CFD Study of Different Aircraft
Cabin Ventilation Systems
on Thermal Comfort and
Airborne Contaminant Transport
Abhishek Raina (abhra126)
Logeshkumar Srinivasan Venkatesan (logsr834)
Link¨opings universitet Institutionen f¨or ekonomisk och industriell utveckling
Link¨opings universitet Institutionen f¨or ekonomisk och industriell utveckling ¨
Amnesomr˚adet Mekanisk v¨armeteori och str¨omningsl¨ara Examensarbete 2020|LIU-IEI-TEK-A–20/03640ˆaSE
CFD Study of Different Aircraft
Cabin Ventilation Systems
on Thermal Comfort and
Airborne Contaminant Transport
Abhishek Raina (abhra126)
Logeshkumar Srinivasan Venkatesan (logsr834)
Academic supervisor: J¨org Schminder Industrial supervisors: Roland G˚ardhagen Examiner: Hossein Nadali Najafabadi
Link¨oping universitet SE-581 83 Link¨oping, Sverige
Abstract
Aircraft Cabin Ventilation systems are crucial for not only maintaining a fresh sup-ply of air but also help in proper air distribution control and reducing air borne pathogen contamination. Passenger thermal comfort is of vital importance for a comfortable cabin environment and thus the need to measure environmental param-eters such as velocity and temperature stratification for different ventilation systems is paramount. Experimental setups often lead to investigation uncertainties and lim-itations of measured data in a mock-up model when compared to a real cabin. This is due to simplifications either made in the geometry or air supply systems and thus careful comparison of airflow differences due to the simplifications should be consid-ered. Computational Fluid Dynamic (CFD) models of aircraft cabins can provide a virtual solution for a physical phenomenon (in this case, airflow distribution of an aircraft ventilation system) and thus, such simplifications can be studied and comprehended while reducing the cost and time associated with experimental se-tups. CFD studies however, do require thorough verification and validation to avoid compromise on accuracy. This study investigates different aircraft cabin ventilation systems using CFD to analyze air flow distribution and its implications on the ther-mal comfort and contaminant transport in the cabin. The CFD study results are verified by conducting a mesh sensitivity study since there is no experimental inves-tigation to validate against. This master thesis project was performed at Link¨oping University in the Applied Thermodynamics and Fluid Mechanics division at the Department of Management and Engineering.
A generic single aisle cabin of a regional jet aircraft is modelled and further im-plemented in a CFD solver to simulate different Aircraft ventilation systems. The aircraft cabin is modelled using the Autodesk Fusion 360 CAD tool and a CFD model is setup in ANSYS FLUENT using a RANS RNG K-epsilon turbulence model with Enhanced wall treatment. Human Manikins are also designed to represent passen-gers and are included as heat sources to study thermal distribution. The mouth is used to release CO2 to stimulate breathing through respiration. A tracer gas (CO2)
is used to represent a pathogen which is discharged from an occupant as a cough or sneeze to study its diffusion path and infection risk. The aircraft cabin is reduced to a cross section of one row of four seats abreast with a periodic boundary condition which is used to imitate the entire length of the cabin to help reduce meshing as well as computational cost.
Acknowledgements
This master thesis was performed at Link¨oping University at the Department of management and Engineering in Link¨oping during the spring of 2019. We would like to thank our supervisors Roland G˚ardhagen and J¨org Schminder for their guidance and support during our thesis work. We owe them immense gratitude for their encouragement, patience, and vast knowledge on the subject of Computational fluid dynamics. They have been crucial in helping us develop this project by solving problems every step of the way. We would also like to thank our examiner, Hossein Nadali Najafabadi for his valuable input and help on the subject of fluid dynamics.
Nomenclature
Abbreviations and Acronyms
Abbreviation Meaning
LiU Link¨oping University
CFD Computational fluid dynamics
CAD Computer aided design
CPU Central processing unit
IATA International Air Transport Association SARS Severe Acute Respiratory Syndrome CDV Cabin Displacement Ventilation CPV Cabin Personalized Ventulation
CMV Cabin Mixed Ventilation
RANS Reynolds Averaged Navier Stokes equation ECS Environment Control System
FAR Federal Aviation Regulations HEPA High Efficiency Particulate Air RNG k-epsilon Renormalization Group k-epsilon PIV Particle Image Velocitmetry
PMV Predicted Mean Vote
PPD Predicted Percentage of Dissatifaction
BOI Body of Influence
MV Mixed Ventilation
DV Displacement Ventilation
PV Personalized Ventilation
CO2 Carbon dioxide
ASHRAE American Society of Heating, Refrigerating and Air-Conditioning Engineers
HRE Heat Removal Efficiency
HTC Heat Transfer Coefficient
Latin Symbols
Symbol Description Units
A Area m2 c Heat capacity W m−2K−1 ~n Normal vector [−] p Pressure [P a] t Time [s] ˙
q Heat transfer due to conduction W m−2 u, v, w Velocity in x, y and z direction ms−1 u0, v0, w0 Fluctuating Components in x, y and z
direction
Symbol Description Units
V Velocity in u, v, w ms−1
T Temperature [K]
h Heat transfer coefficient due to convec-tion
W/m2.K
Greek Symbols
Symbol Description Units
α Angle [degree]
µ Dynamic viscosity kgm−1s−1
Πij Pressure-velocity gradient tensor m2s−3
ρ Density kg/m3
Subscripts and superscripts
Abbreviation Meaning
Gk Generation of turbulent kinetic energy due to mean
velocity gradients
Gb Generation of turbulent kinetic energy due to buoyancy
α Inverse effective Prandtl number for dissipation of
tur-bulent kinetic energy
Ri Net rate of production of species (i) by chemical
reac-tion
Si Rate of creation by addition from the dispersed phase
∆THA Mean temperature difference between head and ankle
Contents
1 Introduction 1 1.1 Background . . . 1 1.2 Objective . . . 4 1.3 Limitations . . . 4 2 Theory 7 2.1 Ventilation Systems of an Aircraft. . . 72.1.1 Types of Ventilation System. . . 7
2.1.2 Mixing Ventilation (MV) . . . 8
2.1.3 Displacement Ventilation (DV) . . . 8
2.1.4 Personalized Ventilation (PV) . . . 8
2.2 Environment Control System (ECS) . . . 9
2.2.1 Aircraft ECS Regulations by FAR . . . 9
2.2.2 Aircraft ECS Recommendations by ASHRAE . . . 10
2.3 Thermal Comfort Evaluation . . . 10
2.3.1 Predicted Mean Vote (PMV) . . . 11
2.3.2 Predicted Percentage of Dissatisfied(PPD) . . . 12
2.4 Heat Removal Efficiency (HRE) . . . 12
3 Method 13 3.1 Computer Aided Model (CAD) . . . 13
3.1.1 Human Geometry . . . 15
3.2 CFD Model . . . 16
3.3 Model Meshing . . . 17
3.3.1 Mesh Independent Study . . . 18
3.4 Contaminant transport study using a tracer Gas . . . 20
3.5 Numerical Setup . . . 21
3.6 Boundary Conditions. . . 22
4 Results 25 4.1 Velocity Distribution in the Cabin with Humans . . . 25
4.2 Temperature Distribution in the Cabin with Humans . . . 29
4.3 Heat Transfer Coefficient on Humans for Different Ventilation Systems 30 4.4 PMV and PPD in the Cabin . . . 32
4.5 Heat Removal Efficiency and Mean temperature difference . . . 33
4.6 CO2 (ppm) Distribution in the Cabin . . . 34
5 Discussion 37
5.1 Aircraft cabin with humans . . . 37
5.1.1 Mixing Ventilation . . . 37
5.1.2 Displacement Ventilation . . . 38
5.1.3 Personalized Ventilation . . . 39
5.1.4 Ventilation systems ranking . . . 40
5.1.5 Methodology . . . 42
6 Conclusions 45 Appendices 50 A First appendix 51 A.1 Contaminant transport visualization through volume render of CO2 mass fraction in the aircraft cabin . . . 51
1
Introduction
1.1
Background
Commercial air travel by aircraft’s is still the safest and quickest way to travel. The number of people travelling by commercial aircraft in recent years is remarkable. According to the International Air Transport Association (IATA)[1], statistics show 4.3 billion people travelled by air in 2017 which was a 7.3% increase from the year 2016 and is expected to increase by 8.2 billion in 2037. These passengers, within an aircraft cabin are exposed to a combination of environmental factors including low air pressure, low humidity and air contaminants such as air borne pathogens carrying diseases and infections [2].
Flight crews are at a higher risk since they cover longer flight hours than any other passenger per month [3]. The emergence of diseases like Tuberculosis and severe acute respiratory syndrome (SARS) can affect passengers from a contagious passen-ger source. In the case of Tuberculosis for a flight duration of 8 hours, passenpassen-gers seated up to two rows have been found to be in the contamination radius while for SARS, it has been reported to infect passengers up to seven rows from the contam-inant source [3].
An aircraft cruising at high altitudes is subjected to extreme temperature and pres-sure unsuitable and harmful for a human being, therefore a pressurized and en-vironmental control system is used to protect humans from the extreme ambient environment. This system is suitable for spread of pathogens carried by passengers and crew. Aircraft Cabin ventilation systems come in to play to help reduce this transmission of air borne pathogens and therefore play a vital role in not only re-ducing risk of contamination by infected passengers but maintaining a crucial air distribution system to control internal temperature and pressure. The need for strict temperature, CO2, air velocity distribution and contamination control is highly
re-quired with increasing air travel, high occupant density, inability of occupants to leave at will and long-haul distance flights.
Aircraft Ventilation Systems are of different types with the most widely used venti-lation system being the mixing distribution system in which fresh air is introduced either from the cabin ceiling or the sides and air outlet vents on both lower sides of the cabin deck. The others include the Cabin Displacement Ventilation (CDV) and the Cabin Personalized Ventilation (CPV) which are discussed in detail in the report. There have been various experimental and numerical studies on different ventilation systems on various aircraft cabin types. Experimental studies are conducted on either aircraft cabin mock-ups or on stationary aircrafts. Numerical studies are conducted by applying CFD to calculate air flow distributions. Some of the research is often conducted by investigating both an experimental and CFD approach to compare and analyze the results obtained from both.
Matthias K¨uhn and Johannes Bosbach et al. [4] did an experimental study of mixed and forced ventilation systems on a full-scale mock-up of an Airbus A380 upper cabin deck. Airflow velocity and temperature on iso-thermal and cooling states were an-alyzed with various inlet configurations on the cabin. It was measured by PIV and temperature sensors respectively. The results obtained from the measuring instru-ments showed that the various factors affecting the flow field inside the cabin were impinging jet interactions, negative buoyancy, and human thermal plumes. The im-pact of these factors contrasted significantly depending on the ventilation systems and airflow rate settings of the supply inlets.
Zhang Z and Chen X et al. [5] study investigated an experiment and a CFD study on a twin-aisle aircraft cabin. The transport of gaseous particles and aerosol par-ticulate contaminant were studied in detail using CFD with the Lagrangian particle trajectory method. Air and temperature profiles were measured along with the dif-ferent positions in the cabin. The airflow velocities measured from the jet diffusers in the cabin were non-uniform during an experimental investigation which makes an error in giving flow boundary conditions for CFD study. This study concluded that the validation of an experimental and CFD study was not free from errors when comparing airflow velocity profiles. Hence, accurate validation of experimental and CFD was difficult.
Fiser J and Jicha M’s [6] study involved a detailed investigation of the experimental setup and an exact replica for the CFD study. Different ventilation systems were an-alyzed on the cabin mock-up with different dimensions of air supply ducts. Predicted mean vote (PMV) and Predicted percentage of dissatisfied (PPD) were studied for all the ventilation systems in different ambient conditions. Airflow velocity was measured for different ventilation systems using CFD simulations and compared against experimental results. The study concluded that under-aisle displacement ventilation depending on the ambient temperature provides good performance over another system while the mixed ventilation system provided with the best stable ventilation performance at all seats and under different ambient conditions at the expense of higher draught velocities.
Zhang Z and Zhang W’s [7] study focused on the under-aisle air supply ventilation and tested necessary thermal comfort parameters based on the ASHRAE Standards. CO2 gas coming out of passenger’s mouth inside the cabin between different seats.
Mixing ventilation and displacement ventilation were also compared and analyzed. This study concluded that mixing ventilation maintaining uniform temperature and CO2 concentration at the risk of higher draught velocities for the passengers.
Fi-nally, displacement ventilation prevents cross-contamination and maintains a good breathing zone for passengers.
Wu Y and Liu H’s [8] studied personal ventilation in an aircraft cabin by interview-ing 40 people. They were exposed to different air supply rates from the personal ventilation nozzles, different clothing, and cold environment. Then their perceived air quality, draft rate and comfort level with respect to ambient conditions were examined. This experiment concludes that people were more susceptible to the
thermal comfort level in an aircraft cabin than in the buildings. The effects of the nozzle air supply from the Personalized ventilation system on the micro-environment of adjacent passengers were also worthy of further research.
Bosbach and Lange [9] studied an experimental novel displacement ventilation in an aircraft cabin of a Dornier 728 aircraft. Six different ventilation scenarios were studied of mixing, displacement, and ceiling based displacement systems. Integral quantities of the temperature difference between cabin air and incoming air, the heat removal potency, the mean temperature stratification and also the mean veloc-ity levels were used to analyze the proportion of discontent in passengers so as to investigate and score the ventilation scenarios. This study concludes that velocity and temperature levels increase with the velocity of incoming air during different ventilation scenarios but the stratification of temperature and heat removal potency decreases. Further studies will need to be addressed in the ventilation concepts in order to compare with respect to their dynamic performance, like a up or pull-down scenarios, which were important under operational conditions.
Zhao and Zhang et al. [10] work deals with an in-depth study of different turbulence models for predicting fluid and heat transfer in four different enclosed environments with different ventilation scenarios and compared with an experimental study. Three different zones with multiple line positions were chosen in the test area, and proper-ties were measured accordingly. The predicted air velocity, temperature and turbu-lence levels of natural convection, forced convection, mixed convection and strong buoyancy flow cases were compared against experimental results in those locations. Among the test cases, each turbulence model has its own advantages and disadvan-tages. Their study concluded that RNG k-epsilon and V2f models performs better in building and aircraft environments.
Experimental setups used to imitate aircraft cabin ventilation types can be more of a tedious task involving multiple setup changes including inlet and outlet vent distribution for different ventilation type. Further more, experimental setups in aircraft cabin mock ups often lead to a discrepancy between the mock up and the real aircraft cabin [11]. This is due to the reason that cabin mock up geometries and air supply systems are simplified when compared to real cabins and so whether a mock up can substitute a real cabin environment is always contentious [11]. CFD simulations on the other hand can help simulate different ventilation systems by multiple design iterations and analyze their airflow distribution and save a significant amount of physical and labor costs involved in experimental investigations. CFD studies can also be applied to analyze the effects of environmental parameters inside the aircraft cabin such as velocity, temperature and air borne contaminants.
1.2
Objective
The objective of this master thesis is to design a parametric CAD model of a single aisle passenger cabin of a regional jet aircraft with human manikins as passengers and to further execute it in a setup of Computational Fluid Dynamics (CFD) solver ANSYS FLUENT and analyze simulations of different aircraft ventilation systems. Design a detailed parametric 3D model of a generic narrow body aircraft cabin including ventilation system air supply inlets and air exhaust outlets. The inlets and outlets are modelled as strips by approximating ventilation inlet and outlet average nozzle areas from actual aircraft cabins.
To setup a CFD model running a RANS Turbulence model to simulate various aircraft cabin ventilation systems.
To analyze the different ventilation systems and study their performance on thermal comfort by evaluating velocity, temperature and CO2 profiles measured at locations
close to the occupants in the cabin.
The mouth is used to release CO2 to simulate breathing through respiration and a
contaminant transport study using a tracer gas concept with an infected passenger dispersing contaminated air.
1.3
Limitations
1. The aircraft cabin model which is implemented in the CFD setup for this study is simplified by not taking the entire length of the aircraft cabin but instead a section of the aircraft cabin with one row of seats. The entire length of the cabin is imitated by using a periodic boundary condition in the AN-SYS FLUENT solver to limit computational cost as well as to reduce mesh complexity.
2. The ventilation air supply inlets and air extract outlets consist of high velocity jets coming out from a narrow set of nozzles located under and above the overhead baggage bins running along the length of the entire cabin [12]. The approximate area of these nozzles were then factored into the length and the area of the strips used for the same purpose in the cabin geometry. This was done mainly to reduce mesh cells which would help save meshing as well as simulation computational cost.
3. A human geometry is modelled to mimic a human passenger seated in an aircraft cabin is as proximate as possible which is adequate to study the inter-action of airflow distribution and temperature for thermal comfort. The CAD geometry, therefore is kept as minimal by removing features such has hands, fingers and toes.
4. A detail and complex geometrical model follows difficulties in both meshing and computational cost. In order to satisfy both these processes, geometry details are simplified by removing the parts which are deemed unnecessary for the flow simulations. Many of these parts which were designed in detail such as
the personalized vents, windows, cabin seats were subtracted or their surfaces cleaned up by fillet operation in order to still capture their interaction and ensure a smooth meshing process. For example, the cabin seat’s sharp edges were filleted around the corners and the individual cylindrical nozzles used to stimulate personalized ventilation and reading lights were re-modelled as a single oval surface to be used as a personalized air inlet supply. Human manikin body surfaces were contoured with smooth features.
2
Theory
2.1
Ventilation Systems of an Aircraft.
2.1.1
Types of Ventilation System
Typical Commercial aircraft cabin ventilation systems make use of re circulation of air where 50% of the air in the cabin is fresh supplied either from the engine bleed air or the Auxiliary power unit and the other 50% is filtered, recirculated air.
(a) Mixing Ventilation (b) Displacement Ventilation
(c) Personalized Ventilation
Figure 1: Different Ventilation configurations illustration. [blue arrows indicate fresh air released from inlet diffuser, red arrows indicate outlet for air extraction, yellow arrows depict thermal plumes arising from heat sources] (a) Mixing Ventilation. (b) Shows the CAD modelled using the dimensions with human manikins
The high temperature air from the compressor is then cooled down by the Environ-mental control system (ECU) to comfortable levels before introducing it into the passenger cabin [13]. The supply and exhaust of air into the cabin interior is done through air discharge ducts and exhaust air vents which can be arranged in different configurations. The different ventilation configurations used in this study is illus-trated in figure1. There are mainly three main types of ventilation configurations, namely mixing, displacement and personalized ventilation systems ventilation.
2.1.2
Mixing Ventilation (MV)
Mixing flow ventilation is a type that uses mechanized systems to deliver fresh air at high velocity from inlets which are placed above and below the overhead baggage bins. This creates a circulation of air in the aircraft cabin which causes the mixing of fresh and recirculated air. The supplied air will mix properly before reaching the occupants and removes contaminants and heat from cabin through the outlet vents. The airflow rate of the inlet nozzle is based on the heat and humidity level in the cabin. It is a common type of system used by most aircraft manufacturers. This type of system provides overall good thermal comfort but is more prone to contaminant spread throughout the cabin from an infected occupant and also has high draught rates when compared to other methods [14].
2.1.3
Displacement Ventilation (DV)
Displacement ventilation differs from Mixing as fresh air is supplied at floor level as apposed to supply of fresh air from overhead ceiling level in mixing ventilation. The fresh cool air creates a pool of air at the floor level and is supplied at low velocity. The passenger’s heat interacts with this cool air and the warm air currents or thermal plumes move towards the ceiling where they are extracted to outside. Thus two zones are created, namely an occupant zone and a contaminant zone which is at the ceiling level. Aircraft manufacturers are slowly moving to implementing this type from the widely used mixing ventilation due to its low incoming velocity and removal of heat from occupants providing a healthy environment [15].
2.1.4
Personalized Ventilation (PV)
Personalized ventilation delivers fresh air directly to the occupants. This creates a barrier of fresh air around the passenger and protects from airborne diseases or other contaminants. This method provides a healthy and pleasant feel to the passenger since the clean air flows close to the breathing zone. Many delivery methods are available for this system in the aircraft such as nozzle on the front seat or overhead the passenger under the baggage bins. Although, higher draught velocities from these diffusers can lead to discomfort from prolonged exposure [16].
2.2
Environment Control System (ECS)
An Environment Control System (ECS) is used to provide a safe environment for passengers during the travel and is thus considered important. It involves ventila-tion, pressure control, contaminant dispersal control and airflow requirements for distribution & re-circulation in an aircraft cabin. An aircraft undergoes different phases during its flight and experiences an outside temperature range of -55◦C to 50◦C, ambient pressure range of 101 kPa to 11 kPa and relative humidity of 10-20% inside the cabin. ECS is crucial in maintaining the changes in air pressure, density and temperature providing a healthy environment for passengers and cabin crew with proper comfort level.
2.2.1
Aircraft ECS Regulations by FAR
Federal Aviation Regulations (FAR) certifications provide regulations for the air-craft’s ECS system in the United States of America while the European Joint Avi-ation Authorities (JAA) provide necessary regulAvi-ations for ECS design for aircraft manufacturers in the European nations. In any case, working rules based on FAA or JAA controls are connected independently by the country of registry [2].
FAR part 25 [17] section enlists the ventilation requirements for a commercial aircraft to ensure the comfort level and safety of passengers and crews. It is summarized as follows:
1. Under normal operating conditions, the ventilation system provides an ade-quate air supply of 9.8 g/s for each passenger. This air supply rate should be maintained during an emergency and in the event of failure of any component of the ventilation system also.
2. Carbon dioxide (CO2) concentrations should not exceed 0.5% of the cabin
volume.
3. The pressurization system must ensure an internal pressure of 75 kPa above a cabin altitude of 2440 m which is also the maximum allowed drop in cabin pressure. It should also maintain the same minimum pressure level of 75 kPa during the descent and climb phase of the flight.
4. Ozone levels in the cabin should be maintained at 0.25 ppm by volume above an altitude of 9800 m. It should be reduced by using catalytic destruction process in the ECS system otherwise.
5. The temperature levels in the cabin should be maintained between the 19◦C to 27◦C. The cabin inlet air temperature has to be kept high or low depending on the ambient environment.
6. Airflow requirements have to be maintained for cases namely heat removal, pressurization, contaminants, and comfort level. An airflow rate of 0.01 m3/s has to be maintained for each passenger and it can be distributed either by fresh air or filtered air.
Re-circulation of air is common in the cabin ECS system of modern aircraft and hence, 50% fresh air and 50% recirculated filtered air is supplied to inside the aircraft cabin and this percentage of filtered air is increased by modern systems. High Efficiency Particulate Air (HEPA) filters are used to remove airborne pathogens, bacteria and viruses but cannot remove gaseous pollutants from the air. Chemical adsorption methods are also used by activating charcoal to remove the contaminants from the recirculated air.
2.2.2
Aircraft ECS Recommendations by
ASHRAE
The American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), which is an American association further provides guidelines on nec-essary comfort level parameters for the passengers as well as cabin air quality for commercial aircrafts [18]. ASHRAE standards are used to determine the differ-ent combinations of indoor thermal comfort factors as well as personal factors that will create thermal environmental conditions that are acceptable to most occupants within an enclosed room. The above-mentioned thermal comfort and personal fac-tors are temperature, radiation, humidity, airspeed, metabolic rate, and occupant clothing insulation. This standard does not take account factors such as air qual-ity, acoustics, lighting, and contamination. Airflow momentum of 0.1 to 0.4 m/s is recommended for the passengers comfort level [18].
2.3
Thermal Comfort Evaluation
Human thermal comfort evaluation has been a topic of interest with developments through formal studies, academic papers, integrated and shared knowledge emerging since the 19th century. [19] Povl Ole Fanger, a professor at the international centre for indoor environment and energy at the Technical University of Denmark and an expert in the field of thermal comfort hypothesized that human thermal comfort was based on one’s skin temperature and sweat temperature. Through further climate chamber experiments, Fanger’s hypothesis evolved to declare that thermal comfort could be established through evaluation of metabolic rate, clothing insulation and environmental conditions of an individual and is today recognized globally in the ASHRAE 55 and ISO 7730 standards for evaluating indoor environments [20]. The comfort equation was derived by Fanger from extensive literature survey on experiments on thermal comfort in 1970s and was used to predict thermal comfort conditions in various environments. Its validity was later considered by comparing the predicted thermal comfort conditions with experimental studies of subjective responses of people and through Fangers own carefully designed and controlled ex-periments [19]. One such comparison with an experimental study conducted by Nevins et al. (1966) and McNall et al. (1968) found excellent agreement for inactive persons (seated) while a reasonable agreement for active persons was met. PMV and PPD were later introduced by Fanger as a practical method for evaluation of thermal environments. [19]
2.3.1
Predicted Mean Vote (PMV)
PMV [21] is a thermal sensation index that predicts the mean sensation of votes on a seven point thermal sensation scale (Table5) for a group of persons for any given combination of air temperature, mean radiant temperature, air velocity, humidity, activity and clothing. [19] [20] The PMV index translates the comfort equation on the PMV scale where -3 indicates cold, -2 cool, -1 slightly cool, 0 neutral, +1 slightly warm, +2 warm, +3 hot. It expresses human perception of a feeling of hot or cold within enclosed places for example in an aircraft cabin.
The factors which influence thermal comfort and to calculate the PMV are tem-perature (ta), airspeed (V), mean radiant temperature (MRT) (tr), metabolic rate
of human (M), clothing insulation (Icl) and humidity in the aircraft. The following
equation (1) to (4) is used for calculating PMV.
Various methods in ASHRAE 55 and ISO standards are outlined for certain types of environments which are used to gather information on variables which factor in to the PMV equation such as metabolic rate, insulation and relative humidity [20]. Variables such as air temperature and airspeed velocity is measured from the aircraft cabin CFD simulations in this study.
P M V = (0.303 × e-0.036M+0.028) × (M − W ) − 3.05 × 10-3 × [5733 − 6.99 × (M − W ) − Pa] − 0.42 × [(M − W ) − 58.15] − 1.7 × 10-5× M × (5867 − Pa) − 0.0014 × M × (34 − ta) − 3.96 × 10-8 × fcl× [tcl+ 273)4− (tr+ 273)4] − fcl× hc× (tcl− ta) (1) tcl = 35.7 − 0.028(M − W ) − Icl 3.96 × 10-8× fcl[(tcl+ 273)4− (tr+ 273)4] + fcl× hc× (tcl− ta) (2) hc= max(2.38(tcl− ta)0.25, 12.1 √ V ) (3) fcl = [1 + 0.2Iclf orIcl ≤ 0.5, 1.05 + 0.1Iclf orIcl ≥ 0.5] (4) where Pa is the vapor partial pressure of water; fcl is the surface area coefficient
of clothing; tcl is the surface temperature of clothing; hc is the convective heat
dissipation coefficient; W is the external work of the human body.
Table 5: Seven point thermal sensation scale
PMV +3 +2 +1 0 -1 -2 -3
Thermal
2.3.2
Predicted Percentage of Dissatisfied(PPD)
PPD [21] is the estimated percentage of the number of people who feel uncomfort-able according to the predicted mean vote from the total number of people in a given thermal climate. PPD is a function of PMV which reflects the percentage of thermally dissatisfied passengers in the aircraft cabin.
P P D = 100 − 95e-(0.03358×P M V4+ 0.2179 × P M V2)(5)
2.4
Heat Removal Efficiency (HRE)
Heat Removal Efficiency [9] is the amount of energy needed to sustain a certain mean aircraft cabin temperature. The higher the value of the HRE, lower will be the amount of energy consumption required for cooling the aircraft cabin. The best possible value for ventilation is known to be an HRE value of 0.5 (deduced from equation 6below) indicating to a case of a perfectly mixed fluid [9].
HRE = 0.5 × Tout− Tin Tcabin− Tin
(6)
where Tout is outlet temperature, Tin is inlet temperature and Tcabin is average
3
Method
3.1
Computer Aided Model (CAD)
The detailed CAD model was created in Autodesk fusion 360 for the entire aircraft cabin complete with galleys, closets, lavatory, a personalized overhead ventilation and baggage compartments. The dimensions of the cabin cross section were refer-enced from generic narrow body aircraft’s. Figure2 shows the aircraft cabin cross section dimensions on the left and on the right, the CAD model (front view) with human manikins seated inside which are designed using the Fusion 360 tool to rep-resent passengers.
(a) Aircraft Cabin cross section specification (b) Aircraft Cabin CAD model, front view
Figure 2: (a) Illustrates the Aircraft Cabin interior cross section dimensions. (b)
Shows the CAD modelled using the dimensions with human manikins
Figure 3: Overhead
Personalized vent
nozzle and reading
lights
The aircraft cabin has a four abreast seating capacity with eight rows in total. Seat pitch, which is the distance between two same points between two consecutive seats, was averaged at about 32 inches from several airlines seat pitch data. The overhead personalized AC vents (Figure3) were modelled as four 3D cylinders to stimulate two air vent nozzles (verti-cal downwards air flow direction) and two reading/personal lights. Other geometrical features such as double sided win-dows, multiple fuselage hull layers, a lavatory seperation and baggage compartments were designed in a way that these de-tails could easily be removed/added later during the study. An elaborate model also helps in capturing the flow physics accurately as close to the real world scenario. Figure4shows the entire CAD model of the aircraft cabin complete with interior components marked and labelled.
Figure 4: Aircraft Cabin interior components
An actual aircraft cabin ventilation system uses a number of high velocity jets from a narrow set of nozzles placed above and/or under the baggage compartments. Each of these nozzles contain two to three rows of alternating slots which produce the high velocity air jets. The inlet and outlet strips surface area which is used for this same purpose in the CFD study is approximated by taking the average area of the nozzles and then factored into the length and width of the strips. This was crucial in order to simplify the complexity of meshing which would directly reduce mesh cell count but is also sufficient to represent the ventilation air supply delivery. The air supply inlet and air outlet strips shown in figure5are used to supply cabin air and extract the same. Appropriate boundary conditions are used on these strips to simulate a ventilation system.
3.1.1
Human Geometry
The Human manikin is modelled to represent a human passenger seated inside an aircraft for which the dimensions are taken from the work done by Yuan & Peng [22]. Initial Simulations led to multiple design iterations for which the final geometry is rendered without hands, fingers and toes. An oval surface with dimensions imitating a human mouth is inserted on the front face in order to simulate exhalation of e.g. CO2 and production of infection by sneezing.
(a) Human manikin (front view) (b) human manikin (ISO view)
3.2
CFD Model
Figure 7: Aircraft cabin cut section of single row extruded for CFD study (Highlighted in red)
(a) Aircraft Cabin section (b) Aircraft Cabin after boolean operation (Used
for CFD study)
Figure 8: (a) Shows the aircraft cabin after extruding a cut section of one row (b) Shows aircraft cabin after Boolean operation. This model is the one used for CFD simulations.
The entire aircraft cabin is deemed too complex with a lot of parts leading to in-creased mesh and simulation cost due to the limited hardware capability of the computer system used for CFD. The length of the cabin is thus reduced to a cross section of a single row which along with a translational periodic boundary condition on both front and back faces of the reduced cross section will help simulate the realistic whole cabin (figure 9). A Boolean cut operation (figure 8 b) is performed within the CAD software to extract the computational fluid model (figure8b) from the geometry model (figure8 a).
3.3
Model Meshing
The mesh generation process was done in ANSYS Fluent meshing 19.2. A CFD study’s performance depends upon the quality of mesh. A good mesh quality will reduce the computational time by increasing the rate of convergence and stability. A finer mesh is used closer to the human manikins, walls and overhead baggage bin because of the larger airflow and temperature gradients that are generated in their vicinity. The first step in the meshing process was to create a proper surface mesh. An appropriate sizing field is given to the region where complex flow physics have to be captured. Two bodies of influence (BOI) are added near the human manikins (figure 9) and local face meshing is employed on the walls. The surface mesh is generated with a skewness of 0.65 which indicates a good quality mesh. A Prism type mesh is employed on the humans, seats, and walls of the cabin to capture the boundary layer region properties with a prism layer generation set to 15 layers (figure 9) with a smooth transition. Yplus value of less than 1 is achieved with a growth ratio of 1.2, to ensure smooth growth. Volume meshing is then generated with a polyhedral type with a skewness of 0.89 and an orthogonal quality of 0.31 which indicates the sufficient quality of the mesh.
Figure 9: Aircraft cabin mesh using a body sizing from body of influence and inflation layers of prism cells created along human and cabin wall boundaries.
The polyhedral mesh type is used for the entire domain as it is an automatically generated mesh that is similar to a tetrahedral mesh but overcomes its disadvantages by reducing the total number of element count. Polyhedral mesh type have several neighboring faces which allow it to exchange properties to a large number of faces thus reducing numerical diffusion when the flow is not perpendicular to any of the faces. Also, the gradient quantities obtained from this mesh type are far better approximated than the hex type while reducing numerical diffusion due to non-alignment of the flow [23]. This mesh type is particularly better for strong buoyancy flows [23]. Although it raises element count and computing time due to a large number of neighboring faces on each cell when compared to hexahedral type mesh, it is compensated by the exactness of numerical results [23].
3.3.1
Mesh Independent Study
Four different sizes of 4, 6, 8 and 10 million mesh elements are taken respectively for the study. The average volume velocity and temperature is computed to con-duct the mesh independence study. Furthermore, Velocity and temperature profiles (figure 10) are plotted on three different measuring lines (figure 10) in the cabin and were analyzed. The three measuring lines are placed in the center front of each passenger and center of the aisle corridor to capture the flow properties in front of the passengers breathing zone. Since flow behaviour of air distribution in the cabin is assumed to be symmetric in nature, only one side of the cabin is placed with the measuring lines.
(a) cross section and Line positions (Front View) (b) Line positions (Top View)
Figure 10: Line profiles used for measuring velocity and temperature at three different positions in the cabin (highlighted in red) in (a) and (b) along with cross-section of aircraft cabin used for CFD study (a).
A larger difference is observed between the 4 million mesh element size and the other three mesh sizes in the velocity and temperature profiles taken at the three measuring positions as seen in figure 11. In all measuring positions in the cabin, mesh element sizes of 6, 8 and 10 million cells exist in close proximity with each other. At a height of 1m, which is near the human head, a small difference in velocity and temperature profiles is observed on 6, 8 and 10 million mesh element
sizes. Based on the interpretation from both the profiles and average values, a mesh element size of eight million is chosen for this study.
0 0.2 0.4 0.6 Velocity (m/s) 0 0.5 1 1.5 Cabin Height (m) Window Seat 4M 6M 8M 10M 0 0.2 0.4 0.6 Velocity (m/s) 0 0.5 1 1.5 Cabin Height (m) Aisle Seat 4M 6M 8M 10M 0 0.2 0.4 0.6 Velocity (m/s) 0 0.5 1 1.5 2 Cabin Height (m) Aisle 4M 6M 8M 10M 20 25 30 35 Temperature (°C) 0 0.5 1 1.5 Cabin Height (m) Window Seat 4M 6M 8M 10M 18 20 22 24 26 Temperature (°C) 0 0.5 1 1.5 Cabin Height (m) Aisle Seat 4M 6M 8M 10M 19 19.5 20 Temperature (°C) 0 0.5 1 1.5 2 Cabin Height (m) Aisle 4M 6M 8M 10M
Figure 11: Comparison of velocity and temperature profile on different mesh sizes.
Table 6: Mesh Independent Study
Mesh Size Average Percentage Average Percentage Velocity (m/s) Difference Temperature (◦C) Difference
4 Million 0.085 - 25.92
-6 Million 0.099 15.3% 24.61 5.18%
8 Million 0.108 8.63% 24.06 2.23%
10 Million 0.113 2.7% 23.73 1.41%
A percentage difference on average temperature and velocity is also considered for the mesh study. For each mesh element size, the cabin average velocity and temper-ature is measured and listed as shown in table6. A difference is taken of the velocity and temperature value for each mesh size with the value of velocity or temperature respectively above it. The difference is then listed as a percentage. The first mesh size is of four million and is taken as the base mesh. The six million mesh element size has quite a significant percentage difference when compared with the four mil-lion mesh size. The difference obtained is around 15% and 5% for average velocity and temperature respectively. This difference is gradually reduced when mesh ele-ment size is increased to eight and ten million mesh size. A less than 3% difference for average velocity and temperature between ten and eight million mesh size is thus considered acceptable for this study that the solution is independent of the mesh size. It is very important to see if the mesh captures the flow physics in the domain and in order to verify, an empty cabin is first simulated to analyze and inspect the working setup for any deviation. Figure12 illustrates the velocity contour plot and velocity profiles taken at positions (figure 10) for mixing ventilation in the aircraft cabin but without humans and seats. Proper mixing is observed inside the cabin with
close to zero air velocity at the center at either side of the cabin near the window seat regions as can be seen in the velocity contour plot. Inlet diffuser jets above and below baggage compartments have their jet flow meet at center of aisle which results in high air velocity distribution at the aisle. This is subsequently seen in the velocity profiles in figure12 (a) for which the aisle receives high velocity at the center but lower at the cabin floor. The window seat and aisle seat show high air velocities below the baggage compartment and near the cabin floor while the center of these positions receive the lowest air velocity.
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Velocity (m/s) 0 0.5 1 1.5 2 2.5 Cabin Height (m) Velocity Distribution Window Aisle Seat Aisle
(a) Velocity Profile (b) Velocity Contour
Figure 12: Velocity distribution in an empty cabin on different positions.
3.4
Contaminant transport study using a
tracer Gas
Numerical investigations classify viruses as airborne contaminants and their disper-sion is modelled by the species continuity equation in CFD [24]. Also, the sudden high velocity jet of contaminated air discharged from a persons mouth is mixed with spray and hence the number of infected particles from the infected individual is unknown. Viruses of nano scale compared to bacteria of micro scale can be classi-fied as a gaseous substance, even though they exist in particle form. Furthermore, particles of size smaller than 0.1µm do not sink easily into the atmosphere and thus they spread around. It is therefore, reasonable to choose a tracer gas such as CO2 or
N2O, being heavier than air, or some other gas with air-like properties, for use in the
study of virus diffusion pathways [25]. A high velocity jet (representing a sneeze or cough) of contaminated air is expelled from the mouth of one infected passenger in the cabin. This contaminated air or virus is represented by CO2 which is the tracer
gas used to study the transport of the contaminant. The index or infected passenger is then rotated to a different seating position as shown in figure 13 and simulated for the two cases separately for all ventilation types. Also to note, the respiration CO2 (not contaminated) rate which is set otherwise for all the passengers in all the
ventilation type simulated scenarios is not considered for the contaminant transport study, hence, the index passenger is the only occupant in the cabin releasing a gas through the mouth in the aircraft cabin.
(a) Window index passenger (b) Aisle index passenger)
Figure 13: Passenger as contaminant source in different seating configurations simu-lated for the three ventilation types
3.5
Numerical Setup
The steady state simulations are carried out in ANSYS Fluent 19.2 with pressure based solvers because of low velocity flows (no compressibility effects) in the aircraft cabin. The RNG k-epsilon model with Enhanced wall treatment is employed for turbulence as it is favoured for indoor flow simulations. This model performs well in various enclosed environments where large thermal gradients are expected [10]. The gradient discretization is done with the Least squares cell method and the so-lution obtained from this gradient calculation was assumed to vary linearly. This default Fluent method is good for unstructured meshes (skewed & distorted) and less expensive in terms of computational cost. The standard scheme, which evalu-ates the pressure gradients at the faces is used for the pressure discretization. The upwind second-order scheme is used to discretize the equations of momentum. In this scheme, quantities are calculated using a multidimensional linear reconstruction approach at the cell faces. The higher-order accuracy of the cell faces is achieved by the Taylor series expansion of the cell-centered solution about the cell centroid. First-order scheme is used for the turbulence parameters. The convergence criteria of 1e-5 are set for the continuity and momentum equations, 1e-6 for energy equation and 1e-4 for species transport equations. The species transport model is modeled by solving conservation equations of convection and diffusion sources for each com-ponent species. The conservation equation for species is of the following form:
∂
∂t(ρYi) + ∇ · (ρ~vYi) = −∇ · ~Ji+ Ri+ Si (7) where Ri is the net rate of production of species i by chemical reaction, Si is the
rate of creation by addition from the dispersed phase and ~Ji is the diffusion flux of
species i which arises due to gradients of concentration and temperature [26]. The Discrete Ordinates (DO) model is used to calculate radiation contribution in the cabin [27]. Table 7shows the list of settings used for the simulations.
Table 7: Solver Settings
Equations Discretisation
p-v scheme Coupled
Turbulence Model RNG K-epsilon with EWT Gradient Least squares cell based
Pressure Standard
Momentum & Energy 2nd order upwind Turbulence 1st order upwind
Species 2nd order upwind
3.6
Boundary Conditions
A cabin inlet velocity of 0.52 m/s is used for this study based on the required airflow rate per passenger as stated by FAR regulations. To achieve the free outflow from the domain, a pressure outlet of 0 Pa static pressure is set. No-slip wall condition denotes that normal and tangential velocity of the fluid velocity between a moving fluid and a stationary wall is zero. This is used on the cabin wall, seats and human manikin. The cabin wall and seats are assumed to be adiabatic, while the human manikin skin has a constant temperature of 37◦C [28]. Translational periodic boundary condition is assigned to both front and back faces of the reduced cross section cabin domain since the cabin has a geometry of an expected simulation for thermal/fluid flow in a periodic recurrence.
The CO2 respiration rate from the mouth of the passenger is set as a mass flow
inlet with a mass flow rate of 9e-5 kg/s and a CO2 mole fraction of 0.05. A sudden
high velocity jet with contaminated air is used to represent an infected passenger is set for the window and aisle passenger individually (refer figure13) for the three ventilation scenario’s. The mass flow rate for the high velocity jet of contaminated air is set as 1.8e-4kg/s where the velocity was taken at 4.5 m/s [29]. Since all the air
coming out of the index passenger is assumed as infectious, a CO2 mole fraction of 1
is used. The boundary conditions which are used in the ANSYS fluent simulations are listed below in table8 and illustrated in figure 14and 15.
Table 8: Boundary Conditions
Region Boundary Condition MV&DV PV Inlet Velocity Inlet 0.52 m/s 0.26 m/s Mouth Inlet Mass Flow Inlet 9e-5 kg/s 9e-5 kg/s
Outlet Pressure Outlet 0 Pa 0 Pa
Wall Adiabatic Wall – –
Human No Slip Wall 37◦C 37◦C
(a) Mixing Ventilation
(b) Displacement Ventilation
Figure 14: Illustration of boundary conditions used for Mixing and Displacement
4
Results
4.1
Velocity Distribution in the Cabin
with Humans
Figure 16: Comparison of velocity profile on different ventilation systems.
Figure 16 displays the comparison of velocity profiles for three different ventilation systems, namely mixed, displacement and personalized systems inside the aircraft cabin at three different locations plotted vertically. The profiles help depict flow dis-tributions along with the height of the cabin and therefore at different body levels of the passenger. Window and aisle seat passengers are subjected to low draught velocities from the floor deck up to the human head in all the different ventilation systems. Higher draught velocity near the sidewall or window passenger is observed below the baggage compartment area and subsequently above the passenger’s head. The aisle corridor receives overall better airflow velocity due to the diffuser jet under the baggage compartment and the flow curved along the baggage wall. When look-ing at the human body levels, DV and PV systems provide lower air velocities than MV systems near the human head and neck region in all the measuring positions. On contrary to the above observations, the PV system provides a higher momentum of air in the thigh part of the window seat passengers. PV and DV systems prove to be ineffective in providing good airflow for the aisle corridor at the human head and neck levels when compared to the MV system. Air velocity starts high from the ceiling level for all ventilation systems and gradually decreases towards the cabin floor. Among them, the PV system has a lower velocity rate when compared to others.
(a) Mixing Ventilation (b) Displacement Ventilation
(c) Personalized ventilation
Figure 17: Velocity Contour plots of the three different ventilation system types, (a) Mixing ventilation (inlets located over and under head of baggage bin, outlets at floor level), (b) Displacement ventilation (inlets located at floor level, outlets at overhead of baggage bin), Personal ventilation (inlets located over and under head of baggage bin and personal inlets overhead passenger, outlets at floor level)
Figure 17 (a) displays the velocity contour plot for the MV system where the jet flow from the inlets located above the baggage bin (overhead) flows along the ceiling wall and meets the jet flow from the inlet diffusers located below the baggage bin (underhead) where they combine and further start pouring down the aisle. The flow direction is better depicted in figure18where we observe the flow forming a vortex of clockwise air circulation on both sides in the occupant zone. The air then exits the cabin at the outlets located at the floor level. Higher draught is observed in the aisle corridor and reduces after reaching the occupant zone.
The displacement ventilation system (figure 17 b) which has the inlet and outlet configuration opposite to that of the mixing ventilation shows characteristics similar to the MV system but with an overall tendency for the airflow to rise up (figure 18
d). The air supply from the bottom pools at the floor level and rises along the aisle corridor. The seats seem to block most of the airflow from rising at the occupant zone.
Figure 17 (c) illustrates the velocity contour of the PV system. The Inlet diffusers located directly above the window passengers are termed as personal ventilation sources. Also, both the overhead and underhead inlets are activated. The jet flow from the underhead diffuser mixes with the personal diffuser jet which sways the personal diffuser jet flow slightly to the right and left on each side of the window passenger respectively. This forms a barrier of air on each of the window occupant to their side.
Figure18 helps to better outline the details of the airflow field. The colored arrows also represent the range of velocity at that particular region. The red lines indicate the general air structure for each ventilation system. Since the flow field is close to symmetric, only the left side of the cabin is chosen to show the red lines. The side vector profiles (figure 18 d & f) of the displacement and personalized ventilation are taken at planes at the aisle and window passenger respectively. In the case of the displacement ventilation, the vectors show general air flow rising up towards the ceiling while for the personal ventilation, the air is seen to form a barrier for the window seat passenger and descends towards the outlet. The second front profile for the mixing ventilation (figure 18 b) helps demonstrate the clockwise air circulation and also the possible path of the virus when exhaled.
(a) Mixing Ventilation (front view) (b) Mixing Ventilation (front view)
(c) Displacement Ventilation (front view) (d) Displacement Ventilation (side view)
(e) Personalized ventilation (front view) (f) Personalized ventilation (side view) Figure 18: Calculated airflow vector field for (a) Mixing ventilation (b & c)
Displace-ment ventilation and (d & e) Personalized ventilation systems. Red lines indicate
4.2
Temperature Distribution in the Cabin
with Humans
Temperature distribution profiles from figure19shows a low temperature range from the passenger’s head (1.23 m from the cabin floor) down to the thigh (0.5 m from the cabin floor) for the window and aisle seats for all ventilation systems. From the thigh height down to where the feet touch the floor deck, the temperature levels peak for window and aisle seat passengers. In the window seat, the PV system maintains a temperature level lower than the other two systems from head to thigh region and then gradually increases from thigh to leg. The DV system provides elevated temperature levels at the aisle seat from the head down to the thigh of the occupant when compared to the other systems. Throughout the aisle corridor, the temperature level is observed to be low and uniform for all the ventilation systems.
15 20 25 30 35 Temperature (°C) 0 0.5 1 1.5 2 Cabin Height (m) Window Seat MV DV PV 15 20 25 30 35 Temperature (°C) 0 0.5 1 1.5 2 Cabin Height (m) Aisle Seat MV DV PV 15 20 25 30 35 Temperature (°C) 0 0.5 1 1.5 2 Cabin Height (m) Aisle MV DV PV
Figure 19: Comparison of temperature profile on different ventilation systems.
Figure 20 depicts the temperature distribution contour plots in the cabin near hu-mans. The temperature was more elevated between the humans in the window and aisle seat while optimum (temperature range between 19◦C to 27◦C as required by FAR regulations) temperature was observed in the aisle and cabin floor in all the ventilation systems. The aisle seat passenger whose side faces the aisle experiences more heat transfer in their arms and legs due to high momentum jet flow of air from the inlets in all the ventilation systems. In the DV system, the thermal plumes from the humans induce with the rising fresh cool air from the inlets below and rises up till under the overhead baggage bins. Reduced temperature levels was observed between the human passengers in the PV system when compared to the other two systems.
(a) Mixing Ventilation (b) Displacement Ventilation
(c) Personalized ventilation
Figure 20: Temperature contour plots of three different ventilation systems
4.3
Heat Transfer Coefficient on Humans for
Different Ventilation Systems
The surface heat transfer coefficient is the heat flux divided by the difference between the local wall temperature and the adjacent cell temperature. The heat transfer coefficient in all the three different ventilation scenarios depicts the transfer of heat from the human to the cabin surrounding. The surface heat transfer coefficient is implemented from the available heat transfer variables under the wall fluxes category for post-processing in ANSYS Fluent.
From figure21 (a), aisle seat passengers for mixing ventilation have a heat transfer coefficient higher than the other passengers at their side shoulders, arms and leg regions facing the aisle which ranges from 4 to 25 W.m-2.K-1. This is due to the under head diffuser jet flow curving along the wall and directly pouring down the aisle. The DV system passengers (figure 21 b) experience a low heat transfer coefficient range overall with the lower leg regions experiencing a high heat transfer coefficient as a result from the bottom located inlet diffusers.
Figure 21 (c), depicts the personalized ventilation systems heat transfer coefficient on the humans. The window passengers head, thighs and shoulders experiences
higher heat transfer which ranges from 10 to 30 W.m-2.K-1 due to the direct jet of cool air from the personalized inlet located directly above. The aisle seat passengers experience similar characteristics of that observed in the MV system for aisle seat passengers for the same reason.
(a) Mixing Ventilation (b) Displacement Ventilation
(c) Personalized Ventilation
Figure 21: Heat transfer coefficient distribution contour plots of three different venti-lation systems
Table 9: Mean heat transfer coefficient on humans for different ventilation systems.
Ventilation Types Mean heat transfer coefficient (W.m-2.K-1)
Mixing Ventilation System 4.14
Displacement Ventilation System 2.89 Personalized Ventilation System 6.36
4.4
PMV and PPD in the Cabin
Figure 22: PMV and PPD profiles of naked humans on different ventilation systems.
Figure22depicts the PMV and PPD values of the passengers with a clothing insula-tion of zero and thus assumed naked in the aircraft cabin. The window passenger in the MV system perceives a thermal feeling of moderate on the seven point comfort scale from the head down to the thigh level. A short peak above +2 is recorded from the thigh level down to the foot shortly after.
The aisle seat passenger does not look comfortable in the MV system with fluctu-ating PMV values ranging from -2 to +1 and is reflected on their PPD.
The aisle corridor receives the highest dissatisfaction for all ventilation systems with PPD above 50%.
Displacement ventilation provides better thermal comfort at all measuring positions with PPD below 20% for the window and aisle passengers.
PV displays a constant PMV of -2 in the aisle corridor and from the head down to the thigh level for the window and the aisle passenger after which a sudden peak to a PMV of +2 is measured from the thigh down to the foot for window and aisle passenger. PPD is also the highest for PV at all measuring locations.
Figure 23: PMV and PPD profiles of humans with summer outfits on different venti-lation systems.
Figure 23 depicts the PMV and PPD values of human with summer outfits in the aircraft cabin. There is not much change observed in PMV from the window and aisle seat passenger in MV and DV systems while the PV system recorded an increase in PMV from -2 to close to 0. The shift from zero insulation to a summer outfit, however, is towards from the moderate to a slightly warm to warm range in PMV for MV and DV systems at window and aisle seat locations.
The aisle corridor also recieves an increase in PMV from -2 to -1 for the three ventilation scenarios. PPD is now placed below 40% for all ventilation systems. The aisle corridor is observed to obtain the highest variation in PPD in comparison to that obtained from the naked passengers.
4.5
Heat Removal Efficiency and Mean
tem-perature difference
The mean temperature difference (∆THA) between head and foot level as well as
Heat Removal Efficiency (2.4) is measured for all ventilation systems [9]. The ∆THA
is calculated by taking the mean temperature at head and foot level on a plane directly infront of the passenger. Figure24reveals PV performing better in terms of both the least temperature difference between head and foot level and the highest in HRE. MV reaches an HRE around 0.5 which is the theoretical ideal which expresses Tout = Tcabin([9]) from equation6. DV has the lowest HRE out of the three which
is expected with the increase in distance between the inlet and outlet and also the low inlet velocity rate from the diffusers does not allow for a thoroughly mixing of fluids.
Figure 24: Mean temperature difference (∆THA) between head and foot level and Heat Removal Efficiency (HRE) for all three ventilation types. [1 (MV), 2 (DV) and 3 (PV)]
4.6
CO
2(ppm) Distribution in the Cabin
Figure 25: CO2 ppm level in the cabin near humans on different positions
Figure25 depicts the cabin CO2 levels in all three ventilation systems. The
person-alized ventilation systems had a lower CO2 distribution level in window and aisle
seat when compared to mixing and displacement ventilation systems. The maximum CO2 level of 130 ppm was reached in window and aisle seats for the personalized
ventilation systems. In the mixing ventilation system higher CO2 level of 475 ppm
and 380 ppm was reached in window and aisle seat respectively near the breathing zone. CO2 levels was quite uniform from head to thigh region in window and aisle
aisle corridor, CO2 levels were found to be lower with good breathing zone.
Fur-thermore, below the overhead cabin baggage region CO2 levels reached peak value
of 1500 ppm for displacement ventilation system in the window seat.
4.7
Contaminant Transport Study
Figure 26 depicts the contour plots of Mass fraction of CO2 used to represent the
airborne pathogen for each ventilation systems which is taken at a plane of a dis-tance of 0.055 m from the passenger’s face. The range of values depicted on the left of each figure presented below is displayed via the local range option in ANSYS CFX post. It displays the minimum and maximum range value on the plane (men-tioned above) in order to take advantage of the full color range to better highlight the contaminant pathogen. In order to investigate the contaminant spread inside the entire cabin volume, a volume render is also extracted (see Appendix A: figure
27 and28) which is discussed further in the report.
For the case of Mixing ventilation, both window and aisle passenger as index pas-sengers (figure26 a & b) show a high level probability of infecting the neighbouring passenger as the concentration is high near the breathing zone.
Displacement ventilation reduces the transport of the pathogen with minimum risk of infecting the neighbouring passenger with mass fraction values close to null at their breathing zone (figure26 c & d).
The PV system effectively isolates the spread of the airborne pathogen from the window passenger by forcing it towards the outlet and thus minimizing the risk of the aisle passenger getting infected (figure26 e). The window passenger is also un-affected with the aisle passenger as the index patient in figure26 f.
Table 10 depicts the measured average mass fraction values of the contaminant in the entire cabin for different ventilation systems with the window seat and aisle seat passenger simulated as index passengers individually for all ventilation systems. The PV system is the most effective in reducing the overall virus present in the cabin when compared with the MV and DV systems while DV shows the highest risk of further spreading the virus within the cabin.
Table 10: Average mass fraction of contaminant in cabin volume for different ventila-tion systems.
Ventilation Type Index Passenger Index Passenger at window seat at aisle seat
Mixing Ventilation 0.0017 0.0014
Displacement Ventilation 0.0029 0.0028 Personalized Ventilation 0.00064 0.0010
(a) MV Window index passenger (b) MV Aisle index passenger
(c) DV Window index passenger (d) DV Aisle index passenger
(e) PV Window index passenger (f) PV Aisle index passenger
Figure 26: Contaminant transport visualization through contour plots of CO2 mass
5
Discussion
5.1
Aircraft cabin with humans
5.1.1
Mixing Ventilation
Mixing Ventilation type is defined by the formation of a re-circulation zone within the occupant zone and a thorough mixing of air. Air velocity as revealed by the velocity profiles increases from the window seat towards the aisle corridor (Figure
16). This is because of the high momentum jet which is forced from diffuser strips and into the cabin aisle corridor after which circulates due to inertial, viscous and buoyancy forces forming a vortex. As the jet flow enters the occupant zone, the draught loses it’s momentum from the circulating vortex and could also be effec-tively obstructed by passenger seats. This re-circulation region can be reduced by increasing the incoming velocity in the inlets at the expense of higher draught inside the cabin.
In a mixing ventilation system, most of the heat transfer happens by forced convec-tion inside the aircraft cabin. A large temperature difference of 9 degrees is recorded using the inbuilt probe tool in ANSYS CFX post which is observed across the seat width of the aisle passenger. This difference is visible in the temperature contour plots in figure20. This drastic change in temperature is a result of forced convection which the aisle passenger recieves from the high momentum of inlet jet flow located underneath the baggage bin. This difference could be a cause for discomfort for the aisle passenger.
For MV, there is a temp difference of less than 2 degrees between the head and ankle level of the passenger at all three measured locations. This difference should not cause any discomfort for the passengers.
The analytical form (calculated based on the combined quantitative combination of the environmental and individual variables in Fanger’s equation) of PMV and PPD for the mixing ventilation expressed in figure 22 reveal the window seat passenger to have a better overall thermal comfort experience than the aisle seat passenger and in the aisle corridor. The PMV for the window passenger averages out with a thermal feeling of moderate on the thermal comfort scale (Table5) from the head to just before the thigh level after which there is a sudden jump to a warm sensation of +2 and back to 0 on the thermal scale. This sudden spike can be explained by the heat dissipation from the human leg region as the position of the measuring line (figure 10) runs close to the legs and at a distance from the rest of the manikin. The aisle seat passenger is seen subjected to an oscillation of thermal sensations from head to feet which go back and forth from -2 to +1 on the scale indicating a thermal perception from cool to slightly warm. This is likely as the aisle seat passenger is caught in between the high momentum jet from the diffuser strip underneath the baggage bin and the circulating air vortex formed in the occupant zone.
