Development of a system for stress-related material development of polymer-based tribological materials by combining simple mathematical methods with artificial neural networks

通过将简单的数学方法与人工神经网络相结合，开发聚合物基摩擦材料的应力相关材料开发系统

• 批准号: 399606374
• 负责人: Professor Dr.-Ing. Alois K. Schlarb
• 金额: --
• 依托单位: Lehrstuhl für Verbundwerkstoffe (CCE)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/399606374?language=en
• 关键词: Development; system; stress; related; material

The aim of the proposed project is a model-based description and simulation of the time-dependent tribological behavior especially of the wear for an extensive collective of temperature, normal force, sliding speed, counterbody roughness, contact geometry and composition of the body material. Therefore, a combination of analytical methods and the method of Artificial Neural Networks is used. Based on the findings an optimized PEEK compound should be proposed by using a backward simulation approach and experimentally verified.

提出的项目的目的是基于模型的描述和模拟的时间依赖性的摩擦学行为，特别是磨损的温度，法向力，滑动速度，对应体粗糙度，接触几何形状和组成的身体材料的广泛的集体。因此，本文采用了解析法和人工神经网络相结合的方法.基于这些发现，应该通过使用反向模拟方法提出优化的PEEK化合物并进行实验验证。