体育场馆设计优化

Daniel Joseph, A. B. Kim, M. Haeusler
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引用次数: 2

摘要

将计算优化工具应用于体育场馆设计已经成为一种普遍的做法。然而,优化通常只发生在宏观层面(分析整个体育场),而不是微观层面(从每个座位看)。因此,在微观层面上的设计细节(如护栏)可能会被忽视,从而给运营商带来经济损失。因此,该研究认为,每个座位都应该有一个清晰的视野,以避免财务问题。为了解决这个问题,研究团队开发并评估了一个允许将现有设计导入Rhino的脚本。首先,脚本通过颜色编码响应系统评估每个座位的视图。其次,设计师可以选择各自的座位,从乘客的视线观察到场地上的各个点,分析障碍物发生的位置。这种“双目视野”使设计师能够在项目完成之前从每个座位上评估盲点。由于脚本允许设计师自动化微观层面的分析,通过比较传统方法和自动化方法用于设计优化的时间,该研究可以说为体育场设计提供了重大改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimisation for Sport Stadium Designs
Applying computational optimisation tools for sport stadium designs has become common practice. However, optimizations often occur only on a macro level (analysing stadium as a whole) and not on a micro level (a view from each seat). Consequently, items on a micro level with design details like guardrails can be overlooked, leading to financial losses for operators. Hence, the research argues that every seat is encouraged to have a clear field of view to avoid financial complications. In order to address this problem the research team developed and evaluated a script that allowed importing an existing design into Rhino. Firstly, the script evaluates the view of each seat via a colour coded response system. Secondly, the designer can select the respective seat, and view the sightline from the occupant’s sightline to various spots on the field to analyse where the obstruction is occurring. This ‘binocular view’ enables the designer to evaluate blind spots from each seat prior to project completion. As the script allows the designer to automate the micro level analysis, the research arguably provides a significant improvement for stadium design by comparing the time used for a design optimisation in a conventional method with the automated one.
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