A performance-based generative design framework based on a design grammar for high-rise office towers during early design stage

IF 3.1 1区 艺术学 0 ARCHITECTURE
Liwei Chen, Ye Zhang, Yue Zheng
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Abstract

In the past decade, the construction speed of high-rise office towers worldwide has exhibited explosive growth. The unique morphological characteristics of high-rise office towers result in higher shape factors and relatively larger thermal loads. The traditional workflow of “design-evaluation” in the early stages of design imposes constraints on the diversity of tower morphology, the timeliness of performance evaluation, and the efficient integration of systems. Therefore, targeting the geometric characteristics of high-rise office towers, a systematically developed and universally applicable design grammar, named “Vertex-Based Polygonal Generative Grammar (VPGG)” is proposed. Additionally, a corresponding early-stage performance driven High-rise Office Tower Generative Design Framework (HOT_GDF) is introduced. Case study results demonstrate that, with the support of Artificial Neural Network, utilizing this system can not only globally explore the diversity of tower morphologies but also efficiently uncover greater energy-saving potential in complex architectural forms compared to simpler cubic forms, with an improvement of up to 7.76% during the early stages of design. Designed from the perspective of architects, the framework achieves logical, refined, and visual real-time interaction between computers and human minds during the early stages of tower design. This enhances design efficiency and facilitates design decision-making. It systematically integrates considerations for environmental performance, such as thermal load and thermal comfort, into the design process. Furthermore, it couples various aspects of morphological design with corresponding building performance, helping users in making design decisions from a rational and quantifiable perspective. This captures greater design potential, encompassing both form and performance, for high-rise office towers during the initial design phase.

Abstract Image

基于设计语法的高层办公大楼早期设计阶段基于性能的生成设计框架
近十年来,全球高层办公大楼的建设速度呈现爆发式增长。高层办公大楼独特的形态特征导致其外形系数较高,热负荷相对较大。传统的设计前期“设计-评价”的工作流程限制了塔楼形态的多样性、绩效评价的及时性和系统的高效集成。因此,针对高层办公大楼的几何特点,提出了一种系统发展和普遍适用的设计语法——“基于顶点的多边形生成语法(VPGG)”。此外,还介绍了相应的早期绩效驱动的高层办公大楼生成设计框架(HOT_GDF)。案例研究结果表明,在人工神经网络的支持下,利用该系统不仅可以在全球范围内探索塔楼形态的多样性,而且可以有效地揭示复杂建筑形式与简单立方体形式相比更大的节能潜力,在设计早期阶段的节能效果可达7.76%。该框架从建筑师的角度设计,在塔楼设计的早期阶段实现了计算机与人的思想之间的逻辑,精炼和可视化的实时交互。这提高了设计效率,便于设计决策。它系统地将环境性能的考虑因素,如热负荷和热舒适,纳入设计过程。此外,它将形态设计的各个方面与相应的建筑性能相结合,帮助用户从理性和可量化的角度做出设计决策。这在初始设计阶段为高层办公大楼捕获了更大的设计潜力,包括形式和性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.20
自引率
2.90%
发文量
430
审稿时长
30 weeks
期刊介绍: Frontiers of Architectural Research is an international journal that publishes original research papers, review articles, and case studies to promote rapid communication and exchange among scholars, architects, and engineers. This journal introduces and reviews significant and pioneering achievements in the field of architecture research. Subject areas include the primary branches of architecture, such as architectural design and theory, architectural science and technology, urban planning, landscaping architecture, existing building renovation, and architectural heritage conservation. The journal encourages studies based on a rigorous scientific approach and state-of-the-art technology. All published papers reflect original research works and basic theories, models, computing, and design in architecture. High-quality papers addressing the social aspects of architecture are also welcome. This journal is strictly peer-reviewed and accepts only original manuscripts submitted in English.
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