Special Session 126: Machine Learning and New Framework for Solving Partial Differential Equations

A novel shape optimization approach for source identification in elliptic equations

Wei Gong
Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Peoples Rep of China
Co-Author(s):    Wei Gong and Ziyi Zhang
Abstract:
In this talk, we propose a novel shape optimization approach for the source identification of elliptic equations. This identification problem arises from two application backgrounds: actuator placement in PDE-constrained optimal controls and the regularized least-squares formulation of source identifications. The optimization problem seeks both the source strength and its support. By eliminating the variable associated with the source strength, we reduce the problem to a shape optimization problem for a coupled elliptic system, known as the first-order optimality system. As a model problem, we derive the shape derivative for the regularized least-squares formulation of the inverse source problem and propose a gradient descent shape optimization algorithm, implemented using the level-set method. Several numerical experiments are presented to demonstrate the efficiency of our proposed algorithms.