Institut national des sciences appliquées de Strasbourg GENIE CLIMATIQUE ET ENERGETIQUE APPENDICES

Institut national des sciences appliquées de Strasbourg GENIE CLIMATIQUE ET ENERGETIQUE APPENDICES DEVELOPMENT OF A TOOL, BASED ON THE THERMAL DYNAMIC SIMULATION SOFTWARE TRNSYS, WHICH RUNS PARAMETRIC STUDIES TO ASSESS OUTDOOR COMFORT WITH THE PERCEIVED TEMPERATURE End-of-studies project carried out at TRANSSOLAR in Stuttgart By Hélène PERRINEAU Supervised by B. FLAMENT (INSA) and A. BILLARD (Transsolar) AUGUST 2013

Table of contents of the appendices Appendix A: Sheet explaining how to use the Excel file to analyze PT results...2 Appendix B: Influence of the opaque surfaces surrounding the windows of the 3D model on the mean radiant temperature calculated in TRNSYS...3 Appendix C: Comparison between the outside air temperature taken from the meteorological data and the temperature of the air inside the model in TRNSYS...5 Appendix D: Influence of the ground reflection coefficient for diffuse radiation on the diffuse solar radiation that effectively reaches the ground of the TRNSYS 3D model...8 Appendix E: Study of a plaza in Bahrain, influence of the floor covering on the PT...14 Appendix F: Study of a plaza in Bahrain, PT and its parameters in the base case...18 Appendix G: Additional study to the comparison led between the existing EES tool and the developed VAM tool...20 Appendix H: First preliminary study for the study of a plaza in Bahrain, influence of the surface temperatures applied on the walls around the plaza...21 Appendix I: Second preliminary study for the study of a plaza in Bahrain, influence of the composition of the soil on the plaza...24 Appendix J: Overview of the results for the study of a plaza in Bahrain with additional cases...27 Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 1

Appendix A: Sheet explaining how to use the Excel file to analyze PT results Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 2

Appendix B: Influence of the opaque surfaces surrounding the windows of the 3D model on the mean radiant temperature calculated in TRNSYS To model an outdoor space not shaded with TRNSYS, a fully glazed box should be drawn in SketchUp. However, as TRNSYS is designed to model indoor spaces, a window has to be embedded in a wall. Moreover, the insulation matrix (to distribute beam radiation on surfaces in the detailed mode based on 3D data) cannot be generated when the glazed area is too high. For instance, for a surface of 40 m 2, a window can only occupy 98 % of the total area: a 3-cm wide opaque component is required around it. The opaque component around the window can generate shading inside the box and lower the mean radiant temperature. Objective This study aims at evaluating the influence of the opaque components surrounding the windows on the mean radiant temperature for an outdoor space located in Germany. Hypothesis The study is led for an outdoor space without any shading, as shown on the figure 1. The space is located in the city of Passau in Germany. The boundary conditions of the 3D model are described in section 3. The resolution of the sky is medium with 577 patches. 4 m Width of the opaque component around the windows: 3 cm Figure 1: Model in Sketchup of the outdoor space without any shading run in TRNSYS Results and analysis The Mean Radiant Temperature (MRT) is calculated in the middle of the space. The results can only be assessed visually by checking both the MRT and the total solar radiation (from the meteorological data) over the year. The shade effect of the opaque components can then be observed as indicated on the figure 3 with red circles. The shade effect influences the MRT and the PT less than 7 days during the year, i.e. 2 % of the time. Conclusion The influence of the opaque components on the MRT and on the PT is negligible over the year. However, a way to reduce this effect is presented thereafter: it can be useful if a study concentrates on a day when the shade effect can be observed. Additional study: reduction of the shade influence of the opaque components As the area of the opaque components cannot be reduced, the aim is to lower their influence by using a higher insulation matrix resolution. In TRNSYS, in order to generate an insulation matrix (to distribute beam radiation on surfaces in the detailed mode based on 3D data), the sky hemisphere is divided into patches according to the Tregenza model. Every single patch is represented by a point. Then, distribution factors are calculated for every surface of a zone for each window and each sky patch. Two resolutions of the sky subdivision can be adopted: medium with 577 patches and high with 2305 patches. In this study, the two resolutions are compared on a day when the shade influence of the opaque components can be noticed: February 5 th. The outdoor space considered is the one described in the hypothesis. The figures 2 and 3 show the results. The MRT and the perceived temperature (PT) are measured in the middle of the space. On the figure 2, the shade effect of the opaque components can be seen on the sun path diagram on the right. On the figure 3, with 577 patches, the influence of the opaque components on the MRT and PT can be observed whereas their influence cannot be seen with 2305 patches. In conclusion, increasing the resolution of the sky to calculate the insulation matrix reduces the influence of the opaque components around the windows on the MRT. However, the computation time is increased with a detailed sky subdivision. Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 3

Figure 2: Sun path diagram on February 5th 577 patches 2305 patches 577 patches 2305 patches Figure 3: Comparison between 577 patches and 2305 patches for a model without any shading Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 4

Appendix C: Comparison between the outside air temperature taken from the meteorological data and the temperature of the air inside the model in TRNSYS Objectives The first aim of the study is to compare the air temperature considered by TRNSYS in a space modeled with the outside air temperature taken from the meteorological data for an outdoor space located in Germany. The second aim of this study is to identify ways to reduce the differences observed between the two air temperatures. Hypothesis The comparison is led for an outdoor space without any shading, as shown on the figure 4. The space is located in the city of Passau in Germany. The boundary conditions of the 3D model are described in section 3. The infiltration rate is directly proportional to the wind velocity at all times. Tzone 4 m Figure 4: Model of the outdoor space without any shading run in TRNSYS Given that the space is not shaded, the outside air temperature taken from the weather data, T amb, and the air temperature considered by TRNSYS inside the zone, T zone on the figure 4, should be equal. Results and analysis The results are shown for the whole year on the figure below. Figure 5: Air temperatures over the year The air temperature of the zone is not equal at all times to the outside air temperature, T amb. During the whole year, the air temperature of the zone is above (T amb + 1) and below (T amb - 1) during 6 % of the time. During winter time, from December to February, it happens during 14 % of the time. This phenomenon is linked to the model of the air change rate in the zone which directly influences the temperature inside the zone. Indeed, the air change rate is directly proportional to the wind velocity. When there is no wind, the air change rate is equal to zero: it leads to the rise of the air temperature of the zone above T amb, as shown on the figure 6 for a winter week. Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 5

Figure 6: Air temperature and wind velocity during a winter week Solution to reduce the differences between the air temperature inside the zone and the outside air temperature In order to prevent the temperature inside the zone to go over the outside air temperature when the wind velocity is equal to zero, a minimum infiltration rate can be set. During the previous study, the infiltration rates ranged between 0.4 and 466.2 vol.h -1 over the year. In an additional study, three minimum infiltration rates are considered when the wind velocity is equal to zero: 5, 10 and 15 vol.h -1. The results are shown on the figures 7, 8 and 9. Min infiltration rate = 0 vol.h -1 Min infiltration rate = 10 vol.h -1-1 Min infiltration rate = 5 vol.h Min infiltration rate = 15 vol.h -1 Figure 7: Air temperature over the year in function of the minimum infiltration rate Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 6

Min infiltration rate = 0 vol.h -1 Min infiltration rate = 10 vol.h -1-1 Min infiltration rate = 5 vol.h Min infiltration rate = 15 vol.h -1 Figure 8: Air temperature during a winter week in function of the minimum infiltration rate Infiltration rate when there is no wind [vol.h -1 ] 0 5 10 15 Percentage of time when the temperature of the zone is below (Tamb -1) or above (Tamb +1) Over the year 6.2 % 3.1 % 0.8 % 0.2 % During winter time 14.1 % 9.4 % 2.8 % 0.7 % Figure 9: Percentage of time when the zone temperature is deviating from the outside air temperature in function of the minimum infiltration rate The lowest deviation is reached when the minimum infiltration rate is equal to 15 vol.h -1. Conclusion When the air change rate is directly proportional to the wind velocity at all times, the air temperature of the zone rises above the outside air temperature taken from the weather data when the wind velocity is equal to zero. That is the reason why a minimum infiltration rate has to be set. For the city of Passau in Germany, for a space without any shading, the lowest deviation between the air temperature from the meteorological data and inside the zone is reached when the minimum infiltration rate is set to 15 vol.h -1. Thus, this value can be integrated as a fixed parameter for the location of Passau. For a different location, the same study should be done. Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 7

Appendix D: Influence of the ground reflection coefficient for diffuse radiation on the diffuse solar radiation that effectively reaches the ground of the TRNSYS 3D model Simulations showed that, for an outdoor space without any shading modeled in TRNSYS in 3D, the diffuse solar radiation hitting the ground is not equal to the theoretical amount that should hit a horizontal surface. Those differences can be explained by the model of distribution of diffuse radiation used in TRNSYS, as described in section 3.1.4. The ground reflection coefficient for diffuse radiation is involved in this distribution. To increase the amount of diffuse radiation hitting the ground up to the theoretical amount that should reach it, a work around can be to increase the ground reflection coefficient for diffuse radiation. Objective The study aims at assessing the influence of the ground reflection coefficient for diffuse radiation on: the amount of diffuse radiation hitting the ground of the space modeled and on the PT for an outdoor space in Bahrain, first without any shading and then surrounded by buildings. The study is divided into two comparisons. Hypothesis of the first comparison The study is led for an outdoor space without any shading as shown on the figure 10. The space is located in the city of Muharraq in Bahrain: it is the plaza studied in section 5 except that the buildings surrounding the plaza are not modeled. The boundary conditions of the model are described in section 5.2 except that the walls around the plaza are replaced by vertical fictive surfaces as described in section 3. 3 m Figure 10: 3D model of the outdoor space without any shading, 1 st comparison Cases of the first comparison Five ground reflection coefficients for diffuse radiation are considered: 0.2 (case B), 0.4 (case C), 0.6 (case D), 0.8 (case E) and 1 (case F). The case A shows the amount of solar radiation (direct and diffuse) that should hit a horizontal surface when there is no shading. Results of the first comparison The results are shown on the figures 12 and 13 in the following pages. Analysis of the results of the first comparison In Muharraq, during spring and summer, for the different ground reflection coefficients considered, the diffuse solar radiation hitting the ground can be underestimated up to 22 % and overestimated up to 40 %. The lowest deviation is reached with a ground reflection of 0.6 during spring and 0.8 during summer. If we assume that the diffuse solar radiation hitting the ground should not be overestimated, the best compromise between spring and summer is a ground reflection coefficient equal to 0.6 (case D). In comparison to the case D with a ground reflection of 0.6, the differences in perceived temperatures with the other reflection coefficients go up to 0.7 C during spring and up to 0.8 C during summer. Hypothesis of the second comparison The study is led for the same outdoor space as in the first comparison, the plaza in the city of Muharraq studied in section 5. Contrary to the first comparison, the buildings surrounding the Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 8

plaza are modeled, as shown on the figure 11 below. The boundary conditions of the model are described in section 5.2. Figure 11: 3D model of the outdoor space with surrounding buildings, 2 nd comparison Cases of the second comparison Only the cases B (ground reflection coefficient equal to 0.2) and D (ground reflection coefficient equal to 0.6) were considered in the second comparison with the buildings because the case B corresponds to the value usually considered in TRNSYS and the case D is the one which leads to the lowest deviations in the first comparison. The case A shows the amount of solar radiation (direct and diffuse) that should hit a horizontal surface when there is no shading. Results of the first comparison The results are shown on the figures 14 and 15 in the following pages. Analysis of the results of the second comparison In the cases B and D, the diffuse solar radiation hitting the ground is significantly lower than the diffuse radiation that should reach a horizontal surface which is not shaded: it shows that the ground is shaded by the buildings. With a ground reflection coefficient equal to 0.2 (case B) instead of 0.6 (case D), the differences in perceived temperatures can reach up to 0.3 C. The influence of the ground reflection coefficient for diffuse radiation is not significant. Conclusion In the city of Muharraq in Barhain, the ground reflection coefficient has a significant influence on the amount of diffuse solar radiation hitting the ground of the space modeled (it can increase by up to 40 % the amount of diffuse radiation compared to the theoretical amount) but the influence is not significant on the perceived temperature in the end (up to 0.8 C at maximum). Moreover, the impact of the ground reflection coefficient for diffuse radiation on the perceived temperature is higher for an outdoor space which is not shaded than for a space surrounded by buildings. For a different location and another outdoor space, the influence of the ground reflection coefficient for diffuse radiation should be checked. Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 9

A-Undisturbed solar radiation B-GRDREF = 0.2 C- GRDREF = 0.4 D- GRDREF = 0.6 E- GRDREF = 0.8 F- GRDREF = 1.0 C-A D-A E-A F-A Mean -38.4-21.2-4 +13.1 +30.3 Max -99.7-76.1-54.4 +45.4 +70.1 Max(diff/A) -22% -16% -12% +28% +40% Reference: case A Differences in diffuse solar radiations c B-D C-D E-D F-D Mean -1.6-0.8 +0.8 +1.5 Max -2.7-1.3 +1.3 +2.7 Reference: case D Differences in ground surface temperatures B-D C-D E-D F-D (Mean value of all the comfort points) Mean -2.1-1.1 +1.0 +2.1 Max -3.8-1.9 +1.8 +3.7 Reference: case D Differences in mean radiant temperatures B-D C-D E-D F-D Figure 12: Influence of the ground reflection without buildings, PT parameters in function of time for a spring week Mean -0.4-0.2 +0.2 +0.4 Max -0.7-0.4 +0.4 +0.7 Reference: case D Differences in perceived temperatures Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 10

A-Undisturbed solar radiation B-GRDREF = 0.2 C- GRDREF = 0.4 D- GRDREF = 0.6 E- GRDREF = 0.8 F- GRDREF = 1.0 C-A D-A E-A F-A Mean -47.7-34.0-20.3-6.6 +7.2 Max -97.7-77.3-56.9-39.9 +58.0 Max(diff/A) -21% -17% -13% -9% +20% Reference: case A Differences in diffuse solar radiations B-D C-D E-D F-D Mean -1.3-0.7 +0.7 +1.3 Max -2.9-1.4 +1.4 +2.8 Reference: case D Differences in ground surface temperatures (Mean value of all the comfort points) B-D C-D E-D F-D Reference: case D Differences in perceived temperatures Figure 13: Influence of the ground reflection without buildings, PT parameters for a summer week Mean -1.7-0.8 +0.8 +1.7 Max -3.6-1.8 +1.8 +3.5 Reference: case D Differences in mean radiant temperatures B-D C-D E-D F-D Mean -0.3-0.2 +0.2 +0.3 Max -0.8-0.4 +0.4 +0.8 Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 11

A-Undisturbed solar radiation B-GRDREF = 0.2 D- GRDREF = with buildings 0.6 with buildings B-D Mean -12.4 Max -22.6 Differences in diffuse solar radiations B-D Mean -0.6 Max -1.0 Differences in ground surface temperatures (Mean value of all the comfort points) B-D Mean -0.8 Max -1.5 Differences in mean radiant temperatures B-D Mean -0.2 Max -0.3 Differences in perceived temperatures Figure 14: Influence of the ground reflection with buildings, PT parameters in function of time for a spring week Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 12

A-Undisturbed solar radiation B-GRDREF = 0.2 D- GRDREF = with buildings 0.6 with buildings B-D Mean -9.9 Max -21.7 Differences in diffuse solar radiations B-D Mean -0.5 Max -1.1 Differences in ground surface temperatures (Mean value of all the comfort points) B-D Mean -0.7 Max -1.4 Differences in mean radiant temperatures B-D Mean -0.1 Max -0.3 Differences in perceived temperatures Figure 15: Influence of the ground reflection with buildings, PT parameters in function of time for a summer week Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 13

Appendix E: Study of a plaza in Bahrain, influence of the floor covering on the PT Objective The aim is to study the influence of the floor covering on the PT by comparing a white marble, a yellow marble and concrete. Those coverings were pre-selected by the architects designing the plaza. Cases In the base case A, the top layer of the ground is made of yellow marble. In the case B, yellow marble is replaced by white marble which has the same conductivity and thermal capacity, but a different solar absorption and long wave emissivity. In the case C, the whole ground composition is different than in the base case as shown on the figure 17 below. The main feature is the top layer made of concrete. A-Yellow marble B-White marble C-Concrete Cases A and B Figure 16: three cases to study the influence of the floor covering α and ε: solar absorption and long wave emissivity of the upper ground layer Figure 17: Composition of the ground and properties of the upper layer for each case The top layer of the ground affects the amount of solar radiation absorbed by the ground and the heat transfers by long wave radiation with the surroundings. Thus, the floor covering influences the ground surface temperature and the mean radiant temperature on the plaza. Results The results are shown in the figures 18 to 21. A: α = 0.65, ε = 0.56 B: α = 0.30, ε = 0.89 C: α = 0.60, ε = 0.91 Case C Analysis of the results during spring: case B compared to case A Variables of the PT The total solar radiation absorbed by the ground is 54 % lower with the white marble than with the yellow marble, as the solar absorption coefficient of the white marble is 54 % lower than the one of the yellow marble. As a result, the ground surface temperature can be reduced by up to 11.9 C during the day and by up to 2.6 C during the night by using white marble instead of yellow marble. However, the mean radiant temperature increases by up to 3.9 C during the day and by up to 0.4 C during the night when using white marble. Indeed, as the white marble is more reflective, the surrounding walls are hit by a larger amount of solar radiation, which results in an increase of their surface temperatures compared to the surrounding surfaces in the case A with yellow marble, as shown for the wall a in the results. Therefore, the mean radiant temperature is higher for white marble than for yellow marble. In the end, the perceived temperature can be increased by up to 0.4 C during the day by using white marble instead of yellow marble. Thermal perceptions during the day The influence of the floor covering on the thermal perceptions on the plaza is negligible. Conclusion In Muharraq, in spring and summer, using white marble or concrete instead of yellow marble increases the Perceived Temperature by 0.4 C at maximum during the day. Using white marble or concrete instead of yellow marble does not have an effect on the thermal stress perceived on the plaza during the day in spring and summer. Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 14

A-Yellow marble B-White marble C-Concrete C-A Mean -116.9 0.0 Max -259.8 0.0 Differences in total solar radiations C-A Mean -6.0-0.8 Max -11.9-2.2 Night Mean -1.3-1.1 Max -2.6-1.7 Differences in ground surface temperatures (Mean value of the 20 comfort sensors) (Mean value of the 20 comfort sensors) C-A Figure 18: Influence of the floor covering, parameters of the PT in function of time for a spring week Note: In case C, 2 parameters are changing in comparison to the other cases (floor covering and composition of the ground). Thus, the effect of the 2 parameters on the ground surface temperature cannot be split up. Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 15 Mean +1.7 +0.9 Max +3.9 +1.8 Night Mean +0.1 +0.2 Max +0.4 +0.4 Differences in mean radiant temperatures C-A Mean +0.1 +0.1 Max +0.4 +0.4 Night Mean -0.1 0.0 Max -0.1-0.1 Differences in perceived temperatures

A-Yellow marble B-White marble C-Concrete C-A Mean -86.1 0.0 Max -245.1 0.0 Differences in total solar radiations C-A Mean -4.7-0.5 Max -12-2.5 Night Mean -1.2-0.9 Max -3.9-2.3 Differences in ground surface temperatures (Mean value of the 20 comfort sensors) (Mean value of the 20 comfort sensors) Figure 19: Influence of the floor covering, parameters of the PT in function of time for a summer week C-A Mean +1.1 +0.6 Max +3.3 +1.8 Night Mean +0.0 +0.1 Max -0.4 +0.1 Differences in mean radiant temperatures C-A Mean +0.1 +0.1 Max +0.4 +0.3 Night Mean -0.1 0.0 Max -0.2-0.1 Differences in perceived temperatures Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 16

A-Yellow marble B-White marble C-Concrete Figure 20: Influence of the floor covering, weekly frequency of thermal perceptions, for a spring week during day only A-Yellow marble B-White marble C-Concrete Figure 21: Influence of the floor covering, weekly frequency of thermal perceptions, for a summer week during day only Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 17

Appendix F: Study of a plaza in Bahrain, PT and its parameters in the base case The spring week studied takes place from May 21 st to 27 th. During this week, the air temperature ranges between 25 C and 38 C, with a maximum amplitude of 13 C between day and night. The mean radiant temperature ranges between 22 C and 52 C, with a maximum amplitude of 29 C between day and night. The wind velocity at 1 m above the ground reaches rather high velocities, up to 4.5 m.s -1.The relative humidity ranges between 30 % and 70 %. The maximum humidity ranges are reached during the night when the ambient temperature is minimal. Relative Mean radiant temperature Perceived temperature Air temperature Figure 22: Parameters of the PT for the base case, for a spring week The PT ranges between 20 and 40 C. It implies that comfort is not achieved. We will assume that, in Muharraq, a thermal sensation which is comfortable to warm is acceptable. The thermal perception is slightly warm and warm during 21 % of the week when the sun shines. Comfort has to be improved. and night Figure 23: Frequency of thermal perceptions in the base case, for a spring week Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 18

The summer week studied takes place from July 21 st to 27 th. During this week, the air temperature ranges between 29 C and 43 C, with a maximum amplitude of 12 C between day and night. The mean radiant temperature ranges between 29 C and 58 C, with a maximum amplitude of 29 C between day and night. The wind velocity at 1 m above the ground reaches up to 4 m.s -1.The relative humidity ranges between 38 % and 73 %. The maximum humidity ranges are reached during the night when the air temperature is minimal. Relative Mean radiant temperature Perceived temperature Air temperature Figure 24: Parameters of the PT for the base case, for a summer week The PT ranges between 30 and 47 C. Therefore, comfort is not achieved. We will assume that, in Muharraq, a thermal sensation which is comfortable to warm is acceptable. The thermal perception is warm during only 1 % of the week when the sun shines, and very hot during 88 % of the time. Comfort has to be improved. and night Figure 25: Frequency of thermal perceptions in the base case, for a summer week Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 19

Appendix G: Additional study to the comparison led between the existing EES tool and the developed VAM tool Objective This study aims at testing one hypothesis of the comparison led between the 1D and the 3D based tools in section 4: the boundary temperature of the vertical walls of the 3D model. The objective is to quantify the differences in the PT calculated by the EES tool and by the VAM tool for different boundary temperatures. Cases Three different boundary temperatures for the vertical walls of the 3D model are tested: the sky temperature (T sky ), the outside air temperature (T amb ) and the mean between the ground surface temperature (T ground ) and the sky temperature (as considered in the study led in section 4). Night is not taken into account in this comparison for the reasons mentioned in section 4.5.1. Results and analysis The figure 26 shows the results. Boundary condition in TRNSYS Jan Feb Mar Apr Mai Jun Jul Aug Sep Oct Nov Dec T vertical walls = T sky 68% 64% 23% 36% 57% 50% 62% 47% 21% 17% 9% 25% T vertical walls = T amb 52% 37% 11% 14% 21% 26% 30% 19% 5% 0% 1% 5% T vertical walls = (T ground + T sky )/2 44% 32% 3% 4% 7% 6% 7% 7% 3% 4% 4% 5% Figure 26: Percentage of time when PT TRNSYS is below (PT EES 2 C) or above (PT EES + 2 C) In January and February, the first two months of the year, deviations are higher than during the rest of the year. As those higher differences do not appear at the end of the year, they are not linked to the weather data at that time. Those deviations can be a result of the time necessary for the system to reach his balance. From March to December, the differences in the PT (+- 2 C) take place: between 9 % and 62 % of the time when the vertical surfaces of the 3D model are at the fictive sky temperature, between 0 and 30 % when they are at the ambient air temperature, and between 3 and 7 % when they are at the mean between the ground surface temperature and the sky temperature. Conclusion The boundary condition on the vertical walls of the 3D model in the VAM tool that leads to the closest results to the EES tool is the mean temperature between the ground surface temperature and the fictive sky temperature. Indeed, it reproduces the boundary conditions of the 1D model of the EES tool. This is the boundary condition that was used during the comparison led in section 4. Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 20

Appendix H: First preliminary study for the study of a plaza in Bahrain, influence of the surface temperatures applied on the walls around the plaza The surfaces temperatures of the walls around the plaza, on the interior side of the buildings, are determined in the base case by making a thermal simulation of the buildings in TRNSYS Light, as described in section 5.2. The aim is to determine a floating boundary condition for the walls surface temperatures which is closer to reality than an arbitrary fixed value. Indeed, a wall surface temperature inside a building is an attenuation of the outside air temperature according to the thermal properties of the building envelope. However, a rougher boundary condition could have been chosen to avoid the simulations: for instance, the outside air temperature could have been directly applied. Objective The aim of the study is to compare the influence on the PT of a rough and a more elaborated boundary condition. Cases In the base case A, the boundary conditions on the walls surrounding the plaza are elaborated: they come from a TRNSYS Light simulation. In the case B, the boundary conditions are rough: they are equal to the outside air temperature T amb. The surface temperature on the inside of the walls, T boundary, influences the surface temperature on the outside, T so. In the end, the mean radiant temperature is the parameter of the PT affected. A-T boundary from Trnsys Light B-T boundary equal to T amb Figure 27: Case A with a refined boundary condition and case B with a rough boundary condition Results The results are presented in the following pages in the figures 28 and 29. Note about the results presented The surfaces temperatures are shown only for the wall «a» located on the East side of the plaza. The same behavior can be observed on each wall of the plaza, with a shift in time and amplitude depending on the orientation of the surface. Analysis of the results The wall a boundary temperatures in case A and B are different in amplitude and shifted in time. The amplitude between day and night of the outside air temperature equals 10 C, whereas for the temperature on the inside of the building calculated with TRNSYS Light, the amplitude equals only 3 C. Moreover, there is a shift in time: the peak values are reached later on the inside of the building (for temperatures calculated with TRNSYS Light) than by the outside air temperature. Indeed, the boundary temperature in case A (calculated with TRNSYS Light) corresponds to an attenuation of the ambient temperature thanks to the thermal properties of the building envelope. The highest differences in the wall a surface temperatures on the outside between the two cases can be observed during the night, when the sun stops shining, and at the beginning of the day, when the solar radiations are not yet hitting this wall facing west. At that time, the difference in surface temperatures between the two cases can reach at maximum 3.1 C during spring and 3.3 C during summer. When the sun is hitting the surface, the outside surface temperatures in the two cases are close. The difference in mean radiant temperatures between the two cases can reach at maximum 0.8 C during spring and summer. As a result, the difference in perceived temperatures between the two cases is at maximum of 0.3 C during spring and summer. Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 21

Conclusion In Muharraq, during the day in spring and summer, the difference in perceived temperatures between the elaborated and the rougher boundary condition on the walls is at maximum equal to 0.3 C. However, it is worth noticing that, when solar radiations do not hit the wall (at night), the differences in outside surface temperatures between the two cases can reach up to 3.1 C during spring and 3.3 C during summer. A-T boundary from Trnsys Light B-T boundary equal to T amb For wall a on the East side Night Mean -0.9-0.9 Max -3.1-2.7 Differences in wall surface temperatures T so: Wall a surface temperature, T so Wall a boundary temperature, T boundary (Mean value of all the comfort points) (Mean value of all the comfort points) Night Mean -0.2-0.2 Max -0.8-0.7 Differences in mean radiant temperatures Night Mean -0.1-0.1 Max -0.3-0.3 Differences in perceived temperatures Figure 28: Influence of the walls boundary conditions, PT parameters in function of time for a spring week Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 22

A-T boundary from Trnsys Light B-T boundary equal to T amb Night Mean -1.0-0.9 Max -3.3-2.8 Differences in wall surface temperatures T so Wall a surface temperature, T so Wall a boundary temperature, T boundary (Mean value of all the comfort points) (Mean value of all the comfort points) Night Mean -0.3-0.2 Max -0.8-0.7 Differences in mean radiant temperatures Night Mean -0.1-0.1 Max -0.3-0.3 Differences in perceived temperatures Figure 29: Influence of the walls boundary conditions, PT parameters in function of time for a summer week Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 23

Appendix I: Second preliminary study for the study of a plaza in Bahrain, influence of the composition of the soil on the plaza The accurate composition of the soil is unknown on the plaza studied. However, a study led about the city of Muharraq by John R. Yarwood [13] mentions the presence of sand. The soil is the fifth and deeper layer of the ground. Objective This study aims at assessing the influence of the definition of this parameter on the PT on the plaza by comparing two different sandy soils. Cases In the base case A, the ground is modeled with the soil 1 whereas in case B, the ground is modeled with the soil 2. The soil 1 is composed of heavy sand with a water content of 15% and the soil 2 is composed of light sand with a lower water content of 5 %.The following table shows the properties of the two soils. Density Diffusivity Thermal Total ground U Conductivity Soil Composition dry wet capacity value kj.h -1.m -1.K -1 kg.m -3 m 2.day -1 kj.kg -1.K -1 kj.h -1.m -2.K -1 heavy sand, 15% 3.8*3.6 = 13.68 1925 1 1786*** 0.097 ** 1.89*** 4.876 water ** ** light sand, 5% 0.9*3.6 = 3.24 1285 1.747 2 1271 ** 0.0875 ** 0.70 *** water ** ** * TRNSYS, ** ASHRAE Fundamentals, *** calculated Figure 30: Composition and thermal properties of the soils 1 and 2 The composition of the soil influences the ground undisturbed temperature and as a result its surface temperature. In the end, the mean radiant temperature is the parameter of the PT affected. A-With soil 1 B-With soil 2 Figure 31: Case A with soil 1 and case B with soil 2 Results The results are presented in the following pages in the figures 32 and 33. Analysis of the results The ground undisturbed temperatures are different in each case as they depend on the diffusivity of the ground, as described in section 3.1. In spring and summer, the ground undisturbed temperature in the case B with the soil 2 is 0.3 C higher than in the case A with the soil 1. As a result, the surface temperature in case B with the soil 2 is at maximum 0.8 C higher during spring and 1.1 C higher in summer than in the case A with the soil 1. The difference in mean radiant temperatures between the cases is at maximum of 0.1 C during spring and 0.2 C during summer. The differences in mean radiant temperatures are lower than the differences in the ground surface temperatures. Indeed, the mean radiant temperature takes into account the long wave radiative effect of all the surrounding surfaces, the ground is only one of them. As a result, the difference in perceived temperatures between the 2 cases is at maximum of 0.1 C. Conclusion In Muharraq, during the day in spring and summer, the difference in perceived temperatures between a soil composed of heavy sand with a water content of 15 % and a soil composed of light sand with a water content of 5 % is at maximum equal to 0.1 C since the diffusivities of the two soils are close. Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 24

A-With soil 1 B-With soil 2 Night Mean 0.6 0.6 Max 0.8 0.8 Differences in ground surface temperatures 18.2 C 17.9 C Night Mean 0.3 0.3 Differences in boundary temperatures (Mean value of all the comfort points) (Mean value of all the comfort points) Night Mean 0.1 0.1 Max 0.1 0.1 Differences in mean radiant temperatures Night Mean 0.0 0.1 Max 0.1 0.1 Differences in perceived temperatures Figure 32: Influence of the properties of the soil, PT parameters in function of time for a spring week Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 25

A-With soil 1 B-With soil 2 Night Mean 0.7 0.7 Max 1.0 1.1 Differences in ground surface temperatures 18.2 C 17.9 C Night Mean 0.3 0.3 Differences in ground boundary temperatures (Mean value of all the comfort points) (Mean value of all the comfort points) Night Mean 0.1 0.1 Max 0.2 0.2 Differences in mean radiant temperatures Night Mean 0.0 0.1 Max 0.1 0.1 Differences in perceived temperatures Figure 33: Influence of the properties of the soil, PT parameters in function of time for a summer week Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 26

Appendix J: Overview of the results for the study of a plaza in Bahrain with additional cases Base Shading 1-With trees 2-With low-e membrane when sun shines Wind 3-No wind on the person 4-Fan when Tamb < 32 C Humidity 5-Dehumidification to 40 % RH 6-Dehumidification to 20 % RH Evap cooling 7-Efficiency: 40 % 8-Efficiency: 80 % Humidity, Air T 9-Humidity minus 5 g.kg -1 10-Temperature minus 5 C 11-Temperature minus 5 C, same RH Shading, Wind, Air T, Humidity Low-e, fan, evap cooling 40 %, 2 + 4 + 7 Low-e, fan, cooling, dehumidification 2 + 4 + 11 Figure 34: Frequency of thermal perceptions for the main cases, for a spring week during the day Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 27

Base Shading 1-With trees 2-With low-e membrane when sun shines Wind 3-No wind on the person 4-Fan when Tamb < 32 C Humidity 5-Dehumidification to 40 % RH 6-Dehumidification to 20 % RH Evap cooling 7-Efficiency: 40 % 8-Efficiency: 80 % Humidity, Air T 9-Humidity minus 5 g.kg -1 10-Temperature minus 5 C 11-Temperature minus 5 C, same RH Shading, Wind, Air T, Humidity Low-e, fan, evap cooling 40 %, 2 + 4 + 7 Low-e, fan, cooling, dehumidification 2 + 4 + 11 Figure 35: Weekly frequency of thermal perceptions for the main cases, for a summer week during the day Student: Perrineau Hélène - Development of a tool to run parametric studies of outdoor comfort - 28