Mathematical Modeling of Multiphysics Coupled Systems—Models, Algorithms, and Scalable Computing
|
Organizer(s): |
Name:
|
Affiliation:
|
Country:
|
Yifan Wang
|
Texas Tech University
|
USA
|
Haibiao Zheng
|
East China Normal University
|
Peoples Rep of China
|
Yizhong Sun
|
Hong Kong Baptist University
|
Peoples Rep of China
|
|
|
|
|
|
|
|
|
Introduction:
| | Whether we are modeling lab-on-a-chip microfluidics, tracking micro-plastics in the
bloodstream, optimizing offshore wind-turbine aerodynamics, or simulating plasma
behavior in fusion reactors, we encounter the same multiphysics challenge: viscous
flow, electro-osmosis, particulate or solute transport, biochemical reactions,
aerodynamic or magnetic loads, structural deformation, and thermal exchange are
entangled in tight feedback loops. These diverse applications share a core challenge:
solving nonlinear and strongly coupled system of partial differential equations with
rigorously quantified uncertainty.
This special session will unite mathematicians, computational scientists, and engineers
to advance the state of the art in model formulation, algorithm design, and scalable
implementation for multiphysics PDEs. Topics include monolithic and partitioned time-
integration, physics-aware preconditioners, reduced-order and surrogate modeling, and
open-source ecosystems for multiphysics simulations that foster reproducibility. By
exchanging best practices and spotlighting pressing engineering problems, participants
will identify common bottlenecks, spark collaborations, and outline a roadmap for next
generation multiphysics simulation at exascale.
|
|
|
|
|
|
