8 citations · 21 across the 6 of their papers we have counts for
6 papers
Towards Universal Mesh Movement Networks
Mingrui Zhang, Chunyang Wang, Stephan Kramer +5
Solving complex Partial Differential Equations (PDEs) accurately and efficiently is an essential and challenging problem in all scientific and engineering disciplines. Mesh movemen…
E2N: Error Estimation Networks for Goal-Oriented Mesh Adaptation
Joseph G. Wallwork, Jingyi Lu, Mingrui Zhang +1
Given a partial differential equation (PDE), goal-oriented error estimation allows us to understand how errors in a diagnostic quantity of interest (QoI), or goal, occur and accumu…
Efficient optimization of a regional water elevation model with an automatically generated adjoint
Tuomas Kärnä, Joseph G. Wallwork, Stephan C. Kramer
Calibration of unknown model parameters is a common task in many ocean model applications. We present an adjoint-based optimization of an unstructured mesh shallow water model for…
M2N: Mesh Movement Networks for PDE Solvers
Wenbin Song, Mingrui Zhang, Joseph G. Wallwork +8
Mainstream numerical Partial Differential Equation (PDE) solvers require discretizing the physical domain using a mesh. Mesh movement methods aim to improve the accuracy of the num…
Parallel Metric-Based Mesh Adaptation in PETSc using ParMmg
Joseph G. Wallwork, Matthew G. Knepley, Nicolas Barral +1
This research note documents the integration of the MPI-parallel metric-based mesh adaptation toolkit ParMmg into the solver library PETSc. This coupling brings robust, scalable an…
Computing Derivatives for PETSc Adjoint Solvers using Algorithmic Differentiation
J. G. Wallwork, P. Hovland, H. Zhang +1
Most nonlinear partial differential equation (PDE) solvers require the Jacobian matrix associated to the differential operator. In PETSc, this is typically achieved by either an an…