Adaptive Shading Systems for Urban Thermal Comfort in Mixed-Use Buildings

Thesis Abstract

The rapid urbanization and climate variability increasingly challenge thermal comfort in mixed-use buildings, where diverse activities and dense urban canyons create complex solar gains, glare, and overheating risks. Adaptive shading systems offer a promising approach to modulate daylight and heat transfer while preserving visual comfort and external aesthetics, yet empirical evidence linking design parameters, occupant outcomes, and energy performance remains fragmented. This study aims to develop, implement, and evaluate an integrated adaptive shading framework that enhances urban thermal comfort without compromising daylighting and energy efficiency in mid-rise mixed-use contexts. Specific objectives are (1) to identify and formalize design variables for adaptive shading systems responsive to temporal and environmental cues; (2) to calibrate a dynamic shading model integrated with building energy simulation to predict thermal loads, daylight autonomy, and glare indices; (3) to assess occupant thermal and visual comfort, productivity, and perceived satisfaction through field measurements and surveys; (4) to quantify energy savings, peak demand reduction, and lifecycle cost implications; and (5) to formulate evidence-based guidelines for design, control strategies, and policy implications for urban mixed-use developments. The methodology adopts a mixed-methods, multi-site approach. A portfolio of three representative mid-rise mixed-use buildings in a temperate urban climate will serve as case studies. The population includes building occupants (n ? 240) and facility managers, with a purposive sample ensuring diverse floors, functions, and occupancy patterns. A two-phase data collection will be conducted over 12 months (i) instrumented monitoring of indoor environmental conditions (temperature, relative humidity, radiant temperature, air velocity), daylight metrics (illuminance, daylight factor), and energy use associated with shading actuations; and (ii) occupant surveys and interviews, complemented by observational logs for glare experiences and comfort votes. Instruments include calibrated data loggers (±0.2°C/±2% RH), sky-dome daylight sensors, high-resolution photoelectric sensors for luminance, and standardized questionnaires for thermal comfort (PMV/PPD), visual comfort, and perceived productivity. The adaptive shading system will be developed as a networked, autonomous façade with electrochromic and motorized louvers, integrated with a climate-responsive control algorithm that blends model predictive control (MPC) with occupant-adjustable overrides. Analytical techniques comprise quantitative and qualitative methods. Building energy simulations (EnergyPlus) coupled with a daylighting model (Daysim) will forecast performance under baseline and adaptive shading scenarios, with sensitivity analyses on glazing properties, shading response times, and occupancy schedules. Statistical analyses will include multilevel linear modeling to examine relationships between shading performance, thermal comfort indices, and energy consumption across spaces and times. Regression analyses will identify predictors of occupant satisfaction, while time-series analysis will explore daily and seasonal dynamics. Qualitative data from interviews will be analyzed thematically, triangulated with survey results to illuminate perceived comfort and behavioral adaptation. Theoretical framing will draw on the Preference-Performance Theory and the Theory of Adaptive Comfort to interpret how adaptive shading mediates comfort perceptions and behavioral responses under variable urban heat loads. Expected findings include significant improvements in daytime comfort metrics (reduced thermal dissatisfaction by at least 20% and glare incidents by 30%), enhanced daylight autonomy without excessive cooling loads, and measurable net energy savings (5–15% depending on case). The study anticipates identifying optimal control stratgeies that balance occupant comfort, daylight provision, and energy performance, including trade-offs between visual comfort and thermal gains under different occupancy patterns. The contribution to knowledge lies in (a) an empirically validated, climate-responsive shading framework for mixed-use urban buildings, (b) an integrated methodology linking design parameters, control strategies, and occupant outcomes, and (c) practical guidelines for engineers, architects, and policymakers aimed at achieving resilient, energy-efficient urban buildings. In conclusion, adaptive shading demonstrates potential to harmonize thermal comfort, daylighting, and energy performance in complex urban settings, informing design standards, façade performance criteria, and sustainable urban development policies. Recommendations include adopting MPC-enabled shading systems with occupant override options, early-stage façade performance modeling in design processes, and policy incentives to encourage adaptive shading retrofits in existing mixed-use portfolios.