Comparison of steady state transmission with transient heat algorithm of EnergyPlus

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List of Contents List of Figures ............................................. 1 List of Tables............................................... 2 List of Variables .......................................... 2 Chapter 1: Background knowledge on steady-state heat loss/gain with solar and wind effects ................................................. 4 Section A: Conductive Heat Transfer ...... 4 Section B: Sol-air Temperature ............... 4 Section C: External Film Coefficient (â„Žđ?‘œ) 5 Chapter 2: Introduction to the project and discussion of the given building and selected location ......................................... 5 Section A: Background of REPRO .......... 5 Section B: Description of Analysed Building.................................................... 6 Section C: Location ................................. 6 Chapter 3: Development/ Validation/ Application of REPRO/SINGLEFLUX programs for predicting building steady-state heat loss & gain .......................................... 7 Section A1: REPRO Interface and Overview ................................................. 7 Section A2: Simulation Engine of REPRO ................................................................ 8 Section B: SINGLEFLUX interface .......... 9 Section C: Parametric Study with REPRO .............................................................. 11 Chapter 4: Comparison of REPRO with commercial software ................................. 16 Section A: Setting up EnergyPlus and REPRO.................................................. 17 Section B: Methodology......................... 18 Section C: Results and Discussion ........ 18 Chapter 5: Specific Conclusions and Recommendations Drawn from the Project .................................................................. 21 References................................................ 22 Appendices ............................................... 23

Figure 7: REPRO main menu ..................... 7 Figure 8: 'Internal loads and settings' panel 7 Figure 9: Simulation result window ............. 7 Figure 10: Plot of heat flux contribution from each element .............................................. 8 Figure 11: Heat gain/loss as a function of indoor temperature ..................................... 8 Figure 12: SINGLEFLUX interface .............. 9 Figure 13: SINGLEFLUX control panel ....... 9 Figure 14: Detailed view of Main Menu, showing the different areas of user interface .................................................................. 10 Figure 15: Parameter adjustment panel .... 12 Figure 16: Under settings, select the type for simulation.................................................. 12 Figure 17: Result window with hourly and cumulative wall heat displayed ................. 12 Figure 18: Tabulated result of cumulative heat gain by each element ........................ 12 Figure 19: Heat gain through element as a function of indoor temperature and element property..................................................... 13 Figure 20: Heat flow through different elements w.r.t their property ..................... 14 Figure 21: %contribution from each building element-summ. ......................................... 14 Figure 22: %contribution from each building element (winter) ........................................ 14 Figure 23: Rate of change of contribution to total building heat by individual parameter 15 Figure 24: Modify outdoor temperature on REPRO ..................................................... 18 Figure 25: Modify wind speeds on REPRO .................................................................. 18 Figure 26: Modify radiation values on REPRO ..................................................... 18 Figure 27: Heat flow w.r.t different elements .................................................................. 19 Figure 28: Difference between REPRO and EP w.r.t heat gain of element from REPRO .................................................................. 20 Figure 29: Power law form for the wind convection coefficient (W/m2 K): h = a + bVn; [10] ............................................................ 23 Figure 30: Linear equation form for the wind convection coefficient (W/m2 K): h = a + bV; [10] ............................................................ 24 Figure 31: REPRO Simulate window- chart showing heat flow through different elements at each of the six-analysis hour ................ 25 Figure 32: REPRO Comparison windowheat gain through different elements as a function indoor temperature ...................... 25

List of Figures Figure 1: Resistance offered by the wall towards heat flow; after Manz [4] ................ 4 Figure 2: Thermal resistance of multi-layered wall [4] ......................................................... 4 Figure 3: Plan of building under study ......... 6 Figure 4: Building plan with different elememts labeled ........................................ 6 Figure 5: Location of Bangalore [22] ........... 6 Figure 6: Monthly average climate data for Bangalore [23]............................................. 7

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Figure 33: SINGLEFLUX Main window showing the net heat gains from wall as a function of indoor temperature .................. 26 List of Tables Table 1: Logical sequence of program command .................................................... 8 Table 2: Meteorological data used in study .................................................................. 11 Table 3: Building data used to simulate heat flow ........................................................... 11 Table 4: Coefficient of linear relation of type y(%)=mx(element) + c .............................. 15 Table 5: Modified meteorological parameters for comparison .......................................... 18 Table 6: %deviation of EnergyPlus from REPRO ..................................................... 19 Table 7: Detailed element dimension and area ........................................................... 24 Table 8: Absolute value of heat gain/loss as a function of both the parameter setting and indoor temperature. ................................... 27

Stores the wind speed for 6 different times

WallThickness(2 Stores wall thickness for ) 3 types of wall Stores wall conductivity for 3 types of wall

Wallabsorp(2)

Stores wall absorptivity for 3 types of wall

GlazingUval(2)

Stores U-value for 3 types of window

GlazingTrans(2)

Solar transmittance for 3 types of window

Floorthick(2)

Stores thickness for 3 types of floor

Floorconduct(2)

Stores conductivity for 3 types of floor

Roofabsorp(2)

Stores absorptivity for 3 types of roof

Roofthick(2)

Stores thickness for 3 types of roof

Tin

Inside zone temperature

LightLoad

Stores the lighting load

EquipLoad

Stores the equipment load

noPpl

Number of people

PplLoad

Heat produced from each person

Airchange

Rate of air change for zone ventilation

Simulation variables All variables are of type Double unless stated otherwise: Temporary variable to hold temp a value for a further addition Temporary variable to hold temp2 a value for a further addition Holds the ‘type’ number for SimulateType which the simulation is to be carried. Can range from (int) 0-2 Global variable to prevent flag re-simulation in case the user presses simulate (boolean) again Loop variable, which also i acts like timestep for (integer) passing arguments Stores formatted value of hourvalue summer heat quantity temporarily Stores formatted value of hourvalue2 winter heat quantity temporarily HeatLossGain variables All variables are of type Double unless stated otherwise:

Main Menu variables All variables are of type Double unless stated otherwise: Stores the outside TempOut(5) temperature for 6 different times

Wallconduct(2)

Stores conductivity for 3 types of roof

The following are of different type: Loop counter to select Lbl Label all labels in a panel and re-color them Loop counter to select a pic Picture picture in the panel and view/hide it

List of Variables

WindSpeed(5)

Roofconduct(2)

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wallArea(19) wallDirection(1 9) wallShadingCo eff(5,19) wallRvalue(2) wallUvalue(2) glazingArea(3) glazingShadin gCoeff(5, 3) glazingDirectio n(3) roofArea

Holds areas of all 20 wall surfaces Holds the direction of each of the wall surfaces, which can range from 0-7 2D array to store sunlit fraction for each wall surface at each of the 6 hours (total 120 value) Array to store resistances of the three types of wall Array to store U-values of the three types of wall Holds areas of all 20 wall surfaces Sunlit fraction of the 4 windows for all 6 times (total 24 values)

temp

temp2

defaultRadVH (53) defaultShade Wall(119) defaultShadeG laze(23) i, j R U Tsol

Direction the windows face

Area of roof The sunlit fraction for roof roofShadingCo for each of the 6 hours (in eff(5) this case always 1) floorArea Area of floor Stores the radiation falling SolarRad(5,8 on surfaces facing 9 ) different direction, for each of the 6 hours Heat quantity flowing Qwalls(5) through all walls combined, for 6 hours of study Heat quantity flowing through all windows Qglazing(5) combined, for 6 hours of study Heat quantity flowing Qfloor(5) through the floor, for 6 hours of study Heat quantity flowing Qroof(5) through the roof, for 6 hours of study Ventilation heat flow for Qventi(5) each of the 6 hours Sum of ventilation, Qother(5) equipment, people and lighting load for each hour Rso(5) External surface resistance 0.13, Internal surface Rsi resistance

deltaT glazePos groundTemp ventilationGain peopleGain

Temporary variable used for addition and other calculation Temporary variable used for addition and other calculation Stores the default radiation falling on 9 different direction facing surfaces, for each hour Stores the default sunlit fraction of 20 different wall surfaces, for each hour Stores the default sunlit fraction of 4 different windows. for each hour Loop variable Resistance (L/Îť) U-value Sol-Air temperature Net temperature difference across a surface Loop variable Temperature of ground Heat gain/loss through ventilation Heat produced by all people

CompareResult variables All variables are of type Double and classifier Private, unless stated otherwise: Stores inside temperatures Tin(4) for comparison Net heat flow through roof roofHeat for combined 3 hours Net heat flow through walls wallHeat for combined 3 hours Net heat flow through floor floorHeat for combined 3 hours Net heat flow through glazeHeat windows for combined 3 hours Net heat gain through ventiHeat ventilation for combined 3 hours

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Chapter 1: Background knowledge on steady-state heat loss/gain with solar and wind effects

đ?‘…=

1 đ??ż 1 +∑ + â„Žđ?‘– đ?‘˜ â„Žđ?‘œ

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Section A: Conductive Heat Transfer Heat conduction is the transfer of thermal energy between regions of matter due to a temperature gradient [1]. In fact, it is due to movement of electrons from higher temperature to lower temperature, which is physically describing the transfer. Fourier’s law describes heat conduction through materials, and in general is given by: đ?‘ž = −đ?‘˜âˆ‡đ?‘‡ [1] Where q is heat flux (W/m²), k is a constant and đ?›ťT is the gradient of temperature. A special case of one-dimensional linear conduction turns out to be:

Figure 1: Resistance offered by the wall towards heat flow; after Manz [4]

and is the inverse of the total thermal transmittance of the wall, which is referred to as U-value (W/m²K). In case of multilayer structure, individual resistances are added and then the inverse yields the net U-value, and hence the summation of resistances in eq 5.

đ?‘‘đ?‘‡ [2] đ?‘‘đ?‘Ľ The proportionality constant k is called thermal conductivity and its units are W/mK. It is the rate at which heat is conducted through a material under specific condition, and is also denoted by Îť. Multiplying equation 2 by area perpendicular to direction of heat flow gives total heat, and integrating across the material thickness we get: đ?‘žĚ‡ = −đ?‘˜

đ?‘„=

đ?‘˜đ??´ đ??ż

∆đ?‘‡

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Where kA/L is called conductance (inverse of resistance, R=L/kA) and is extrinsic property. In case of walls, which is exposed to air, the heat is exchanged by convection between air and wall surface [2]. In the process, a thin fluid film is formed on the surface, which offers resistance to the flow of heat [3]. From Newton’s equation of convective heat transfer:

Figure 2: Thermal resistance of multi-layered wall [4]

The conductivity of a material is an intrinsic physical property and has been determined for various substances experimentally [4]. For buildings (i.e. surfaces) which are exposed to the outside environmental conditions, the effect of radiation, wind, heat direction along with surface properties including roughness, absorptivity, geometry etc determine the external surface temperature and film coefficient [5].

đ?‘„ = â„Žđ??´âˆ†đ?‘‡ [4] Where h is convective heat transfer coefficient and the resistance is 1/hA (analogous to electrical resistance R=V/I). Thus, in effect, the net resistance offered by the wall towards heat flow is sequential addition of surface and material resistances (see figure 1). đ?‘‡đ?‘– is inside air, đ?‘‡1 is inside wall surface, đ?‘‡2 is outside wall surface and đ?‘‡đ?‘œ outside air temperatures, while â„Žđ?‘– and â„Žđ?‘œ are surface coefficients at inside and outside surface respectively. The net resistance (in m²K/W) is:

Section B: Sol-air Temperature The concept of the sol-air temperature đ?‘‡đ?‘ đ?‘Ž , was introduced as the equivalent temperature of convective and radiative environment for a surface [6]. It also includes solar radiation [7] and is given by [8] as the equation:

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đ?›źđ??źđ?‘ â„Žđ?‘&#x; đ?‘‡đ?‘&#x; + â„Žđ?‘? đ?‘‡đ?‘œ + [6] â„Žđ?‘œ â„Žđ?‘œ And on simplifying [9], the sol-air temperature

adopted by buildings standards and simulation program (see appendices). EnergyPlus has 5 options to choose from, each being a separate model for calculation. It includes Simple, TARP, DOE-2, MoWiTT and AdaptiveConvectionAlgorithm.

đ?‘‡đ?‘ đ?‘Ž =

đ?›źđ??źđ?‘ + đ?‘‡đ?‘œ [7] â„Žđ?‘œ Where đ?›ź is absorptivity of solar radiation of material, đ??źđ?‘ is total solar radiation (W/m²), â„Žđ?‘&#x; /â„Žđ?‘? is radiative/convective heat transfer coefficient (W/m²K). From Eq 4-5, we know đ?‘…đ?‘œ = 1/â„Žđ?‘œ and therefore Eq 8 becomes: đ?‘‡đ?‘ đ?‘Ž =

đ?‘‡đ?‘ đ?‘Ž = đ?›źđ??źđ?‘ đ?‘…đ?‘œ + đ?‘‡đ?‘œ

The simple option adopts the relation outlined in ASHRAE 2001 [15], which assumes a constant value of â„Žđ?‘œ = 34 for đ?‘Ł ≅ 6.7đ?‘š/đ?‘ and â„Žđ?‘œ = 22.7 for đ?‘Ł ≅ 3.4đ?‘š/đ?‘ . TARP model proposes changes in wind speed with height [14], same as BLAST. DOE-2, MoEiTT and the model developed by Liu and Harris [16] consider full scale experiment with đ?‘Ł10 and power law to derive â„Žđ?‘œ [10].

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Section C: External Film Coefficient (â„Žđ?‘œ ) Numerous researches have been done to obtain an all-encompassing method to calculate external heat transfer coefficient taking into account all variables. A detailed review done by Mirsadegi et.al [10] outlines the implemented methodology in different programs and simulation.

Schaak [17] and Jennings [18] carried experiments with materials of varying roughness. For smooth surfaces it is proposed to use: â„Žđ?‘œ = 10.7 + 4.96đ?‘Ł [13] And for rough surface (only when v<5m/s)

The model by McAdam [11] reports that:

â„Žđ?‘œ = 6.2 + 4.3đ?‘Ł [14] In the present version of REPRO, since the wind speeds are low during simulation period and materials used in theory (EnergyPlus) as well as in practice are rough, equation 14 has been implemented.

đ?‘?

đ?‘Ł [9] â„Žđ?‘œ = 5.678 [đ?‘š + đ?‘› ( ) ] 0.3048 Where v is wind velocity and m, n, p are roughness parameters (see appendices). Various programs implement a linear form of this equation segregated in different wind speed ranges. For instance, CIBSE guide proposes:

In case of surfaces coupled with ground, only conduction is considered. In such cases it is important to determine the depth and temperature of the soil which is in contact. Although ground temperatures are more stable than ambient air, near surface temperatures correlate with the external environment [19]. Khandaker et al [20] investigated soil samples and established the following regression equation at depth of 10cm below ground level-

â„Žđ?‘œ = 4.1đ?‘Ł + 5.8 [10] Manz [4], instead, proposes a relation connecting even temperature as in the case of forced convection: đ?‘‡ 0.7 [11] â„Žđ?‘œ = 7.126đ?‘Ł ( ) 273 However, the most comprehensive system developed is by The Building Loads Analysis and System Thermodynamics (BLAST) developed by wind tunnel experiments by Sparrow et al [12] and combines both the forced and natural convection. Similarly, the model developed by Nusselt and Jurges [13], is in the form: 0.8

đ?‘‡đ?‘” = 6.224 + 0.842 ∗ đ?‘‡đ?‘œ [15] Since the study area resembles that of the current project under investigation, equation 15 is used to calculate the temperature of the ground responsible for floor heat flux. Chapter 2: Introduction to the project and discussion of the given building and selected location

â„Žđ?‘œ = 7.13đ?‘Ł 0.78 + 5.35đ?‘’ −0.6đ?‘Ł [12] Palyvos [14] reviewed major experiments and classified the relations into three major types -linear, -power law and -boundary layer condition. Many of the linear relations derived from other complex correlations have been

Section A: Background of REPRO Numerous programs exist to calculate the energy fluxes and HVAC demand in a [5]

building. Most systems rely on non-steady state heat conduction method which considers the thermal diffusivity and effusivity of the material [4]. This in short is a time dependant function.

An irregular shaped open-plan design is to be assessed for heat transmission. The building is a single storey, 4-meter, structure and is aligned along north-south axis. Each side has a window of height 2m, but with varying width (see figures 3, 4). The building construction detail can be specified in the program, where the user has choice to select from three different types of material.

In preliminary study, a steady state transmission can also help in establishing the performance of the design. The aim of this project is to develop a computer application, called REPRO, which can simulate the steady state heat transmission through a given building design. Following which it can be used to carry out a parametric research on the effects of different variables on the heat flow through the building. For this purpose, users have a choice of entering the hourly environmental data for up to 6 hours and calculating the different heat fluxes through the building elements.

For ease of reference, all elements have been assigned a unique code. Beginning from top-right of the plan, walls are denoted by W followed by the sequence number. Using a similar logic windows are denoted by WIND, floor by F and roof by R. Refer to appendix for detailed element dimensions.

A second program to check for accuracy and validate the results from REPRO has also been developed and is called SINGLEFLUX. Although the core simulation engine, written in Visual Basic, is independent of the designthe main interface is linked to the original building under study. Visual Studio 2012 developed by Microsoft® is used to design and debug the application. To draw comparisons between the two methods (steady and non-steady state thermal transmissions), the developed computer application (REPRO) is checked against EnergyPlus.

Figure 4: Building plan with different elememts labeled

Section C: Location Bangalore (12°N, 77°E), is the capital of the Indian state of Karnataka and is in southern India. The inland city is at a height of 900m and experiences tropical savanna climate (Aw according to Koppen classification [21]). An annual average temperature of 23~25°C is enjoyed by this temperate city.

Section B: Description of Analysed Building

Figure 5: Location of Bangalore [22]

Summer temperatures are highest in May varying from 33°C to 22°C (average). Winters

Figure 3: Plan of building under study

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are coolest in December and ranges from 16°C to 27°C (average) [24]. Hourly average radiation during summer is 472 Wh/m² and in winter 374 Wh/m².

program. The top three open a second set of buttons to view different environmental and building parameters in detail. Under Climate, users can view/modify the outside dry-bulb temperature, wind speed and radiation. Building button allows user to view/modify the construction of the building -namely wall, floor, roof and window apart from viewing architectural drawings. Heat Calculation allows one to view/modify the internal loads and shading on outside surfaces (see Figure 8).

Figure 6: Monthly average climate data for Bangalore [23]

The study has been done using only a representative day of the two season -21st May for summer, -21st December for winter; and the time period of analysis is from 2pm to 4pm. Chapter 3: Development/ Validation/ Application of REPRO/SINGLEFLUX programs for predicting building steady-state heat loss & gain

Figure 8: 'Internal loads and settings' panel

Within each of the building elements, users have option to enter up to three types of construction. After the settings have been checked and the type of construction decided, users need to click Simulate button (found as secondary button under Heat Calculation). A new window is displayed (see figure 9), while in the background, heat fluxes through each building element is calculated. Should the user click simulate without having selected the type, then the settings panel is re-opened, and user asked to choose the type.

Section A1: REPRO Interface and Overview The program basically comprises of three main parts, -the Main Menu (Figure 14), where the users can adjust the building/environmental parameters, -the Simulation Engine, which runs in the background to calculate all types of gains and losses, and lastly -the Results and Comparison section, where the heat quantities are displayed. Additionally, a Help section is also included, which lists some useful information on how to run the program as well as provides key data.

Figure 9: Simulation result window

This window (Figure 9) lets users, individually study the hourly heat fluxes though each building element. On the left edge, a series of buttons are located, each of which prints some result to the centre of the screen. It is important to note here that the button ‘Whole Building’ displays the combined sum of both

Figure 7: REPRO main menu

A welcome screen (Figure 7) greets the user as soon as the program loads. On the very left edge of the main menu is a list of six buttons pertaining to different section of the [7]

internal and environmental heat quantities. A plot of results can be generated by clicking Plot button (Figure 10).

accessed by the user, does all the calculation when initiated. This module is the core feature and executes the following: •

• •

Figure 10: Plot of heat flux contribution from each element

After simulation has been done, the button Compare in the main menu becomes active and can be clicked to study the effect of changing indoor temperature on heat quantity. Clicking this will open a new window (Figure 11) and allows to display either the summer or winter parametric result (top left buttons in Figure 11). Users can exit these windows by pressing the back button.

Assigning default values to the text boxes for ease of user. In this case default values pertaining to Bangalore have been implemented. Reading the data from text boxes and writing them to class variables, which can be used in calculations. Calculating heat gain/loss through the different building elements; namely roof, wall, glazing, floor, ventilation and the combined internal load.

These functions are called by the program during run-time with specific simulation type and the internal temperature, and their return format is an array of type Double. The sequence of command execution as below: • •

• Figure 11: Heat gain/loss as a function of indoor temperature

Most panels have a short description about them on the lower right corner (Figure 8 and 14). Apart from that, Help button opens a new window to explain the different sections of the program and explain the various quantities. Users can also load the default values of Bangalore by pressing the default button, located on the lower left of each panel (Figure 8). To terminate the program, users need to click on Exit located at the bottom left of the main menu.

o o o o o

Section A2: Simulation Engine of REPRO

o

Each window is controlled by a form, wherein the code manages the contents on the window. These forms can only access the results generated by the simulation engine and modify them as required. In fact, only the engine, which is in the form of a separate module (HeatLossGain) and cannot be

Call function; by passing the arguments simulation type and -indoor temperature. Run a loop, which corresponds to the time under study. In this case it is 2pm, 3pm and 4pm for both summer and winter day. Thus, array positions 0-2 links 2,3,4pm summer time; and 3-5 links 2,3,4pm winter time. For each of hour, find the net U-value of the construction, sol-air temperature at its outer surface, temperature difference and finally insert the heat flow (kWh) in an array (see table 1). Return this array. đ?‘… = đ?‘Ąâ„Žđ?‘–đ?‘?đ?‘˜đ?‘›đ?‘’đ?‘ đ?‘ /đ?‘?đ?‘œđ?‘›đ?‘‘đ?‘˘đ?‘?đ?‘Ąđ?‘–đ?‘Łđ?‘–đ?‘Ąđ?‘Ś đ?‘ˆ = đ?‘…đ?‘ đ?‘– + đ?‘… + đ?‘…đ?‘ đ?‘œ(đ?‘Ąđ?‘–đ?‘šđ?‘’) đ?‘‡đ?‘ đ?‘œđ?‘™ = đ?‘†đ?‘œđ?‘™đ?‘Žđ?‘&#x;đ?‘…đ?‘Žđ?‘‘(đ?‘Ąđ?‘–đ?‘šđ?‘’, đ?‘‘đ?‘–đ?‘&#x;đ?‘’đ?‘?đ?‘Ąđ?‘–đ?‘œđ?‘›) ∗ đ?‘Žđ?‘?đ?‘ đ?‘œđ?‘&#x;đ?‘?đ?‘Ąđ?‘–đ?‘Łđ?‘–đ?‘Ąđ?‘Ś ∗ đ?‘…đ?‘ đ?‘œ(đ?‘Ąđ?‘–đ?‘šđ?‘’) ∗ đ?‘†â„Žđ?‘Žđ?‘‘đ?‘–đ?‘›đ?‘”đ??śđ?‘œđ?‘’đ?‘“đ?‘“(đ?‘Ąđ?‘–đ?‘šđ?‘’) ∆đ?‘‡ = đ?‘‡đ?‘œđ?‘˘đ?‘Ą + đ?‘‡đ?‘ đ?‘œđ?‘™ − đ?‘‡đ?‘–đ?‘› đ?‘„(đ?‘Ąđ?‘–đ?‘šđ?‘’) = đ?‘ˆ ∗ đ??´ ∗ ∆đ?‘‡/1000 đ?‘„đ?‘&#x;đ?‘Žđ?‘‘ (đ?‘Ąđ?‘–đ?‘šđ?‘’) = đ?‘†đ?‘œđ?‘™đ?‘Žđ?‘&#x;đ?‘…đ?‘Žđ?‘‘(đ?‘Ąđ?‘–đ?‘šđ?‘’, đ?‘‘đ?‘–đ?‘&#x;đ?‘’đ?‘?đ?‘Ąđ?‘–đ?‘œđ?‘›) ∗ đ?‘Žđ?‘&#x;đ?‘’đ?‘Ž ∗ đ?‘Ąđ?‘&#x;đ?‘Žđ?‘›đ?‘ đ?‘šđ?‘–đ?‘Ąđ?‘Ąđ?‘Žđ?‘›đ?‘?đ?‘’ ∗ đ?‘†â„Žđ?‘Žđ?‘‘đ?‘–đ?‘›đ?‘”đ??śđ?‘œđ?‘’đ?‘“đ?‘“

[16] [17] [18] [19] [20] [21]

Table 1: Logical sequence of program command

•

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Convective heat transfer (Rso), radiation (SolarRad) and shading coefficient (ShadingCoeff) are all time dependent and keep changing every hour. To

account for this, an array for each is created which stores hourly value. Their values are calculated and stored in the array when the program calls the InputData subroutine.

REPRO which gave a total quantity through that type. In brief, users can find the heat flux through each wall element separately. The application was written in visual basic and designed in Visual Studio 2012, same as REPRO.

The advantage of this algorithm is that the main engine remains independent and modular. In case the program is upgraded, or new features added, this core can essentially remain the same. Only new call statements must be introduced to link all parts. For instance, if the program were to extend the study period by few more hours, then, only the array size and number of call statements need to be adjusted to account for the change.

Its interface (Figure 12) is simple and straightforward consisting of only one form. On the left are options to select the surface which one wants to calculate flux through, and in the centre the results are displayed. The selection of any element, in fact, loads its default values in the panel called ‘Surface Property’ where the user can assess the construction and weather data, as well as select the range of inside temperature (Figure 13). Once that is analysed, the calculate button must be clicked, located on the bottom of the display panel. This displays the heat flux as a function of indoor temperature.

Once simulation is done for one type, the results are held in RAM to be accessed by any other method. This is used by the compare window to plot the changes. Unless the simulation is not run, the array storing the heat quantities is not initialized (since the module HeatLossGain is never called) and cannot be accessed. In case the user changes one or any data in the text box, Simulate has to be clicked again to fill the arrays with modified heat fluxes. As additional part of the study, this program is compared to energyplus in terms of both the results produced and algorithm used. To establish similar grounds, environmental values from weather file of Bangalore [25] is used for both REPRO and EnergyPlus simulation. Sunlit fraction (or shading coefficient) generated from EnergyPlus is also fed into REPRO.

Figure 13: SINGLEFLUX control panel

Section B: SINGLEFLUX interface

Since the environmental data is static in this application, the user must be able to specify all input explicitly, including outside temperature, wind speed, radiation in that direction and shading coefficient apart from building data. Although this may appear as a drawback, the advantage is that it allows for exact calculations to be made without depending too heavily on programming capability and recursive algorithm. Figure 12: SINGLEFLUX interface

The calculation logic is as follows:

A second program called SINGLEFLUX was developed to corroborate REPRO. The main feature of this application is the ability to display individual surface heat flux, unlike

•

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Read the values from the text boxes and store them in the program variables during runtime.

•

đ?‘…đ?‘ đ?‘œ •

•

•

•

used, the variable scope terminates. In this case the user has to press calculate again if the values are revised.

After reading the text boxes, calculate the U-value and Tsol-air for the surface under study. Equation and values used in REPRO is repeated here for Rso and Rsi to maintain consistency. đ?‘…đ?‘ đ?‘– = 0.13 1 = 6.2 + (4.3đ?‘Ł)

Preliminary checks of REPRO involve locating errors in scripting and debugging. Further validation is done element wise and compared with SINGLEFLUX. The process used for walls is described below, other elements were corroborated using a similar methodology:

[22] [23]

Run a loop for each of the indoor temperature, and in each iteration call by value the function: Heat<Element>, by passing the U value, area and temperature difference as arguments This function is in a separate module called CalculateHeatValues. The separation, as explained in REPRO, allows for faster debugging and upgrading of versions. Moreover, parts of program can be reused for other tasks. The function returns the product of the passed arguments. In case the function is HeatGlazing it returns the sum of conductive gain (Eq 17, without dividing by 1000) and radiative gain (Eq 18). Format and print the result on screen

• •

• •

• •

Select one summer time, e.g.4pm and note the net heat gain from walls. Also note all environmental and building parameters used for simulation, e.g. construction type, outside temperature etc. Radiation and sunlit fraction has been used from external source and hence the default values are same for both program. In SINGLEFLUX, check heat quantity for each of the 20 walls and note the result (convert to kW). After adding them compare with REPRO value. Repeat this for some other time In case they are same for both cases, move on to next element.

The process is time-consuming, but helps in removing glitches, for instance missing formula coefficient etc.

Although the logic is similar to REPRO, it differs by the use of memory. In case of REPRO the results are held in RAM for reuse, unlike SINGLEFLUX where once

Figure 14: Detailed view of Main Menu, showing the different areas of user interface

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Section C: Parametric Study with REPRO

Winter radiation (W/m²) 0, 0, 0, 0, 310, at 4pm – in order 590, 520, 150, N,NE,E,SE,S,SW,W,NW, 315 Horizontal

The following parameters were studied to observe the impact on building heat loss/gain • • • • • •

Table 2: Meteorological data used in study

Ventilation rate Glazing U-value Wall material and depth Roof material and depth Floor material and depth Indoor air temperature

For building parameters, the local building construction practices and design parameters were noted. For walls, the typical material used for construction is brick which is usually 2-brick thick (0.2m) with mortar cement. New construction also uses concrete blocks of varying depth – most popularly 0.3~0.5m. Average brick conductivity is around 0.6~1.0 W/mK, while that of concrete is 1~1.8 W/mK [26]. Although wall insulation is not common in this region, nevertheless it is studied here to assess the nature of heat flux. Three types of wall used in this study include EPS foam (0.2m,0.035W/mk), brick wall (0.3, 0.84W/mk) and concrete wall (0.5m, 1.63W/mk).

Methodology For each study, the values of all variables were kept constant (shown bold in table 3) except the parameter under observation. 21st May was selected for summer study as the month records highest temperatures, while 21st December was selected for winter. Environmental condition was assumed constant over an hour. Three hours per day (2pm, 3pm and 4pm) were simulated and added together to give summer/winter data. The meteorological and building data is shown in table 2 and 3.

Building Parameters Air change rate (ac/hr) 2, 3, 4 Glazing U-value 0.15, 1.8, 2.6 (W/m²K) Glazing transmittance 0.5 Wall thickness (m) 0.2, 0.3, 0.5 Wall conductivity 0.035, 0.84, (W/mK) 1.63 Wall absorptivity (%) 0.4 Roof thickness (m) 0.4, 0.6, 0.8 Roof conductivity 0.04, 0.1, 0.4 (W/mK) Roof absorptivity (%) 0.6 Floor thickness (m) 0.3, 0.5, 0.7 Floor conductivity 0.14, 0.42, 1.13 (W/mK) Internal temperature °C 20, 21, 22, 23, 24 Lighting load (W) 64 Equipment load (W) 50 Occupancy (no#) 12 Body heat rate (W) 100

Meteorological Parameters Summer hourly 32.6; 34.0; 33.0 temperature (°C) Winter hourly 25.6; 26.0; 24.7 temperature (°C) Summer hourly 4.7; 4.2; 3.8 windspeed (m/s) Winter hourly windspeed 2.2; 2.1; 1.9 (m/s) Summer radiation (W/m²) 180; 0; 0; 0; 0; at 2pm – in order 165; 415; 420; N,NE,E, SE,S,SW, 865 W,NW, Horizontal Summer radiation (W/m²) 190, 0, 0, 0, 0, at 3pm – in order 260, 560, 530, N,NE,E,SE,S,SW,W,NW, 690, Horizontal Summer radiation (W/m²) 200, 0, 0, 0, 0, at 4pm – in order 295, 615, 575, N,NE,E,SE,S,SW,W,NW, 470, Horizontal Winter radiation (W/m²) 0, 0, 0, 46, 445, at 2pm – in order 590, 385, 0, N,NE,E,SE,S,SW,W,NW, 690 Horizontal Winter radiation (W/m²) 0, 0, 0, 0, 395, at 3pm – in order 640, 510, 80, N,NE,E,SE,S,SW,W,NW, 525 Horizontal

Table 3: Building data used to simulate heat flow

Similarly, for roof the colloquial approach has been timber but modern buildings implement concrete. Insulation on roof is used in many buildings for multiple reasons. The materials in this study are insulation board with timber framing (0.4m, 0.04W/mk), light concrete (0.6m, 0.1W/mk) and brick batting with screed having a combined effect of 0.8m and 0.4W/mK. Floors are usually compacted with [11]

broken bricks/stone chips followed by earth and polished with a layer of screed. Many places also have timber parquet. This study uses wooden floor (0.3m, 0.14W/mK), screed (0.5m, 42W/mK) and dense concrete (0.7m, 1.13W/mK).

which can be found by clicking on plot in the simulation result window (Figure 9). The chart produced by REPRO only compares heat flow through the building fabric, for a detailed analysis including ventilation gain, users need to navigate to compare and read the values directly from the printed table (Figure 18). After each simulation, heat loss/gain through the element under study at different indoor temperatures (both summer and winter) is noted from the tabulated window and shown in Figure 19.

Saint Gobain’s Indian catalogue and technical datasheet is used as a guide to determine window type, since it has a major market share in India. 3 products from the company brochure have been used here single glazed (2.6 W/m²K), double glazed standard windows (1.8 W/m²K) and highperformance triple glazed window (0.15 W/m²K). Being a temperate climate, the suggested ventilation rate is 3~4 ac/hr. The study is conducted using 2,3 and 4 ac/hr. Since the program is capable of storing 3 vales of data for each parameter, the methodology involves simulation, by changing the type for each run (Figure 15 and 16). After each run, the 3-hour total heat flow through the element was noted (Figure 17), along with the total gains in the building.

Figure 17: Result window with hourly and cumulative wall heat displayed

Figure 18: Tabulated result of cumulative heat gain by each element Figure 15: Parameter adjustment panel

To measure the rate of change of contribution of that element to the total building heat gain/loss, a graph was plotted between element property and its percentage contribution in the total building heat flow (see Figure 23). A linear equation, of the form y=mx+c, is plotted for each element and the coefficients shown in table 4. Where y is the %contribution of the element and x is the physical parameter under study. In all these cases indoor temperature was assumed constant at 20°C.

Figure 16: Under settings, select the type for simulation

A graph was plotted between each parameter vs its contributing heat gain/loss (Figure 20). Each building element contributes differently to the total heat flow; a pi-chart of percentage contribution from each type (base construction) is plotted for both summer and winter time and shown in Figure 21 and 22. REPRO is also able to produce this chart,

Results and Discussion In both Figure 20 and 23, the parameters are sequentially shown from graph A through H, where: A-effect of air change rate, B-effect of glazing thermal transmittance (U-value), Ceffect of wall thickness, D-effect of wall conductivity, E-effect of roof depth, F-effect of [12]

roof conductivity, G-effect of floor depth and H-effect of floor conductivity on steady state heat flow measured as sum of hourly gain/loss. Figure 19 (graphs A-P) is a plot of heat flow through a building parameter as a function of both the property of that element and the internal temperature. Each element is evaluated separately for summer and winter and iso-lines are drawn for points connecting same heat flow (see appendix for absolute values).

causes change in heat flow. In general, the plotted iso-curve graphs suggest that as indoor temperature increases, heat flow decreases for both summer and winter; which can be seen by shift in color towards the cooler spectrum. In, fact during winters almost all graphs show close to 0 heat flow. This is due to the decreased heat difference between inside and outside. These curves help in optimizing a design when a particular condition is constraint. For instance, if the cost of conditioning the space is fixed, then the design can be optimized between indoor temperature and material selection by following the constrained color

Vertical color bands in Figure 19 indicate that heat flow is relatively constant over different indoor temperatures, while horizontal isolines suggest that only the material property

Figure 19: Heat gain through element as a function of indoor temperature and element property

[13]

25

30

20

25

15 10

15 10 5

0

3 4 Air change ac/hr

0 0.15 1.8 2.6 Glazing U-value W/m²K

Graph A

0.2

Graph B

Wall conductivity vs Wall heat gain

Heat kWh

25 20 15 10

Roof conductivity vs Roof heat gain

5

12

4

10

Heat kWh

30

3 2 1 0

Graph D

0.04 0.1 0.4 Conductivity W/mK Graph F

Floor thickness vs Floor heat gain

Floor conductivity vs Floor heat gain 14 12

Energy kWh

8

Energy kWh

4

0.6 0.8 Roof thickness (m)

Graph E

10

6

0 0.4

0.035 0.84 1.63 Conductivity W/mK

8

2

5 0

0.3 0.5 Thickness (m)

Graph C

Roof thickness vs Roof heat gain

35

Wall thickness vs Wall heat gain

20

5 2

Heat kWh

Heat kWh

45 40 35 30 25 20 15 10 5 0

Heat kWh

Heat kWh

Glazing U-value vs Window heat gain

Ventilation rate vs Ventilative heat gain

6 4 2

Legend

10 8

Summer Winter

6 4 2 0

0

0.14

0.3 0.5 0.7 Floor thickness (m)

0.42

1.13

Conductivity W/mK

Graph G

Graph H

Figure 20: Heat flow through different elements w.r.t their property

Element contribution in Summer 7.04 3.38

Element contribution in Winter 8.17

4.8 4.97

26.16

4.97 37.18

25.7 27.22 28.51

21.9 Ventilation

Glazing

Wall

Roof

Floor

Ventilation

Miscellaneous

Figure 21: %contribution from each building element-summ.

Glazing

Wall

Roof

Floor

Miscellaneous

Figure 22: %contribution from each building element (winter)

[14]

%of ventilation gain

%of wall conduction gain

%of glazing gains

45%

36%

30%

33%

40% 27%

35%

30%

30%

27%

24%

25%

24% 21%

20%

21%

15% 1.5

2

2.5 3 ac/hr

3.5

4

4.5

18%

18% 0

0.7

1.4 2.1 U-value

Graph B

Graph A

%of wall conduction gain 8% 6% 5% 4%

20%

3% 2%

10%

1% 0%

0% 0

0.5 1 1.5 wall conductivity W/mK

Graph D

2

0.6

%of roof conduction gain 18% 16% 14% 12% 10% 8% 6% 4% 2% 0%

7% 30%

0.2 0.3 0.4 0.5 wall thickness

Graph C

%of roof conduction gain

40%

0.1

2.8

0.2

0.4

0.6 0.8 1 roof thickness (m)

Graph E

0

0.1 0.2 0.3 0.4 roof conductivity

0.5

Graph F

%of floor conduction gain

%of floor conduction gain

12%

16%

10%

14%

Legend

12%

8%

10%

6%

8%

4%

6%

Summer Winter

4%

2%

2%

0% 0

0.2 0.4 0.6 floor thickness (m)

0.8

Graph G

0% 0

0.3 0.6 0.9 floor conductivity W/mK

1.2

Graph H

Figure 23: Rate of change of contribution to total building heat by individual parameter

1 2 3 4 5 6 7 8

Ventilation rate Glazing U value Wall thickness Wall conductivity Roof thickness Roof conductivity Floor thickness Floor conductivity

Summer m c 0.0791 0.1281 0.0152 0.1914 -0.3781 0.3789 0.2006 0.0382 -0.0589 0.0716 0.2756 0.0044 -0.1334 0.1430 0.1209 0.0137

Table 4: Coefficient of linear relation of type y(%)=mx(element) + c

[15]

Winter m 0.0649 0.0097 -0.3768 0.2066 -0.0841 0.3801 -0.0965 0.0884

c 0.0632 0.2676 0.3928 0.0433 0.1036 0.0085 0.1022 0.0086

band until a point where the balance between material property and indoor environment is met. It can further be extended to include a 2nd constraint in the form, say, indoor condition. In this case, an isotherm intersection with the iso-curves will give a region of material property which can achieve the desired state.

The next element to have a radical impact is the roof conductivity (graph F-Figure 23) With a winter slope of 0.38, decreasing the conductivity by 1 W/mK will decrease its participation in the total heat gain by 38%. A similar trend is shown by wall conductivity (graph D-Figure 23). Floor properties impact lesser than wall and roof, but the least is that of glazing (see table 4). With an increase of 1 W/mK U-value, the window contributes 1.5% more towards the total building gain (summer). Although the absolute value could be much higher (~5kWh), the change in its contribution is very less. A highly improved window would be needed to reduce its percentage participation. In fact, while ventilation does contribute majorly to the building heat flow, a change in the air supply by 1 or 2ac/hrs will have no different percentage contribution.

The heat flow in case of summer varies greatly, we observe, from Figure 20, that all parameters except for the element depth/thickness, have a positive correlation with heat gain. Increasing any parameter leads to increased heat gain through that element. Moreover, the slope for summer and winter is different suggesting that not only the building parameter but also the environmental factors effect heat flow. Ventilation contributes to highest ratio of building heat gain, 37% in summer (Figure 21), followed by gains from wall and glazing. Gains from walls are higher than windows in summer, while during winter they are almost equal. Considering the area of these elements (wall-235 m², window-39.5m²), the heat flux through window is significantly higher than walls, owing to its transparent nature.

Conclusion The design requires optimization for either summer or winter climate. In case if it is summer, priority should be given to wall properties first, since their improvement would lead to reduced contribution of walls in building heat flow. This should be followed by decreasing roof conductivity, then floor properties and finally glazing. Since in most cases fresh air requirement is stipulated by law, ventilation loss/gain can be decreased by having other auxiliary systems.

Roof contributes least to the total gains, primarily due to its thick depth. Even though it is exposed to solar radiation, gains from roof is less than that of the floor. Couple of reasons can be associated with it, 1-higher ground surface temperature than air temperature, 2-lower U-value of roof.

In case where the optimization is for winter season, priority should be given to roof conductivity. Adjustment of wall properties is next, followed by floor properties. During winters, glazing although contributes to about 28% of building heat gain, a change in its Uvalue will not have much impact in its percentage share, the slope being ~0.01. Rather ventilation should be adjusted which has a slope of ~0.06 (see table 4).

Owing to the different physical quantities being parameterised, absolute values of heat quantities cannot be compared. Instead it will be more appropriate to compare the heat flow as a function of their specific property. Also, in case where optimization is needed in the design, it will be noteworthy to study these linear functions (Figure 23). It is striking to note that despite the fact that walls play 2nd major role in building heat flow, its contribution changes drastically when its properties are changed. The slope of its thickness curve (graph C-Figure 23) for both summer and winter is ~-0.38, suggesting a drastic reduction in heat flow contribution by slight increase of wall thickness (38%)

Chapter 4: Comparison of REPRO with commercial software Results from REPRO are compared with EnergyPlus to understand the behaviour and differences between the two programs. The objective is to establish a relationship factor between the two program, allowing for approximation of results. [16]

•

Section A: Setting up EnergyPlus and REPRO Available commercial packages use nonsteady state heat transmission algorithm to calculate heat fluxes for several reasons. Most importantly to represent the real material behaviour which exhibits time dependant property defined by thermal diffusivity. Also, the outdoor environmental conditions are not stable leading to varying fluxes on the surface. To circumvent this issue and set up other physics engine, following configuration is used in the model: •

•

•

•

•

•

•

•

• •

Heat balance algorithm is set to Conduction Transfer Function to consider only sensible heat and ignore the moisture storage or diffusion in the construction elements. Timestep is set to 1 step per hour, i.e. at an interval of 60minutes. This makes the heat flow constant over a long period of time. Run period is set to 21st of May and December, with a compact schedule entered such that the building will be operational only from 2pm to 4pm. Monthly ground temperature is set to 33.75 for May and 27.65 for December. This is calculated by using equation 15, with ‘To=3hour average of outside temperature’. NoMass materials are defined for surfaces, with roughness set to MediumRough and properties same as in table 3. No-mass material removes the scope for heat storage and thermal lag since both, diffusivity and effusivity, of the material are set to 0. In case of NoMass material, EnergyPlus does not allow thickness. To solve this problem, instead of thickness, thermal resistance is adjusted in each case so that it has the same effect as increased/decreased depth of surface. Glazing material is set to have transmittance as 0.5, thickness 0.01m (10mm) and their conductivities adjusted to have net U-value as in table 3. Gains by people is ignored, since people contribute to both sensible and latent heat, which has not been considered in REPRO. A fixed quantity of 1.2kWh will instead be added in the final calculation.

•

•

•

Similarly for other internal gains (lighting and equipment), which is a constant energy source independent of the building or environmental condition – fixed quantity of 114kWh is added. Ventilation is set to natural which ignores the efficiency of the system as well heat gains by fan. Heat flow is dependent on the temperature difference across the building surfaces, for this study the internal air temperature was assumed to be constant at 20°C. To maintain constant zone air temperature in EnergyPlus, an HVAC template is created with ideal load system. The heating and cooling setpoint temperatures are set to 20°C, making sure the zone is always conditioned to a constant value. EnergyPlus uses total radiation falling on a surface to calculate heat exchange, moreover CIBSE guide does not specifically provide information pertaining to the study area. Radiation intensity from weather file is used instead. Other environmental parameters were also modified due to the use of location specific weather data: Modified Meteorological Parameters Summer hourly 32.2675; 32.81; temperature (°C) 33.0 Winter hourly 25.6; 25.6525; temperature (°C) 25.175 Summer hourly 0.665; 0; 0 windspeed (m/s) Winter hourly windspeed 2.4375; 2.1475; (m/s) 1.995 Summer radiation (W/m²) 196, 196, 196, at 2pm – in order 212, 291, 316, N,NE,E, SE,S,SW, 271, 197, 509 W,NW, Horizontal Summer radiation (W/m²) 179, 179, 179, at 3pm – in order 179, 278, 366, N,NE,E,SE,S,SW,W,NW, 344, 226, 495 Horizontal Summer radiation (W/m²) 153, 153, 153, at 4pm – in order 153, 227, 396, N,NE,E,SE,S,SW,W,NW, 422, 291, 452 Horizontal 35, 35, 35, 36, Winter radiation (W/m²) 36, 36, 36, 35, at 2pm – in order 68

[17]

N,NE,E,SE,S,SW,W,NW, Horizontal Winter radiation (W/m²) at 3pm – in order N,NE,E,SE,S,SW,W,NW, Horizontal Winter radiation (W/m²) at 4pm – in order N,NE,E,SE,S,SW,W,NW, Horizontal

23, 23, 23, 23, 23, 23, 23, 23, 45 9, 9, 9, 9, 9, 9, 9, 9, 19 Figure 26: Modify radiation values on REPRO

Table 5: Modified meteorological parameters for comparison

Section B: Methodology

Environmental data in REPRO is adjusted to match that of EnergyPlus. •

To measure the conductive heat gain through walls, roof and floor, Surface_Average_Face Conduction_Heat_Transfer_Energy is requested as output. The sum of all surfaces (W00 to W19) gives the total heat flow contributed by the walls. For glazing, the variable Zone_Windows_Total_Heat_Gain_ Energy, represents the best form of heat transmission since it does not consider the effect of re-radiation by the window surfaces. It only accounts for transmitted solar radiation, convective heat flow, near IR and short-wave radiative gains. Energyplus defines this variable as ‘sum of the solar and conductive gain to the zone from all windows’. Ventilation gains are measured by Zone_Ventilation_Sensible_Heat_Gain_Ene rgy. This is the heat gain occurring when the ventilation air temperature is higher than zone air temperature, and only sensible heat gains are considered.

Select Climate on the main menu, located as the first button on the primary list. Followed by D.B.Temp, which appears as the first button on the secondary list (Figure 24). Change the temperature as in table 5.

Figure 24: Modify outdoor temperature on REPRO

•

Modify wind speed by clicking, the second button on the secondary list, -wind (Figure 25).

After each simulation, the sum of heat flow between the period 2pm to 4pm is noted for both summer and winter time. This is simultaneously processed for both REPRO and EnergyPlus, and the heat flow contributed by the parameter under study is plotted using MS Excel®. The difference between the two application is also recorded. Section C: Results and Discussion Figure 27, graphs A through H is a plot of the heat gain (from the parameter under study) with respect to the change in the parameter value. In each graph summer and winter data of both REPRO and EnergyPlus is plotted for comparison. To understand the relation, it is necessary to analyse the relative change in output from each program, hence the difference between the two for each parameter under study is also noted.

Figure 25: Modify wind speeds on REPRO

•

Lastly adjust the radiation rose on REPRO to match table 5. This involves selecting time for each rose and changing both the summer and winter radiation values (Figure 26).

[18]

40

14

35

12

30

Heat kWh

25 20 15

Effect of Wall thickness 30 25 20

10 8

15

6

10

4

5

2

0

10 5

0 1.5

2 2.5 3 3.5 4 Ventilation rate Ac/hr

4.5

Graph A 35

0 0

1 2 Glazing U-value W/m²K

3

Graph B

Effect of Wall conductivity

0

Effect of Roof conductivit

10

18

25

8

15

15

6 4

12 9 6

10

2

3

5

0

0

0

-2 0

0.5 1 1.5 Wall conductivity W/mK

2

Graph D

-3 0.2

0.4 0.6 0.8 Roof thickness (m)

Graph E

1

0

0.1 0.2 0.3 0.4 0.5 Roof conductivity W/m²K

Graph F

Effect of Floor conductivit

Effect of Floor thickness 10 9 8 7 6 5 4 3 2 1 0

14 12

Heat kWh

Heat kWh

10 8 6 4 2 0 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Floor thickness (m)

Graph G

0

0.2 0.4 0.6 0.8 1 Floor conductivity

1.2

Graph H

Legends: ●REPRO summer ▲EnergyPlus summer ●REPRO winter ▲EnergyPlus winter Dashed line – Trendline for REPRO Solid line – Trendline for EP Figure 27: Heat flow w.r.t different elements

Ventilation Rate Glazing U-value Wall thickness Wall conductivity Roof thickness Roof conductivity Floor thickness Floor conductivity

0.6

21

30

20

0.2 0.4 Wall thickness (m)

Graph C

EFfect of Roof thickness

12

Heat kWh

Heat kWh

Effect of Glazing Uvalue

Heat kWh

Heat kWh

16

Heat kWh

Effect of Ventilation rate

45

y(diff)=mx(REPRO)+c m c 0.1417 -0.4485 0.9143 -0.8723 0.2792 2.2727 0.6447 -0.1616 0.9812 -0.0536 0.9335 0.1096 0.3241 -0.7537 0.3099 -0.5904

Table 6: %deviation of EnergyPlus from REPRO

[19]

%Deviation from REPRO Summer Winter 12.90% 10.01% 85.46% 61.65% 60.25% 58.84% 55.31% 93.55% 106.97% 93.65% 109.62% 20.35% 0.11% 20.55% -0.22%

Ventilation heat differenc 6

12

10

3 2 1

Difference kWh

10

4

8 6 4 2

5

Graph B

10

Difference kWh

20

5

0

5 10 15 20 25 30 REPRO wall gain (kWh) function of conductivity

8 6 4

Graph D

0 0

3 6 9 12 REPRO roof gain (kWh) function of thickness

Graph E

15

20

25

30

Roof heat difference 18 16 14 12 10 8 6 4 2 0 0

5 10 15 20 REPRO wall gain (kWh) function of conductivity

Graph F

Floor heat difference

Floor heat difference 4 3.5 3 2.5 2 1.5 1 0.5 0 -0.5 -1

2.5

Difference kWh

2

Difference kWh

10

Graph C

2

0

5

REPRO wall gain (kWh) function of thickness

Roof heat difference 12

10

0

Difference kWh

Wall heat difference 25

15

4

0 3 6 9 12 15 REPRO window gain (kWh)

REPRO ventilation gain (kWh) Graph A

6

0

-2

10 15 20 25 30 35 40

8

2

0

0

Difference kWh

Wall heat difference 12

Difference kWh

Difference kWh

5

Window heat difference 14

1.5 1 0.5 0 -0.5 0

3 6 9 REPRO floor gain (kWh) function of thickness

Graph G

0

5 10 15 REPRO floor gain (kWh) function of conductivity

Graph H

Figure 28: Difference between REPRO and EP w.r.t heat gain of element from REPRO

Figure 28, graphs A through H is a plot of the difference between the two programs w.r.t heat gain/loss by REPRO. Both the summer and winter data have been plotted on the same graph. A line connecting the points, of the form y=mx+c, is drawn and its coefficient noted. Here y is the difference of heat flow between the programs (REPRO-EnergyPlus) and x is the absolute heat flow through that element as calculated by REPRO (Table 6). Again, since deviation is also a function of initial heat quantity, a percentage difference

is calculated w.r.t REPRO (% = Table 6.

đ?‘…đ??¸đ?‘ƒđ?‘…đ?‘‚−đ??¸đ?‘ƒ đ?‘…đ??¸đ?‘ƒđ?‘…đ?‘‚

) in

From Figure 27, we observe that except for gains through ventilation and floor, all other elements show increasing divergence from REPRO as heat flow increases, either by decreasing element thickness or increasing its conductivity. In fact, the winter trend of REPRO is almost similar to summer trend of EP (EnergyPlus). This higher heat fluxes as calculated by REPRO is persistent with all [20]

variables, and we see that divergence is small when heat fluxes are small for both programs. Increasing any condition leads to significant difference during summer, while in winter the difference is quite less.

The main difference between walls and roof lies in the fact that the convective heat transfer coefficient is different in different direction and thus will have varying surfaces resistances for walls and roof. Differences between REPRO and EP lies in the fact that while Eq. 14 was implemented in REPRO, the model used in EP was DOE-2. A comparison of the equation variable is shown below:

For the roof (graph E-F, Figure 27), summer and winter trend of EP and winter trend of REPRO are almost similar, while summer trend is steeply increasing. Heat fluxes through wall also show higher divergence in case of summer. It can be deduced that when temperature difference across the surface is high (summer average đ?‘‡đ?‘–đ?‘› − đ?‘‡đ?‘œđ?‘˘đ?‘Ą ≅ 8°đ??ś, while winter average đ?‘‡đ?‘–đ?‘› − đ?‘‡đ?‘œđ?‘˘đ?‘Ą ≅ 5°đ??ś) the heat flux through the element as calculated by REPRO is significantly higher than EP. In cases where the temperature difference is less, both programs give comparable results.

REPRO EP (DOE-2)

â„Žđ?‘œ = 6.2 + 4.3đ?‘Ł

[24]

â„Žđ?‘œ = 11.58 + 6.806đ?‘Ł

[25]

Thus, the surfaces when analysed in REPRO will have a different convective heat transfer coefficient than EP, resulting in higher gains. Other factors which produces a lower EP estimate are:

Each building element also shows different degree of divergence and can be seen by the slope of graphs A-H in Figure 28, or Table 6. Again, we see that ventilation has the least slope suggesting that the results from both programs are similar to a large degree, and not much deviation is observed in EP with increasing heat fluxes as shown by REPRO. Heat fluxes through floor is next, with slope ~17°. Wall follows next with slope of around 20°. In case of roof and glazing the slope is nearly 45°, it follows that with every kWh increase in heat flux calculated by EP, REPRO will give double the difference from EP as before.

• • • •

•

The effect of wind direction on the building Re-radiation by the surfaces leading to potential loss of heat. Effect of edge loss Effect of humidity, which has not been taken into account in REPRO. In fact since only sensible heat is requested from EP, the results show quite less heat fluxes. Time delay effect of heat transmission

Chapter 5: Specific Conclusions and Recommendations Drawn from the Project

The difference between the two program is divergent in nature in absolute terms, while relatively each element has different participation. In summers, for ventilation gains, and gains through floor, REPRO estimates 20% higher than values from EP. Nearly 60% higher estimates in case of walls and glazing. While in case of roof the difference is staggering 90% more than EP. In winter, floor gains from REPRO estimate less than 1% higher than EP, while for walls it remains the same i.e. around 60% higher than EP. It is most surprising to note that roof gain estimates from REPRO are more than double than EP. In fact, from graph E-F, Figure 27, EP estimates that the roof will lose heat to the outside. Contrary to REPRO which estimates heat gain.

Until the mid-1960s only simple hand calculation methods were available for calculating energy use in buildings. A slight advanced form of the methodology is adopted in REPRO, which although useful when computational resources are limited and expensive, it simplifies and neglects some important factors such as transient thermal storage in building materials, time dependent heat transfer etc. and the fact remains that the actual building performance is different from REPRO. After comparing with commercial softwares, it needs to be calibrated to account for the differences. In this case, REPRO needs additional models to take into account the loss/gains from time-delay actions, differential heat transfer coefficients and any [21]

other correction factors. Introduction of a second-degree polynomial as a function of temperature difference across the surface could potentially help in decreasing the high estimates by REPRO. Which in case of EnergyPlus is quite less.

absolute heat quantities the case may be different. In short, the idea is to use computational power of visual basic in preliminary building heat flow calculations to help in early stages. When the design approaches a certain complexity with multiple elements to consider it is better to use commercial products or introduce correction factors in REPRO.

A second comparison is needed with another commercial software, e.g. TRANSYS to see the effect of various heat calculation algorithms. Presently, REPRO is good for estimating loads for short duration, or for relatively constant outdoor conditions which would mimic steady state transfer. Moreover, we have observed that the accuracy higher in case of low temperature difference between indoors and outdoors.

References

[1]

J. Meseguer, I. Pérez-Grande and A. Sanz-Andrés, Spacecraft Thermal Control, Woodhead Publishing Limited, 2012. [2] R. McMullan, Environmental Science in Building, 2018. [3] R. Karwa, Convective Heat Transfer, 2016. [4] H. Manz, Building Physics, 2014. [5] K. A. Ohlsson, R. Ostin and T. Olofsson, “Step-transient method for measurement of the heat transfer coefficient at surfaces exposed to simulated building outdoor environments using the sol-air thermometer,” Journal of Building Physics, 2018. [6] T. Olofsson, K. A. Ohlsson and R. Östin, “Measurement of the environmental temperature using the sol-air thermometer,” Energy Procedia, 2017. [7] C. Mackey and L. Wright, “Summer comfort factors as influenced by the thermal properties of building materials”. [8] K. Rao and E. Ballantyne, “Some investigations on the Sol-Air temperature concept,” Division of Building Research Technical Paper No. 27. [9] ISO Switzerland., “Thermal insulation Building elements - In-situ measurement of thermal resistance and thermal transmittance,” 2014. [10] M. Mirsadeghi, D. Cóstola, B. Blocken and J. Hensen, “Review of external convective heat transfer coefficient models in building energy simulation programs: Implementation and uncertainty,” Applied Thermal Engineering, 2013. [11] W. McAdams, “Heat Transmission”. [12] E. Sparrow, J. Ramsey and E. Mass, “Effect of finite width on heat transfer and

Similarly, even when results are compared between different commercially available softwares, there is difference. This is due to the implemented algorithm and transfer coefficients in each program. In such cases the simulation results are corroborated with actual building measurement on site, to determine the correction factors. During initial design stages and preliminary building form finding exercises, REPRO could play an important role in determining the heat flow by parametrizing the different building properties, orientation, spatial variables etc. Tables and graphs displayed in REPRO could help decide optimum building conditions (see appendix), and identify major contributors to building loads, aiding designers. Iso graphs provide a visual method to optimize building parameters for a given building load. This can be useful when cost of conditioning is predetermined by external factors. For the given building and location under study, it was discovered that ventilation contributes maximum to the total building gain, but the change in ventilation will not have a big impact, in fact not even windows. The key lies in modifying wall properties firstly, since any change in wall will significantly lead to changes in heat contribution. Being the second contributor to heat gain, its impact is prominent in calculating loads. Secondly roof and floor needs modification. Followed by window and lastly by ventilation. When it comes to

[22]

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[20]

fluid flow about an inclined rectangular plate,” Journal of Heat Transfer, 1979. W. Nusselt and W. Jurges, “The cooling of a plane wall by an air flow”. J. Palyvos, “A survey of wind convection coefficient correlations for building envelope energy systems’ modeling,” Applied Thermal Engineering, 2008. ASHRAE, “ASHRAE Fundamentals Handbook,” 2001. Y. Liu and D. Harris, “Full-scale measurements of convective coefficient on external surface of a low-rise building in sheltered conditions,” Building and Environment, 2007. A. Schaak, Industrial Heat Transfer, Chapman & Hall. B. Jennings, Environmental Engineering, International Textbook. G. Tsilingiridis and K. Papakostas, “Investigating the relationship between air and ground temperature variations in shallow depths in northern Greece,” Energy, vol. 73, 2014. I. I. Khandaker, K. Anisuzzaman and I. Tanaz, “Correlation between Atmospheric Temperature and Soil Temperature,” Atmospheric and Climate Sciences, 2015.

[21] M. C. Peel, B. L. Finlayson and T. A. McMahon, “Updated world map of the Köppen-Geiger climate classification,” 2007. [22] “WorldAtlas,” [Online]. Available: https://www.worldatlas.com/as/in/ka/wher e-is-bangalore.html. [23] Climate Consultant. [24] NOAA, “NOAA National Centers for Environmental Information,” [Online]. Available: https://www.ncdc.noaa.gov/. [25] EnergyPlus, “EnergyPlus Weather,” [Online]. Available: https://energyplus.net/weatherlocation/asia_wmo_region_2/IND/IND_Ba ngalore.432950_ISHRAE. [26] Engineering ToolBox , “Engineering ToolBox,” [Online]. Available: https://www.engineeringtoolbox.com/ther mal-conductivity-d_429.html. [27] International Energy Agency (IEA), “Oil Crises and Climate Challenges: 30 Yearsof Energy Use in IEA Countries,” Paris, 2004. [28] “Gaisma,” [Online]. Available: https://www.gaisma.com/en/location/milan .html.

Appendices

Figure 29: Power law form for the wind convection coefficient (W/m2 K): h = a + bVn; [10]

[23]

Figure 30: Linear equation form for the wind convection coefficient (W/m2 K): h = a + bV; [10]

Sl. No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Element Name W00 W01 W02 W03 W04 W05 W06 W07 W08 W09 W10 W11 W12 W13

Width m 3.00 2.25 4.75 3.25 3.50 2.50 2.75 1.25 1.25 4.25 1.30 1.75 1.25 4.00

Height m 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00

Area m² 12.00 9.00 11.00 13.00 14.00 10.00 11.00 5.00 5.00 17.00 4.00 7.00 5.00 17.00

Sl. No. 15 W14 16 W15 17 W16 18 W17 19 W18 20 W19 21 WIND00 22 WIND01 23 WIND02 24 WIND03 25 R00 26 F00 Total Walls Total Window

Table 7: Detailed element dimension and area

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7.80 1.75 3.75 1.50 5.50 9.80 4.75 2.25 7.75 5.00 -

4.00 4.00 4.00 4.00 4.00 4.00 2.00 2.00 2.00 2.00 -

16.00 7.00 15.00 6.00 22.00 29.00 9.50 4.50 15.50 10.00 192.78 192.78 235 39.5

Figure 31: REPRO Simulate window- chart showing heat flow through different elements at each of the six-analysis hour

Figure 32: REPRO Comparison window- heat gain through different elements as a function indoor temperature

[25]

Figure 33: SINGLEFLUX Main window - showing the net heat gains from wall as a function of indoor temperature

Summer Indoor Temperature Ventilation rate 2 3 4 Glazing Uvalue 0.15 1.8 2.6 Wall thickness 0.2 0.3 0.5 Wall conductivity 0.035 0.84 1.63 Roof thickness 0.4 0.6 0.8

20

21

22

20.36 30.54 40.72

18.82 28.22 37.63

17.27 25.91 34.55

15.41 17.99 19.24

15.39 17.78 18.93

27.26 21.12 14.56

Winter 23

24

21

22

23

24

15.73 14.19 23.60 21.28 31.46 28.38

8.38 6.84 12.57 10.26 16.76 13.68

5.30 7.94 10.59

3.75 5.63 7.51

2.21 3.32 4.42

15.37 17.56 18.62

15.35 15.34 17.35 17.14 18.32 18.01

12.64 12.63 13.71 13.49 14.22 13.91

12.61 13.28 13.60

12.59 12.57 13.07 12.85 13.30 12.99

25.54 19.79 13.64

23.82 18.45 12.72

22.09 20.37 17.12 15.78 11.80 10.88

16.65 15.03 13.07 11.80 9.14 8.25

13.41 10.52 7.36

11.79 10.16 9.25 7.98 6.47 5.58

1.3 21.1 31.4

1.2 19.8 29.4

1.1 18.5 27.4

1.0 17.1 25.5

1.0 15.8 23.5

0.83 0.75 13.07 11.80 19.02 17.17

0.66 10.52 15.31

0.58 0.50 9.25 7.98 13.46 11.61

4.11 2.78 2.10

3.97 2.68 2.03

3.83 2.59 1.95

3.69 2.49 1.88

3.55 2.40 1.81

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20

3.52 2.38 1.80

3.38 2.29 1.73

3.24 2.20 1.66

3.11 2.10 1.59

2.97 2.01 1.52

Roof conductivity 0.04 0.1 0.4 Floor thickness 0.3 0.5 0.7 Floor conductivity 0.14 0.42 1.13

1.13 2.78 10.25

1.09 2.68 9.90

1.05 2.59 9.56

1.01 2.49 9.21

0.98 2.40 8.86

0.97 2.38 8.71

0.93 2.29 8.36

0.90 2.20 8.02

0.86 2.10 7.68

0.82 2.01 7.34

9.04 5.78 4.25

8.36 5.34 3.93

7.67 4.91 3.61

6.99 4.47 3.28

6.30 4.03 2.96

3.72 2.38 1.75

3.04 1.94 1.43

2.35 1.50 1.11

1.67 1.07 0.78

0.98 0.63 0.46

2.06 1.91 1.75 5.78 5.34 4.91 13.34 12.33 11.32

1.59 4.47 10.30

1.44 4.03 9.29

0.85 2.38 5.49

0.69 1.94 4.48

0.54 1.50 3.47

0.38 1.07 2.46

0.22 0.63 1.45

Table 8: Absolute value of heat gain/loss as a function of both the parameter setting and indoor temperature.

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