Reference number : GC-2017-Q2-04388, amendment number : , agreement type : G, recipient legal name : Czekanski, Aleksander (York University)|Czekanski, Aleksander (Université York), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Collaborative Research and Development Grants - Project, program name french : Subventions de recherche et développement coopérative - projet, program purpose english : 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., program purpose french : 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., agreement title english : Intelligent material and design correlation methodology towards wheel caster systems under realistic operational conditions, agreement title french : Intelligent material and design correlation methodology towards wheel caster systems under realistic operational conditions, agreement number : CRDPJ, agreement value : 36000.0, agreement start date : 2017-09-20, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada