Novel mathematical approaches and efficient computational methods for electromagnetic simulation, remote sensing, optimization and design

Abstract

This text proposes development of scalable, accelerated spectral solvers for Partial Differential Equations (PDE) in general domains}, as well as their application in simulation and design in a range of important areas of science and engineering, and study of associated theoretical problems in PDE theory and numerical analysis. In particular, we propose development of efficient numerical methods for (a) The computational solution of linear and nonlinear Partial Differential Equations in fields such as electromagnetism, fluid?dynamics and radiative transfer, as well as (b) Related approaches in inverse design, optimization and machine learning.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 07, 2023
Source ID
FA95502110373

Entities

People

  • Oscar Bruno

Organizations

  • Air Force Office of Scientific Research
  • California Institute of Technology
  • United States Air Force

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Plasma Physics / Magnetohydrodynamics

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms