim-

ilarly (maximal inspiratory flow volume MIFV). In a volume Flow Loop instan-

taneous 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


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 pre-

cise 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


Figure 2.8: Digital Image and Schematic description of Active Servo Lung 5000


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.


Figure 2.9: Schematic experimental setup of the flow field in Humans’

Oropharynx[13]

Figure 2.10: Idealized Model geometry of human oropharynx[13]


Figure 2.11: Schematic aerosol experimental setup with Humans’ Inhaler[21]


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 measure-

ment 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


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 inhala-

tion 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 mea-

surement 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 ex-

halation 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


Figure 3.1: Digital image and Schematic Figure of the mask with the sensor


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


- 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)


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.

4tf = ∆xU

Where ∆x is the distance between the hot wires and U is the flow veloc-

ity. 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


Figure 3.4: Digital Image of the Time of Flight Sensor


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 ex-

perimental 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 devel-

oped. 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


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]


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


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

Figure 3.10: Calibration curve of the extreme low velocity region


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 ap-

proximately 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 si-

nusoidal 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 ventila-

tion measurement is done with 5 different individuals (different height, weight,


Figure 3.12: Frequency response of the Time-of-Flight sensor

upper 0.1Hz middle 0.5Hz below 1Hz


age and sex) taking summation of the volume of inhalation and exhalation re-

spectively 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%.


- 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 ventila-

tion 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 ca-

pacity 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


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 simul-

taneously.

4.1.2 Volume Flow Control System for Exhalation

For the simulation of exhalation, the proportional valve is connected to the pres-

surized 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.


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 oper-

ation 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 be-

cause 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.

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[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 computa-

tional 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

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Issue 25, December 2003

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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:

ρwcwAw∂Tw

∂t︸︷︷︸A

=I2χw

Aw︸︷︷︸B

−πdwh(Tw − T∞)︸︷︷︸C

+ kwAw∂2Tw

∂z2︸︷︷︸D

−πdwσε(Tw4 − T∞

4)︸︷︷︸E

(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,

Aw = πd2w

4is 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


Stefan-Boltzmann constant and ε 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 en-

ergy equation that describes the temperature of the sending wire reads as follows:

ρwcwAw∂Tw

∂t=

I2χw

Aw

− πdwh(Tw − T∞) (A.4)

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:

dTw

dt+ A1(t)Tw = A2(t) (A.5)

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:

dTw

dt=

I2χ∞Aw(ρwcwAw)

+(

I2χ∞α∞Aw(ρwcwAw)

− πdwh

ρwcwAw

)(Tw − T∞) (A.7)

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

h = Nukf

dw

(A.8)

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


Nu = (0.24 + 0.56Re0.45) ·(

Tf

T∞

)0.17

(A.9)

where Re is the wire Reynolds number, which can be described as follows:

Re =Udw

ν(A.10)

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

Tf =Tw + T∞

2(A.11)

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:

dTw

dt=

I2χ∞Aw(ρwcwAw)

+{

I2χ∞α∞Aw(ρwcwAw)

− πkf

ρwcwAw

(0.24 + 0.56Re0.45) · ( Tf

T∞)0.17ρwcwAw

}(Tw−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:

M =πkf

ρwcwAw

(A.13)

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 dis-

tribution around the heated sending wire, and especially the variation with


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:∂U1

∂x1

+∂U2

∂x2

= 0 (A.14)

Momentum Equation:

ρ(

∂Uj

∂t+

∂(UiUj)

∂xi

)= − ∂P

∂xj

− ∂τij

∂xi

, i, j = 1, 2 (A.15)

Energy Equation:

cP

(∂ρT

∂t+

∂(ρUiT )

∂xi

)=

∂

∂xi

(k

∂T

∂xi

), i, j = 1, 2 (A.16)

Where ρ is the density, Ui is the Cartesian velocity component, xi is the


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:

τij = −µ(

∂Uj

∂xi

+∂Ui

∂xj

)(A.17)

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 stand-

ing 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 com-

putation was performed by Al-Salaymeh [3] to estimate the time lag between the

sending temperature signal and the temperature signal at the receiving-wire po-

sition 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


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 (Pe = Re·Pr , where Re depends on the distance ∆x

between the two wires) as the ration between the diffusion time (∆x2

a) and the

convection time (∆xU

), where a is the thermal diffusivity of the fluid ( a = kρcP

).

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

relation ∆tf ≈ ∆xU

is used to estimate the time of flight value when needed.


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


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


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

dt=

πNukf

ρwcwAw

(Ta − Tw) (A.19)

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

MdTw

dt+ Tw = Ta(t) (A.20)

where M is the receiving wire time constant:

M =ρwcwAw

πNukf

(A.21)

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 re-

ceiving 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:

dTw

dt+ A1(t)Tw = A2(t) (A.22)

The time constant of both sending and receiving wires is represented by the

reciprocal of the wire temperature coefficient 1A1(t)

in Equation (A.22). A1(t) can

be written for two wires in the following form:

Sending wire:

A1(t) =πkf

ρwcwAw

(0.24 + 0.56Re0.45)(

Tf

Ta

)0.17

−(

I(t)2χ∞α

Aw(ρwcw

Aw))

(A.23)

Receiving wire:

A1(t) =πkf

ρwcwAw

(0.24 + 0.56Re0.45)(

Tf

Ta

)0.17

(A.24)

The second term ( I2(t)χ∞αAw(ρwcw

Aw) in Equation (A.23) is very small compared with the

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, resis-

tance 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


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

Md∆Tw

dt+ ∆Tw = f(t) (A.25)

where M is the wire time constant, which is equal to 1A1

, and f(t) is the input

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

∆Tw =1

M

∫ t

−∞exp(−t− τ

M)f(τ)dτ (A.27)

The response of the temperature fluctuation ∆Tw in the frequency domain to

the current fluctuations, through the function f(t) is

∆Tw =A

1 + ω2M2(cos(ωt) + Mωsin(ω)t) (A.28)

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


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


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 sup-

ported me through my stay in Germany.

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