技术
- 传感器 - 环境传感器
适用行业
- 建筑物
- 水泥
适用功能
- 产品研发
用例
- 结构健康监测
- 虚拟原型与产品测试
关于客户
本案例研究的客户是丹麦奥胡斯建筑学院。该学校有兴趣探索将基于仿真的拓扑优化(一种汽车、航空和海军工业常用的技术)应用于建筑混凝土结构的潜力。学校的目标是将其与用于混凝土浇筑的聚苯乙烯模板的机器人制造结合起来。该项目由担任项目经理和工程师的 Per Dombernowsky 和负责项目设计和优化方面的 Asbjørn Søndergaard 领导。 Unikabeton 原型项目是丹麦建筑行业八家最大的机构和公司的共同努力。
挑战
丹麦奥胡斯建筑学院热衷于探索将基于仿真的拓扑优化(一种汽车、航空和海军工业常用的技术)应用于建筑混凝土结构的潜力。面临的挑战是将其与用于混凝土浇筑的聚苯乙烯模板的机器人制造结合起来。 Unikabeton 原型项目就是为此目的而创建的,涉及丹麦建筑行业八家最大的机构和公司之间的合作。然而,计算机优化工具的使用对于建筑领域来说很大程度上是陌生的。人们不愿意将设计控制权交给优化软件,而建筑行业的这种保守主义提出了重大挑战。 Unikabeton 项目是最早致力于在建筑设计中使用拓扑优化的学术研究项目之一。考虑到混凝土生产产生的二氧化碳排放量占全球总排放量的 5%,潜在的回报是巨大的。
解决方案
该团队选择 Altair 的 HyperWorks 进行优化实验,特别看重 HyperWorks 套件中的 OptiStruct。他们首先对数字化制造过程进行了结构分析和小规模模拟,将拓扑优化的效果与一系列熟悉的预制和现浇混凝土构件进行了比较。与标准等效结构相比,优化的结构减少了 60% 至 70% 的材料使用量,同时满足规范的结构要求。然后,该团队开始优化由三个不对称放置的混凝土柱支撑的不均匀双弯曲混凝土板。为了满足结构 EPS 模板 CNC 铣削工艺的制造要求,进行了拓扑优化。这些模板由聚苯乙烯块铣削而成,使用传统的组装技术和脚手架在现场组装,并将自密实混凝土浇注到模板中。建筑师必须制定新的设计干预策略,其形式是“非设计空间”——在优化过程中被排除的区域。
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