技术
- 应用基础设施与中间件 - 数据可视化
- 传感器 - 光学传感器
适用行业
- 航天
- 汽车
适用功能
- 产品研发
- 质量保证
用例
- 智能包装
- 智能照明
服务
- 测试与认证
关于客户
本案例研究中的客户是 Zipp Speed Weaponry,一家位于印第安纳波利斯的先进自行车赛车车轮和自行车零部件制造商。在阅读了美国航空航天学会 (AIAA) 会议上发表的研究论文后,Zipp 受到启发,将 CFD 技术应用于其 Firecrest 系列赛车车轮的设计。该公司对挑战关于影响自行车阻力因素的传统观点的研究结果特别感兴趣。这项研究的见解帮助 Zipp 重新描述了他们设计车轮的方法,重点是平衡速度和稳定性的竞争要求。
挑战
在自行车比赛的竞争世界中,自行车的设计和空气动力学对于自行车手的表现起着至关重要的作用。制造商不断尝试不同的车架、车轮和轮胎材料和形状,努力减轻自行车的重量和空气阻力。然而,评估系统级的阻力并隔离组件级数百个设计变量的影响一直是一个挑战。风洞测试等传统方法价格昂贵,而且计算流体动力学 (CFD) 分析工作流程过于冗长而不实用。我们面临的挑战是开发一种高度自动化、可重复的工作流程方法,以加速整个 CFD 流程,并提供有关各种组件在自行车性能中所扮演的角色的新见解。
解决方案
技术人员开发了一种高度自动化、可重复的工作流程方法来加速 CFD 流程。他们使用了各种仿真工具,包括 Altair 的 AcuSolve(一种基于有限元的通用解算器)以及 Intelligent Light 的 FieldView 13 CFD 后处理和可视化软件包。该团队研究了旋转自行车车轮和部件周围的空气动力学流动,评估了 10 个偏航角下的多个车轮和前叉/车架组合。稳态模拟生成约 3.6 GB 的 AcuSolve 数据,而非稳态模拟生成近 1.2 TB 的数据。 FieldView 的使用为团队提供了加速分析、挖掘最有价值的信息以及创建引人注目的图像和动画所需的工具。该团队还利用 FieldView FVX 编程语言自动执行许多后处理任务,从而显着减少迭代所需的时间。
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