Data-Driven Multiscale Science for Tread Compounding

TitleData-Driven Multiscale Science for Tread Compounding
Publication TypeJournal Article
Year of Publication2022
AuthorsC Burkhart, B Jiang, G Papakonstantopoulos, P Polinska, H Xu, RJ Sheridan, LC Brinson, and W Chen
JournalTire Science and Technology
Date Published06/2022

<jats:p>Tread compounding has always been faced with the simultaneous optimization of multiple performance properties, most of which have tradeoffs between the properties. The search for overcoming these conflicting tradeoffs have led many companies in the tire industry to discover and develop material physics-based platforms. This report describes some of our efforts to quantify compound structures and properties at multiple scales, and their subsequent application in compound design. Integration of experiment and simulation has been found to be critical to highlighting the levers in data-driven multiscale compound tread design.</jats:p>

Short TitleTire Science and Technology