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Abstract CPAP is the most common treatment for moderate to severe sleep apnea in adults. Despite its efficacy, patients’ safety, comfort and compliance are issues to be considered and improved in CPAP design. The issues include condensation, carbon dioxide in inhaled air, humidity and temperature of inhaled air. When a CPAP user breaths deeply, there will be some air not fully expelled and may be driven back into the heated air delivery tube (HADT). An interest has existed in what impacts this so called reverse flow may bring about to the CPAP use. The main objectives of this research are to quantify the reverse flow and its influence on carbon dioxide re-breathing, delivered humidity to the patient and condensation in the HADT. Within this thesis, two computer models of the CPAP system have been constructed on Simulink in the Matlab environment. One is about the CPAP fluid dynamic performance and carbon dioxide re-breathing and the other is on thermodynamic performance. The models can predict the dynamic behaviour of the CPAP machine. They are able to mimic the breath induced airflow fluctuation, and flow direction changes over wide real working ranges of ambient conditions, settings and coefficients. These models can be used for future analysis, development, improvement and design of the machine. The fluid dynamic and thermodynamic models were experimentally validated and they have proved to be valuable tool in the work. The main conclusions drawn from this study are: Reverse flow increases when breath load increases and pressure setting decreases. Reverse flow does not definitely add exhaled air to the next inhalation unless the reverse flow is relatively too much. Mask capacity does not influence the reverse flow. The exhaled air re-breathed is mainly due to that stays in the mask, therefore larger mask capacity increases the exhaled air re-breath and the percentage of exhaled air in next inhalation drops when the breath load increases. Deep breathing does not significantly change the total evaporation in chamber. iv
When deep breathing induced reverse flow occurs, condensation occurs or worsens in the HADT near the mask. This happens only when the humidity of the airflow from the CPAP is much lower than that of the exhaled air and the tube wall temperature is low enough for condensation to occur. The deep breathing and reverse flow do not significantly influence the average inhaled air temperature. The overall specific humidity in inhaled air is lower under deep breathing. Mask capacity does not influence the thermal conditions in the HADT and the inhaled air specific humidity. Also the mask capacity does not significantly influences the inhaled air temperature. v
Page 1 and 2: The Effects of CPAP Tube Reverse Fl
Page 3: Acknowledgement First of all, I wou
Page 7 and 8: 2.4.1 Reverse flow calculation ....
Page 9 and 10: 5.3.1 Thermal dynamic model under s
Page 11 and 12: XI.3 Steady state mask thermal bala
Page 13 and 14: List of Figures Figure 1.1 Obstruct
Page 15 and 16: Figure 5.10 Comparison between expe
Page 17 and 18: Figure 6.13 Fluctuation of airflow
Page 19 and 20: Table 5.3 Comparison of condensatio
Page 21 and 22: Nomenclature Symbol Meaning of the
Page 23 and 24: CMFeO CMFet C O C t Concentration o
Page 25 and 26: m C 23 m Ca m cv m Cw m store m i m
Page 27 and 28: Nu Cp Nu dir Nu Ti Nu To Nuwsn Nuws
Page 29 and 30: QMor QMwst QTastn QTicn QTin Q
Page 31 and 32: R Mic R Moc R Ticn R Toc R Torn Mas
Page 33 and 34: V Capacity of the container m 3 V C
Page 35 and 36: 1.1 Background Chapter 1 Introducti
Page 37 and 38: The MRD is worn in user’s mouth w
Page 39 and 40: Figure 1.4 CPAP machine Figure 1.5
Page 41 and 42: 1.3 Literature survey A literature
Page 43 and 44: CPAP fluid dynamic performance with
Page 45 and 46: Chapter 2 Mathematical Modelling of
Page 47 and 48: 2.3 Fluid dynamic analysis This sec
Page 49 and 50: If there are minor pressure drops,
Page 51 and 52: Figure 2.6 Pressure sensor - Honeyw
Page 53 and 54: The pressure readings were taken af
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Figure 2.12 Experimental set up for
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2.3.4 Chamber air space mass balanc
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From the above analysis, the pressu
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Figure 2.18 Full face mask and the
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Inserting Eq. (2.26) and Eq. (2.27)
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Where n( ) t is the airflow proper
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However in reality, mixing turns ou
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Chapter 3 Mathematical Modelling of
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An Environment Control Chamber (Vö
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Figure 3.4 Thermal enthalpy gain of
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Figure 3.6 Heating element beneath
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Figure 3.8 Chamber water heat balan
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Table 3.1 Thermal resistance from h
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3.3.1.2 Heat balance at the outer s
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3.3.2 Heat flow from chamber water
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through ADU which is a function of
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It is assumed that the direct impac
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Sc a a (3.47) Dwa Analogous to th
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and keep them in gaseous status. On
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through the walls and natural conve
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Where d Ca is the specific humidity
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TTa ( n1) is also considered as inl
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R Torn 2 2 ATlor ( TTWn T )( TTWn
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condensation severity but cannot ca
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condensation has occurred at all or
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The inlet is the air from HADT duri
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3.9 Average temperature of inhaled
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Table 4.1 Inputs to the fluid dynam
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Figure 4.2 Simulink TM model for fl
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Table 4.4 Outputs from the overall
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Gain block after input 1 is to conv
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Figure 4.7 Varying Transport Delay
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4.2.5 Mask mixing calculation subsy
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4.3 Computational model of thermal
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Figure 4.11 Block diagram of CPAP t
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Figure 4.13 Simulink TM model for t
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The outputs are listed in Table 4.1
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Figure 4.16 Dynamic chamber-air the
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Figure 4.17 HADT lump thermal balan
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Figure 4.18 Steady state HADT lump
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Figure 4.19 HADT lump air dynamic f
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Figure 4.21Steady state mask full t
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4 Temperature of airflow from HADT
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Average evaporation rate subsystem
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HADT and connects those upstream se
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The experiment was also carried out
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air flowing through the elbow, a ce
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expansion from the elbow to the mas
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Figure 5.12 Environmental control r
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Table 5.1 shows the combinations of
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Figure 5.17 Comparison of model out
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The comparison of experimental resu
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5.3.1.4 Airflow temperature at the
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flow rate had been even further inc
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Figure 5.31 Comparison of condensat
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Table 5.3 Comparison of condensatio
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3. The corrugated grooves on the HA
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5.3.2.1 Validation of evaporation r
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The experiment observation showed t
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Figure 6.1 Reverse flow under diffe
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It can also be seen in Figure 6.2 t
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within the same period. However, wh
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Figure 6.6 Comparison of evaporatio
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Figure 6.8 Airflow velocity in HADT
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Figure 6.11 Airflow velocity in HAD
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In Figure 6.14 the blue curve repre
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6.3.3.1.2 Comparison when heating e
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This vaporization potentiality (coi
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Figure 6.20 In-tube condensation of
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When using different sized masks, t
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Figure 6.23 Average specific humidi
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The average specific humidity in an
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Table 6.5 Comparison of average spe
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6. The deep breathing and reverse f
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Appendices Appendix I Regression of
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Appendix I. Regression of the press
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Figure I. 1 Tested results and the
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Appendix II. Regression of the pres
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Table III. 2 Airflow temperature an
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Appendix IV. The corrugated HADT ou
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The total area of the complicated c
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Figure V. 1 Regression of saturated
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This ratio can be regressed against
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Appendix VII. Details of the CPAP f
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VII.4 The mask pressure subsystem F
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Inputs to this water-centred subsys
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Input port number Input Unit 1 Heat
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input 4 is the portion of impact ar
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VIII.2.3 Water surface mass transfe
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This subsystem also contains two su
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VIII.2.5 Chamber wall 1 heat transf
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Figure VIII. 13 Wall 1 outer surfac
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Wall 2 and 3 inner surface temperat
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Figure VIII. 17 Chamber wall 2 and
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Inputs to this subsystem are listed
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Appendix IX. Details of steady stat
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Figure IX. 3 The HADT lump wall out
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Appendix X. Details of HADT lump ai
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2 Absolute value of airflow velocit
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Figure X. 5 HADT lump inlet absolut
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Figure XI. 2 Steady state mask mixi
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Figure XI. 4 Steady state mask wall
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Input port number Input Unit 1 Aver
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Appendix XII. Details of mask air d
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4 Length of the triangular plate in
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8 Length of the triangular plate in
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Appendix XIII. Details of the auxil
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XIII.3 Breath load average subsyste
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Figure XIII. 7 Average evaporation
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XIV.1.2 Under normal ambient temper
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XIV.2.3 Under high ambient temperat
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XIV.4 Airflow temperature at the en
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XIV.5.2 Under normal ambient temper
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XIV.6.3 Under high ambient temperat
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Appendix XVI. Regression of kinetic
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Figure XVII. 2 Condensation/evapora
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Figure XVIII. 2 Condensation/evapor
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at point C. Right after that, here
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Appendix XIX. Coefficient and param
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Average water thermal conductivity
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Appendix XXI. Fluid dynamic and the
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The lung simulator drives the air.
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Appendix XXII. Model user instructi
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The input blocks and their values a
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Dynamically fluctuating air tempera
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References [1] Good sleep advice. W
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[28] Schettino GPP, Chatmongkolchar
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[60] Marek R, Straub J. Analysis of
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