arXiv subjects

Jacob S. Merson

Publications and source records attributed to Jacob S. Merson.

6 recordsLinked to original sources

arXiv2026

Unstructured Mesh Tools for Fusion Energy System Design

The execution of accurate simulations of fusion energy systems requires the appropriate representation of critical component geometries as well as the coupling of complex fusion physics codes with one another and with engineering analysis tools. This paper examines the challenges of creating simulation workflows that fully leverage existing fusion research codes while integrating them with commercial computer-aided engineering (CAE) software. Key areas addressed include: (a) the construction and meshing of analysis geometries taking full advantage of available geometric modeling and meshing technologies; (b) the effective coupling of fusion physics and engineering analysis codes; and (c) the support for simulation workflows that couple particle and continuum modeling methods.

cs.CE↗

arXiv2026

Transient Multiscale Workflow for Thermal Analysis of 3DHI Chip Stack

Modern package designs make use of technologies such as backside power delivery (BSPD) and 3D stacked chiplets that require accounting for the heterogeneity in back end of the line (BEOL) structures in hot-spot prediction. Multiscale homogenization strategies have been demonstrated to be effective for steady-state simulations, however accurate 3D transient simulations that include BEOL structures remain an open challenge. In this work, we demonstrate a transient thermal workflow that accounts for the 3D heterogeneous structures in the BEOL for problems with strong- and weak- temporal scale separation under the assumption of temperature independent constitutive properties. Our workflow, based on Bloomfield et. al. 2025, automatically extracts, meshes, and homogenizes thermal properties from GDSII and OASIS files to construct thermal property maps. Property maps (heat capacity and conductivity) have been generated for a 1 mm by 1 mm SoC-style model die that was constructed with LibreLane for 100 by 100 grids with 5 micron by 5 micron representative volume elements (RVEs), and 50 by 50 grids with 10 micron by 10 micron RVEs. The expressions for a transient effective conductivity are provided and a demonstration of the impact of the transient effects are provided for a single RVE. Finally, transient conductivity maps have been provided for a time integration timestep of dt=0.001.

cs.CE↗

arXiv2026

A Stochastic Conservative Field Transfer Method for Black-box Multiscale and Multiphysics Coupling

This paper introduces a new method for performing field transfer operations in black-box coupling, when source discretization information is not available. This approach uses a stochastic approximation of the Galerkin projection which leads to a method that asymptotically provides conservation. Error in the accuracy and conservation has been compared to the mesh intersection method and radial basis functions on a simple domain, as well as on meshes of the LTX fusion reactor. For all cases tested, our new method provides higher accuracy and less conservation error than radial basis functions and can be used for black-box coupling, unlike the mesh-intersection method. Additionally, we demonstrate the implementation and performance of our method on an NVIDIA GeForce RTX 4060 GPU, showing that the cost is competitive with the mesh intersection method.

cs.CE↗

arXiv2025

PCMS: Parallel Coupler For Multimodel Simulations

This paper presents the Parallel Coupler for Multimodel Simulations (PCMS), a new GPU accelerated generalized coupling framework for coupling simulation codes on leadership class supercomputers. PCMS includes distributed control and field mapping methods for up to five dimensions. For field mapping PCMS can utilize discretization and field information to accommodate physics constraints. PCMS is demonstrated with a coupling of the gyrokinetic microturbulence code XGC with a Monte Carlo neutral transport code DEGAS2 and with a 5D distribution function coupling of an energetic particle transport code (GNET) to a gyrokinetic microturbulence code (GTC). Weak scaling is also demonstrated on up to 2,080 GPUs of Frontier with a weak scaling efficiency of 85%.

cs.DC↗

arXiv2025

GPU Acceleration of Monte Carlo Tallies on Unstructured Meshes in OpenMC with PUMI-Tally

Unstructured mesh tallies are a bottleneck in Monte Carlo neutral particle transport simulations of fusion reactors. This paper introduces the PUMI-Tally library that takes advantage of mesh adjacency information to accelerate these tallies on CPUs and GPUs. For a fixed source simulation using track-length tallies, we achieved a speed-up of 19.7X on an NVIDIA A100, and 9.2X using OpenMP on 128 threads of two AMD EPYC 7763 CPUs on NERSC Perlmutter. On the Empire AI alpha system, we achieved a speed-up of 20X using an NVIDIA H100 and 96 threads of an Intel Xenon 8568Y+. Our method showed better scaling with number of particles and number of elements. Additionally, we observed a 199X reduction in the number of allocations during initialization and the first three iterations, with a similar overall memory consumption. And, our hybrid CPU/GPU method demonstrated a 6.69X improvement in the energy consumption over the current approach.

cs.DC↗

arXiv2024

A Physics Preserving Neural Network Based Approach for Constitutive Modeling of Isotropic Fibrous Materials

We develop a new neural network architecture that strictly enforces constitutive constraints such as polyconvexity, frame-indifference, and the symmetry of the stress and material stiffness. Additionally, we show that the accuracy of the stress and material stiffness predictions is significantly improved for this neural network by using a Sobolev minimization strategy that includes derivative terms. Using our neural network, we model the constitutive behavior of fibrous-type discrete network material. With Sobolev minimization, we obtain a normalized mean square error of 0.15% for the strain energy density, 0.815% averaged across the components of the stress, and 5.4% averaged across the components of the stiffness tensor. This machine-learned constitutive model was deployed in a finite element simulation of a facet capsular ligament. The displacement fields and stress-strain curves were compared to a multiscale simulation that required running on a GPU-based supercomputer. The new approach maintained upward of 85% accuracy in stress up to 70% strain while reducing the computation cost by orders of magnitude.

physics.bio-ph↗