Public Abstract

DE-SC0023346: Center for Hierarchical and Robust Modeling of Non-Equilibrium Transport (CHaRMNET)

Award Status: Active

Institution: The Regents of the University of Colorado d/b/a University of Colorado, Boulder, CO
UEI: SPVKK1RC2MZ3
DUNS: 007431505

Most Recent Award Date: 07/20/2023
Number of Support Periods: 2
PM: Spotz, William

Current Budget Period: 09/01/2023 - 08/31/2024
Current Project Period: 09/01/2022 - 08/31/2027
PI: Bortz, David

Supplement Budget Period: N/A

Public Abstract

The Center for Hierarchical and Robust Modeling of Non-Equilibrium Transport (CHaRMNET) focuses on laying the mathematical foundations to enable optimal design/control and high-consequence decision making in National-Security and clean-energy settings, where non-equilibrium, multi-scale plasma transport plays a critical role. Such applications are multi-scale in the sense that quantities of interest that we seek to measure at the macroscopic scale are strongly driven by effects at much smaller/shorter scales. While the enormous multi-decade national investment in massively parallel computational resources has had a transformational impact on fields as diverse as aircraft development, the understanding of complex biological processes, subsurface reservoir management, and weather predictions, many of the plasma-driven problems of critical importance remain computationally intractable due to their multi-scale character. This center is motivated by the need to develop accurate long-term modeling of plasma systems for fusion energy and national security that are suitable for optimization and uncertainty quantification at the engineering scale. Plasma-mediated thermonuclear fusion (the subject of a recent Summit at the White House) promises clean energy that is environmentally responsible, which is essential to the survival of the human race and the health of the planet. Thermonuclear fusion also plays an important role in National Security. Developing the mathematical and computational capabilities to address such currently intractable multi-scale problems in plasma science will provide us a means to truly impact both clean energy and national security realms and will make accessible new opportunities to leverage the unique behaviors of plasmas for other engineering applications. Led by Michigan State University and Los Alamos National Laboratory, CHaRMET brings together national leaders from five universities and four national labs in the mathematical modeling of plasmas. The center seeks to build a first-of-its-kind holistic approach that will exploit structure within models to mitigate the curse of dimensionality and to bridge a wide range of length and time scales in plasma science. The curse of dimensionality is a critical challenge that is pervasive throughout computational science and refers to the observation that the resources needed to solve a problem on a computer scale exponentially with the dimension of the problem. Fundamental plasma models are seven dimensional and are presently computationally intractable (with existing mathematical methods and computational resources) to drive optimization and uncertainty quantification at the engineering scale of plasma systems. The CHaRMNET team will take a holistic approach based on (1) a synergistic theoretical and data-driven approach to hierarchical modeling, including a wide range of surrogates; (2) next-generation multi-resolution, mixed-model algorithms that provide a self-adaptive structure in terms of the methods and the models; and (3) structure and asymptotic preserving algorithms that enforce model consistency throughout the model hierarchy. A key component will be a comprehensive characterization of error and uncertainty that will enable automated model selection in addition to facilitating robust design, control, and decision making.

The Center for Hierarchical and Robust Modeling of Non-Equilibrium Transport (CHaRMNET) focuses on laying the mathematical foundations to enable optimal design/control and high-consequence decision making in National-Security and clean-energy settings, where non-equilibrium, multi-scale plasma transport plays a critical role. Such applications are multi-scale in the sense that quantities of interest that we seek to measure at the macroscopic scale are strongly driven by effects at much smaller/shorter scales. While the enormous multi-decade national investment in massively parallel computational resources has had a transformational impact on fields as diverse as aircraft development, the understanding of complex biological processes, subsurface reservoir management, and weather predictions, many of the plasma-driven problems of critical importance remain computationally intractable due to their multi-scale character. This center is motivated by the need to develop accurate long-term modeling of plasma systems for fusion energy and national security that are suitable for optimization and uncertainty quantification at the engineering scale. Plasma-mediated thermonuclear fusion (the subject of a recent Summit at the White House) promises clean energy that is environmentally responsible, which is essential to the survival of the human race and the health of the planet. Thermonuclear fusion also plays an important role in National Security. Developing the mathematical and computational capabilities to address such currently intractable multi-scale problems in plasma science will provide us a means to truly impact both clean energy and national security realms and will make accessible new opportunities to leverage the unique behaviors of plasmas for other engineering applications.

Led by Michigan State University and Los Alamos National Laboratory, CHaRMET brings together national leaders from five universities and four national labs in the mathematical modeling of plasmas. The center seeks to build a first-of-its-kind holistic approach that will exploit structure within models to mitigate the curse of dimensionality and to bridge a wide range of length and time scales in plasma science. The curse of dimensionality is a critical challenge that is pervasive throughout computational science and refers to the observation that the resources needed to solve a problem on a computer scale exponentially with the dimension of the problem. Fundamental plasma models are seven dimensional and are presently computationally intractable (with existing mathematical methods and computational resources) to drive optimization and uncertainty quantification at the engineering scale of plasma systems.

The CHaRMNET team will take a holistic approach based on (1) a synergistic theoretical and data-driven approach to hierarchical modeling, including a wide range of surrogates; (2) next-generation multi-resolution, mixed-model algorithms that provide a self-adaptive structure in terms of the methods and the models; and (3) structure and asymptotic preserving algorithms that enforce model consistency throughout the model hierarchy. A key component will be a comprehensive characterization of error and uncertainty that will enable automated model selection in addition to facilitating robust design, control, and decision making.