Architecture Engineers Award

  High-rise office buildings frequently experience airflow stagnation zones on windward façades, particularly at mid-height levels where wind streams divide upward and downward. These stagnation effects limit natural ventilation potential and increase reliance on mechanical cooling during warm seasons. This study investigates how parametric façade aperture design can strategically enhance airflow distribution and reduce cooling loads in high-rise office buildings. Focus on Stagnation-Level Floor and Design Hypothesis The research concentrates on the floor intersecting the façade stagnation point, where airflow dynamics are most constrained. It is hypothesized that optimized aperture geometry and spatial distribution can redirect pressure differentials to improve indoor ventilation performance and thermal comfort, thereby reducing cooling energy demand without mechanical intervention. Multi-Stage Methodological Framework A multi-stage methodology was implemented integrating com...

The accelerating global transition toward carbon neutrality demands rapid and reliable energy prediction tools for innovative building systems such as Building-Integrated Photovoltaic (BIPV) modular buildings. Conventional physics-based simulation methods, while accurate, are computationally intensive and unsuitable for real-time design optimization. This study proposes a novel machine learning-based rapid energy prediction methodology tailored specifically to the thermal and geometric characteristics of modular BIPV-integrated buildings. Feature Engineering for Modular Building Representation A comprehensive feature engineering framework was developed to capture the distinctive attributes of modular construction. The approach incorporates six-surface thermal property encoding, geometric parameters, and detailed solar irradiance calculations to represent envelope exposure and inter-module interactions. This structured encoding ensures that key thermal behaviors and photovoltaic infl...

Building Integrated Photovoltaic (BIPV) façades play a critical role in advancing net-zero and energy-positive building strategies by simultaneously serving as envelope elements and renewable energy generators. However, optimizing BIPV façades is challenging due to competing performance objectives, particularly photovoltaic energy generation and indoor daylighting quality. This study proposes a parametric optimization framework to systematically address these trade-offs during early-stage design. Challenges in Balancing Energy Generation and Daylighting Façade design decisions, such as window-to-wall ratio (WWR), directly influence solar exposure on opaque surfaces for photovoltaic efficiency while also affecting indoor daylight availability and visual comfort. Increasing PV-active areas often reduces daylight penetration, whereas excessive glazing can compromise energy generation potential. These conflicting requirements necessitate a multi-objective optimization approach. Paramet...

The increasing demand for old building renovation presents complex spatial, functional, and technical challenges that exceed the capacity of conventional design workflows. In response, this paper investigates the application of deep reinforcement learning (DRL) to enable automated architectural space composition under predefined built environment constraints. By integrating artificial intelligence into architectural design processes, the study positions computational intelligence as a strategic tool to improve efficiency, adaptability, and decision-making in renovation-oriented architectural practice. Reinforcement Learning Framework for Architectural Design The research establishes a dedicated reinforcement learning platform centered on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm. This framework enables multiple agents to collaboratively explore spatial configurations while responding to shared environmental constraints. By framing architectural space compo...