ETHOS: Enabling Technologies for High-Order Simulations
The Enabling Technologies for High-Order Simulations (ETHOS) project performs research of fundamental mathematical technologies for next-generation high-order simulations algorithms. The current focus is on advancing the theoretical understanding and practical utility of unstructured meshes with arbitrarily high-order curvilinear elements by researching key challenges associated with high-order mesh quality optimization and simulation-driven adaptivity.
With support from the Applied Mathematics research program in the Department of Energy (DOE) Office of Science, the ETHOS team performs fundamental research that is broadly applicable to many high-order simulation approaches, including high-order finite elements and tightly coupled arbitrary Lagrangian-Eulerian (ALE) simulations of interest to the DOE. Our research builds on the Target-Matrix Optimization Paradigm (TMOP) and nonlinear variational minimization to develop new node-movement strategies for high-order mesh quality optimization and adaptation in both purely geometric settings, as well as in the context of a given physical simulation.
High-order meshes are difficult to control
- High-order simulations rely on high-order meshes, and bad mesh quality leads to small time steps and applications failures.
- In addition to good geometric quality, applications can require high-order mesh adaptivity to dynamic simulation features.
Our solution: Develop theory that rigorously defines high-order mesh quality
- We are extending the TMOP of Knupp to high-order meshes, defining pointwise quality based on sub-zonal information, and optimizing the mesh node positions with respect to an aggregated quality measure. The TMOP variational minimization technique is based on optimizing an objective function that depends on a quality metric measuring the difference between the current and target geometric parameters of the mesh.
- We are currently exploring (nonlinear) solvers for the global optimization problem, incorporating research in constrained optimization, linear and nonlinear solvers, and preconditioners.
- We are developing the TMOP-based variational formulation for the upcoming exascale architectures.
- We are also interested in mesh generation, surface optimization, h- and hp-refinement, and more.
Impact: Mesh optimization is relevant to a wide range of applications. Some innovations under the ETHOS project include:
- Methods for systematic generation of geometric target parameter values (size, aspect-ratio, skew, and orientation) that vary over mesh elements or sample points. Permits flexible and precise control over essential geometric quality features of mesh, tailored to any specific application.
- Simulation-based adaptivity to optimize meshes during runtime using the solution of the PDE. This approach has already demonstrated significant impact in improving solution accuracy and computational efficiency for ALE hydrodynamics.
- Adaptivity with node-limiting to optimize the geometric quality of the mesh while minimizing the change associated with a discrete function defined on the original mesh. This functionality enables tangential relaxation for surface meshes and optimization of meshes for multi-material applications.
- Mesh optimization for applications where symmetry preservation or adaptation to physics is important (e.g., inertial confinement fusion [ICF] and tokamak magnetohydrodynamics).
- TMOP-based energy estimator to augment r-adaptivity with anisotropic mesh refinement. This allows us to satisfy size and aspect-ratio targets in cases where the topology of the original mesh does not allow the geometric targets to be met.
- The ETHOS algorithms are freely available on the MFEM website.
Vladimir Tomov (LLNL)
Patrick Knupp (Dihedral, LLC)
Tzanio Kolev (LLNL) – Project Leader
Veselin Dobrev (LLNL)
Ketan Mittal (LLNL)
- Many of the high-order mesh optimization algorithms developed in the ETHOS project are freely available in a user-friendly form in the MFEM finite element library.
- See in particular the Mesh Optimizer miniapp in the miniapps/meshing directory and the TMOP sources in the fem directory.
- V. Dobrev, P. Knupp, Tz. Kolev, K. Mittal, R. Rieben, and V. Tomov, Simulation-Driven Optimization of High-Order Meshes in ALE Hydrodynamics. Computers & Fluids, 104602 (2020).
- P. Knupp, Target formulation and construction in mesh quality improvement (No. LLNL-TR-795097). Lawrence Livermore National Laboratory, Livermore, CA (2019).
- V. Dobrev, P. Knupp, Tz. Kolev, and V. Tomov, Towards Simulation-Driven Optimization of High-Order Meshes by the Target-Matrix Optimization Paradigm, In International Meshing Roundtable (pp. 285-302). Springer, Cham (2019).
- V. Dobrev, P. Knupp, Tz. Kolev, K. Mittal, and V. Tomov, The Target-Matrix Optimization Paradigm for High-Order Meshes, SIAM J. Sci. Comput., 41(1), pp. B50–B68, (2019).
- R. Anderson, V. Dobrev, Tz. Kolev, R. Rieben, and V. Tomov, High-Order Multi-Material ALE Hydrodynamics, SIAM J. Sci. Comp., Vol. 40(1), pp. B32–B58, (2018).
- P. Knupp, Introducing the target-matrix paradigm for mesh optimization by node movement, Engineering with Computers 28(4), pp. 419–429, (2012).
- Size and aspect-ratio based adaptivity using a material indicator function defined on a cartesian mesh.
- Simulation-based r-adaptivity for the gas impact problem. Click here for a movie.
- Comparison of a cartesian mesh and an optimized mesh for the triple-point problem. r-adaptivity using the solution at runtime enables mesh alignment with material interfaces which reduces numerical discretization error.
- Comparison of a mesh obtained from multi-material ALE hydronamics calculation in Laghos with r-adaptivity and hr-adaptivity meshes.
- Some fun mesh optimization using images. The meshes shown below are colored by element sizes.