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

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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.