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Analysis of the impact of the location of a window type air-conditioner on thermal comfort in an office room

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Title:
Analysis of the impact of the location of a window type air-conditioner on thermal comfort in an office room
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Book
Language:
English
Creator:
Begdouri, Hamza
Publisher:
University of South Florida
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Tampa, Fla.
Publication Date:

Subjects

Subjects / Keywords:
Heat
Convection
Flow
Relative humidity
Contaminant removal
Dissertations, Academic -- Mechanical Engineering -- Masters -- USF   ( lcsh )
Genre:
government publication (state, provincial, terriorial, dependent)   ( marcgt )
bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

Notes

Summary:
ABSTRACT: This study considers airflow simulations to evaluate the impact of different window air-conditioner locations on the thermal comfort in an office room (OR). This thesis compares the air distribution for an office room by using computational fluid dynamics (CFD) modeling to previously studied rooms. The air distribution was modeled on a typical office room window air conditioning unit, air supply from a high pressure on the top and the low pressure exhaust on the bottom considering the existing manufacturing ratios for surface areas. The discharge angle for the supply grill of the AC unit was varied from 20 to 40 degrees. The position of the air conditioner was also varied and studied at 60%, 75% and 90% of the total height of the room. In addition, the location of the occupant within the office room was varied, two locations were studied, one where the occupant is far from the unit and the other to closer to the AC unit at the middle of the room.Predictions of the air movement, room temperature, room relative humidity, comfort level, and distribution of contaminants within the office room are shown. Analysis of these simulations is discussed. Energy estimations are also performed and evaluated. The positions of the air-conditioner unit, the inlet angle and the occupant position in the office room have shown to have an important impact on supply controlling air quality and thermal comfort. Results are in good agreements with the experimental data.The primary function of a HVAC (heating refrigerating and air conditioning) system is the generation and maintenance of comfort for occupants in a conditioned space 1. This work also provides a detailed analysis of three-dimensional mixed convective flow induced by a window air conditioning system. Using a three dimensional CFD simulation, several characteristics of human comfort are analyzed.
Thesis:
Thesis (M.S.M.E.)--University of South Florida, 2005.
Bibliography:
Includes bibliographical references.
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Mode of access: World Wide Web.
Statement of Responsibility:
by Hamza Begdouri.
General Note:
Title from PDF of title page.
General Note:
Document formatted into pages; contains 175 pages.

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aleph - 001681109
oclc - 62776423
usfldc doi - E14-SFE0001005
usfldc handle - e14.1005
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ABSTRACT: This study considers airflow simulations to evaluate the impact of different window air-conditioner locations on the thermal comfort in an office room (OR). This thesis compares the air distribution for an office room by using computational fluid dynamics (CFD) modeling to previously studied rooms. The air distribution was modeled on a typical office room window air conditioning unit, air supply from a high pressure on the top and the low pressure exhaust on the bottom considering the existing manufacturing ratios for surface areas. The discharge angle for the supply grill of the AC unit was varied from 20 to 40 degrees. The position of the air conditioner was also varied and studied at 60%, 75% and 90% of the total height of the room. In addition, the location of the occupant within the office room was varied, two locations were studied, one where the occupant is far from the unit and the other to closer to the AC unit at the middle of the room.Predictions of the air movement, room temperature, room relative humidity, comfort level, and distribution of contaminants within the office room are shown. Analysis of these simulations is discussed. Energy estimations are also performed and evaluated. The positions of the air-conditioner unit, the inlet angle and the occupant position in the office room have shown to have an important impact on supply controlling air quality and thermal comfort. Results are in good agreements with the experimental data.The primary function of a HVAC (heating refrigerating and air conditioning) system is the generation and maintenance of comfort for occupants in a conditioned space [1]. This work also provides a detailed analysis of three-dimensional mixed convective flow induced by a window air conditioning system. Using a three dimensional CFD simulation, several characteristics of human comfort are analyzed.
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PAGE 1

Analysis Of The Impact Of The Loca tion Of A Window Type Air-Conditioner On Thermal Comfort In An Office Room by Hamza Begdouri A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering Department of Mechanical Engineering College of Engineering University of South Florida Major Professor: Muhammad Rahman, Ph.D. Autar Kaw, Ph.D. Frank Pyrtle, III, Ph.D. Date of Approval: March 28, 2005 Keywords: heat, convection, flow, rela tive humidity, contaminant removal Copyright 2005, Hamza Begdouri

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Dedication To my father for his patience and support A mon pre pour sa patience et son support

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Acknowledgments I would like to thank Dr. Muhammad Rahman for giving me the opportunity to do my masters under his guidance. Also I would like to thank Dr. Luis Rosario for his wonderful assistance, Dr. Autar Kaw and Dr. Frank Pyrtle for their uplifting sprits and their sharpness, Micheal Jurczyk MSME and Son Ho MSME for their help and commitment to excellence. All the staff at the mechanical engineering depa rtment at the Universi ty of South Florida, Sue Britten, Sherly Tervort, and wes Frusher. Mr. Richard Lafond, Director of En gineering at Leslie Controls fo r his help and leniency.

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i Table of Contents List of Tables iii List of Figures v Abstract x Chapter 1 – Introduction 1 1.1Overview of Two Dimensional Simulation of Window Type Air-Conditioning in an Office Room 1 1.2 Overview of Three Dimensional Simulati on of Window Type Air-Conditioning in an Office Room 4 1.3 Thesis Outline 6 1.4 Nomenclature 7 Chapter 2 – Simulation Approaches 9 2.1 Introduction 9 2.2 Governing Equations 10 2.3 Thermal Comfort Assessment 13 2.4 Energy Consumption 15 Chapter 3 – Two Dimensional Simu lation of Window Air-Conditioner in an Office Room 16 3.1 Introduction 16 3.2 CFD Model 17 3.3 Results and Discussion 20 Chapter 4 – Three Dimensional Simulation of Window Air-Conditioner in an Office Room 56 4.1 Introduction 56 4.2 CFD Model 57 4.3 Results and Discussion 61 4.3.1 Simulation with 30o inlet angle 61 4.3.2 Simulation with 20o inlet angle 92 4.3.3 Simulation with 40o inlet angle 119 Chapter 5 – Conclusions and Recommendations 147 5.1 Two Dimensional Simulation of Office Room 147

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ii 5.2 Three Dimensional Simulation of Office Room 148 5.3 Recommendations 149 References 151 Appendices 153 Appendix A: FIDAP Program of Two Di mensional Simulation for an Office Room 154 Appendix B: FIDAP Program of Three Dimensional Simulation for an Office Room 161

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iii List of Tables Table 3-1 Simulation matrix.............................................................................................17 Table 3-2 Dimensions parameters of Fig.3-1, meter(s)....................................................18 Table 3-3 Boundary conditions.........................................................................................19 Table 3-4 Comparison of experimental data [7], CFD model [7], and current CFD model.........................................................................................................45 Table 3-5 Comparison of CFD mode l [8] and current CFD model..................................46 Table 3-6 Conditions of the second pos ition (closer to the unit) compared with base case....................................................................................................50 Table 3-7 Simulations and relative humidity....................................................................51 Table 3-8 Simulations and contaminant removal effectiveness.......................................53 Table 3-9 Changing occupant position and % energy Consumption................................55 Table 4-1 Simulation dimensions.....................................................................................58 Table 4-2 Simulation boundary conditions.......................................................................59 Table 4-3 Cross-sectional planes examined......................................................................60 Table 4-4 Relative humidity in the studied planes............................................................82 Table 4-5 Comparison of relative humidity and temperature in 30o inlet angle 2-D and 3-D models...........................................................................................90 Table 4-6 Concentration of contaminant and CRE, for 30o inlet angle............................92 Table 4-7 Comparison of relative humidity and temperature in 20o inlet angle 2-D and 3-D models...........................................................................................93 Table 4-8 Concentration of contaminant and CRE, for 20o inlet angle..........................112

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iv Table 4-9 Relative humidity in the studied planes..........................................................116 Table 4-10 Comparison of relative humidity and temperature in 40o inlet angle 2-D and 3-D models...............................................................................120 Table 4-11 Concentration of contaminant and CRE, for 40o inlet angle........................124 Table 4-12 Relative humidity in the studied planes........................................................131

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v List of Figures Figure 3-1 Sketch of the 2D model of office room...........................................................18 Figure 3-2 Velocity field, base case, values of speed are in (cm/s)..................................21 Figure 3-3 Temperature profile, base case........................................................................22 Figure 3-4 Water vapor dist ribution, base case................................................................23 Figure 3-5 Contaminant c oncentration, base case...........................................................24 Figure 3-6 Velocity field, 20o inlet angle, values of speed are in (cm/s)..........................26 Figure 3-7 Temperature pr ofile, inlet angle at 20o............................................................27 Figure 3-8 Water vapor distri bution, inlet angle at 20o....................................................28 Figure 3-9 Contaminant concentration, inlet angle at 20o................................................29 Figure 3-10 Velocity field, 400 inlet angle, values of speed are in (cm/s)........................31 Figure 3-11 Temperature pr ofile, inlet angle at 40o..........................................................32 Figure 3-12 Water vapor distri bution, inlet angle at 40o..................................................33 Figure 3-13 Contaminant concen tration, inlet angle at 40o..............................................34 Figure 3-14 Velocity field, unit at 60% of he ight, values of speed are in (cm/s).............36 Figure 3-15 Temperature profile unit at 60%of height....................................................37 Figure 3-16 Water vapor distributi on, unit at 60% of height............................................38 Figure 3-17 Contaminant concentrat ion, unit at 60% of height........................................39 Figure 3-18 Velocity field, unit at 90% of he ight, values of speed are in (cm/s).............41 Figure 3-19 Temperature profile unit at 90% of height...................................................42

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vi Figure 3-20 Water vapor distributi on, unit at 90% of height............................................43 Figure 3-21 Contaminant concentrat ion, unit at 90% of height........................................44 Figure 3-22 Temperature profiles of both si mulations and experiment vs. Height..........46 Figure 3-23 Thermal sensa tion vs. inlet angle..................................................................47 Figure 3-24 Predicted mean vote vs. inlet angle...............................................................47 Figure 3-25 Thermal sensation vs. unit height..................................................................48 Figure 3-26 Predicted mean vote vs. unit height..............................................................49 Figure 3-27 Predicted percentage diss atisfied (PPD) vs. inlet angle................................50 Figure 3-28 Predicted percentage diss atisfied (PPD) vs. unit height................................51 Figure 3-29 % Energy consumption vs. inlet angle..........................................................54 Figure 3-30 % Energy consumption vs. unit height.........................................................54 Figure 4-1 Layout of the 3D simulated office room.........................................................58 Figure 4-2 Temperature profile on plane 1, inlet angle of 30o..........................................62 Figure 4-3 Temperature profile on plane 2, inlet angle of 30o..........................................63 Figure 4-4 Temperature profile on plane 3, inlet angle of 30o..........................................64 Figure 4-5 Contaminant profile on plane 1, inlet angle of 30o.........................................66 Figure 4-6 Contaminant profile on plane 2, inlet angle of 30o.........................................67 Figure 4-7 Contaminant profile on plane 3, inlet angle of 30o.........................................68 Figure 4-8 Velocity profile on plane 1, inlet angle of 30o................................................69 Figure 4-9 Velocity profile on plane 2, inlet angle of 30o................................................70 Figure 4-10 Velocity profile on plane 3, inlet angle of 30o..............................................71 Figure 4-11 Temperature profile on plane 5, inlet angle of 30o........................................72 Figure 4-12 Temperature profile on plane 4, inlet angle of 30o........................................73

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vii Figure 4-13 Temperature profile on plane 6, inlet angle of 30o........................................74 Figure 4-14 Contaminant profile on plane 5, inlet angle of 30o.......................................76 Figure 4-15 Contaminant profile on plane 4, inlet angle of 30o.......................................77 Figure 4-16 Contaminant profile on plane 6, inlet angle of 30o.......................................78 Figure 4-17 Velocity profile on plane 5, inlet angle of 30o..............................................79 Figure 4-18 Velocity profile on plane 4, inlet angle of 30o..............................................80 Figure 4-19 Velocity profile on plane 6, inlet angle of 30o..............................................81 Figure 4-20 Relative humidity on plane 1, inlet angle of 30o...........................................83 Figure 4-21 Relative humidity on plane 2, inlet angle of 30o...........................................84 Figure 4-22 Relative humidity on plane 3, inlet angle of 30o...........................................85 Figure 4-23 Relative humidity on plane 5, inlet angle of 30o...........................................87 Figure 4-24 Relative humidity on plane 4, inlet angle of 30o...........................................88 Figure 4-25 Relative humidity on plane 6, inlet angle of 30o...........................................89 Figure 4-26 Temperature profiles fo r both simulations vs. height...................................91 Figure 4-27 Temperature profile on plane 1, inlet angle of 20o........................................94 Figure 4-28 Temperature profile on plane 2, inlet angle of 20o........................................95 Figure 4-29 Temperature profile on plane 3, inlet angle of 20o........................................96 Figure 4-30 Contaminant profile on plane 1, inlet angle of 20o.......................................97 Figure 4-31 Contaminant profile on plane 2, inlet angle of 20o.......................................98 Figure 4-32 Contaminant profile on plane 3, inlet angle of 20o.......................................99 Figure 4-33 Velocity profile on plane 1, inlet angle of 20o............................................100 Figure 4-34 Velocity profile on plane 2, inlet angle of 20o............................................101 Figure 4-35 Velocity profile on plane 3, inlet angle of 20o............................................102

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viii Figure 4-36 Relative humidity on plane 1, inlet angle of 20o.........................................103 Figure 4-37 Relative humidity on plane 2, inlet angle of 20o.........................................104 Figure 4-38 Relative humidity on plane 3, inlet angle of 20o.........................................105 Figure 4-39 Temperature profile on plane 4, inlet angle of 20o......................................106 Figure 4-40 Temperature profile on plane 5, inlet angle of 20o......................................107 Figure 4-41 Temperature profile on plane 6, inlet angle of 20o......................................108 Figure 4-42 Contaminant profile on plane 4, inlet angle of 20o.....................................109 Figure 4-43 Contaminant profile on plane 6, inlet angle of 20o.....................................110 Figure 4-44 Contaminant profile on plane 5, inlet angle of 20o.....................................111 Figure 4-45 Velocity profile on plane 4, inlet angle of 20o............................................113 Figure 4-46 Velocity profile on plane 5, inlet angle of 20o............................................114 Figure 4-47 Velocity profile on plane 6, inlet angle of 20o............................................115 Figure 4-48 Relative Humidity on plane 4, inlet angle of 20o........................................117 Figure 4-49 Relative Humidity on plane 5, inlet angle of 20o........................................118 Figure 4-50 Relative Humidity on plane 6, inlet angle of 20o........................................119 Figure 4-51 Temperature profile on plane 1, inlet angle of 40o......................................121 Figure 4-52 Temperature profile on plane 2, inlet angle of 40o......................................122 Figure 4-53 Temperature profile on plane 3, inlet angle of 40o......................................123 Figure 4-54 Contaminant profile on plane 1, inlet angle of 40o.....................................125 Figure 4-55 Contaminant profile on plane 2, inlet angle of 40o.....................................126 Figure 4-56 Contaminant profile on plane 3, inlet angle of 40o.....................................127 Figure 4-57 Velocity profile on plane 1, inlet angle of 40o............................................128 Figure 4-58 Velocity profile on plane 2, inlet angle of 40o............................................129

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ix Figure 4-59 Velocity profile on plane 3, inlet angle of 40o............................................130 Figure 4-60 Relative Humidity on plane 1, inlet angle of 40o........................................132 Figure 4-61 Relative Humidity on plane 2, inlet angle of 40o........................................133 Figure 4-62 Relative Humidity on plane 3, inlet angle of 40o........................................134 Figure 4-63 Temperature profile on plane 4, inlet angle of 40o......................................135 Figure 4-64 Temperature profile on plane 5, inlet angle of 40o......................................136 Figure 4-65 Temperature profile on plane 6, inlet angle of 40o......................................137 Figure 4-66 Contaminant profile on plane 4, inlet angle of 40o.....................................138 Figure 4-67 Contaminant profile on plane 5, inlet angle of 40o.....................................139 Figure 4-68 Contaminant profile on plane 6, inlet angle of 40o.....................................140 Figure 4-69 Velocity profile on plane 4, inlet angle of 40o............................................141 Figure 4-70 Velocity profile on plane 5, inlet angle of 40o............................................142 Figure 4-71 Velocity profile on plane 6, inlet angle of 40o............................................143 Figure 4-72 Relative Humidity on plane 4, inlet angle of 40o........................................144 Figure 4-73 Relative Humidity on plane 5, inlet angle of 40o........................................145 Figure 4-74 Relative Humidity on plane 6, inlet angle of 40o........................................146

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x Analysis of the Impact of the Location of a Window Type Air-Conditioner on Thermal Comfort in an Office Room Hamza Begdouri ABSTRACT This study considers airflow simulations to evaluate the impact of different window air-conditioner locations on the thermal comfort in an office room (OR). This thesis compares the air distribution for an office room by using computational fluid dynamics (CFD) modeling to previously st udied rooms. The air distribution was modeled on a typical office room window air conditioning unit, air supply from a high pressure on the top and the low pressure e xhaust on the bottom considering the existing manufacturing ratios for surface areas. The di scharge angle for the supply grill of the AC unit was varied from 20 to 40 degrees. The position of the air conditioner was also varied and studied at 60%, 75% and 90 % of the total height of the room. In addition, the location of the occupant within the office room was varied, two locations were studied, one where the occupant is far from the unit an d the other to closer to the AC unit at the middle of the room. Predictions of the air mo vement, room temperature, room relative humidity, comfort level, and distribution of contaminants within the office room are shown. Analysis of these simulations is disc ussed. Energy estimations are also performed and evaluated. The positions of the air-conditioner unit, the inlet angle and the occupant position in the office room have shown to ha ve an important impact on supply controlling

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xi air quality and therma l comfort. Results are in good agre ements with the experimental data. The primary function of a HVAC (heatin g refrigerating and air conditioning) system is the generation and maintenance of comfort for occupants in a conditioned space [1]. This work also provides a detailed an alysis of three-dimensional mixed convective flow induced by a window air conditioning system. Using a three dimensional CFD simulation, several characteristic s of human comfort are analyzed. The results of this study show a strong relation between the pos ition of the wall-mounted air conditioning unit and the thermal comfort of the occupant. The results ar e in good agreement with the experimental data and the two dimensional simulation.

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1 Chapter 1 Introduction 1.1 Overview of Two Dimensional Simulati on of Window Type Ai r-Conditioning in an Office Room The air conditioning system has a great impact on the quality of life in this century indicating the great significance of this field in the world. Air-conditioning systems usually provide year-round control of several air conditions, namely, temperature, humidity, cleanliness, and air motion. Window air units are easy to install and can be plugged into any office circuit that is not shared with any other major equipment. Larger room air conditioners need th eir own dedicated circuit. The air-conditioning market in the world ha s grown considerably in the last few years. It continues its phe nomenal growth in line with the many residential and commercial projects taking plac e particularly in developi ng countries. As competition intensifies in the global residential air condit ioning market, prices will tend to fall. This trend should open markets to new end-user s who could not previously afford air conditioning because it was considered to be a luxury item. By increasing end-user exposure to air conditioning in shops, offices and cars, there is a transition among consumers to an air-conditioned lifestyle. This means that the market for self-contained, window or wall-type air conditi oning machines is growing ra pidly because its price and simplicity of installation.

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2 One of the most common air conditioning problems in office spaces is improper operation. All office’s windows and outside doors must be closed when an air conditioner unit is operating. Other common problems with existing window air conditioners result from faulty installation, poor service procedures, and inadequate maintenance. Improper installation of your air conditioner can result in bad airflow distribution. Many times, the air conditioner location does not match that stated by the manufacturer's specifications. If proper refrigerant charging is not performe d during installation, the performance and efficiency of the unit is impaired. Service technicians often fail to find refrigerant charging problems or even worsen existing pr oblems by adding refrigerant to a system that is already full. Air c onditioner manufacturers genera lly make rugged, high quality products. If an air cond itioner is installed correctly, or if major installa tion problems are found and fixed, it will perform efficientl y for years with only minor routine maintenance. However, many window air condit ioners are not instal led correctly due to lack of general guidelines. As an unfort unate result, modern energy-efficient air conditioners can perform almost as poor ly as older inefficient models [2]. In several countries, the use wall mounted air conditioners is great because of low cost, maneuverability and frequently due to seasonal sever weather conditions. However, many applications are arbitrarily judged due to lack of information and guidelines about these units. Few occupants of rooms either offices or bedrooms equipped with wallmounted air conditioners are ever satisfied w ith comfort levels. Occ upant would routinely change positions or the setting on the units. Similar to FEA (Finite Element Analysis), CFD use is a very re liable technique in studying and analyzing fluid patterns. Most im portantly CFD is helpful in solving for

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3 specific fluid properties by simultaneously computing multiple fluid equations. The simulation procedure is depends on needs for each application, it allows changes of boundary conditions accordingly. CFD is used in every domain where it is important to predict fluid behavior e.g. medical study of bodily flui ds, transmission lines carrying steam or fuel etc. The continued progress of CFD in recent times have disclosed the potential of economical yet effective way for improving HVAC system in the design phase, with less experiment required One advantage of CFD si mulations is that it allows specific of a room that has relevant airflow. CFD models have been used to st udy indoor air quality (IAQ) situations, pollutant distribution, a nd performance of air conditioning systems (Chow and Fung [3], Emmerich [4], Gadg il and [5]). Hirnikel [6] investigated contaminant removal of three distribution syst ems for bars and rest aurants by using CFD simulations. They showed that directiona l airflow systems could reduce people’s exposure to contaminants. Experimental work has been done on studying wall-mounted air conditioning units; most described experiments are base d on physical measurements of different variables. Some of these studies were associ ated CFD models have been applied to study HVAC system for window unit applications [7] [8] CFD has previously gave remarkable results for similar studies of thermal comfort and contaminant removal [9], where si milar characteristics of the human comfort inside an office room where numerically computed thus clarified multiple predictions made in setting the boundary conditions. Seve ral models of CFD simulations are being utilized in building and m oving vehicles for HVAC studie s, statistical, dynamic, and

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4 transient models [10]. Listed and coupled with their optimum applica tions they can give outstanding predictions depending on the use. List of these models and the newest impr ovements that have be en achieved in the last eight years are listed in the ASHRAE (A merican society of heating refrigerating and air-conditioning engineer s) literature review of adva nce thermal comfort presented by Yanzheng [11]. This list shows recent adva nces in thermal comfort modeling bases on heat balance, direct statistical and neutral network approaches. They show that the heat exchange com ponent of the model provides the input for the thermoregulation model, the heart of the comfort level model. The present study analyses fluid flow in an office room pr esented in a two dimensional model. Using CFD simulations numerical simulations were made to investigate the velocity, temperature, therma l comfort and air quality in the office room. Proper assumptions are made and several observations are note d. The corresponding results are studied and explai ned in the following sections 1.2 Overview of Three Dimensional Simula tion of Window Type Air-Conditioning in an Office Room Comfort in rooms cooled by window-type air conditioner has always been an issue, most commonly thought to be a malf unction of the unit itself. Several studies including the present one have proved that co mfort levels are influenced mainly by more physical parameters including installed positi on, supply air speed, angle of flow, inlet flow temperature, as well as indoor air distri bution. Change in size of the cooled space is not always compensated by change of air flow speed or inlet temperature in order to

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5 obtain optimum comfort, because of rela tive humidity changes and typical air distribution. Installed position of the window-type ai r-conditioning unit, if all other boundary conditions are constant, is the most importa nt parameter to create optimum comfort levels. Many studies have been made in the past using CFD Co mputational Fluid Dynamics to study HVAC systems in office room s. CFD has proven to be most effective and cost efficient for HVAC systems especia lly in the design phase. One advantage of CFD simulations is that it allows specific condi tions of a room that has relevant airflow. However, there is no standard turbulent model or numerical scheme for all indoor room simulations, which indicates that the fi rst priority and one of the most important steps of CFD simulation, is to choosing the appropriate turbulent model to suit a specific application. Wall mounted air-conditioners are usually installed in the middle of the office room, from high above the standing height to the bottom of the room if the windows are low enough. This arbitrary height position and the distance from the occupant to the unit are usually the cause of human discomfort pr ovoking a change of the setting of the unit. Settings of wall-mounted unit can be changed, both for airflow speed or inlet angle can change and improve thermal comfort in offices, however, it is not ne cessarily the answer. The present study analyses fluid flow in an office room presented in one three dimensional model. Velocity, air quality, temperature, and thermal comfort were investigated using CFD simulations and nume rical computations. Proper assumptions are

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6 made and several observations are noted. The corresponding resu lts are studied and explained in the following sections. Indoor thermal comfort conditions are primarily computed using velocity, relative humidity and temperature. These c onditions are determined by solving coupled equations for the conservation of mass, mo mentum and energy for the carrier fluid including species then by solving the same equations for the each specie (water vapor, and contaminant gas). It is primarily assume d that for air conditioning applications in a closed space that the conditions are steady st ate, and the focus is directed to certain regions of interest e.g. the imme diate working space around the person. The objective of this section is to pr edict the impact of the location of a wallmounted air conditioner on the thermal comf ort and compare it to a previous tow dimensional model as well as other similar CFD simulations. 1.3 Thesis Outline This thesis presents and compares the CFD simulations of two identical office rooms cooled with a window type air conditi oning unit. Chapter 2 outlines the simulation approach for each problem. The two dimensional problem is described in Chapter 3, where inlet angle, location of the unit with respect to height, and the occupant location position have been varied. The thermal comfor t has been studied and compared to each variation. In Chapter 4, an id entical problem was studied in three dimensional simulation, where horizontal and vertical sections have been studied. Heat transfer and thermal comfort indices were analyzed and compared for each section. FIDAP, a Fluent.Inc CFD

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7 software package, was used for all simula tions. The output was analyzed using FIDAP post processing package and Microsoft excel. Additional experimental data was taken from literature. 1.4 Nomenclature C Mean contaminant concentration, kg of contaminant/kg of air mixture cp Specific heat of air, J/(kg.K) D Mass diffusivity of species in air, m2/s fcl Ratio of clothed surface area to nude surface area g Gravity acceleration, m/s2 h Heat transfer coefficient, W/(m2.K) I Thermal resistance, m2K/W k Thermal conductivity of air, W/(m.K) m Concentration of species, kg of species/kg of air mixture M Metabolic heat generation flux, W/m2 of naked body area p Pressure; partial pressu re (with subscript), Pa T Temperature; mean temperature (with subscript), C u velocity, m/s v Mean air speed rela tive to the body, m/s W External work, W/m2 of naked body area Y Thermal sensation index Ei Energy consumption Ratio TActual Average temperature difference to outside temperature TDesign Simulation temperature differe nce to outside temperature

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8 Greek Symbols Thermal expansion coefficient, 1/K Relative humidity Viscosity of air, kg/(m.s) Density of air, kg/m3 Subscripts S1 Water vapor S2 Contaminant a Air BZ Breathing zone cl Clothing E Exhaust ref Reference S Supply

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9 Chapter 2 Simulation Approaches 2.1 Introduction It is necessary to have the velocity, temperature and the relative humidity in order to determine the indoor thermal conditions in a room. These conditions are determined by solving coupled equations for the conserva tion of mass, momentum and energy for the carrier fluid including species then for the each specie. It is primarily assumed that for air conditioning applications in a closed space th at the conditions are steady state, and the focus is directed to certain regions of interest e.g. the immediate working space around the person. Variations of the unit position are studied, changing of the inlet flow angle are also explored. Also the effect of the person’ s location within the office room is presented. Energy estimations are also performed. The fluid properties were taken at reference temperature of Tref =22 0C = 295 K and their values are as follows: = 1.8273 E-5 kg/(m.s) cp= 1.0043 E3 J/(kg.K) k= 2.5776 E-2 W/(m.K) = 1.1967 kg/m3 =3.3932E-3 K-1

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10 D1= 0.2513E-5 m2/s D2= 0.2308E-5 m2/s 2.2 Governing Equations For an incompressible flow of air as a carrier for multiple components such as water vapor, contaminant gas, and of course dry air, and considering only the density of the buoyancy term to be varying keeping all properties of the flui d to constants, the equation of conservation of mass app lied to a whole carrier fluid is : 0 u (2.1) Assuming no chemical reactions nor source and that the mass di ffusivities of all species are constant, thermal diffusion (Soret effect) is negligible, the mass conservation equation of water vapor and contam inant gas as carried species is 1 2 1 1D m m u (2.2) And, 2 2 2 2D m m u (2.3) In most HVAC application, the concentrations of the species are minimal which makes the buoyancy dependency on them neglig ible. Thus the equation of conservation of linear momentum looks as follows, refT T p g u u u2 (2.4)

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11 With no heat generation nor inter-diffu sion, also having constant thermal conductivity throughout the pr ocess, the equation of energy conservation is T k T cp 2 u (2.5) The parameters of boundary conditions of our problem were implemented in the solving method for equation from Eq.2.1 through Eq.2.5 as follows, To satisfy continuity and momentum Eq.2.1 and Eq.2.4 respectively, a constant velocity was given to the in let fluid keeping all other pa rts (walls and light) at zero velocity including person. For Eq.2.2 and Eq.2.3 which are the contaminant and the water vapor equations, a constant flux of both was associated with the person, constant flux of water vapor for the inlet keeping the flux of the contaminant at zero, and zero flux of both species for all other elements of the room. A constant temperature was given to the inlet, walls and person, also a constant heat flux wa s associated with light fixture in order satisfy Eq.2.5. By computing these equations for a twodimensional flow problem, temperature, pressure, velocity on the x-axis, velocity on the y-axis, species 1, and specie 2 are solved for. Relative humidity is obtained using, te mperature, pressure, and water vapor concentration and following the procedure described by ASHRAE [12] as follows: ws wp p (2.6) Where,

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12 1 137802 0 62198 0 101325 m m p pw (2.7) And, 15 273 ln 546 6 15 273 10 445 1 15 273 10 176 4 15 273 10 864 4 516 5 15 273 10 800 5 exp 10003 8 2 5 2 3 T T T T T pws (2.8)

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13 2.3 Thermal Comfort Assessment For thermal comfort assessment, Fanger m odel [13] is mostly used by ASHRAE [12]. Because it is based on steady state en ergy balance this model was specifically designed for office room applications even though its use has taken a broader domain. PMV, Predicted Mean Vote is a parameter that determines thermal comfort based on the metabolic rate, kind of clothing, velo city, temperature, and humidity in the occupied space. Fanger determines the PMV to be, a cl c cl a cl cl a w wT T h f T T f T M p M W M p W M W M W M 4 4 8 5 3273 273 10 96 3 34 0014 0 5867 10 7 1 15 58 42 0 99 6 5733 10 05 3 028 0 036 0 exp 303 0 PMV (2.9) where a cl c cl a cl cl cl clT T h f T T f I W M T 4 4 8273 273 10 96 3 028 0 7 35 (2.10) greater is whichever v 1 12 or 38 25 0 25 0 c a cl ch T T h (2.11) K/W m 078 0 for 645 0 05 1 K/W m 078 0 for 29 1 00 12 2 cl cl cl cl clI I . I I f (2.12) PMV is directly related to the Predicted Percentage Dissatisfied PPD index, it is an estimating on human reaction to such temper atures and humidity ratios in the room. This relation is stated as follows. PPD = 100-95-n (2.13) Where, n = 0.03353 PMV4 + 0.2179PMV2 (2.14)

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14 Thermal sensation ( Y) is another parameter shown usua lly as an index that reflects the effect of surrounding (humidity, length of exposure) and personal (sex, size) variables on the thermal respons e and comfort level, Rohles and Nevins [14] predict the thermal sensation for average sexes combined wi th a standard 3 hour exposure time to be 802 6 000278 0 243 0 w ap T Y (2.15) ASHRAE, which also set a similar scal e for the PMV has set a scale for the thermal sensation to vary between -3 and 3: -3 being the coldest and 3 being the hottest as follows: 3= hot 2= warm 1= slightly warm 0= neutral -1= slightly cool -2= cool -3= cold Another variable studied in the evaluation of comfort levels in a closed working space is the Contaminant Removal Effectivenes s (CRE). It is determined by evaluating the average concentration in the breathing zone; the breathing zone is defined as: the region within an occupied space between pl anes is between 3 and 72 in. (75 and 1800 mm) above floor and more than 2 ft (600 mm) from the walls or fixed air-conditioning equipment [15] concentration at the inle t and at the outlet. And it is given by

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15 S BZ S EC C C C CRE (2.16) Where CBZ is the mean (average) concentration is the room, CS is the mean concentration in the supply, and CE the mean concentration at the exhaust (outlet). Assuming that there is no contaminant in the supply air Eq.16 becomes, BZ EC C CRE (2.17) 2.4 Energy Consumption Percentage Energy consumption is an important feature to be estimated in our work given by, 100 ] [ % Design Design ActualT T T n Consumptio Energy (2.18) This estimation is based on a 20 0F temperature difference between the design conditions and the actual temperature difference from our simulations under the same outside conditions.

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16 Chapter 3 Two Dimensional Simulation of Window Air-Conditioner in an Office Room 3.1 Introduction The objective of this chapter is to pred ict the impact of the location of a wallmounted air conditioner on the thermal comfort by varying discharge angles of the inlet, unit location, and occupant posi tion. This part of the work also compares results to previous CFD work and experimental data from previous work [7, 8]. As Table 3-1 presents the complete set of conditions used in the simulations. Three different sets of simulations were perf ormed, simulation 1 to 3 the inlet angle was changed from 20 to 40 degrees, while the height location of the unit and the position of the occupant were kept constant. Simulations 2, 4, and 5 considered the changes in the location of the AC unit keeping constant the inlet angle and the pos ition of the occupant. Simulations 2 and 6 represent the changing the posi tion of the occupant while k eeping all other parameters constants All these sets of simulations will allow the analysis of three factors influencing the thermal comfort in the office space: Locatio n of the unit, inlet angle, and position of the occupant.

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17 Table 3-1 Simulation matrix Simulation Number Inlet Angle % Unit Height from Total Height Position of Occupant 1 20 75% L1 2 30 75% L1 3 40 75% L1 4 30 60% L1 5 30 90% L1 6 30 75% Lx 3.2 CFD Model The office room was modeled as 2D rect angular region as shown in Figure 3-1, with an air conditioning unit at a given height of one of its sides (wall) of the room, a person configured as an upright smaller recta ngle placed at a distance from the unit, and a light fixture located at about half the width of the room and placed on the upper horizontal side (ceiling).

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18 Figure 3-1 Sketch of the 2D model of office room The numerical values of dimensions L1 to L9 used for the computations in this paper are presented in Table 3-2. Table 3-2 Dimensions parameters of Fig.3-1, meter(s) Name LengthNameLength L 4.8 L5 0.2 L1 3.2 L6 1.1 L2 2.7 L7 1.2 L3 1.7 L8 0.2 L4 0.3 L9 2.4

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19 The boundary conditions were chosen in order to complete the computational simulations. As Table 3-3 Shows, these cond itions are based on a typical office room cooled by a window AC unit. Table 3-3 Boundary conditions Entity Temperature and Heat Flux Velocity m/s Water Vapor Concentration Contaminant Concentration Inlet T=19 0C 3.50 c1 = 0.01 c2= 0 Walls T=24 0C 0 0 Person T = 34 0C 0 Flux=5E-6 kg/(m.s2) Flux=1E-8 kg/(m.s2) Light Flux= 50 W/m2 0 0 0 Outlet T=0 C Flux=0 0 0 0 The CFD simulations estimated variables such as pressure, velocity, temperature, and contaminant concentration for each cell throughout the entire office in accordance with mass, energy, and con centration equations. For eac h simulation, velocity and temperature were calculated first by solv ing the coupled equations, and then species concentrations (water vapor, and contaminan t gas) were studied with known a velocity field. With velocity, temperature, pressure and the species concentration known and using the method outlined by ASHRAE [15], the relative humidity is computed by inputting the temperature and the water vapo r concentration executing and for every cell of the studied space.

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20 Thermal sensation was calculated by using the person’s immediate surrounding temperature and pressure from the output CFD files and inputting in it into Eq.2.15. All cases simulated used the boundary c onditions presented in Table 3-3. The predicted mean vote (PMV) was calculated us ing equations Eq.2.9 to Eq.2.12 and the predicted percentage classified (PPD) inde x was evaluated using equations Eq.2.14 and Eq.2.15. Energy estimation was calculated us ing Eq.2.18 for each unit location being evaluated. In addition, contaminant removal effectiveness was calculated using Eq.2.13 3.3 Results and Discussion Figure 3-2 represents the velocity distribu tion in an office room being cooled by a window air conditioning unit; the figure shows the velocity profile for the base case (simulation 2 in Table 3-1). The velocity vect or and magnitude (speed) are illustrated for every section of the studied room. The fluid en ters the room from th e inlet on the left at angle of 30 at a speed of 3.5 m/s, it is h eading for the ceiling when it gets pushed to a steeper angle as incoming air encounters the air coming back from the previous circulations, the fluid then hits the ceiling and flows a parallel path until it reaches the light. Airflow then curves at sharp angle towa rds the floor, turns towards the left side of the room, flows parallel to the wall then exis t through the outlet. Also there are few splits of flow throughout the office room, the most important one is around and away from the person where airflow turns to the opposite wall after hitting the ground and mixes with the incoming air at the light fixture. Figure 3-3 shows the temperature profile fo r the basic case, on the side of the unit the temperature remains relatively unchanged an d low. Once air gets closer to the person

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21 and the light, temperature rises quickly. Air is considerably warmer at the light and around the person. Also, notice that the temper ature is warmer on the other side of the person where the split of airflow around the person as Fig. 3-2 shows. Figure 3-2 Velocity field, base case, values of speed are in (cm/s) The temperature profile is similar to the analysis of [8] where the vertical crosssection of the plan adjacent to the unit (Fig. 3-2, case b [8]) shows the same pattern inside the room. Water vapor in the room co mes from two sources, the inlet flow and the person’s transpiration; Fig.3-4 shows the water va por concentration, which is used with temperature in order to predict relative humidity at every section of the room. Notice that

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22 the concentration increases once the flow r eaches the occupant; the air-vapor mixture collects the vapor from the pers on and transports on the flow path. The driest section is around the light where the temper ature is at its highest and the moistest sections are around the person where transpiration is constant and on the far corner of the room where there is not much linear flow, only a stagnant circular motion of air. Figure 3-5 indicates contaminant distributi on, assuming as in the boundary conditions that the contaminant comes from the pers on only, is noticeable that contaminant concentration is at its highest around the pe rson. The flow then transports contaminant with different concentrati ons at different locations. Figure 3-3 Temperature profile, base case

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23 Figure 3-4 Water vapor di stribution, base case

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24 Figure 3-5 Contaminant c oncentration, base case

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25 When inlet angle is changed to 20 degrees (case1, Table3-1) as Fig.3-6 shows, as predicted the air direction is similar to the base case with the exception that the flow travels along the ceiling for a shorter distan ce, it is however clear that flow follows almost the same pattern as the previous case and flow split under the occupant is not as significant. This behavior expl ains the temperature profile shown in Fig.3-7 where warm temperature behind the person is taking a wide r region and more cold temperatures are distributed along the walls. Water vapor is mainly present between the person and the unit where temperatures are cooler, Fig.3-8. This behavior should result in hi gh relative humidity as it is the case. Figure 3-9 displays the contaminant concentr ation distribution in the office room. Since the occupant is the only source of contaminant, it is normal that the highest concentrations are in the person’s immedi ate surroundings. However, the amount of contaminant transported is lower than the base case.

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26 Figure 3-6 Velocity field, 20o inlet angle, values of speed are in (cm/s)

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27 Figure 3-7 Temperature pr ofile, inlet angle at 20o

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28 Figure 3-8 Water vapor distri bution, inlet angle at 20o

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29 Figure 3-9 Contaminant concentration, inlet angle at 20o

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30 At 40 degrees discharge angle( case3, table 3-1), flow is directed immediately upward making a longer travel along the ceiling with hi gh velocities at the front of the room, between unit and occupant, Fig.3-10. Notice that airflow split under the occupant is significant which allows some of the cold air to travel behind the person. Figure 3-11 confirms these observations as more cold air is found behind the person; however most of cold air is meanly con centrated between the person and the unit. Immediate surroundings of the person are still fairly warm. Water vapor concentration is low around the occupant indicat ing a high thermal reading in that region. Even with warm temperature around the occupant, co ntaminant is removed and transported following the velocity pattern, Fig.3-13. Also contaminant can be found on both sides of the person.

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31 Figure 3-10 Velocity field, 400 inlet angle, values of speed are in (cm/s)

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32 Figure 3-11 Temperature pr ofile, inlet angle at 40o

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33 Figure 3-12 Water vapor distri bution, inlet angle at 40o

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34 Figure 3-13 Contaminant concen tration, inlet angle at 40o

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35 For the second set of simulations the height of the unit is changed. First, the unit is moved to a height equal to 60% of the total office room height (cas e4, Table3-1). Notice in Fig.3-14, as airflow enters, it is directly oriented to the ceiling, and the person is directly in the path of the high speed downwar d flow. Air then splits on the head of the occupant then returns towards the outlet with a portion that travels around the other side of the person. Figure 3-15 hot air is carried out from the person and from the light fixture, which results in high temperatures, behind the occupant a nd in the flow path of returned air. Water vapor is removed from occupant and ca rried out following the velocity profiles throughout the office room, Fig.3-16. Similar to water vapor, and due to high velocities in front of the occupant, contaminant is rem oved from the top person to bottom, and high contaminant concentration is also located in the path of the returning air.

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36 Figure 3-14 Velocity field, unit at 60% of height, values of speed are in (cm/s)

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37 Figure 3-15 Temperature prof ile, unit at 60%of height

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38 Figure 3-16 Water vapor distribut ion, unit at 60% of height

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39 Figure 3-17 Contaminant concentrat ion, unit at 60% of height

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40 The unit is moved now to height equal to 90% of office room height (case 4, Table3-1). From Fig.3-18, the airflow trav els at high velocities along the walls then curves towards the floor. The occupant is directly in the fl ow path. Notice how flow splits on top of the person and is almost evenly divided. Most of the air returns directly to the outlet leaving a significant portion that has to travel around the person before retu rning. Figure 3-19 shows lower temperatures throughout the offi ce room, notice lower temperatures of the portion that traveled around the person. Also, air from occupa nt is being cooled before reaching the outlet, opposite to what is shown on Fig.3-15. Due to colder temperature, more water vapor is noticeable behind the person is this case as Fig.3-20 shows. Notice how the pattern of concentration follows the cold airflow trajectory. Contaminant in Fig.3-21 is shown to be mo re efficiently removed compared Fig.3-17, due to high flow velocities experienced by occupant; the concentrations are minimal in the occupant’s immediate surroundings

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41 Figure 3-18 Velocity field, unit at 90% of height, values of speed are in (cm/s)

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42 Figure 3-19 Temperature profile unit at 90% of height

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43 Figure 3-20 Water vapor distribut ion, unit at 90% of height

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44 Figure 3-21 Contaminant concentrat ion, unit at 90% of height Fig.3-23 and Fig.3-24 show the thermal sensation and the predicted mean vote (PMV) as a function of inlet flow angle for the imme diate space around the person. For better prediction of thermal comfort this section focuses on regions expanding 10 centimeters from the person in every direc tion. However, PMV and thermal sensation take different approaches, thermal sensation correlates comfort level with the length of exposure, temperature, humid ity, sex. On the other hand PMV measures the reaction of people to certain conditions, for a particular individual based on ac tivity, air velocity, (metabolic rate), and clothing.

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45 We notice that the thermal sensation is within an acceptabl e range even when increasing the inlet angle, Fig.3-23. However, the PMV Fig.3-24, indicates the comfort is in the cold side when the angle is low then increases to acceptable comfort as the angle goes up. This shows that not like the PMV, th e thermal sensation is independent of the inlet angle. In [7] Similar results were obt ained for the temperature the experiment and CFD model Table 3-4. Also they obtained e xperimentally a comparable PMV= -0.71 and PPD = 16%, versus the present study with PM V = -0.76 and PPD = 17.1%, Table3-5. The difference is meanly because of initial and boun dary conditions, like the size of the room, external walls, size of the person, and the inlet angle. Table 3-4 Comparison of experiment al data [7], CFD model [7], and current CFD model Temperature [0C] Experimental data [7] 24.3 CFD [7] 23.3 CFD Current 23.4 Figure 3-22 shows the temperature at a speci fic height of the room in each of the CFD simulations in addition to the temperatur e collected using experimental methods [7]. It is noticeable that the pattern of present simulation is lower than the previous one; this can only be explained by the offset parameters chosen for each study.

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46 Table 3-5 Comparison of CFD m odel [8] and current CFD model PMV PPD % CFD [3] 0.71 16 CFD 0.76 17 0 0.5 1 1.5 2 2.5 1820222426Temperature in [C]Height of Room in [m] Temperature of Current CFD Simulation Temperature of Previous CFD Simulation Temparature from Experiment Figure 3-22 Temperature profiles of both si mulations and experiment vs. Height

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47 Comfort zone -3 -2 -1 0 1 2 3 2025303540 Inlet Flow Angle (degrees)Thermal Sensation Scale Figure 3-23 Thermal sensation vs. inlet angle Comfort zone-3 -2 -1 0 1 2 3 2025303540 Inlet Flow Angle (degrees)Predicted Mean Vote PMV Figure 3-24 Predicted mean vote vs. inlet angle

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48 When varying the height of the air conditioning unit with respect to the base case the thermal sensation shows almost same pr ofile, Fig.3-25. Sensation is cold in both higher and lower cases due cold temperature around the occupant who is located directly in the airflow path. Fig. 3-26 shows PMV very low in high and the low cases due high to velocities. Again, the occupant is in the path of the airflow, he feel s great speed air at low temperatures. This should give local thermal di scomfort to the occupant especially at unit height of 90% of total office room height. Ve locity of airflow in this case is very high coming form the ceiling hitting the occupant st raight on thus, creating a very cold zone around him. This observations show in Fi g.3-27 and Fig.3-28 where the Percentage Dissatisfied index PPD, which shows the pred icted percentage of people that would dissatisfied in such conditions. Since PPD and PMV are directly related, it is only logical that coldest cases i nvoke the most discomfort for occupants. Comfort zone -3 -2 -1 0 1 2 3 60%75%90% Height of unit (% of total height)Thermal sensation scale Figure 3-25 Thermal sensation vs. unit height

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49 Comfort zone -3 -2 -1 0 1 2 3 60%75%90%Unit height (% of total height)Predicted Mean Vote PMV Figure 3-26 Predicted mean vote vs. unit height Table 3-6 shows that the Thermal sensat ion, PMV, PPD, relative humidity, and contaminant removal effectiveness. First, the PMV value for position 2 (closer to the unit) is lower than the value for base case; these values are related to the high airflow velocities around the occupant at position 2. Notice a local discomfort PPD of 65% at position 2 compared to only 15% for the base case, a sharp increase on the amount of people that could feel uncomfor table if they only move to the middle of the office room. Even though the thermal sensat ion shows both case within the comfort zone, the speed of flow so much greater in position 2 thus not preferable for occ upants to be in that position

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50 Table 3-6 Conditions of the second position (clo ser to the unit) compared with base case Base Case (Position 1) Position 2 PMV -0.6842 -1.80 PPD% 14.8417 64.96 RH% 61.8400 56.55 Thermal Sensation 0.1405 -0.17 CRE 0.0138 0.47 0 10 20 30 40 50 60 70 203040 Inlet angle (Degrees)PPD (%) Figure 3-27 Predicted percentage di ssatisfied (PPD) vs. inlet angle

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51 0 20 40 60 80 100 120 60%75%90% % Unit HeightPPD (%) Figure 3-28 Predicted percentage di ssatisfied (PPD) vs. unit height Table 3-7 shows an average re lative humidity in every simulation, which in fact is in each case an average value taken for a ll the local relative humidity using local temperatures and water vapor concentrations Table 3-7 Simulations and relative humidity Simulation Number Inlet Angle % Unit Height from Total Height RH % 1 20 75% 69.21 2 30 75% 61.84 3 40 75% 56.61 4 30 60% 66.58 5 30 90% 69.96 6 30 75% 56.55

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52 The CRE Contaminant Removal Effectiv eness is shown in Table 3-8 as a dimensionless Ratio between the average co ncentrations of the contaminant in the occupied zone (Breathing Zone ) and the contaminant at the outlet. In the first set of simulations, 1 to 3, Table 3-1, where the in let angle was the variable keeping everything else constant. Notice that at lower inlet angl e (case 1) the CRE is higher compared with cases 2 and 3. This is due to fact the more of the occupant’s body is in the path of the airflow, which results in more contaminant removed from the surroundings of the occupant. The second set of simulations, 2 (b ase case), 4 and 5 Table 3-2, for window air conditioner location at high height (90% of total office room height, case 4, Table 3-1) and at low height (60% of tota l office room height, case 5, Ta ble 3-1), more air is hitting the occupant directly from the ceiling, air speed and temperature around the occupant explain the CRE number being hi gher then the base case, the high velocity airflow takes more contaminant cases 4 and 5 however, compared to case 1, Table 3-2, low temperatures prevent removing more contaminant. The thir d set of simulation case 2 (base case) and case 6 from Tabl e 3-1, notice that high airf low velocity around the person allows a better removal of contaminant compared to the base case where the velocity magnitude is smaller.

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53 Table 3-8 Simulations and contaminant removal effectiveness Simulation Number Inlet Angle % Unit Height from Total Height CRE 1 20 75% 2.75 2 30 75% 0.014 3 40 75% 0.27 4 30 60% 1.108 5 30 90% 1.84 6 30 75% 0.47 From Fig. 3-29, Fig. 3-30 and Table 39 show the impact of the window air conditioner location on energy consumption. Th is following evaluation using Eq.18 is based on a nominal case where the difference between the outside temperature and the average room temperature is 200F. Notice that there is en ergy consumption of around Ei =3.36% for the worst case possible in the first set of simulations (cases 1, 2, and 3) is when the inlet angle is 200 Fig.3-29, this is because in case 2 Table 3-2 the relative humidity is maximum out of al l three simulations as shown in Table 3-7. On the other hand the energy consumption for the height varia tion set of simulations (cases 2, 4, and 5 respectively) is around Ei =3.51% for 90% height of the AC unit shown on figure 14. Again, notice that the relative humidity in this case is at its maximum value from as shown in Table3-7.

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54 0 0.5 1 1.5 2 2.5 3 3.5 4 202530354045 Inlet Flow Angle Degrees% Energy Consumption Figure 3-29 % Energy consumption vs. inlet angle 0 0.5 1 1.5 2 2.5 3 3.5 4 6065707580859095Height of unit (% of total height)% Energy Consumption Figure 3-30 % Energy consumption vs. unit height Table 3-9 shows that the minimum energy expenditure Ei=0.388% is when the occupant is close to the air conditioning unit showing that th e average temperature of the

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55 room is lower in this case. This is a plausi ble result looking at the relative humidity Table 3-7, since the relative humidity is at its lowe st in when the person is in the middle of the room. Table 3-9 Changing occupant pos ition and % energy Consumption Base Case % Energy Consumption Position 1 1.713 Position 2 0.388

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56 Chapter 4 Three Dimensional Simulation of Window Air-Conditioner in Office Rooms 4.1 Introduction The chapter provides a detailed analysis of three-dimensional mixed convective flow induced by a window air conditioning system. It also intends to extend the understanding of location of wa ll-mounted units and their eff ect on human comfort. It is very important that computa tional models be made in three-dimensional simulations, doing so, all the relevant characteristics of fl uid flow and heat tran sfer can be captured and analyzed. Temperature, relative humidity, contaminant concentration, and velocity profiles of both horizontal and vertical cross sections ar e studied and compared. In addition, when modeling three-dimensional si mulations, fewer assumptions have to be made, this makes results more compa tible to actual encountered cases. Other studies in energy and environmen tal analysis were conducted using 3D modeling in order to have a better unders tanding of rooms cooled by wall type air conditioners, comparing and evaluating differe nt CFD softwares for the same simulation [16]. Also studies have focused on only ai r conditioning diffuse r angles and their influence on comfort level in computer rooms [17].

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57 4.2 CFD Model In this chapter, the CFD software Fluent was used in two phases. First, GAMBIT was utilized to make the model office room w ith a unit, an occupant, and a light fixture. Also, GAMBIT was used mesh the model. Then FIDAP was used to analyze the office room using all assumptions and boundary conditions. Modeled room size was 4.8m (length) x 3.7m (width) 2.7m (height) and unit was at manufactur ing ratio dimensions between inlet and outlet. Also the light fixt ure was modeled in the center of the ceiling and with standard size. The turbulent model used to numerica lly compute all properties was Mixinglength model with segregated solution sche me. Due to the size of the office room, mixing-length model was chosen because it’ s high precision and reduced memory use and computation time. The room was modeled as a 3D cube as shown is Figure 4-1 with and air conditioning unit at one vertical side, and a person represente d by a smaller vertical cube positioned at an offset from the center. Also, the light fixture is represented by a section area on the upper horizontal plane of the cube (ceiling).

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58 Figure 4-1 Layout of the 3D simulated office room Table 4-1 shows corresponding dimensi ons of the simulated office room, Table 4-1 Simulation dimensions Name Length Name Length L 4.8 L5 0.2 L1 3.2 L6 1.1 L2 2.7 L7 1.2 L3 1.7 L8 0.2 L4 0.3 L9 2.4

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59 Table 4-2 gives the boundary conditions used form this simulation, these values of temperature, fluxes, and concentrations ar e taken from a typical application for a wall mounted air conditioning unit used to cool an office. Table 4-2 Simulation boundary conditions Entity Temperature and Heat Flux Velocity m/s Water Vapor Concentration Contaminant Concentration Inlet T=19 oC 3.50 c1 = 0.011 c2= 0 Walls T=24 oC 0 0 Person T = 34 oC 0 Flux=5E-7 kg/(m.s2) Flux=1E-5 kg/(m.s2) Light Flux= 50 W/m2 0 0 0 Outlet T=0 C Flux=0 0 0 0

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60 Velocity and temperature were calculate d first by solving the coupled equations, and then species concentrations (water vapor and contaminant gas) were studied with known a velocity field. Relative humidity is computed by inputting the temperature pressure, water vapor concentration and ex ecuting for every cell of the studied space using Temperature, pressure, and water vapor concentration using the method outlined by ASHRAE [12] The simulations were done in three runs, where inlet angles were set at 20o, 30o, and then 40o. First, the simulation with a 30o inlet angle then 20o and 40o respectively. On the output files six cross-sec tional (planes) were studies as Table 4-3 shows, the six planes studied, three horizontal and three ve rtical, and their location with respect to the office room. Table 4-3 Cross-sectional planes examined Plane Orientation Coordinates in [m] 1 Vertical Y = 1.85 2 Vertical Y = 0.975 3 Vertical Y = 2.825 4 Horizontal Z = 1.35 5 Horizontal Z = 0.675 6 Horizontal Z = 2.025

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61 The examination of these six planes will allow a detailed anal ysis of the heat transfer and thermal comfort associated with air movement and temperature inside the office room. 4.3 Results and Discussion 4.3.1 Simulation with 30o inlet angle Temperature distribution th roughout the room is anal yzed first in the three vertical planes shown in Fig. 4-2, Fig.4-3, and Fig.4-4. In Fig.4-2 the temperature rises around the light fixture and the occupant, the heat transfer from the light is very significant because of the high local temperatur e. The same is true around the occupant where the surrounding air gets warmer as it get closer to the person. Fig.4-3 and Fig.4-4 are identical in describing the temperature pr ofile as expected by the symmetry of the simulation and the position of the planes studied, the temperature magnitude is on the low side since from both ends; the two studied pl anes do no intersect wi th the person and the light fixture

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62 Figure 4-2 Temperature profile on plane 1, inlet angle of 30o

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63 Figure 4-3 Temperature profile on plane 2, inlet angle of 30o

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64 Figure 4-4 Temperature profile on plane 3, inlet angle of 30o

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65 Figures 4-5. 4-6 and 4-7 show the distribution of the cont aminant on the three vertical planes 1, 2, 3, first Fig.4-5 shows that the contaminant’s most significant concentrations are meanly around the person since the person is the only source of that flux. Notice that contaminant distribution around the person is uneven, which is due to the airflow direction shown in Figure 4-8. Since the air di rection is meanly from top to bottom, the occupant releases contaminant which is th en pushed downward away from the head of the occupant which explains why more contaminant is found towards the back and bottom of the office room, also contaminan t is found around the occupant. Fig.4-5 shows very minimal concentrations in the adjacent pl ane, plane 2. The scale of the Fig.4-5 had to be changed to show the concentrations of contaminant in plane 2. The symmetry of the model dictates the concentrations in plane 3, which is the case in this simulation.

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66 Figure 4-5 Contaminant profile on plane 1, inlet angle of 30o

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67 Figure 4-6 Contaminant profile on plane 2, inlet angle of 30o Chapter 1

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68 Figure 4-7 Contaminant profile on plane 3, inlet angle of 30o

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69 Velocities around the occupant on the vertical planes 1, 2, 3 are displayed in Fig.4-8, Fig.4-9, and Fig.4-10. Again Fig.4-9 and Fig.4-10 are very similar in showing the velocity profile on the vertical planes 2 and 3 because of the symmetry of the simulation on both sides of the office room. Fig.4-8 sh ows how the flow circulates around the person, notice that the inlet angle is 300 which drive airflow to the ceiling of the room however from Fig.4-8 we see that th e angle is sligh tly higher than 30o because air entering the room is pushed upward by th e air from the previous circulation. Figure 4-8 Velocity profile on plane 1, inlet angle of 30o

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70 Figure 4-9 Velocity profile on plane 2, inlet angle of 30o

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71 Figure 4-10 Velocity profile on plane 3, inlet angle of 30o

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72 Figure 4-11, Figure 4-12, and Figure 4-13 describe the te mperature distribution in the horizontal planes 5, 4, and 6 respectively, as we can see the temperature gets colder as the air gets away from the occupant, Fig.411. Plane 5 intersects with the occupant a distance that allows for a significant convectiv e heat transfer, this gives clear idea about the temperature directly surrounding the o ccupant and how much does the person’s temperature affects the immediat e surrounding air around him or her. At the middle of the room the temperature has similar distribution with exception that plane 4 does not intersect with the occupa nt, the convective heat transfer is mildly less than in plane 5 however, it is noticeabl e that immediately above the person the air temperature is high, Fig.4-12. Figure 4-11 Temperature profile on plane 5, inlet angle of 30o

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73 Figure 4-12 Temperature profile on plane 4, inlet angle of 30o

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74 Plane 6 shown in Fig.4-13 shows the same patte rn as in plane 4, only this time the high temperature is influenced by the closeness of the light fixture. Notice how the circular high temperature profile is closer to the person and has a slight offset in the direction of the light. It is not immediately above the o ccupant. The light fixtur e has great influence on the heat transfer in the hi gh section of the room, even if cooling air moves towards the occupant, the high temperature is around the light which is lo cated in the center of the ceiling. Figure 4-13 Temperature profile on plane 6, inlet angle of 30o

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75 Contaminant distribu tion of the office room analy zed by horizontal planes shows as first predicted, the contamination se cretion from the pe rson is uneven. High concentrations are found towards the bottom back section of the room as Table.4-6 shows. It is clear from comp aring Fig.4-14, Fig.4-15 and Fi g.4-16 that the concentration of contaminant within the office room dimi nished as the height increases. This is explained by the airflow move ment inside the room and around the occupant, which is meanly directed downwards.

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76 Figure 4-14 Contaminant profile on plane 5, inlet angle of 30o

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77 Figure 4-15 Contaminant profile on plane 4, inlet angle of 30o

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78 Figure 4-16 Contaminant profile on plane 6, inlet angle of 30o

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79 As the airflow enters the o ffice room and circulates aro und the person, it follows a specific trajectory as shown in Fig.4-17, Fig.418, and Fig.4-19 for planes 4, 5 and 6. The high speed airflow goes around the person from the top and tw o sides; as the height decreases Fig.4-17 effectively shows that hi gh speed air shown in Fig.4-19 is evenly dispersed around the room’s ceiling and walls before being guided downward. Notice the circulation pattern around the person; it explains the temperature and the contaminant distribution in the office room. Figure 4-17 Velocity profile on plane 5, inlet angle of 30o

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80 Figure 4-18 Velocity profile on plane 4, inlet angle of 30o

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81 Figure 4-19 Velocity profile on plane 6, inlet angle of 30o Relative humidity is a very important factor of indoor human thermal comfort especially in office rooms cooled by wallmounted units. Table 4-4 shows values of average relative humidity in the studied planes. Knowing the symmetry of the simulation and, in agreement with Fig.4-21 and Fig.4-22 the values of relative humidity are very acceptable. Notice that values of relative humidity in the vertical planes 3 and 4 in Table 4-4 are equals and the profiles shown in Fi g.4-21 and Fig.4-22 agree to the numerical values. Even though the numerical value of re lative humidity in the center plane 2 is lower than the adjacent planes, Table 4-4. Fig.4-20 shows a high relative humidity around the light and the person with is explained by the heat transfer magnitude at these

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82 locations due to high temperatur es. Fig.4-2 agrees with this profile. Further more due to high temperature, the relative Humidity decreas es considerably as the airflow get closer to the occupant. Table 4-4 Relative humidity in the studied planes Planes Relative Humidity % 1 39.58 2 59.85 3 59.80 4 55.85 5 56.69 6 58.02

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83 Figure 4-20 Relative humidity on plane 1, inlet angle of 30o

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84 Figure 4-21 Relative humidity on plane 2, inlet angle of 30o

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85 Figure 4-22 Relative humidity on plane 3, inlet angle of 30o

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86 As Table 4-4 shows the numerical value of the average relative humidity in the horizontal planes 4, 5, and 6 increase as he ight increases. Cool airflow velocity in the upper planes of the room is very high which explains the increase in average relative humidity in the high sections of the o ffice room. However, as predicted by the temperature profile Figures 4-11, 4-12, and 4-13, the relative humidity is greater around the person. The heat around the occupant is pr esumed transferred at a high constant rate that heats air surrounding it, raising its temperature th us decreasing the immediate relative humidity. Fig.4-24 and Fig.4-25 show planes that do no intersect with the occupant, yet as temperature in Fig.4-12 and th e convective heat transf er ratio predict it, the relative humidity is low immediately above the person and as the air get closer to the light fixture.

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87 Figure 4-23 Relative humidity on plane 5, inlet angle of 30o

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88 Figure 4-24 Relative humidity on plane 4, inlet angle of 30o

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89 Figure 4-25 Relative humidity on plane 6, inlet angle of 30o Table 5-5 compares the values of averag e relative humidity and temperature in this three-dimensional model, to a redu ced two-dimensional model using the same boundary conditions (chapter3). The relative humidity and temperature are inversely proportional, this shows in Ta ble 4-5, and the values are very close. The small the difference in numbers is due to the assumptions made for both cases and the difference in precision of solution since two turbulent models were used to solve for each case. Also to get the same results in 3-D model as in 2D model one has to assume all entities are extended to full length of the office room.

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90 Table 4-5 Comparison of relative humidity and temperature in 30o inlet angle 2-D and 3-D models Simulated Models Average Relative Humidity % Average Temperature 0C Three Dimensional 58.47 24.4 Two Dimensional 62.86 22.1 Figure 4-26 shows the averages temp erature values for present study In comparison with the three dimensional CFD mode ling done in [8], with respect to height of the office room, the temperatures compar ed are from three points with the same coordinate in all three cases. Fig.4-26 shows the two CFD models are in agreement with the temperature pattern as the height increases, as stated above the fluid’s temperature is low at height that include the airflow trajectories. The experimental data has similar results except that the temperature in th is case grows proportionally to the height. Discrepancies in this case ar e explained by difference in so lution schemes and different initial boundary conditions

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91 0 0.5 1 1.5 2 2.5 222324252627 Temparatures in [C]Heights in [m] CFD current CFD [2] Experiment [2] Figure 4-26 Temperature profiles fo r both simulations vs. height Table 4-6 compares the contaminant concen trations in the 6 planes studied also shows the value of CRE in each plane. As pred icted by Figures 4-14, 4-15, and 4-16, it is clear from Table 4-6 especia lly in planes 4, 5, and 6 (Horizontal planes) that the concentration of contaminant increases as th e height of the office room decreases. The concentration on vertical planes 1, 2, and 3 is very straightforwar d because the highest concentration is on the plane that intersects the o ccupant (plane1). CRE values are directly proportional to conc entration values as CRE is a ratio of these concentrations with the amount cleared by airflow through the outlet.

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92 Table 4-6 Concentration of contaminant and CRE, for 30o inlet angle Studied planes Contaminant concentration CRE 1 0.00404 4.29E-4 2 0.00104 0.001669 3 0.00104 0.001669 4 0.000851 0.002041 5 0.000782 0.002217 6 0.000986 0.001861 Theses numbers agree with the velocity profile as the CRE is highest in the middle plane (plane 1) where there is more air circulating at high velocity since plane 1 intersects with unit. As stated before the symmetry of the office room horizontally makes the plane 2 and plane 3 have the same characteristics. 4.3.2 Simulation with 20o inlet angle Temperature profiles are shown in Fig.427, Fig.4-28, and Fig.4-29 for vertical planes; it is noticeable that the low temper atures are around the walls and the ceiling. Warm temperatures exist at th e proximity of the light fixt ure and around the person as in the case of 30o inlet angle. However, lower values ar e noticed in this case. At planes 2 and 3 temperatures profiles are very similar due to the vertical symmetry of the office room. Figures 4-39, 4-40, and 4-41 show temperat ure profiles on the hor izontal planes 4, 5, and 6 respectively. Around the person in Fi g.4-39, we see that the temperature lower

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93 between the person and the unit however, even when close to the person Fig.4-40, the profile is still wide due to high velocities which keep local temperatures colder. Plane 6 Fig.4-41 shows the air temperature are cold around the wall and even more so in the middle and away from the light. Table 4-7 shows the comparison of the ove rall average temperatures and relative humidity in this 3-D simulation with it coun terpart in Chapter 3. As predicted the 3-D simulation show a lower relative humidity a nd lower temperature due to the high number of nodes analyzed. Table 4-7 Comparison of relative humidity and temperature in 20o inlet angle 2-D and 3-D models Simulated Models Average Relative Humidity % Average Temperature oC Three Dimensional 70.89 21.22 Two Dimensional 75.99 20.15

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94 Figure 4-27 Temperature profile on plane 1, inlet angle of 20o

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95 Figure 4-28 Temperature profile on plane 2, inlet angle of 20o

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96 Figure 4-29 Temperature profile on plane 3, inlet angle of 20o Figures 4-30, 4-31 and 4-32 show the distributio n of the contaminant on the three vertical planes 1, 2, 3, first Fig.4-30 shows that the contaminant’s most significant concentrations are mainly around the person since the person is the only source of that flux. Since the air direction is mainly from top to bottom, the occupant releases contaminant which is then pushed downward away from the head of the occupant which explains why more contaminant is found towards th e back and bottom of the offi ce room, also contaminant is found around the occupant. Fig.4-31 shows very minimal concentrations in the adjacent plane, plane 2. The symmetry of the model dict ates the concentrations in plane 3, which is the case in this simulation.

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97 Figure 4-30 Contaminant profile on plane 1, inlet angle of 20o

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98 Figure 4-31 Contaminant profile on plane 2, inlet angle of 20o

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99 Figure 4-32 Contaminant profile on plane 3, inlet angle of 20o Fig.4-33 shows how the flow circulates around the person, notice that the inlet angle is 200 which drive airflow to the ceiling of the room however from Fig.4-33 we see that the angle is slightly higher than 20o because air entering the r oom is pushed upward by the air from the previous circulation. Figures 4-34 and 4-35 are similar in describing airflow behavior due to the symmetry of the office room.

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100 Figure 4-33 Velocity profile on plane 1, inlet angle of 20o

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101 Figure 4-34 Velocity profile on plane 2, inlet angle of 20o

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102 Figure 4-35 Velocity profile on plane 3, inlet angle of 20o As Relative humidity is inversely proportiona l to temperature, Fig.4-36, Fig.4-37, and Fig.4-38 show a profile similar to temperature. Relative humidity gets lower as airflow approaches the person and the light fixture, and as predicted is lower and constant on both sides of the room.

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103 Figure 4-36 Relative humidity on plane 1, inlet angle of 20o

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104 Figure 4-37 Relative humidity on plane 2, inlet angle of 20o

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105 Figure 4-38 Relative humidity on plan e 3, inlet angle of 20o

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106 Figure 4-39 Temperature profile on plane 4, inlet angle of 20o

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107 Figure 4-40 Temperature profile on plane 5, inlet angle of 20o

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108 Figure 4-41 Temperature profile on plane 6, inlet angle of 20o Contaminant distribu tion of the office room analy zed by horizontal planes shows as first predicted, the contamination se cretion from the pe rson is uneven. High concentrations are found towards the bottom back section of the room as Table 4-8 shows. It is clear from comp aring Fig.4-42, Fig.4-43 and Fi g.4-44 that the concentration of contaminant within the office room dimi nished as the height increases. This is explained by the airflow move ment inside the room and around the occupant, which is meanly directed downwards.

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109 Figure 4-42 Contaminant profile on plane 4, inlet angle of 20o

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110 Figure 4-43 Contaminant profile on plane 6, inlet angle of 20o

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111 Figure 4-44 Contaminant profile on plane 5, inlet angle of 20o Table 4-8 shows that contaminant is being cl eared very rapidly from plane 1 however, it agrees with predictions that the contaminant is concentrated at the bottom levels of the room.

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112 Table 4-8 Concentration of contaminant and CRE, for 20o inlet angle Studied planes Contaminant concentration CRE 1 3.27E-3 2.41E-5 2 6.94E-6 0.011345 3 6.94E-6 0.011345 4 0.000701 0.00125 5 0.000672 0.001305 6 0.000756 0.00116 Looking at the horizontal planes, high speed airflow goes around the person from the top and two sides; as the height decrea ses Fig.4-45 effectively shows that high speed air shown in Fig.4-46 is evenly dispersed around the room’s ceiling and walls before being guided downward. Notice th e circulation pattern around th e person; it explains the temperature and the contaminant distribution in the office room.

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113 Figure 4-45 Velocity profile on plane 4, inlet angle of 20o

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114 Figure 4-46 Velocity profile on plane 5, inlet angle of 20o

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115 Figure 4-47 Velocity profile on plane 6, inlet angle of 20o As Table 4-9 shows the numerical value of the average relative humidity in the horizontal planes 4, 5, and 6 increases as heig ht increases. Cool airflow velocity in the upper planes of the room is very high which explains the increase in average relative humidity in the high sections of the o ffice room. The heat around the occupant is presumed transferred at a hi gh constant rate that heats air surrounding it, raising its temperature thus decreasing the immediate relative humidity. Fig.4-48 and Fig.4-49 show planes that do no intersect w ith the occupant, yet as temp erature in Fig.4-40 and the convective heat transfer ratio predict it, the re lative humidity is low immediately above the person and as the air get cl oser to the light fixture.

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116 Table 4-9 Relative humidity in the studied planes Planes Relative Humidity % 1 39.96 2 59.57 3 59.57 4 69.96 5 70.33 6 67.74 Notice from Table 4-9 that rela tive humidity is very low in plane 1 even with cold air flowing in it. This explai ned by the presence of the light and the occupant in plane 1.

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117 Figure 4-48 Relative Humidity on plane 4, inlet angle of 20o

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118 Figure 4-49 Relative Humidity on plane 5, inlet angle of 20o

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119 Figure 4-50 Relative Humidity on plane 6, inlet angle of 20o 4.3.3 Simulation with 40o inlet angle Temperature distribution th roughout the room is anal yzed first in the three vertical planes shown in Fig.4-51, Fig.4-52, and Fig.4-53. In Fig.4-51 the temperature rises around the light fixture a nd the occupant, the heat transf er from the light is very significant because of the high local temperatur e. The same is true around the occupant where the surrounding air gets warmer as it ge t closer to the person. Fig.4-52 and Fig.453 are identical in describing the temperature profile as expected by the symmetry of the simulation and the position of the planes studied, the temperature magnitude is on the low

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120 side since from both ends; the two studied pl anes do no intersect wi th the person and the light fixture. In addition Table 4-10 shows a compar ison between the 3-D model and the corresponding 2-D model shown in Chapter 3. Table 4-10 Comparison of relative humidity and temperature in 40o inlet angle 2-D and 3-D models Simulated Models Average Relative Humidity % Average Temperature 0C Three Dimensional 52.15 25.32 Two Dimensional 56.98 23.43 Again the 3-D model show higher temperat ures and low relative humidity in the office room. The amount of nodes averaged in the 3-D model exceeds the one in the 2-D model which explains the differences.

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121 Figure 4-51 Temperature profile on plane 1, inlet angle of 40o

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122 Figure 4-52 Temperature profile on plane 2, inlet angle of 40o

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123 Figure 4-53 Temperature profile on plane 3, inlet angle of 40o Contaminant concentration is very noticeable in Fig.4-54 it showing how contaminant is cleared from the occupant in a downward fa shion and pushed in the direction of the office floor. Table 4-11 shows that the contamin ant is more present at the bottom planes of the office room; this is due low velocitie s of the returned air shown in Fig.4-57.

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124 Table 4-11 Concentration of contaminant and CRE, for 40o inlet angle Studied planes Contaminant concentration CRE 1 0.00288 1.51E-5 2 7.19E-7 0.06091 3 7.19E-7 0.06091 4 0.000963 4.53E-5 5 0.000841 5.19E-5 6 0.001246 3.50E-5 As predicted by the inlet angle of 40o, the contaminant is more present in this case than the two cases mentioned above. Especially on the bottom planes where the airflow velocity is low, the contaminant is more concentrated at these planes.

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125 Figure 4-54 Contaminant profile on plane 1, inlet angle of 40o

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126 Figure 4-55 Contaminant profile on plan e 2, inlet angle of 40o

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127 Figure 4-56 Contaminant profile on plan e 3, inlet angle of 40o Figure 4-57, Figure 4-58, and Figur e 4-59 show the velocity prof ile in the vertical planes, the flow enters the office room with a discha rge angle of 40o then it is directed toward the ceiling as for previous cases. In the horizon tal planes 4, 5, and 6 Fig.4-69, Fig.4-70, and Fig.4-71, airflow follow the same behavi or only at lower velocities which explains the high concentration of contamin ant in the bottom of the room

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128 Figure 4-57 Velocity profile on plane 1, inlet angle of 40o

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129 Figure 4-58 Velocity profile on plane 2, inlet angle of 40o

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130 Figure 4-59 Velocity profile on plane 3, inlet angle of 40o Relative humidity is a very important factor of indoor human thermal comfort especially in office rooms cooled by wall-m ounted units. Table 4-12 shows values of average relative humidity in the studied planes. Knowing the symmetry of the simulation and, in agreement with Fig.4-61 and Fig.4-62 the values of relative humidity are very acceptable. Notice that values of relative humidity in the vertical planes 3 and 4 in Table 4-12 are equals and the profiles shown in Fig.4-61 and Fig.4-62agr ee to the numerical values. Even though the numerical value of re lative humidity in the center plane 2 is lower than the adjacent planes, Table 4-12. Fig.4-60 shows a high relative humidity around the light and the person wi th is explained by the heat transfer magnitude at these locations due to high temperatures. Fig.4-60 agr ees with this profile. Further more due to

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131 high temperature, the relative Humidity decreas es considerably as the airflow get closer to the occupant. Table 4-12 Relative humidity in the studied planes Planes Relative Humidity % 1 39.90 2 58.72 3 58.72 4 68.44 5 67.73 6 70.56

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132 Figure 4-60 Relative Humidity on plane 1, inlet angle of 40o

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133 Figure 4-61 Relative Humidity on plane 2, inlet angle of 40o

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134 Figure 4-62 Relative Humidity on plane 3, inlet angle of 40o

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135 Figure 4-63 Temperature profile on plane 4, inlet angle of 40o

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136 Figure 4-64 Temperature profile on plane 5, inlet angle of 40o

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137 Figure 4-65 Temperature profile on plane 6, inlet angle of 40o

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138 Figure 4-66 Contaminant profile on plan e 4, inlet angle of 40o

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139 Figure 4-67 Contaminant profile on plan e 5, inlet angle of 40o

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140 Figure 4-68 Contaminant profile on plan e 6, inlet angle of 40o

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141 Figure 4-69 Velocity profile on plane 4, inlet angle of 40o

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142 Figure 4-70 Velocity profile on plane 5, inlet angle of 40o

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143 Figure 4-71 Velocity profile on plane 6, inlet angle of 40o

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144 Figure 4-72 Relative Humidity on plane 4, inlet angle of 40o

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145 Figure 4-73 Relative Humidity on plane 5, inlet angle of 40o

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146 Figure 4-74 Relative Humidity on plane 6, inlet angle of 40o

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147 Chapter 5 Conclusions and Recommendations 5.1 Two Dimensional Simulation of Office Room Multiple cases could be taken and studied fo r HVAC office rooms with the use of CFD. The present simulations have demonstrated that the position of the wall-mounted air conditioner has a significant effect on the comfort level of the person occupying it. In Chapter 3, it is clear that the base case (case 2, Table 3-2) is very comfortable for one person doing minimal work in an office us ing a window air conditioner. If PMV is considered, the base case a nd the 40 degree inlet angle case (case 3, Table 3-2) are comfortable regardless of the thermal sensati on index because as it is shown above, inlet angle has very little effect on PMV index. Considering moving the unit either up or down has a significant effect on the occupant’s co mfort as shown above. As airflow velocity becomes greater around the occupant creatin g a very cold sensation, the level of discomfort increases (PPD). This is an indicator that height of the air conditioning unit has a great effect on the air velocity’s dire ction and magnitude in side the office room, thus on the comfort of occupants. Moving the person closer to the air conditioning units (case 6, Table32) increases his or her sens ation of cold, which is a good indicator that preferable distance needed away from the is necessary to create good thermal comfort. Contaminant Removal Effectiveness CRE is gr eatly affected by the speed of airflow as well as its temperature. As demonstrated, th e greatest CRE occurs when velocities around the occupant, who is the main source of air contamination in this study. Case 1, Table 3-

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148 2, displays the maximum CRE because airflow velocity is high as well as temperature. On the other hand cases 4 and 5 show great CRE however air temperature prevents an effective contaminant removal. Energy savings in the 40o angle case (case 3, Table 3-2) is the preferable since minimum energy is needed to create comfort, since the relative humidity (Table 3-7) is low in this case. Case 6, where the occupant is closer to the air conditioning unit, shows similar energy saving value; however therma l comfort is not ideal in this case. 5.2 Three Dimensional Simulation of Office Room HVAC designs are increasingly improving due to a significant increase in CFD usage, FLUENT used in this study was a cr edible tool for the present simulations. The solution obtained concurred with the predicte d results and previous simulations using FIDAP and other CFD softwares. Also, the pr esent simulation agreed with experimental data collected for a similar layout with similar boundary conditions. The location of a window type air-conditioner ha s great influence on the heat transfer and comfort level in office rooms. It is clear, after studying this office room, that airflow around the room has a very specific pattern, which clearly influences the heat, relative humidity, and CRE for occupants. As demonstrated CRE is affected by ai rflow velocity and temperature, CRE is great when velocities are high which allo w a great clean up of the surrounding air especially considering that CRE is a ratio involving the outlet contaminant concentrations.

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149 Relative humidity is inversely proportional to the temperature, as discussed above in regions (cells) where temper ature is high; the relative hum idity is low e.g. surrounding the person and around the light fi xture. Also, following the ai rflow trajectory through the room and since air is cooler than the entities around it, we can see that relative humidity is higher on the regions adjacent to the pe rson and low on the section intersecting with the person which a source of heat to the surroundings. Horizontally, relative humidity is high in the high sections of the office room, again this due to the high cool airflow velocities and low temp erature throughout air trajectory. 5.3 Recommendations There is always a combination of inlet angle, height of air-conditioning unit, and occupant position that are ideal for each app lication. Not only for office rooms but also in general use, it is shown now that a window air conditioner ha s a particular setting for each application. This study can help the manu facturers or suppliers focu s on potential consumer needs for a specific application, in orde r to achieve the ideal thermal comfort. Also, if window air conditioners are used in the properly, fewer occupants would experience thermal discomfort and more dema nd will be noticed. For instance it is known that central units as stated above are more e fficient and eventually more reliable, however central units cool whole buildings including spaces that do no t to be cooled. If prior to an

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150 application, a simulation of the design is pe rformed including all the boundary conditions involved, a window unit could be a pe rfect fit for a small office room. Two dimensional models are very affec tive when describing heat transfer and thermal comfort in HVAC applications. The results from the two dimensional model were very accurate and in accordance with three dimensional models and experimental data. It is however critical to make the proper assumptions in order to compensate for the differences. However, three dimensional modeling is more reliable because it is closer to actual studied problems and also de mands less correctional assumptions. Now CFD softwares are very reliable, cost of HVAC design will drop considerably if more CFD si mulations are performed instead of physical collection of data that takes time, laboratory equipment, and money that could be invested elsewhere. Other studies can be inspired by the pres ent work, using CFD, preferably three dimensions modeling. Residential and commerci al spaces can be analyzed and more data can be obtained for different conditions. Mo re occupants can be added to the CFD models. Houses or working spaces can be studied, which will provide critical information about the proper location of wa ll-mounted air conditioners in order to create ideal thermal comfort.

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151 References [1] Principles of Heating Ventilating and Air Conditioning by Sauer H,J., Howell R.H. and Coad W.J. Edited by ASHRAE 2001. [2] Energy-Efficient Air Conditioni ng US Department of Energy http://www.eere.energy.gov/consum erinfo/factsheets/aircond.html [3] Chow W.F., and Fung W.F., 1996, “ Numerical studies on indoor air flow in occupied zone of ventilated and air-conditioned space ,” Building and Environment, 31, pp.319344. [4] Emmerich S.J., 1997, “ Use of computational fluid dy namics to analyze indoor air quality issues ,” NISTIR 5997, Building and Fire Res earch Laboratory, National Institute of Standards of Technology, Gaithersburg, MD. [5] Gadgil A.J., Finlayson E.U., Ho ng K.H., and Sextro R.G., 1999, “ Commercial CFD software capabilities for modeling a pulse release of po llutant in a large indoor space ,” Proceeding of Indoor Air ’99, Edingburg, 4, pp. 749. [6] Hirnikel D.J., Lipowicz P.J., and Law R.W., 2002, “ Predicting contaminant removal effectiveness of three air dist ribution systems by CFD modeling ,” ASHRAE Transactions, 108 (1), pp.350-359. [7] Y.C. Shih, H, Chiang, and R.J Shyu., 2000, The impact of the “Coanda Effect” On Indoor Air Motion Generated by a Window-Type Air-Conditioner Chutung, Hisinchu, Taiwan 310, R.O.C. [8] H.C Hsu, H, Chiang, Y.C. Shih and R.J Shyu., 2000, Implementation of displacement ventilation System by Using Wall-Mounted Air Conditioning, Hisinchu, Taiwan, R.O.C. [9] Son Hong Ho, 2004, Numerical Simulation of Ther mal Comfort and Contaminant Transport USF, Florida. [10] Fountain, M., C. Huizenga, 1995, A thermal sensation model for use by the engineering profession ASHRAE Project 781-PR Final report

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152 [11] G. Yanzheng, B. W Jones, M.H Hosni, T.P Gielda, 2003, Litera ture Review of the Advances in Thermal Comfort Modeling, ASHRAE, Kansas City. [12] ASHRAE, 1997, ASHRAE Handbook of Fundamentals American Society of Heating, Refrigerating and Air Conditioni ng Engineers, Inc., Atlanta, Georgia. [13] Fanger P.O., 1970, Thermal Comfort analysis and applications in environmental engineering McGraw-Hill, New York. [14] Rohles F.H.Jr. and Nevins R.G., 1971, The Nature of Thermal Comfort for Sedentary Man, ASHREA Transactions 77 (1), pp.239-244. [15] ANSI/ASHRAE Standard 55, 1992, Th ermal Environment conditions for Human Occupancy. American Society of Heating, Refrigerating and Air Conditioning Engineers, Inc., Atlanta, Georgia. [16] Gaspar. P. D., Barroca. R.F., Pitarm a R.A., 2003,” Performance Evaluation of CFD codes in Building Energy and Environmental Analysis”, Eighth International IBPSA Conference, Eindhoven, Netherlands, August 11-14. [17] Richtr .J.,Jicha .M., Katolicky .J., 2001, “ Numerical Modeling of The Influence of Angle Adjustment of A/C Diffuser Vanes on Thermal Comfort in a Computer Room” Sventh International IBPSA Conference, Rio de Janeiro, Brazil, August 13-15.

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153 Appendices

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154 Appendix A: FIDAP Program for Two Dimensional Simulation for Office Room TITLE ( ) Wall mounted air conditioning unit (2D) / FI-GEN FI-GEN( ELEM = 1, POIN = 1, CURV = 1, SURF = 1, NODE = 0, MEDG = 1, MLOO = 1, MFAC = 1, BEDG = 1, SPAV = 1, MSHE = 1, MSOL = 1, COOR = 1 ) / ADD POINTS POINT( ADD, COOR, X = 0, Y = 0 ) POINT( ADD, COOR, X = 0, Y = 10 ) POINT( ADD, COOR, X = 0, Y = 120 ) POINT( ADD, COOR, X = 0, Y = 162 ) POINT( ADD, COOR, X = 0, Y = 192 ) POINT( ADD, COOR, X = 0, Y = 206 ) POINT( ADD, COOR, X = 0, Y = 270 ) POINT( ADD, COOR, X = 480, Y = 0 ) POINT( ADD, COOR, X = 480, Y = 10 ) POINT( ADD, COOR, X = 480, Y = 120 ) POINT( ADD, COOR, X = 480, Y = 162 ) POINT( ADD, COOR, X = 480, Y = 192 ) POINT( ADD, COOR, X = 480, Y = 206 ) POINT( ADD, COOR, X = 480, Y = 270 ) POINT( ADD, COOR, X = 240, Y = 0 ) POINT( ADD, COOR, X = 260, Y = 0 ) POINT( ADD, COOR, X = 320, Y = 0 ) POINT( ADD, COOR, X = 340, Y = 0 ) POINT( ADD, COOR, X = 240, Y = 270 ) POINT( ADD, COOR, X = 260, Y = 270 ) POINT( ADD, COOR, X = 320, Y = 270 ) POINT( ADD, COOR, X = 340, Y = 270 ) POINT( ADD, COOR, X = 320, Y = 120 ) POINT( ADD, COOR, X = 340, Y = 120 ) POINT( ADD, COOR, X = 320, Y = 10 ) POINT( ADD, COOR, X = 340, Y = 10 ) POINT( ADD, COOR, X = 320, Y = 162 ) POINT( ADD, COOR, X = 320, Y = 192 ) POINT( ADD, COOR, X = 320, Y = 206 ) / ADD LINES POINT( SELE, ID ) 1, 7 CURVE( ADD, LINE ) POINT( SELE, ID ) 8, 14 CURVE( ADD, LINE ) Appendix A (continued) POINT( SELE, ID ) 1 15, 18 8

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155CURVE( ADD, LINE ) POINT( SELE, ID ) 7 19, 22 14 CURVE( ADD, LINE ) POINT( SELE, ID ) 23 24 26 25 23 CURVE( ADD, LINE ) POINT( SELE, ID ) 23 27 28 29 21 CURVE( ADD, LINE ) POINT( SELE, ID ) 17 25 CURVE( ADD, LINE ) POINT( SELE, ID ) 18 26 CURVE( ADD, LINE ) POINT( SELE, ID ) 10 24 CURVE( ADD, LINE ) / ADD SURFACES POINT( SELE, ID ) 7 14 1 8 SURFACE( ADD, POIN, ROWW = 2 ) / ADD MESH EDGES CURVE( SELE, ID = 1 ) MEDGE( ADD, SUCC, INTE = 10, RATI = 0, 2RAT = 0, PCEN = 0 ) Appendix A (continued) CURVE( SELE, ID = 2 ) MEDGE( ADD, SUCC, INTE = 17, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 3 ) MEDGE( ADD, SUCC, INTE = 14, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 4 ) MEDGE( ADD, SUCC, INTE = 13, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 5 ) MEDGE( ADD, SUCC, INTE = 11, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 6 ) MEDGE( ADD, SUCC, INTE = 16, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 7 )

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156MEDGE( ADD, SUCC, INTE = 10, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 8 ) MEDGE( ADD, SUCC, INTE = 17, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 9 ) MEDGE( ADD, SUCC, INTE = 14, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 10 ) MEDGE( ADD, SUCC, INTE = 13, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 11 ) MEDGE( ADD, SUCC, INTE = 11, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 12 ) MEDGE( ADD, SUCC, INTE = 16, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 13 ) MEDGE( ADD, FRST, INTE = 60, RATI = 0.2, 2RAT = 0.2, PCEN = 0 ) CURVE( SELE, ID = 14 ) MEDGE( ADD, SUCC, INTE = 14, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 15 ) MEDGE( ADD, SUCC, INTE = 14, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 16 ) MEDGE( ADD, SUCC, INTE = 12, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 17 ) MEDGE( ADD, SUCC, INTE = 18, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 18 ) MEDGE( ADD, FRST, INTE = 60, RATI = 0.2, 2RAT = 0.2, PCEN = 0 ) CURVE( SELE, ID = 19 ) MEDGE( ADD, SUCC, INTE = 14, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 20 ) MEDGE( ADD, SUCC, INTE = 14, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 21 ) MEDGE( ADD, SUCC, INTE = 12, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 22 ) MEDGE( ADD, SUCC, INTE = 18, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 23 ) MEDGE( ADD, SUCC, INTE = 12, RATI = 0, 2RAT = 0, PCEN = 0 ) Appendix A (continued) CURVE( SELE, ID = 24 ) MEDGE( ADD, SUCC, INTE = 17, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 25 ) MEDGE( ADD, SUCC, INTE = 12, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 26 ) MEDGE( ADD, SUCC, INTE = 17, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 27 ) MEDGE( ADD, SUCC, INTE = 14, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 28 ) MEDGE( ADD, SUCC, INTE = 13, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 29 ) MEDGE( ADD, SUCC, INTE = 11, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 30 ) MEDGE( ADD, SUCC, INTE = 16, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 31 ) MEDGE( ADD, SUCC, INTE = 10, RATI = 0, 2RAT = 0, PCEN = 0 ) CURVE( SELE, ID = 32 ) MEDGE( ADD, SUCC, INTE = 10, RATI = 0, 2RAT = 0, PCEN = 0 )

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157CURVE( SELE, ID = 33 ) MEDGE( ADD, SUCC, INTE = 18, RATI = 0, 2RAT = 0, PCEN = 0 ) / ADD MESH LOOPS CURVE( SELE, ID ) 1, 6 18 19 20 30 29 28 27 26 31 15 14 13 MLOOP( ADD, MAP, EDG1 = 6, EDG2 = 3, EDG3 = 6, EDG4 = 3 ) CURVE( SELE, ID ) 23 33 9 10 11 12 22 21 30 29 Appendix A (continued) 28 27 MLOOP( ADD, MAP, EDG1 = 2, EDG2 = 4, EDG3 = 2, EDG4 = 4 ) CURVE( SELE, ID ) 32 24 33 8 7 17 MLOOP( ADD, MAP, EDG1 = 2, EDG2 = 1, EDG3 = 2, EDG4 = 1 ) CURVE( SELE, ID ) 31 25 32 16 MLOOP( ADD, MAP, EDG1 = 1, EDG2 = 1, EDG3 = 1, EDG4 = 1 ) / ADD MESH FACES SURFACE( SELE, ID = 1 ) MLOOP( SELE, ID = 1 ) MFACE( ADD ) SURFACE( SELE, ID = 1 ) MLOOP( SELE, ID = 2 ) MFACE( ADD ) SURFACE( SELE, ID = 1 )

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158MLOOP( SELE, ID = 3 ) MFACE( ADD ) SURFACE( SELE, ID = 1 ) MLOOP( SELE, ID = 4 ) MFACE( ADD ) / MESH MESH FACES MFACE( SELE, ID ) 1, 4 MFACE( MESH, MAP, ENTI = "air" ) MFACE( SELE, ALL ) MFACE( MESH, MAP, ENTI = "air" ) / MESH MAP ELEMENT( SETD, EDGE, NODE = 2 ) MEDGE( SELE, ID = 5 ) MEDGE( MESH, MAP, ENTI = "inlet" ) MEDGE( SELE, ID = 4 ) MEDGE( MESH, MAP, ENTI = "outlet" ) MEDGE( SELE, ID = 19 ) MEDGE( MESH, MAP, ENTI = "light" ) MEDGE( SELE, ID ) 23, 26 MEDGE( MESH, MAP, ENTI = "person" ) Appendix A (continued) MEDGE( SELE, ID ) 1, 3 6, 18 20, 22 MEDGE( MESH, MAP, ENTI = "walls" ) END( ) FIPREP( ) DENSITY( SET="air", CONS = 0.0012047 ) VISCOSITY( SET="air", CONS = 0.0001817) / Using the two equations • model) CONDUCTIVITY(SET="air", CONS = 2563 ) SPECIFICHEAT( SET="air", CONS = 10040000 ) DIFFUSIVITY( SET ="water_vapor" CONS = 0.2513) DIFFUSIVITY( SET ="contam_gas" CONS = 0.2308) ENTITY( FLUI, NAME = "air", PROPERTY="air", SPECIES=1, MDIFF="water_vapor",SPECIES=2, MDIFF="contam_gas" ) ENTITY( PLOT, NAME = "inlet" ) ENTITY( PLOT, NAME = "outlet") ENTITY( PLOT, NAME = "walls" ) ENTITY( PLOT, NAME = "person" ) ENTITY( PLOT, NAME = "light" ) BCNODE( VELO, ENTI = "inlet", CONS, X = 303.1, Y = 175 ) BCNODE( VELO, ENTI = "walls", ZERO ) BCNODE( VELO, ENTI = "person", ZERO ) BCNODE( VELO, ENTI = "light", ZERO )

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159BCNODE( TEMP, ENTI = "inlet", CONS = 19 ) BCNODE( TEMP, ENTI = "walls", CONS = 24 ) BCNODE( TEMP, ENTI = "person", CONS = 34 ) BCFLUX( HEAT, ENTI = "light", CONS = 5000 ) BCNODE( SPEC=1, ENTI = "inlet", CONS = 0.010 ) BCFLUX( SPEC=1, ENTI = "person", CONS = 6E-8 ) BCNODE( SPEC=2, ENTI = "inlet", CONS = 0 ) BCFLUX( SPEC=2, ENTI = "person", CONS = 1E-6 ) CLIPPING( MINI ) 0, 0, 0, 0, 19, 0, 0, 0, 1e-20, 1e-20 CLIPPING( MAXI ) Appendix A (continued) 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 DATAPRINT( CONT ) EXECUTION( NEWJ ) OPTIONS( UPWI ) PRINTOUT( NONE, BOUN ) ICNODE( VELO, READ, ALL) PROBLEM( 2-D, NONL,TURB,ENER, SPEC = 1, SPEC = 2) END

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160 Appendix B: FIDAP Program for Th ree Dimensional Simulation for Office Room / ***************************************************************** / Disclaimer: This file was written by GAMBIT and contains / all the continuum and boundary entities and coordinate systems / defined in GAMBIT. Additionally, some frequently used FIPREP / commands are added. Modify/Add/Uncommment any necessary commands. / Refer to FIPREP documentation for complete listing of commands. / ***************************************************************** / / CONVERSION OF NEUTRAL FILE TO FIDAP Database / FICONV( NEUTRAL ) INPUT( FILE="3dr.FDNEUT" ) OUTPUT( DELETE ) END / TITLE Office Room with Wall Mounted Air Conditioning Unit / FIPREP / / PROBLEM SETUP / EXECUTION( NEWJOB ) PRINTOUT( NONE, BOUN ) DATAPRINT( CONT ) / / CONTINUUM ENTITIES / ENTITY( FLUI, NAME = "fluid", PROPERTY="fluid", SPECIES=1, MDIFF="water_vapor",SPECIES=2, MDIFF="contam_gas" ) / / BOUNDARY ENTITIES / ENTITY ( NAME = "walls", WALL ) ENTITY ( NAME = "light", WALL ) ENTITY ( NAME = "outlet", PLOT ) ENTITY ( NAME = "inlet", PLOT ) ENTITY ( NAME = "person", WALL ) / Appendix B (continued) / LOCAL COORDINATE SYSTEMS DEFINED / /COORDINATE ( SYSTEM = 2, MATRIX,CARTESIAN )

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161/0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 1.000000 / / SOLUTION PARAMETERS / SOLUTION( SEGREGATED = 100, VELCONV = .01 ) /PRESSURE( MIXED = 1.E-8, DISCONTINUOUS ) RELAX( HYBRID ) OPTIONS( UPWINDING ) / / MATERIAL PROPERTIES / / Partial list of Material Properties data / DENSITY( SET = "fluid", CONSTANT = 1.2 ) VISCOSITY( SET = "fluid", CONSTANT = 1.8e-5, MIXLENGTH ) CONDUCTIVITY( SET = "fluid", CONSTANT = 2.5776E-2 ) SPECIFICHEAT( SET = "fluid", CONSTANT = 1.0043 ) DIFFUSIVITY( SET ="water_vapor" CONS = 2.513E-5) DIFFUSIVITY( SET ="contam_gas" CONS = 2.308E-5) / / INITIAL AND BOUNDARY CONDITIONS / / BCNODE( VELO, CONSTANT = 0, ENTITY = "walls" ) BCNODE( VELO CONSTANT = 0, ENTITY = "light" ) BCNODE( VELO, CONSTANT, X = 3.03, Y = 0, Z= 1.75, ENTITY = "inlet" ) BCNODE( VELO, CONSTANT = 0, ENTITY = "person" ) BCNODE( TEMP, ENTI = "inlet", CONS = 19 ) BCNODE( TEMP, ENTI = "walls", CONS = 24 ) BCNODE( TEMP, ENTI = "person", CONS = 34 ) BCFLUX( HEAT, ENTI = "light", CONS = 50 ) BCNODE( SPEC=1, ENTI = "inlet", CONS = 0.011 ) BCFLUX( SPEC=1, ENTI = "person", CONS = 5E-7 ) BCNODE( SPEC=2, ENTI = "inlet", CONS = 0 ) BCFLUX( SPEC=2, ENTI = "person", CONS = 1E-5 ) CLIPPING( MINI ) Appendix B (continued) 0, 0, 0, 0, 19, 0, 0, 0, 0.011, 1e-20 CLIPPING( MAXI ) 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ICNODE( VELO, READ, ALL) PROBLEM( 3-D, TURB,ENER, SPEC = 1, SPEC = 2) END