Intelligent material and design correlation methodology towards wheel caster systems under realistic operational conditions

实际操作条件下轮式脚轮系统的智能材料和设计关联方法

• 批准号: 513457-2017
• 负责人: Czekanski, Aleksander
• 金额: $ 2.62万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=618479
• 关键词: Intelligent; material; design; correlation; methodology

The objective of the proposed study is to understand the underlying mechanics of elastomers under realistic loading and boundary conditions. This includes the correlation between material, functionality and design with elastomers performance and durability which is unique and very limited in the literature and industry. This will be achieved through developing a comprehensive test plan and data of elastomer behaviour under several loading and environmental scenarios. Statistical and machine learning methodologies and algorithms will be developed to rationally select the effective design variables for modeling and to predict the performance of elastomer systems, considering the effect of material properties, process treatment and geometrical specifications. This intelligent material and design correlation methodology would serve as a backbone of the engineering design and aid in the development, selection and optimization of new elastomer materials and designs tuned towards specific tasks, benefiting a wide range of applications. This tool would, therefore, be an added value to the body of knowledge and offer an effective design tool towards innovative engineering to the Canadian industry.

建议研究的目的是了解在实际载荷和边界条件下弹性体的基本机理。这包括材料、功能性和设计与弹性体性能和耐用性之间的相关性，这在文献和行业中是独一无二的，也是非常有限的。这将通过制定一项全面的测试计划和弹性体在几种加载和环境情况下的性能数据来实现。将开发统计和机器学习方法和算法，以合理选择有效的设计变量进行建模和预测弹性体系统的性能，同时考虑材料性能、工艺处理和几何规格的影响。这种智能材料和设计相关方法将作为工程设计的支柱，并帮助开发、选择和优化针对特定任务的新弹性体材料和设计，从而使广泛的应用受益。因此，这一工具将是知识体系的附加值，并为加拿大工业提供一种有效的创新工程设计工具。