This study aims to analyze the relationship between spatial identity and natural light through projects that have received the Aga Khan Award for Architecture, and to determine which role of natural light is more effective in creating spatial identity. Within the scope of the study, the roles of natural light in creating spatial identity were determined under 4 main headings – functional, semantic, aesthetic, and psychological roles – with 12 criteria, through literature analysis and synthesis. In the field study, a total of 8 buildings were selected, one public building from each award cycle from 2002-2004 to the final award cycle of 2023-2025; restoration and conservation projects were excluded from the scope of the study. The projects were examined spatially and contextually through jury reports, architectural documents, and visual data. The buildings were classified into three groups – ‘effective’, ‘partially effective’, and ‘ineffective’ – based on their compliance with the criteria in the analysis table, using the parameters determined within the scope of the study. This study established a general assessment of the use of natural light in buildings; it observed that the semantic aspect of natural light is relatively more dominant in relation to spatial identity and is an effective factor in buildings receiving awards. Projects that successfully interpreted and incorporated the criteria reflecting the semantic impact of natural light on spatial identity into their designs were deemed successful by the jury, as determined by examining jury reports. Projects that successfully interpreted and incorporated the criteria reflecting the semantic impact of natural light on spatial identity into their design were found to be successful by the jury.
Optimizing classroom daylighting requires balancing daylight availability and spatial distribution while evaluating a potentially large number of window configurations. This study proposes a deterministic computational framework combining an extended Sky Factor formulation, exhaustive parametric enumeration, analytical screening, and Honeybee–Radiance evaluation. The framework was evaluated in a classroom at Universitas Sam Ratulangi, Manado, Indonesia. A calibrated digital model was used to examine 48,905 viable rectangular-window configurations defined on a 0.20 m discretization grid. Configurations satisfying the Indonesian National Standard (SNI 03-2396-2001) were ranked using the analytical Sky Factor criteria and four-point TAD, and the top 10% of compliant configurations (295 states) were subsequently evaluated using Honeybee–Radiance. The calibrated Honeybee–Radiance model showed a global MAPE of 10.24% against the available field measurements at three assessment points. The best-performing configuration among the 295 Radiance-evaluated candidates reduced the window-to-wall ratio from 46.20% to 23.68%, increased the average Daylight Factor from 0.63% to 1.35%, and reduced the daylight contrast ratio from 10.41:1 to 9.51:1 in the reported DIALux cross-check. The study demonstrates a transparent two-stage procedure that provides complete analytical coverage of a finite single-rectangle parameterization while limiting high-fidelity simulation to shortlisted candidates. The quantitative findings are restricted to the stated classroom geometry, optical boundary conditions, overcast-sky assumptions, and discretization.
Shading devices have a significant role in controlling the balance of daylight availability and solar control in office buildings. However, previous studies have focused primarily on horizontal shading systems, kinetic facades or conventional flat vertical fins. The potential of curved vertical fins in optimizing daylight has not been studied. Furthermore, the penalty schemes used in most optimization studies are uniform and do not guide the search process well towards solutions satisfying the performance requirements. The present study proposes a daylight-driven optimization framework for curved vertical shading devices applied on a south-facing office façade in Tehran, located in a hot semi-arid climate. The proposed framework combines parametric modelling, annual daylight simulation and NSGA-II optimization with a new LEED-inspired multilevel penalty function. The approach was two-stage: parametric exploration of simple shading configurations followed by form-finding optimization of curved vertical fins defined by 5 control points. The optimization was performed to maximize Useful Daylight Illuminance (UDI) and Spatial Daylight Autonomy (sDA) while minimizing Annual Sunlight Exposure (ASE). About 1,800 assessed design alternatives reached UDI values of 78.51–86.82%, sDA values of 75.89–94.64%, and ASE values of <10%, fulfilling all the preset daylight-performance criteria. The results show that the adoption of curved vertical fins significantly expands the feasible solution space compared to the conventional uniform-depth systems. Further sensitivity analysis revealed that the upper control points of the fin profile have the biggest influence on the daylight performance, while the lower control points have only small effects. The proposed framework offers an effective strategy for daylight-responsive facade design and demonstrates the potential of integrating geometric adaptability with graded constraint handling in performance-based architectural optimization.
Designing sustainable neighborhoods involves conflicting objectives. The complex parameters of neighborhoods make it challenging for designers to achieve these objectives. While trees provide shading for pedestrians and increase thermal comfort, they reduce solar radiation by shading building facades. They affect the amount of daylight entering indoors and the outdoor view. In addition to trees, it is necessary to consider building parameters and their effects on neighborhood performance while designing sustainable neighborhoods. Existing studies offer limited approaches to integrating tree allocation and building parameters, and further research is necessary to achieve multiple performance objectives using machine learning while overcoming the computational load of neighborhood simulation. This study aims to quantify the impacts of building parameters and tree placement on daylighting, solar radiation, view, and Universal Thermal Climate Index (UTCI). It generates a parametric model in Rhino/Grasshopper, including L-shaped, rectangular, and square buildings with random and grid tree allocation parameters. It uses an Artificial Neural Network (ANN) model to reduce the computational load of simulations and to provide a decision-support system that addresses complex neighborhood problems arising from combinations of tree allocation and building parameters. 1000 samples for each model, obtained from simulation, were used to train the ANN. The model successfully predicted incident solar radiation and UTCI with R² values exceeding 0.99. The optimization highlighted that grid allocation decreased UTCI to 31.15 °C, while random allocation performed 31.30 °C. The grid system minimized UTCI to 31.15 °C, increasing solar radiation to 1.33 kWh/m². L-shaped buildings decreased UTCI, while rectangular buildings increased the green view ratio to 97%. Furthermore, rectangular buildings receive daylight more uniformly than square or L-shaped forms. There is no single solution for neighborhood design; however, creating design alternatives enables designers to make data-driven decisions during the conceptual design process to identify building and tree parameters for sustainable neighborhoods.
Inadequate visual comfort in classrooms can impair the physical and mental well-being of teachers and students, making sufficient daylight essential in academic environments, particularly in hot, arid climates. This study investigates shading devices (SDs) for improving daylight performance in an existing university classroom. Parametric analysis and optimization used Autodesk Revit (BIM) with Insight plugins. An iterative, multi-objective loop evaluated each shading typology against LEED daylighting metrics [Spatial Daylight Autonomy (sDA), Annual Sunlight Exposure (ASE)], Useful Daylight Illuminance (UDI), Unified Glare Rating (UGR), and annual lighting energy, combining it with the best-performing prior configuration until all targets were simultaneously met. The classroom, with a Window-to-Wall Ratio (WWR) of 98% and window-to-floor ratio (WFR) of 52.33%, was highly susceptible to solar incursion. Simulations confirmed direct solar radiation as the primary cause of glare and visual discomfort. The Inclined Multiple Panels SD (Option 4) proved optimal, balancing daylight sufficiency (86% sDA), useful illuminance (78% UDI-autonomous), and visual comfort (UGR 0-5), while reducing annual lighting energy by 14.95%. White aluminum shading systems are recommended for solar reflectivity, durability, easy replacement, and adaptability to future remodeling. The findings highlight SDs' effectiveness in enhancing visual comfort, reducing energy loads, and supporting occupant well-being under intense solar exposure. Because the analysis relies on a single classroom with an unusually high WWR and a fixed morning observation window (8:00-9:15 AM), quantitative results are presented as a validated comparative methodology and decision-support framework for hot, arid-climate classrooms with high glazing ratios, rather than universally generalizable absolute values.
