AI-based Generative Design: A Study on stadium mass optimization based on simulation of sunlight analysis and genetic algorithms

• 발행기관: 한국컴퓨터게임학회
• 저자명: Soochul Shin Wonhyung Lee Youngho Chai
• 간행물 정보: 『한국컴퓨터게임학회논문지』제38권 1호, 76~87쪽, 전체 12쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2025.03.31

국문 초록

Advances in digital tools and building structure technologies have enabled more flexible architectural design, with AI-based performance design gaining considerable attention as a new design methodology. Stadium design must consider the two primary elements of sports events: athletes and spectators. Given that the facade of a stadium directly impacts solar energy efficiency, it is essential to incorporate environmental performance considerations from the initial design phase. This study employs an AI-based Generative Design process to generate a facade form that efficiently manages solar radiation and daylight, satisfying two conflicting performance objectives: max- imizing sunlight for turf growth in the pitch zone and minimizing direct sunlight exposure in the stadium seating zone. The optimal solution derived ranks 331st for pitch zone sunlight and 408th for stadium seating sunlight out of a dataset of 1,000 models. While this solution does not represent the absolute best for either individual objective, it is evaluated as the most balanced alternative, achieving the goal of maximizing sunlight in the pitch zone and minimizing it in the seating zone

목차

1. 서론

2. 관련 연구 분석 및 동향

3. 연구 방법

4. 연구 결과

5. 결론 및 제언

참고문헌

키워드

Stadium design Performance-driven design Generative Design Artificial Intelligence