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At least 991 records · Page 55

Closing the Loop between In Situ Stress Complexity and EGS Fracture Complexity

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

42 ENGINEERING↗

Analysis of Deformation and Fracture Mechanisms in the Harvested Low-Dose Baffle Former Bolt via Advanced Mechanical Tests

This report details the production of tensile specimens from in-service irradiated baffle former bolts (BFBs) and presents the results of a pilot in-situ SEM/EBSD test conducted at Oak Ridge National Laboratory’s Low Activation Materials Development and Analysis (LAMDA) facility. The SEM/EDS results confirmed that the material is AISI 316L steel, not AISI 347, and that no Nb addition was detected in several analyzed locations. EBSD analysis of the microstructure revealed in-grain misorientation gradients indicative of cold work, likely caused by material processing, and no retained ferrite was identified. During straining, dislocation channel formation was the primary deformation mechanism, with twinning also observed in favorably oriented grains at local strains as small as ~1.5%. No strain-induced phase instability was observed, likely due to the fact that the Ni and Cr content reached the upper limits for the 316L steel specification. Multiple microfracture events were observed during the tensile test. Fine strain-induced pores formed at the channel-grain boundary intersection points, while coarser microcracks were associated with non-metallic inclusions. Data analysis is ongoing, and additional tests are planned in the near future to provide more statistics and details.

36 MATERIALS SCIENCE↗

Analysis of Deformation Mechanisms, Strain Localization, and Fracture in Highly Irradiated Austenitic Steels – Light-Water Reactor Core Materials – via Advanced inSEM Techniques

The present report describes the establishing of an advanced experimental approach – high-resolution digital image correlation or µDIC – for testing miniature irradiated specimens in the ORNL’s Low Activation Materials Development and Analysis (LAMDA) facility. As expected, the µDIC approach will allow for studying strain localization inside grains, for instance, during dislocation channel-grain boundary interaction processes. This information is of high importance for understanding degradation processes in irradiated austenitic steels – in-core materials of Light Water Reactors. The Level 4 report provides a brief introduction, lists materials designated for µDIC testing and delivered in LAMDA this FY, discusses methodical concerns and preliminary observations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗