優化自動生成住宿建築之研究

文化大學機構典藏 CCUR > 環境規劃暨生物資源學院 > 環境設計學院 > 建築及都市設計學系所 > 博碩士論文 > Item 987654321/53465

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题名:	優化自動生成住宿建築之研究 A Study of Optimization on Automated Generation of Residential Building
作者:	諶雨萱
贡献者:	建築及都市設計學系
关键词:	用戶偏好平面生成參數化設計優化空間佈局遺傳演算法建築性能模擬 User Preferences Floor Plan Generation Parametric Design Spatial L ayout Optimization Genetic Algorithms Building Performance Simulation
日期:	2024
上传时间:	2024-07-16 14:31:48 (UTC+8)
摘要:	隨著城市化進程不斷加快，現在的城市更加追求人文關懷。如何基於不同個體下，滿足不同個體對住宿建築的需求是目前需要探究的問題。本研究將深入探討居民偏好與住宿建築設計的關係，並針對福州的亞熱帶濕潤氣候，提出一套基於參數化設計的住宿建築佈局優化策略。通過訪談收集福州居民對住宿類型、面積和空間佈局的需求資訊，利用拓撲原理和Grasshopper 外掛程式構建了一個能動態反映居民偏好的參數化住宿建築模型。本文集成建築物理環境模擬和遺傳演算法，探索基於性能條件下建築平面生成的過程，特別強調了參數化設計和建築性能優化二者的關聯。首先通過訪談不同生活需求的居民，歸納其需求並繪製出反映其空間偏好的網路關係圖，進而生成針對個體的空間佈局“泡泡圖????。在參數化設計過程中，引入居住者偏好生成個性化的空間關聯圖和具體平面圖，結合參數化特性運用 Ladybug、Honeybee 等物理模擬軟體優化建築佈局，實現了高度個性化且能效優化的住宿建築設計方案。面對福州極端高溫環境的挑戰，本研究不僅評估了各種優化方案在採光係數和熱舒適性等關鍵方面的表現，還將此評估流程放置于生成前期，以直觀地反映和應對當地氣候地理特色。通過將居民的偏好置於設計過程前端，展示了如何利用參數化設計方法和物理環境模擬技術，實現既滿足居民需求又具有環境可持續性的住宿建築設計。本研究的創新之處在於將居民偏好直接融入住宿設計的參數化過程中，通過前瞻性的設計策略和技術應用，為福州乃至類似氣候條件地區的住宿建築設計提供了新的視角和方法。這些成果對建築設計實踐具有重要意義，也為未來關於居民行為與建築設計相結合的研究提供了寶貴的參考。 With the rapid advancement of urbanization, contemporary cities increasingly emphasize human-centered care. Addressing the varied accommodation needs of different individuals has become a critical issue for investigation. This study delves into the relationship between residents' preferences and accommodation building design, proposing an optimization strategy for accommodation layout based on parametric design, specifically tailored to Fuzhou's subtropical humid climate. By interviewing Fuzhou residents, the study collects data on their preferences regarding accommodation types, area, and spatial layout. Utilizing topological principles and the Grasshopper plug-in, a dynamic parametric accommodation building model reflecting residents' preferences was constructed. This paper integrates architectural physical environment simulation and genetic algorithms to explore the process of building floor plan generation based on performance conditions, emphasizing the correlation between parametric design and architectural performance optimization. Initially, residents with diverse living needs were interviewed to summarize their requirements, which were then used to create network diagrams reflecting their spatial preferences. These diagrams subsequently generated individual-specific spatial layout "bubble diagrams." During the parametric design process, residents' preferences were incorporated to generate personalized spatial correlation diagrams and detailed floor plans. Leveraging parametric characteristics and using physical simulation software like Ladybug and Honeybee, the building layout was optimized to achieve a highly personalized and energy-efficient accommodation design solution. Confronting the challenge of Fuzhou's extreme high-temperature environment, this study not only assessed various optimization schemes in terms of daylight coefficient and thermal comfort but also incorporated this evaluation into the early design stage to intuitively reflect and address the local climatic and geographical features. By placing residents' preferences at the forefront of the design process, the study demonstrates how parametric design methods and physical environment simulation technologies can create accommodation building designs that meet residents' needs while ensuring environmental sustainability. The innovation of this study lies in directly integrating residents' preferences into the parametric design process of accommodation buildings. Through forward-looking design strategies and technological applications, it provides new perspectives and methods for accommodation building design in Fuzhou and other regions with similar climatic conditions. These findings hold significant implications for architectural design practice and offer valuable references for future research combining resident behavior with architectural design.
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