Computational Fluid Dynamics (CFD) refers to numerical methods for simulating the movement of fluid. Due to its efficiency, CFD has been widely used in aerospace engineering and automotive design since the 1970s. It also has potential in architectural design since airflow has been an important player in the design process. However, the CFD users in the building industry tend to be limited to researchers and engineers rather than architectural designers due to the complexity of the simulations including the extensive knowledge required for the processing. The benefit of using CFD would be maximized through its early application by architectural designers since the key design decisions are made in the early stages. In response to this, simulation tools specialized for the early stages of architectural design are developed recently, which offer more user-friendly interfaces. Within this context, the present study aimed to introduce and test the simulation tools for the early stages of design and establish a framework for supporting architectural designers to utilize CFD. Under this objective, a mixed-method approach was employed that includes quantitative and qualitative assessments of simulation tools, development of a knowledge set that can help the users to understand the simulation processes and results, an immersive case study for structuring the procedural model, and a Delphi method for evaluating and reaching a consensus on the proposed framework. / Doctor of Philosophy / Computational Fluid Dynamics (CFD) is a computer simulation method for automating the calculations of the complex equations on the flow of a fluid, such as air or water, and visualizing the calculation results. CFD has been widely used in designing aircraft and cars since the 1970s because of the efficiency of this method compared to physical experiments. CFD also has potential in architectural design since airflow has been an important player in the design process. However, the CFD users in the building industry tend to be limited to researchers and engineers rather than architectural designers due to the complexity of the simulations including the extensive knowledge required for the processing. In response to this situation, more user-friendly simulation tools for non-experts, including designers, are developed recently. Considering this context, the present study tried to introduce and test the simulation tools for designers and develop a framework for supporting architectural designers to utilize CFD in their design processes. Under this objective, both quantitative and qualitative studies were conducted, including the review of relevant articles, computer simulations, a case study with an architectural project example, designed by the author, and a Delphi method in which the recruited experts in architectural design evaluate the proposed framework.

In naturally ventilated buildings, occupants play a key role in the performance and energy efficiency of the building operation, mainly through the opening and closing of windows. To include the effects of building occupants within building performance simulation, several useful models describing building occupants and their window opening/closing behaviour have been generated in the past 20 years. However, in these models, the occupants are classified based on the whole population or on sub-groups within a building, whilst the behavioural difference between individuals is commonly ignored. This research project addresses this latter issue by evaluating the importance of the modelling and prediction of occupants window behaviour individually, rather than putting them into a larger population group. The analysis is based on field-measured data collected from a case study building containing a number of single-occupied cellular offices. The study focuses on the final position of windows at the end of the working day. In the survey, 36 offices and their occupants were monitored, with respect to the occupants presence and window use behaviour, in three main periods of a year: summer, winter and transitional. From the behaviour analysis, several non-environmental factors, namely, season, floor level, gender and personal preference, are identified to have a statistically significant effect on the end-of-day window position in the building examined. Using these factors, occupants window behaviour is modelled by three different classification methods of building occupants, namely, whole population, sub-groups and personal preference. The preference-based model is found to perform much better predictive ability on window state when compared with those developed based on whole population and sub-groups. When used in a realistic building simulation problem, the preference-based prediction of window behaviour can reflect well the different energy performance among individual rooms, caused by different window use patterns. This cannot be demonstrated by the other two models. The findings from this research project will help both building designers and building managers to obtain a more accurate prediction of building performance and a better understanding of what is happening in actual buildings. Additionally, if the habits and behavioural preferences of occupants are well understood, this knowledge can be potentially used to increase the efficiency of building operation, by either relocating occupants within the building or by educating them to be more energy efficient.

The vaccine cold chain is an integral part of the process of storing and distributing vaccines prior to administration. A key component of this cold chain for developing countries is the primary vaccine storage warehouse. As the starting point for the distribution of vaccines throughout the country, these buildings have a significant amount of refrigerated space and therefore consume large amounts of energy. Therefore, this thesis focuses on analyzing the relative importance of parameters for the design of an energy efficient primary vaccine storage warehouse with the end goal of achieving Net-Zero Energy operation. A total of 31 architectural design parameters, such as roof insulation U-Value and external wall thermal mass, along with 14 building control parameters, including evaporator coil defrost termination and thermostat set points, are examined. The analysis is conducted across five locations in the developing world with significant variations in climate conditions: Buenos Aires, Argentina; Tunis, Tunisia; Asuncion, Paraguay; Mombasa, Kenya; and Bangkok, Thailand. Variations in the parameters are examined through the implementation of a Monte Carlo-based global uncertainty and sensitivity analysis to a case study building layout. A regression-based sensitivity analysis is used to analyze both the main effects of each parameter as well as the interactions between parameter pairs. The results of this research indicate that for all climates examined, the building control parameters have a larger relative importance than the architectural design parameters in determining the warehouse energy consumption. This is due to the dominance of the most influential building control parameter examined, the Chilled Storage evaporator fan control strategy. The importance of building control parameters across all climates examined emphasizes the need for an integrated design method to ensure the delivery of an energy efficient primary vaccine warehouse.

This PhD thesis evaluated the applicability of Climate-Based Daylight Modelling (CBDM) as it is presently done. The objectives stated in this thesis aimed at broadly assessing applicability by looking at multiple aspects: (i) the way CBDM is used by expert researchers and practitioners; (ii) how state-of-the-art simulation techniques compare to each other and how they are affected by uncertainty in input factors; (iii) how the simulated results compare with data measured in real occupied spaces. The answers obtained from a web-based questionnaire portrayed a variety of workflows used by different people to perform similar, if not the same, evaluations. At the same time, the inter-model comparison performed to compare the existing simulation techniques revealed significant differences in the way the sky and the sun are recreated by each technique. The results also demonstrated that some of the annual daylight metrics commonly required in building guidelines are sensitive to the choice of simulation tool, as well as other input parameters, such as climate data, orientation and material optical properties. All the analyses were carried out on four case study spaces, remodelled from existing classrooms that were the subject of a concurrent research study that monitored their interior luminous conditions. A large database of High Dynamic Range images was collected for that study, and the luminance data derived from these images could be used in this work to explore a new methodology to calibrate climate-based daylight models. The results collected and presented in this dissertation illustrate how, at the time of writing, there is not a single established common framework to follow when performing CBDM evaluations. Several different techniques coexist but each of them is characterised by a specific domain of applicability.

Changes in weather patterns worldwide and global warming increased the demand for high-performance buildings resilient to climate change. Building Performance Simulation (BPS) is a robust technique to test, assess, and enhance energy efficiency measures and comply with stringent energy codes of buildings. Climate has a considerable impact on the buildings' thermal environment and energy performance; therefore, choosing reliable and accurate weather data is crucial for building performance evaluation and reducing the performance gap. Typical Weather Years (TWYs) have been traditionally used for energy simulation of buildings. Even if detailed energy assessments can be performed using available multi-year weather data, most simulations are carried out using a typical single year. As a result, this fictitious year must accurately estimate the typical multi-year conditions. TWYs are widely used because they accelerate the modeling process and cut down on computation time while generating relatively accurate long-term predictions of building energy performance. However, there is no certainty that a single year can describe the changing climate and year-by-year variations in weather patterns. Nowadays, with increased computational power and higher speeds in calculation processes, it is possible to adopt multi-year weather datasets to fully assess long-term building energy performance and avoid errors and inaccuracies during the preliminary selection procedures. This study aims to investigate the impact of Typical Weather Years and Actual Weather Years (AWYs) on a single-family house and a university building under two opposite climates, Winnipeg (cold) and Catania (hot). First, a single-family house in Winnipeg, Canada, was selected to evaluate how typical weather years affect the energy performance of the building and compare it with AWYs simulation. Two widely used typical weather data, CWEC and TMY, were selected for the simulation. The results were compared with the outcomes of simulation using AWYs derived from the same weather station from 2015 to 2019, which covered the latest climate changes. The results showed that typical weather years could not sufficiently capture the year-by-year variation in weather patterns. The typical weather years overestimated the cooling load while underestimating the heating demands compared to the last five actual weather years. A more extensive study was conducted for more confidence in the findings and understanding of the weather files. The research was expanded by comparing the results of building performance simulation of the single-family house and an institutional building with more complex envelope characteristics belonging to the University of Manitoba under cold (Winnipeg, Canada) and hot (Catania, Italy) climates. Overall, 48 simulations were performed using ten actual weather years from 2010 to 2019 and two TWYs from each climate for both buildings. The results showed that while the TWYs either overestimate or underestimate the cooling and heating demands of both buildings, cooling load predictions were highly overestimated in the heating-dominant climate of Winnipeg, ranging from 10.5% to 82.4% for both buildings by CWEC and TMY weather data. In the cooling-dominant climate of Catania, energy simulations using IWEC and TMY typical weather data highly overestimated the heating loads between 2.8% and 82.4%.

Simulações computacionais são um recurso de grande valia no projeto do edifício, particularmente na área de desempenho ambiental, permitindo predizer fenômenos complexos como desempenho térmico, lumínico, acústico e energético dos edifícios e de seu entorno. O surgimento do BIM (Building Information Modeling ou Modelagem da Informação da Construção), por sua vez, forneceu aos profissionais da indústria da construção novas ferramentas para auxiliar na criação e gestão da informação da construção. Ao combinar um modelo 3D com um banco de dados único do projeto, BIM acaba por reduzir a perda de informação e o retrabalho, permitindo o trabalho colaborativo e aumentando a confiabilidade e rastreabilidade das informações do projeto ao longo do ciclo de vida da construção. Muito antes do BIM, ferramentas de simulação de desempenho do edifício (Building Performance Simulation - BPS, na sigla em inglês) já empregavam modelos 3D, o que significa que especialistas de avaliação ambiental do edifício frequentemente tinham que modelar o edifício - e remodelá-lo cada vez que o projeto fosse alterado - dentro destas ferramentas de modo a executar as análises de desempenho. Neste contexto, a integração entre ferramentas BIM e BPS é fundamental para aumentar a eficiência de uma indústria da construção altamente fragmentada. Nos últimos anos, muitos pesquisadores têm se focado em alcançar tal integração. Este estudo sintetiza as pesquisas nesta questão por meio da revisão sistemática de mais de 250 pesquisas publicadas mundialmente no período de 1991 a 2015. Os resultados mostram que, apesar de um aumento significativo no número de estudos publicados nos últimos cinco anos, a plena integração entre BIM e BPS é um assunto complexo e continua sendo um desafio. Esta revisão sistemática produziu um diagnóstico abrangente e contribui com pesquisadores por revelar padrões, tendências e lacunas da área de pesquisa, orientando assim futuros esforços de pesquisa. / Computer simulations are a valuable resource in building design, notably in the environmental performance field, enabling designers and engineers to predict complex phenomena such as thermal, lighting, acoustic and energy performance. The emergence of BIM (Building Information Modeling), in turn, provided these professionals with new tools to assist in the creating and managing of building information. By combining a 3D model to a unique project database, BIM ultimately reduces the loss of information and rework, allowing collaborative work and increasing reliability and traceability of the project information throughout the construction lifecycle. Long before BIM, Building Performance Simulation (BPS) tools already employed 3D models, meaning that simulationists frequently had to model the building - and remodel it as many times as the design changed - within these tools in order to run performance analyses. In this context, the integration of BIM and BPS tools is critical to increase efficiency of a highly fragmented construction industry. In the past years, many researchers have been focusing on achieving this integration. This study summarizes research on this topic by systematically reviewing over 250 researches published worldwide from 1991 to 2015. Results show that, despite a significant increase in the number of studies published in the last five years, fully integration between BIM and BPS is a complex subject and remains a challenge. This systematic review produced a comprehensive diagnosis and contributes with researchers by revealing patterns, trends and gaps of the research area, orientating future research efforts.

Simulações computacionais são um recurso de grande valia no projeto do edifício, particularmente na área de desempenho ambiental, permitindo predizer fenômenos complexos como desempenho térmico, lumínico, acústico e energético dos edifícios e de seu entorno. O surgimento do BIM (Building Information Modeling ou Modelagem da Informação da Construção), por sua vez, forneceu aos profissionais da indústria da construção novas ferramentas para auxiliar na criação e gestão da informação da construção. Ao combinar um modelo 3D com um banco de dados único do projeto, BIM acaba por reduzir a perda de informação e o retrabalho, permitindo o trabalho colaborativo e aumentando a confiabilidade e rastreabilidade das informações do projeto ao longo do ciclo de vida da construção. Muito antes do BIM, ferramentas de simulação de desempenho do edifício (Building Performance Simulation - BPS, na sigla em inglês) já empregavam modelos 3D, o que significa que especialistas de avaliação ambiental do edifício frequentemente tinham que modelar o edifício - e remodelá-lo cada vez que o projeto fosse alterado - dentro destas ferramentas de modo a executar as análises de desempenho. Neste contexto, a integração entre ferramentas BIM e BPS é fundamental para aumentar a eficiência de uma indústria da construção altamente fragmentada. Nos últimos anos, muitos pesquisadores têm se focado em alcançar tal integração. Este estudo sintetiza as pesquisas nesta questão por meio da revisão sistemática de mais de 250 pesquisas publicadas mundialmente no período de 1991 a 2015. Os resultados mostram que, apesar de um aumento significativo no número de estudos publicados nos últimos cinco anos, a plena integração entre BIM e BPS é um assunto complexo e continua sendo um desafio. Esta revisão sistemática produziu um diagnóstico abrangente e contribui com pesquisadores por revelar padrões, tendências e lacunas da área de pesquisa, orientando assim futuros esforços de pesquisa. / Computer simulations are a valuable resource in building design, notably in the environmental performance field, enabling designers and engineers to predict complex phenomena such as thermal, lighting, acoustic and energy performance. The emergence of BIM (Building Information Modeling), in turn, provided these professionals with new tools to assist in the creating and managing of building information. By combining a 3D model to a unique project database, BIM ultimately reduces the loss of information and rework, allowing collaborative work and increasing reliability and traceability of the project information throughout the construction lifecycle. Long before BIM, Building Performance Simulation (BPS) tools already employed 3D models, meaning that simulationists frequently had to model the building - and remodel it as many times as the design changed - within these tools in order to run performance analyses. In this context, the integration of BIM and BPS tools is critical to increase efficiency of a highly fragmented construction industry. In the past years, many researchers have been focusing on achieving this integration. This study summarizes research on this topic by systematically reviewing over 250 researches published worldwide from 1991 to 2015. Results show that, despite a significant increase in the number of studies published in the last five years, fully integration between BIM and BPS is a complex subject and remains a challenge. This systematic review produced a comprehensive diagnosis and contributes with researchers by revealing patterns, trends and gaps of the research area, orientating future research efforts.

This study examines the potential to conduct building thermal performance simulation (BPS) of unconditioned low-cost housing during the early design stages. By creating a set of regression models (meta-models) based on EnergyPlus simulations, this research aims to promote and simplify BPS in the building envelope design process. The meta-models can be used as tools adapted for three Brazilian cities: Curitiba, São Paulo and Manaus, providing decision support to designers by enabling rapid feedback that links early design decisions to the buildings thermal performance. The low-cost housing unit studied is a detached onestory house with an area of approximately 51m2, which includes two bedrooms, a combined kitchen and living room, and one bathroom. This representative configuration is based on collected data about the most common residence options in some Brazilian cities. This naturally ventilated residence is simulated in the Airflow Network module in EnergyPlus, which utilizes the average wind pressure coefficients provided by the software. The parametric simulations vary the house orientation, U-value, heat capacity and absorptance of external walls and the roof, the heat capacity of internal walls, the window-to-wall ratio, type of window (slider or casement), and the existence of horizontal and/or vertical shading devices with varying dimensions. The models predict the resulting total degree-hours of discomfort in a year due to heat and cold, based on comfort limits defined by the adaptive method for naturally ventilated residences according to ANSI ASHRAE Standard 55. The methodology consists of (a) analyzing a set of Brazilian low-cost housing projects and defining a geometric model that can represent it; (b) determining a list of design parameters relevant to thermal comfort and defining value ranges to be considered; (c) defining the input data for the 10.000 parametric simulations used to create and test the meta-models for each analyzed climate; (d) simulating thermal performance using Energy Plus; (e) using 60% of the simulated cases to develop the regression models; and (f) using the remaining 40% data to validate the meta-models. Except by Heat discomfort regression models for the cities of Curitiba and São Paulo the meta-models show R2 values superior to 0.9 indicating accurate predictions when compared to the discomfort predicted with the output data from EnergyPlus, the original simulation software. Meta-models application tests are performed and the meta-models show great potential to guide designers decisions during the early design. / Esta pesquisa avalia as potencialidades do uso de simulações do desempenho térmico (SDT) nas etapas iniciais de projetos de habitações de interesse social (HIS) não condicionadas artificialmente. Busca-se promover e simplificar o uso de SDT no processo de projeto da envolvente de edificações através da criação de modelos de regressão baseados em simulações robustas através do software EnergyPlus. Os meta-modelos são adaptados ao clima de três cidades brasileiras: Curitiba, São Paulo e Manaus, e permitem uma rápida verificação do desconforto térmico nas edificações podendo ser usados como ferramentas de suporte às decisões de projeto nas etapas iniciais. A HIS considerada corresponde a uma unidade térrea com aproximadamente 51m2, composta por dois quartos, um banheiro e cozinha integrada à sala de jantar. Esta configuração é baseada em um conjunto de projetos representativos coletados em algumas cidades brasileiras (como São Paulo, Curitiba e Manaus). Estas habitações naturalmente ventiladas são simuladas pelo módulo Airflow Network utilizando o coeficiente médio de pressão fornecido pelo EnergyPlus. As simulações consideram a parametrização da orientação da edificação, transmitância térmica (U), capacidade térmica (Ct) e absortância () das paredes externas e cobertura; Ct e U das paredes internas; relação entre área de janela e área da parede; tipo da janela (basculante ou de correr); existência e dimensão de dispositivos verticais e horizontais de sombreamento. Os meta-modelos desenvolvidos fornecem a predição anual dos graus-hora de desconforto por frio e calor, calculados com base nos limites de conforto definidos pelo método adaptativo para residências naturalmente ventiladas (ANSI ASHRAE, 2013). A metodologia aplicada consiste em: (a) análise de um grupo de projetos de HIS brasileiras e definição de um modelo geométrico que os represente; (b) definição dos parâmetros relevantes ao conforto térmico, assim como seus intervalos de variação; (c) definição dos dados de entrada para as 10.000 simulações paramétricas utilizadas na criação e teste de confiabilidade dos meta-modelos para cada clima analisado; (d) simulação do desempenho térmico por meio do software EnergyPlus; (e) utilização de 60% dos casos simulados para o desenvolvimento dos modelos de regressão; e (f) uso dos 40% dos dados restantes para testar a confiabilidade do modelo. Exceto pelos modelos para predição do desconforto por calor para Curitiba e São Paulo, os demais meta-modelos apresentaram valores de R2 superiores a 0.9, indicando boa adequação das predições de desconforto dos modelos gerados ao desconforto calculado com base no resultado das simulações no EnergyPlus. Um teste de aplicação dos meta-modelos foi realizado, demonstrando seu grande potencial para guiar os projetistas nas decisões tomadas durante as etapas inicias de projeto.

This study examines the potential to conduct building thermal performance simulation (BPS) of unconditioned low-cost housing during the early design stages. By creating a set of regression models (meta-models) based on EnergyPlus simulations, this research aims to promote and simplify BPS in the building envelope design process. The meta-models can be used as tools adapted for three Brazilian cities: Curitiba, São Paulo and Manaus, providing decision support to designers by enabling rapid feedback that links early design decisions to the buildings thermal performance. The low-cost housing unit studied is a detached onestory house with an area of approximately 51m2, which includes two bedrooms, a combined kitchen and living room, and one bathroom. This representative configuration is based on collected data about the most common residence options in some Brazilian cities. This naturally ventilated residence is simulated in the Airflow Network module in EnergyPlus, which utilizes the average wind pressure coefficients provided by the software. The parametric simulations vary the house orientation, U-value, heat capacity and absorptance of external walls and the roof, the heat capacity of internal walls, the window-to-wall ratio, type of window (slider or casement), and the existence of horizontal and/or vertical shading devices with varying dimensions. The models predict the resulting total degree-hours of discomfort in a year due to heat and cold, based on comfort limits defined by the adaptive method for naturally ventilated residences according to ANSI ASHRAE Standard 55. The methodology consists of (a) analyzing a set of Brazilian low-cost housing projects and defining a geometric model that can represent it; (b) determining a list of design parameters relevant to thermal comfort and defining value ranges to be considered; (c) defining the input data for the 10.000 parametric simulations used to create and test the meta-models for each analyzed climate; (d) simulating thermal performance using Energy Plus; (e) using 60% of the simulated cases to develop the regression models; and (f) using the remaining 40% data to validate the meta-models. Except by Heat discomfort regression models for the cities of Curitiba and São Paulo the meta-models show R2 values superior to 0.9 indicating accurate predictions when compared to the discomfort predicted with the output data from EnergyPlus, the original simulation software. Meta-models application tests are performed and the meta-models show great potential to guide designers decisions during the early design. / Esta pesquisa avalia as potencialidades do uso de simulações do desempenho térmico (SDT) nas etapas iniciais de projetos de habitações de interesse social (HIS) não condicionadas artificialmente. Busca-se promover e simplificar o uso de SDT no processo de projeto da envolvente de edificações através da criação de modelos de regressão baseados em simulações robustas através do software EnergyPlus. Os meta-modelos são adaptados ao clima de três cidades brasileiras: Curitiba, São Paulo e Manaus, e permitem uma rápida verificação do desconforto térmico nas edificações podendo ser usados como ferramentas de suporte às decisões de projeto nas etapas iniciais. A HIS considerada corresponde a uma unidade térrea com aproximadamente 51m2, composta por dois quartos, um banheiro e cozinha integrada à sala de jantar. Esta configuração é baseada em um conjunto de projetos representativos coletados em algumas cidades brasileiras (como São Paulo, Curitiba e Manaus). Estas habitações naturalmente ventiladas são simuladas pelo módulo Airflow Network utilizando o coeficiente médio de pressão fornecido pelo EnergyPlus. As simulações consideram a parametrização da orientação da edificação, transmitância térmica (U), capacidade térmica (Ct) e absortância () das paredes externas e cobertura; Ct e U das paredes internas; relação entre área de janela e área da parede; tipo da janela (basculante ou de correr); existência e dimensão de dispositivos verticais e horizontais de sombreamento. Os meta-modelos desenvolvidos fornecem a predição anual dos graus-hora de desconforto por frio e calor, calculados com base nos limites de conforto definidos pelo método adaptativo para residências naturalmente ventiladas (ANSI ASHRAE, 2013). A metodologia aplicada consiste em: (a) análise de um grupo de projetos de HIS brasileiras e definição de um modelo geométrico que os represente; (b) definição dos parâmetros relevantes ao conforto térmico, assim como seus intervalos de variação; (c) definição dos dados de entrada para as 10.000 simulações paramétricas utilizadas na criação e teste de confiabilidade dos meta-modelos para cada clima analisado; (d) simulação do desempenho térmico por meio do software EnergyPlus; (e) utilização de 60% dos casos simulados para o desenvolvimento dos modelos de regressão; e (f) uso dos 40% dos dados restantes para testar a confiabilidade do modelo. Exceto pelos modelos para predição do desconforto por calor para Curitiba e São Paulo, os demais meta-modelos apresentaram valores de R2 superiores a 0.9, indicando boa adequação das predições de desconforto dos modelos gerados ao desconforto calculado com base no resultado das simulações no EnergyPlus. Um teste de aplicação dos meta-modelos foi realizado, demonstrando seu grande potencial para guiar os projetistas nas decisões tomadas durante as etapas inicias de projeto.

Daylight availability in buildings faces numerous challenges in a world where energy efficiency,thermal comfort, and sustainability take center stage. Daylight is well-known for its role in reducingartificial lighting consumption and enhancing the well-being and performance of building occupants.However, a crucial issue arises with the incorporation of large windows to introduce natural light, asthis may compromise the thermal efficiency of a room. Designers must strike a delicate balancebetween optimizing daylight and ensuring thermal comfort to achieve energy-efficient buildings. Asthe global population continues to grow and urban areas become more densely populated, this issuebecomes increasingly complex and sensitive to address. Consequently, it is becoming urgent toscrutinize the effectiveness in addressing these challenges. When assessing daylight in various rooms, prevailing requirements in different regulations orstandards tend to mix all types of buildings. The author contends that a more nuanced and tailoredapproach should be adopted, depending on the type of building and the intended room usage. Whilemost studies conducted in Sweden focus on analyzing residential buildings, this master’s Thesis shiftsits focus to Swedish university buildings. The objective is to compare the existing requirement levelswith students' subjective perceptions of daylight quality, with the aim of determining whether thecurrent standards are adequate or should be adjusted. The study centers around a specific building comprising 21 distinct study spaces located at the KTHcampus in Stockholm, Sweden. Each of these spaces possessed unique characteristics that are relevantto the research. To facilitate this investigation, various modeling and daylight simulation tools wereemployed, including Rhinoceros 7, Ladybug Tools, and other editing software such as Microsoft Wordand Adobe illustrator. Ladybug relies on Radiance, a validated daylight simulation engine, for analyzingstatic and dynamic daylight metrics. This thesis, supported by survey and simulation results, illustrates that students studying in universitybuildings have a significantly higher demand for natural light compared to the levels established bySwedish regulations. These findings underscore the imperative need for comprehensive research onthe actual requirements of occupants in university buildings, with the aim of revising and modernizingthe existing Swedish regulations. The potential differentiation in standards between residential anduniversity buildings warrants further exploration. / Dagsljusautonomin i byggnader står inför flera utmaningar i en värld där energieffektivitet, termiskkomfort och hållbarhet står i centrum. Dagsljus är välkänt för sin roll i att minska konstgjord belysningoch förbättra välbefinnandet och prestandan hos byggnadens användare. En viktig fråga uppstår docknär stora fönster används för att införa naturligt ljus, eftersom detta kan kompromissa med rummetstermiska effektivitet. Designers måste hitta en balansgång mellan att optimera dagsljus ochsäkerställa termisk komfort för att uppnå perfekt energieffektivitet. I takt med att den globalabefolkningen fortsätter att växa och stadsområden blir alltmer tätbefolkade, blir denna fråga alltmerkomplex och känslig att hantera. Därför är det brådskande att granska noggrant de befintligaföreskrifterna för dagsljus. När man bedömer dagsljus i olika rum tenderar de rådande kraven i olika föreskrifter eller standarderatt blanda samman alla frekvent använda utrymmen. Författaren hävdar att en mer nyanserad ochskräddarsydd ansats bör användas, beroende på byggnadens typ och avsedd användning av utrymmet.Medan de flesta studier som utförs i Sverige fokuserar på att analysera bostadsbyggnader, ändrardenna magisteruppsats fokus till svenska universitetsbyggnader. Målet är att jämföra de befintligakravnivåerna med studenternas subjektiva uppfattning om dagsljuskvalitet, med målet att fastställaom de nuvarande standarderna är tillräckliga eller bör anpassas. Studien kretsar kring en specifik byggnad som består av 21 olika studieutrymmen som är belägna påKTH:s campus i Stockholm, Sverige. Varje av dessa utrymmen har unika egenskaper som är relevantaför forskningen. För att underlätta denna undersökning användes olika programvaruverktyg, inklusiveRhinoceros 7, Grasshopper, Microsoft Word och Adobe Illustrator. Denna avhandling, stödd av resultat från enkäter och simuleringar, visar övertygande att studentersom studerar i universitetsbyggnader har en betydligt högre efterfrågan på naturligt ljus jämfört medde nivåer som fastställts i svenska föreskrifter. Dessa resultat understryker det akuta behovet avomfattande forskning om de faktiska kraven för användarna i universitetsbyggnader, med målet attrevidera och modernisera de befintliga svenska föreskrifterna. Möjligheten att differentierastandarder mellan bostads- och universitetsbyggnader förtjänar ytterligare utforskning.