(Faculty of Architecture and Urbanism, Laboratory of Environmental Control and Energy Efficiency, Brasília-DF, Tel.: ++ 55 61 3307 2995)

ARCHITECTURAL VARIABLES AND ITS IMPACT IN DAYLIGHTING: USE OF DYNAMIC SIMULATION IN BRAZILIAN CONTEXT Cláudia Naves David Amorim 1, Milena Sampaio Cintra 2, Larissa Olivier Sudbrack 3, Gabriela Elias Camolesi 4 ; Cainã Silva 5 1 University of Brasília, Brasília, Brazil, ² 345 University of Brasília, Brasília, Brazil, clamorim@unb.br (Faculty of Architecture and Urbanism, Laboratory of Environmental Control and Energy Efficiency, Brasília-DF, Tel.: ++ 55 61 3307 2995) Abstract Daylighting in buildings has an important effect regarding environmental quality and energy efficiency. In fact, one of the consequences of good daylighting use in buildings is energy saving, due to the fact that daylight can replace artificial lighting. In this article, dynamic computational simulations are used to investigate the influence of some architectural variables (openings size, internal reflectances and surroundings obstructions with special focus on room depth) in daylighting performance in residential buildings in Brazil. 220 simulations were performed with the software DaySim (REINHART,2005), considering 10 cities in 10 different latitudes of the country in 4 orientations. The results could generate simple rules that guarantee daylight with previously defined levels (minimum of 60 lux in residential buildings) in 70% of room area in 70% of sun hours during the year. These rules were used in the Brazilian Energy Efficiency Regulation for Residential Buildings in Brazil. Keywords: computer simulation, daylighting, room depth, RTQ-R. 1. Introduction Given the environmental issues, pressing the current global architecture context, it can be said that daylight and all its implications related to the design have an important dimension of architecture environmental, functional and quality point of view. It becomes crucial the incorporation of daylight in the project in a consistent manner, optimizing benefits and minimizing negative impacts. (AMORIM, 2007) Brazil has sky conditions generally favorable for the use of daylighting, and the estimated values could fill in much of the lighting needs (PEREIRA, 1993). Even with this potential, Brazil is still in development studies for developing standards or manuals indicating effectively what designers should consider to take advantage of daylighting. There is a lack of knowledge on the architectural variables that influence the performance of daylighting in the built environment. What opening size need to illuminate the environment without being overly affected by the heat load? What is the maximum depth of the environment so that it is properly illuminated with dayighting? There are countless issues that are not approached satisfactorily in standards or manuals and in need of values based on studies that justify them. Inside an internacional context some standards and recommendations relate, for example, the height of the openings and the room depth limit for daylight s improvement. Reinhart (2005) presents some rules about the depth, such as Tips for Daylighting that indicates that one should "keep the room depth between 1.5 and 2 times the height of the window s bar to ensure adequate levels of illumination and good distribution of light "(O'Connor et al. 1997, p. 3-1, apud REINHART, 2005); and Daylighting Guide for Buildings which reports that " there is a direct relationship between the window height and depth of daylighting penetration. Proper lighting normally penetrates 1.5 times the height of the window, and can penetrate up to 2 times considering direct sunlight"(robertson K. 2005, p.4, apud REINHART, 2005). These rules are widely used by designers in general, although they are vague and do not have justifications through research that effectively demonstrate the use of these values. For example, in these rules is not known what is exactly an "appropriate illumination level", which considered minimal daylighting, for wich climatic regions, type of buildings and facades orientation that can be applied

(REINHART, 2005). The widespread use of these rules is due to the simplicity of it (no need for calculations) and their relevance to the project (direct connection between the proportions of the room and the size of the daylighted area). It is important, therefore, to study general rules for daylighting in buildings, grounded in scientific concepts, adapted to different types and adapted to climatic contexts. To establish standards or rules of lighting, the characteristics of each location and building should be considered, because the level of daylighting in a building vary depending on the sky conditions, sun's position, latitude, season, time, etc. Besides, countless building s variables will also influence daylighting performance, such as size and shape of rooms (width, depth and height), area and shape of openings, internal reflectance (walls, ceiling and floor), and the use of sun protection and elements of daylight distribution. In this study, it will be presented specifically the influence of the room depth at the penetration of daylighting, considering various climate contexts and latitudes in Brazil. Regarding the methods for evaluating daylighting performance in buildings, Reinhart, Mardaljevic and Rogers (2006) found that many evaluation methodologies of daylighting, which consider only the Daylight Factor (DLF) and exterior views does not have necessarily the aim of promoting good design integrated with daylighting, but lead to a better philosophy to design with daylighting. In these methodologies, however, some important parameters are neglected, as the seasonality of daylighting. Thus, the authors suggest a new approach considering dynamic metricsfor the performance of daylighting, which consider the local specificity, dynamic interaction between the building, its occupants and the weather and sky over the year. The dynamic metrics of daylightingare based on annual solar radiation data for a specific location, from an annual climatic file, generating a range of illuminance and luminance data inside the building. The main advantage of dynamic performance metrics of daylighting in comparison with the static metrics is that they consider the amount and nature of daily and seasonal variations of daylighting for a certain building at a particular site, together with irregular weather events. Evaluation of daylighting through dynamic metrics requires the use of CAD software and a software of daylighting simulation. The available software for this type of evaluation are based on a combination of Radiance Raytracer with a daylighting coeficient and a sky model. This combination calculates effectively a series of indoor illuminance and luminance of buildings, using an annual climatic file (8760 hours). Several studies have confirmed that the use of daylighting is able to provide significant lighting energy saving (Souza, 1995; Ghis, 1997; CARLO, 2008). However, the research on the behavior of indoor daylighting occur in a punctual manner, and evaluate an architectural aspect to only one location, resulting in little applicable conclusionsto other contexts and to projetual practice of architects and engineers. On the other hand, the Brazilian context now has a recent Regulation Energy Efficiency in Buildings, which this work contributes, specifically in Residential Regulation - RTQ-R (BRAZIL, 2010). So, due to limited existing literature, the complexity of the topic, the importance of daylighting use in buildings and the requirements for energy efficiency in buildings, the research presented in this work contributes to indications for the use of daylighting in a rational and efficient way, focusing specifically on residential buildings. 2. Objective The aim of this work is to present, through studies conducted with dynamic computacional simulations, the influence of the room depth on daylighting performance in residential buildings, considering the climatic context of Brazil, contributing to good practices in architecture for daylighting use and more specifically with the Technical Regulation on Quality Level Residential Energy Efficiency of Buildings (BRAZIL, 2010). 3. Method Given the need for simulation of various existent conditions throughout the year (sky conditions, date and time), it has been necessary the use of simulation software of dynamic metrics - Daysim (REINHART, 2005). 5 models have been developed by combining the following parameters: time of occupation, minimum illuminance needed on the indoor and Autonomy of Daylighting (Daylight Autonomy-DA). Data were organized into spreadsheets and graphs for analysis, making it possible to verify the behavior of daylighting and define a relation between the room depth related to the window s height in order to guarantee a specific condition of daylighting throughout the years in various weather conditions in Brazil. Thus, the methodology used in this work is divided into three steps: 1. Development of the simulation model and analysis parameters 2

2. Computer simulations with the software Daysim to various climatic conditions and latitudes in Brazil; 3. Analysis and discussion of results. 3.1. Development of the simulation model and analysis parameters For this study it has been defined and constructed a base model on a hypotheticalindoor residential of 23m² in order to allow verification of the reach of daylightingdepth in various simulated situations. The model has the same area of the models used for testing thermal and energy performance of the RTQ- R, with increase in length to allow better analysis of daylighting penetration. The environment was modeled with dimensions of 3.00 m wide x 7.66 m long, with a ceiling height of 2.50 m. The opening area has 1/6 of the floor area with dimensions of 3.00 m wide x 1.27 m high and 1 m windowsill (Figure 1). The characteristics of the model surfaces are consistent with those described in Table 1, which is the default program and are consistent with data suggested by Steffy (1990, cited in Souza, 2003) as real reflectance values. Height 2,5m Depth de 7,66 m Picture 1.3D base model Window1,27m Windowsill 1,0m Width de 3,0m Table 1.Surfacecharacteristics Surface Característica Floors 30% de Reflectance Roofs 84% de Reflectance Walls 58% de Reflectance Glass Luminoustransmission 90%. To verify the depth of indoor daylghiting penetration at the hight of the work plan, it has been established a grid of points as indicated by NBR 15215-4 sufficient to characterize an analysis plan. The indoor ambient has, therefore, been divided into equal parts totaling 18 measurementpoints, with spacing of 1 meter from each other, 50 cm away from walls and window (Figure 2). Picture2. Measurement grid pointmodel 3.1.1. Development of models Besides the physical characteristics of the model, for performance evaluation of daylighting, three other variables were defined for simulation: time of occupancy: defining time when the simulation computes the values of daylight; the illuminance of project, which is requirement of minimum illuminance to be served only by daylighting the percentage of independence of daylighting (Daylight Autonomy - DA), which checks the percentage of hours that the level of illuminance of the project is attended(reinhart, MARDALJEVIC E ROGERS, 2006) To analyze the behavior of daylighting before the first variable - Time of Occupancy - were simulated three different times. The first time was simulated occupancy of 6 to 18h, considered a possible period of occupation in a residential ambient. The second simulation time was an adaptation of the first time to the actual hours of sunshine of each simulated location. To do so, through the analysis of solar chart, it was determined that the hours of 3

sunshine to be considered for the simulation would be one hour after sunrise until one hour before sunset during the winter solstice, that is to say, was considered the shortest period of sunshine for each city, according to Table 2. Table2. Second ocupation time used in daylight simulations. CITY LATITUDE Midwinter Time used in simulation sunrise: sunset: starts: ends: São Luis 03⁰21' 06:00 18:00 07:00 17:00 Natal 05 ⁰ 47' 06:00 18:00 07:00 17:00 Maceió 09⁰21' 06:15 17:45 07:15 16:45 Salvador 12⁰58' 06:15 17:45 07:15 16:45 Brasília 15⁰55' 06:30 17:30 07:30 16:30 Belo Horizonte 19⁰55' 06:45 17:15 07:45 16:15 Rio de Janeiro 22⁰54' 06:45 17:15 07:45 16:15 São Paulo 23⁰32' 06:45 17:15 07:45 16:15 Curitiba 25⁰25' 06:45 17:15 07:45 16:15 Florianópolis 27⁰10' 07:00 17:00 08:00 16:00 Porto Alegre 30⁰01' 07:00 17:00 08:00 16:00 The third time of occupation was used from 8 to 16h, which corresponds to the lower time of occupation used in variable hours. The second variable used was the illuminance of the project, which is the level of illumination provided only by daylighting and is considered as a criterion for assessing the Daylight Autonomy (DA). Initially it was required illuminance ranging from 100 lux, it is the minimum amount of useful daylight illuminance (illuminance Useful Daylight - UDI) according to Reinhart (2005). In a second step, the simulations were required level of illuminance of 60 lux, which is in accordance with NBR 15575 (ABNT, 2008). This specifies the level of 60 lux illuminance with only daylighting to rooms, dormitories, kitchens, bathrooms and laundry area. The third variable was used to simulate the percentage of Autonomy of Daylightinging (Daylight Autonomy - DA). Simulations were demanding 80% and 70% of the time of the year with the previously determined level and illuminance (60 lux). Table 3.Summary of variables used in the simulations Thefore, to evaluate the behavior of daylighting and check daylighting depth penetration of indoor ambient, it was necessary to look into various combinations of variables. Consequently, from the base model, the variables time of occupancy, illumination design and range of daylighting were combined in five different cases, generating five models presented in Table 4. Table 4. Variable combination, generating models 1,2, 3, 4 e 5 Models Variable Combinations Models Variable Combinations Model 1 Model2 Model 3 1. Time occupancy 2. illuminancelevelofproject 3. percentage of independence of daylighting (Daylight Autonomy - DA) Hours of occupation from 6h to 18h Illuminance of 100 lux project 80% of daylight autonomy variable occupation Hours Illuminance of 100 lux project 80% ofdaylightautonomy variable occupation Hours Illuminance of 60 lux project 80% ofdaylightautonomy 8 to 18 hs Varies bythe latitude 8 8 às 16hs 100 lux (UDI) 60 lux (NBR 15.575) 80% 70% Modelo 4 Modelo 5 Hours of occupation from 8h to 16h Illuminance of 60 lux project 70% of daylight autonomy variable occupation Hours Illuminance of 60 lux project 70% ofdaylightautonomy 4

3.2. Simulations To start the simulations is necessary to import to the Software Daysim in 3D format, the threedimensional models constructed and characterized in Sketchup program, besides the grid of points for the ambient measurement. Then the parameters of simulation are configured, that guide the program to perform this simulation (REINHART, 2010). After each simulation the Daysim produces a report with values in metric for the analysis of daylighting for each grid point. The metrics provided are as follows: Daylight Factor (DF), Autonomy of Daylighting (Daylight Autonomy - DA), Continuous Daylight Autonomy (DACON), Maximum Daylight Autonomy (DAmax) Natural Illuminance Useful (UDI), DSP and the annual exhibition of light. In this work the metric used was the Autonomy of Daylighting (Daylight Autonomy - DA), which indicates the percentage of hours of the year that a determined illuminance (illuminance Project) is attended only with daylighting. The Daysim imports two types of file format that contains the TRY, the archives.epw and.wea, and extracts necessary information for simulation (REINHART, 2010). In this study, it has been used the Brazilian climate file at he Department Site of Energy(http://apps1.eere.energy.gov/buildings/energyplus/weatherdata_about.cfm), which provides weather data for over 660 locations worldwide. 3.2.1. Simulated Cities The choice of cities to be simulated prioritized the Brazilian capitals according to the difference of latitude and diversity of bioclimatic zones in order to represent better the country as a whole and permit that the influence of latitude and the sky conditions of daylighting behavior can be verified. Thereby, 11 were chosen for the simulations capitals: São Luís(2 58'South), Natal (5.91' South), Maceió (9 51 'South), Salvador (12 9' South), Brasilia (15 86 'South), Belo Horizonte (19 6' Sul), Rio de Janeiro (22 83 'South), São Paulo (23 61' South), Curitiba (25 51 'South), Florianópolis (27 66 'South) and Porto Alegre (30 South). Models 1,3,4 and 5 were simulated for 11 cities in orientations North, South, East and West. Model 2 aimed to verify the daylighting behavior changing latitude and orientation, the simulation is sufficient for only 5 cities among the 11 cities described São Luís (2 58 'South), Maceió (9 51 'South), Brasilia (15 86' South), Curitiba (25 51 'South) and Porto Alegre (30 South) in four directions (North, South, East and West). Therefore, in this sutdy it has been made 196 simulations in total. 3.2.2. Processing and analysis of data To analyze the depth reached by the daylight environment was used in part the methodology developed by Didoné (2009), using different integrated graphic methods for analysis of data generated by simulations. The integrated methods allow a visual assessment of daylightand numerical behavior according to obtained data. After the simulations, the report generated by Daysim provides the values of Daylight Autonomy (DA) in each measurement grid point. These data were inserted on WinSurf software, which converts data table curves in false color with the same DA (ISO-DA) (Figure 3). With generated graphic, is possible to analyze the behavior of daylight in a grid point, viewing the different ranges of DA distributed by the work plan. Then, the generated graphs in WinSurf are exported in an extension.jpg and inserted in AutoCAD 2009, superposed on the room floorplan, with its respective grid points. Thus, it is possible to analyze the behavior of daylighting together with the limits of the room and measuring the depth reached by a particular curve of ISO-DA. 5

Picture 3.ISO-DA graphics for analisysof daylight behavior. In the study presented here, the depth in meters achieved by the daylighting was related to the height of the window. Thus, measurements of depth were made in the plan CAD file divided by 2.27 m (height of the lintel of the window of the models). That is, the depth described in this work equals the depth reached by daylighting with the illuminance of the project previously defined, divided by the height of the window as the following equation: P = P LN / H Where, P= depth (dimensionless) P = depth reached in the environment by daylighting with illuminance design and Daylight Autonomy (DA) defined (in meters) H = Height of the window s bar, that in all models was 2.27 m The depth reached by the daylighting in each simulated model, of each city and each orientation, is measured and data were synthesized are in the form of graphs, generated by Microsoft Excel. From the graphs generated is possible to compare results between different latitudes and orientations. 4. Analysis of results Model 1 had values of depth achieved by the natural light from 0.8 to 1.2 times the window height and there was little difference in relation to latitude and orientation. Within this depth range, there was a tendency towards a lower value for the deep south orientation in cities with higher latitude. Already the results of greatest depth reached by natural light, had the tendency to orientation East and West to cities with lower latitude. The North orientation had intermediate values, as can be seen in chart 1. 2,50 2,00 1,50 0,00 Graphic 1: Model 1 100 lux 8-18 80% PORTO ALEGRE S FLORIANÓPOLIS S RIO DE JANEIRO S CURITIBA S FLORIANÓPOLIS O SÃO PAULO S BRASÍLIA S FLORIANÓPOLIS L FLORIANÓPOLIS N MACEIÓ N PORTO ALEGRE O MACEIÓ S CURITIBA O RIO DE JANEIRO N SALVADOR S RIO DE JANEIRO L NATAL N CURITIBA L NATAL S BRASÍLIA O CURITIBA N BRASÍLIA N PORTO ALEGRE L RIO DE JANEIRO O SÃO PAULO L PORTO ALEGRE N SALVADOR N SÃO PAULO O MACEIÓ O MACEIÓ L SÃO LUIS N SÃO PAULO N SÃO LUIS S BRASÍLIA L SALVADOR O SALVADOR L NATAL O NATAL L SÃO LUIS O SÃO LUIS L 6

The behavior shown in the results of this model was due to occupation time used in simulation. The cities with lower latitude have a schedule of constant sunshine throughout the year, with sunrise around 6 am and sunset around 18h, which is compatible with occupacion time definded for simulation. The city with highr latitude in winter, the hours of sunshine is much smaller than the period stipulated for simulation results, computeded hours where there is no daylighting. And in the summer when the period with sunlight is longer, the hours with extra daylighting are not considered because the occupation have been limited until 18h. In model 2 (Figure 2) it appears that the standard of higherdepth values has to be North orientation for largest latitudes. The East and West orientations became the intermediate values, and south to the cities of higher latitude obtained the lowest values. This behavior of daylighting responds to the higher incidence of direct sunlight in north facade during the day, considering that in this facade direct sunlight is constant in the morning and afternoon, especially at higher latitudes, while East and West orientations receive direct light only in a time of day (morning or afternoon). The South facade receives less direct sunlight, especially at higher latitudes, that s why it has lowest depth. It was also noted that to ensure 100 lux for 80% of the time, although considering the time of occupation variable for each city, the depthvalues would have to be very low, between 1 and 1.44 times the window height, while the literature indicates that the "ideal" for maximum depth is on average 1.5 to 2.5 times the windowheight (REINHART, 2005). Model 3 (Table 3) showed the same depth pattern achieved by the daylighting in the Graphic 2: Model 2 100 lux variável 80% room that Model 2- the standard of the 2,50 higher depth wasnorthorientation to the 2,00 city with higher latitude, the East and West 1,50 orientations maintained intermediate values and Southorientation had the lowest values, especially for lower latitudes. Depth 2,50 2,00 1,50 0,00 SÃO PAULO S SÃO PAULO O CURITIBA O FLORIANÓPOL BELO Graphic 3: Model 3 60 FLORIANÓPOL SÃO PAULO L BRASÍLIA O NATAL S FLORIANÓPOL MACEIÓ O 0,00 Depth CURITIBA S FLORIANÓPOLIS S BRASÍLIA S MACEIÓ S CURITIBA O FLORIANÓPOLIS L MACEIÓ O BRASÍLIA O SÃO LUIS S CURITIBA L FLORIANÓPOLIS O MACEIÓ L MACEIÓ N SÃO LUIS O SÃO LUIS N SÃO LUIS L CURITIBA N FLORIANÓPOLIS N BRASÍLIA L BRASÍLIA N The lowest depth reached by daylighting was South orientation in the city of São Paulo, with a value of 1.41 times the window height, and the highest value was for North orientation in Porto Alegre, 2 times the window height, having in this way the wideness of 0.51. The average depth reached was 1.65 times the window height. This result indicates that by applying the average depth reached by daylighting, 1.65 times the windowheight, ina similar room used as model (without sunscreen, the opening area with 1/6 of the floor area, windowheight of 2.27 and with similar reflectances) shows that up to 3.75 meters deep from the window, are guaranteed 60 lux of daylighting in 80% of the time, considering the time variable occupancy in a year. Model 4 (Figure 4) obtained the same comportment as the daylighting depth reached that occurred in models 2 and 3. This occurred because it was considered the least time of occupation, which guaranteed in simulations hours when there is availability of daylighting in all cities. The main difference between the results of Models 3 and 4 was the increased daylightingdepth achieved in order to lower demand and lower the DA time occupation. In this model, the lowest daylighting depth reachedwas in South orientation in Florianópolis, with a value 1.58 times window height, and the highest value was for North orientationin Sao Paulo, with 2.11 times the window height, and the average daylightingdepth reached was 1.85 times the window height. 7

2,50 2,00 1,50 0,00 Graphic 4: Model 4 60lux 8-16h 70% Depth FLORIANÓPOLIS S CURITIBA S MACEIÓ O FLORIANÓPOLIS FLORIANÓPOLIS L BRASÍLIA S SALVADOR S RIO DE JANEIRO SÃO PAULO O CURITIBA L MACEIÓ L SÃO PAULO L FLORIANÓPOLIS SALVADOR O NATAL N MACEIÓ N BELO BELO SÃO LUIS L CURITIBA N PORTO ALEGRE N BELO Finally, model 5 (Figure 5) shows that the behavior of daylighting followed the pattern of previous models (except Model 1), with higher depth values in Northorientation, mainly to the cities of greater latitude.east and West orientation continued with the trend of intermediate values and Southorientation had the lowest values, especially for cities with lower latitude. It appears that the lowest depth reached by the daylighting was insouth orientation in the city of São Paulo, with a value of 1.53 times the window height, and the highest value was for North orientation in Porto Alegre, with 2.09 times the window height, and the average depth reached in model 5 has declined compared to the previous model, to 1.80 times the window height, because the use of a larger Graphic 6: Comparison of orientation models occupation time. 2,5 2,50 2,00 1,50 0,00 Graphic 5: Mo Depth 2 1,5 1 0,5 0 Norte Sul Leste Oeste Média Modelo 1 Modelo 2 Modelo 3 Modelo 4 Profundidade SÃO PAULO S BRASÍLIA L CURITIBA S FLORIANÓPOLIS S PORTO ALEGRE S RIO DE JANEIRO S CURITIBA O SÃO PAULO L BELO HORIZONTE S FLORIANÓPOLIS O BRASÍLIA S SALVADOR S MACEIÓ S RIO DE JANEIRO O FLORIANÓPOLIS L NATAL S PORTO ALEGRE O SÃO PAULO O BRASÍLIA O SÃO LUIS N Modelo 5 This result indicates that by applying the average depth reached by daylighting, 1.80 times the window height, in a similar room to that used in the model (without sunscreen, the opening area with 1/6 of the floor area, windowheight of 2.27 and with similar reflectances) results that even 4.08 meters depth from the opening, are guaranteed 60 lux of daylighting in 70% of the time, considering the time variable during the occupation years. By analyzing the graphic 6 shows that models 2, 3, 4 and 5 had a similar behavior of the indoorsdaylightingreacheddepth. In these models there was a tendency for lower values of depth are achieved in the south, especially in cities with greater latitude. Already the biggest gains, had the tendency to East and West orientation to cities with lower latitude. While the North orientation had intermediate values. Only Model 1, which used the hours of 6 to 18h, had a different behavior of daylighting for all other situations, in this case the East and West orientation had the greatest results rather than the North orientation. This result is justified by the use of long period of time for occupancy (from 6 to 18h), which computes the results, especially for cities with higher latitude, times that has no daylighting (around 6, 7h in the morning) and excludes the results of hours there was still daylight (after 18h), injuring the results. It has been observed that the use of a smaller time occupation, in Model 4, influenced the results of obtaining the higher depth, being a small time occupation, which guarantees to compute the results only sunny hours. However, the time variable for each latitude was the most consistent, considering that the results reflect the characteristics of sunny hours in each city, without harm or benefit the results for cities at different latitudes. It has been observed, also,that the orientation significantly affects the results achieved, especially in cities with greater latitude. The North orientation had the greatest results in depth, except 8

in Model 1, and reached 2.11 times the height of the window in Model 4. While the maximum value attained by the south was 1.58 times the height of the window, in Model 4. The east and west orientations obtained in most cases, intermediate values, and in all models, the mean direction east got the results a little longer in relation to west orientation. In relation to latitude, it appears that the higher the latitude greater are the results for north orientation and the results are lower for south (see Figures 6, 7, 8, 9 and 10). This behavior is seen in the results of models 3, 4 and 5, which indicate that from latitude -10, the difference in the depth reached by the daylighting of the guidelines is more significant. Graphics 6,7, 8, 9 e 10. Results of the depth reached by the daylight for modelss orientation and latitude. Profundidade 2,50 2,00 1,50 Modelo1 100 lux 6h-18h DA 80% -30-25 -20-15 -10-5 0 Latitude Profundidade Model 2 100 lux Variable DA 80% Latitude Model 3 60lux Variable DA 80% Model 4 60lux 8h-16h DA70% Model 5 60lux Variable DA70% Norte Sul Leste Oeste Concerning to the analysis ofdaylightingautonomy (DA), it was observed that the requirement of the design illuminance of 100 lux at 80% of the time is very high, considering that the depth reached in the range of 1 times the height of window, as indicated in the results of Model 1. This result is far from that indicated by the literature - which is between 1.5 and 2.5 times the height of the window (REINHART, 2005), and shows little if applicable in the reality of building in Brazil, considering that in this case depth limit of the environment, respecting the characteristics established in the model, would be 2.27 meters (which is the height of the window) By using the NBR 15575 recommended, 60 lux for illuminance design with a range of daylighting in 70% of the time, according to the hours of sun each city (Form 5), the results obtained at a depth of daylighting were on average 1.80 times the height of the window. This result was closer to the values reported in the literature, which are between 1.53 and 2.09 times the height of the window (REINHART, 2005). The depth limit resulting from Model 5 represents, in general, that buildings located in Brazil, having the opening area of around 1 / 6 of the floor area, without sunscreen and the internal reflectance standard used in architecture (84% roofs, walls 58% and floors 30%) should have a depth limit of 1.8 times the height of the window to ensure 60 lux throughout the room, in 70% of the time of the year, according to the schedule sun in each location. 5. Conclusions The presented results in this research and the analysis of the simulations demonstrate to be efficient, showing that it is possible to find values that relate the room depth limit with the window height of a certain standard room, in a way to ensure specific conditions of daylighting within Brazilian climate context. Buildings located in Brazil, having the opening area of around 1 / 6 of the floor area, without sunscreen and the internal reflectances of 84% in roofs, 58% in walls and 30% in floors 30% should have a depth limit of 1.8 times the height of the window to ensure 60 lux throughout the room, in 70% of the time of the year, according to the schedule sun in each location. 9

The program Daysim, the main tool used in this research, appears to be appropriate for the daylighting dynamic simulaton. The support software (WinSurf) proves to be an efficient tool to generate representation maps of the simulated results, since it uses the RGB color palette, which is easily recognized. It is necessary to go further in this kind of research in order to fill the lack of knowledge regarding the influence of architecture on daylighting performance, enabling to get values for each specific architecture and climate. It will be possible in this way, to create rules that ensure development of rules applicable to the project known conditions of daylighting and can be implemented in Regulations (specifically in the RTQ-R), standards, building codes, etc., contributing to better project quality and possibly better efficiency energy. 6. References AMORIM, C. N. D.Diagrama Morfológico parte I: instrumento de análise e projeto ambiental com uso de luz natural.paranoá Cadernos de Arquitetura e Urbanismo, n 3.Programa de Pesquisa e Pós Graduação, Universidade de Brasília. Brasília: 2007. ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS.NBR 15.575 -Desempenho de edifícios habitacionais de até cinco pavimentos. Parte 4: Sistemas de vedações verticais externas e internas. Rio de Janeiro: 2008. DIDONÉ, Evelise L.; PEREIRA, Fernando O. R. Introdução à simulação integrada com os programas Daysim e EnergyPlus. Laboratório de Conforto Ambiental LabCon. Departamento de Arquitetura e Urbanismo CTC/ARQ/UFSC. Florianópolis, 2009. DIDONÉ, Evelise L. A influência da Luz Natural na avaliação da eficiência energética de edifícios contemporâneos de escritórios em Florianópolis.Dissertação (Mestrado em Arquitetura e Urbanismo) Programa de Pós-Graduação em Arquitetura e Urbanismo, UFSC, Florianópolis, 2009. Empresa de Pesquisa Energética(EPE). Plano Decenal de Energia PDE 2019.Rio de Janeiro: EPE, 2010. Disponível em: http://www.epe.gov.br/imprensa/pressreleases/20100504_2.pdf. Acesso em 10 de julho de 2010. GHISI, Enedir; TINKER, John A.; IBRAHIM, Siti H. Área de janela e dimensões para iluminação natural e eficiência energética: literatura versus simulação computacional.in.: Ambiente Construído. V.5, n.4, p. 81-93. Associação Nacional de Tecnologia do Ambiente Construído. INSS: 1415-8876. Porto Alegre: 2005 ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS - ABNT. NBR 5461: Iluminação. Rio de Janeiro, 1991.. NBR 5413:Iluminância de interiores. Rio de Janeiro, 1992.. NBR 15215-2: Iluminação natural - Parte 2: Procedimentos de cálculo para a estimativa da disponibilidade de luz natural. Rio de Janeiro, 2005 a. PEREIRA, Fernando O. R. Luz solar direta: tecnologia para melhoria do ambiente lumínico e economia de energia na edificação. In: 2º Encontro Nacional de Conforto no Ambiente Construído, ANAIS. Florianópolis: ANTAC, ABERGO, SOBRAC, 1993. CD-ROM 1990-2009. REINHART, C. F.A simulation-based review of the ubiquitous window-head-height to daylit zone depth rule-of-thumb.in: Internacional Building Simulations Conference 9., Montreal, Canada, 2005. Proceedings Montreal: IBPSA. REINHART, C. F. Tutorial on the Use of Daysim Simulations for Sustainable Design.Harvard University Graduate School of Design, Cambridge, USA. 2010 REINHART, C. F.; MARDALJEVIC,J; ROGERS, Z. Dynamic daylight performance metrics for sustainable building design. NRCC-48669. 2006 SOUZA, M. B. Potencialidade de aproveitamento da luz natural através da utilização de sistemas automáticos de controle para economia de energia elétrica. Tese (Doutorado em Engenharia de Produção) Centro Tecnológico, Universidade Federal de Santa Catarina. Florianópolis: 2003. Acknowledgement: To CNPq for the scholarships from CT-Energ Program (2008). 10

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