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Automatic Optimization of Air Conduct Design Using Experimental Data and Numerical Results

机译:利用实验数据和数值结果自动优化空气导管设计

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摘要

The development of a new product is a process that goes through several phases, each of them requiring the capitalization of data, information, knowledge and experiences gathered from previous projects. This knowledge is kept by a limited number "Experts", and is not necessarily captured in a practical, reusable way, which translates into a loss of time and a delay for the projects. Our approach involves exporting the client's specifications from a PLM platform and constructing a generic product, an automotive air conduct, from them. This generic product is then fed through an optimization cycle to determine the best position and geometrical shape for all its elements. This multi-criteria optimization requires several constraints and objective functions in order to improve the part quality and process reliability needed expected by the Original Equipment Manufacturer (OEM). The need to have a design process less dependent on personal "expert" knowledge was the driving idea behind this work. The automatic optimization of the design of an'air conduct still remains a challenge and the purpose of this work is to contribute to the development of an automatic design tools capable of doing this.
机译:新产品的开发过程涉及多个阶段,每个阶段都需要将以前项目中收集的数据,信息,知识和经验转化为资本。该知识由有限数量的“专家”保存,并不一定以实用,可重用的方式获取,这意味着时间的浪费和项目的延迟。我们的方法涉及从PLM平台导出客户的规范,并从中构造通用产品,即汽车空气导管。然后,将这个通用产品送入优化周期,以确定其所有元素的最佳位置和几何形状。此多准则优化需要几个约束和目标功能,以提高原始设备制造商(OEM)期望的零件质量和过程可靠性。减少对设计过程的依赖取决于个人“专家”知识的需求是这项工作的驱动思想。空气行为设计的自动优化仍然是一个挑战,这项工作的目的是促进能够做到这一点的自动设计工具的发展。

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