313 citations · 704 across the 32 of their papers we have counts for
3 papers · 1 filter
A high-order partitioned solver for general multiphysics problems and its applications in optimization
Daniel Z. Huang, Per-Olof Persson, Matthew J. Zahr
A high-order accurate adjoint-based optimization framework is presented for unsteady multiphysics problems. The fully discrete adjoint solver relies on the high-order, linearly sta…
An efficient, globally convergent method for optimization under uncertainty using adaptive model reduction and sparse grids
Matthew J. Zahr, Kevin T. Carlberg, Drew P. Kouri
This work introduces a new method to efficiently solve optimization problems constrained by partial differential equations (PDEs) with uncertain coefficients. The method leverages…
High-order, linearly stable, partitioned solvers for general multiphysics problems based on implicit-explicit Runge-Kutta schemes
Daniel Z. Huang, Per-Olof Persson, Matthew J. Zahr
This work introduces a general framework for constructing high-order, linearly stable, partitioned solvers for multiphysics problems from a monolithic implicit-explicit Runge-Kutta…