Pushing Multiscale Modeling of Battery Systems through Symbolic-Numeric Computing
Institute for Pure & Applied Mathematics (IPAM) via YouTube
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Explore advanced multiscale modeling techniques for battery systems through symbolic-numeric computing in this 55-minute conference presentation. Learn how mathematical coarse-graining theories create integrated workflows connecting scales from sub-pore to rack-scale levels, developing effective macroscopic reduced-order models with guaranteed accuracy. Discover how automated symbolic deduction accelerates rigorous multiscale model development from months to minutes, reducing time while maintaining theoretical consistency. Examine the application of these frameworks to electrochemical transport modeling from pore-scale to layer-scale and thermal runaway analysis from cell to pack scale. Understand how this approach addresses current limitations of semiempirical models that lack theoretical rigor for handling complex multiscale interactions in battery systems. Gain insights into ongoing work integrating density functional theory (DFT) with pore-scale models, and explore how these advances support battery optimization for electrification and Battery Energy Storage Systems while addressing safety risks associated with suboptimal design and operations.
Syllabus
Ilenia Battiato - Pushing Multiscale Modeling of Battery Systems through Symbolic-Numeric Computing
Taught by
Institute for Pure & Applied Mathematics (IPAM)