TY - CHAP
T1 - Data-Driven Multiscale Science for Tire Compounding
T2 - Methods and Future Directions
AU - Xu, Hongyi
AU - Sheridan, Richard J.
AU - Catherine Brinson, L.
AU - Chen, Wei
AU - Jiang, Bing
AU - Papakonstantopoulos, George
AU - Polinska, Patrycja
AU - Burkhart, Craig
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Modern tire compound design is confronted with the simultaneous optimization of multiple performance properties, most of which have tradeoffs between the properties. In order to uncover new design principles to overcome these historical tradeoffs, multiscale compound experiment, physics, and simulation are being developed and integrated into next-generation design platforms across the tire industry. This chapter describes the efforts in our laboratories to quantify compound structures and properties at multiple scales—from nanometers to microns—and their application in compound simulations. This integration of experiment and simulation has been found to be critical to highlighting the levers in data-driven multiscale compound design. We also provide a glimpse into the next set of capabilities, particularly from data science, which will impact future compound design.
AB - Modern tire compound design is confronted with the simultaneous optimization of multiple performance properties, most of which have tradeoffs between the properties. In order to uncover new design principles to overcome these historical tradeoffs, multiscale compound experiment, physics, and simulation are being developed and integrated into next-generation design platforms across the tire industry. This chapter describes the efforts in our laboratories to quantify compound structures and properties at multiple scales—from nanometers to microns—and their application in compound simulations. This integration of experiment and simulation has been found to be critical to highlighting the levers in data-driven multiscale compound design. We also provide a glimpse into the next set of capabilities, particularly from data science, which will impact future compound design.
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U2 - 10.1007/978-3-030-60443-1_11
DO - 10.1007/978-3-030-60443-1_11
M3 - Chapter
AN - SCOPUS:85099496732
T3 - Springer Series in Materials Science
SP - 281
EP - 312
BT - Springer Series in Materials Science
PB - Springer Science and Business Media Deutschland GmbH
ER -