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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

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↗
DOE OSTI2026

Fracture Analysis of Cohesive Zone Models for Modeling Residual Stress Induced Delamination in Composite Structures

A fracture study of coupon-scale composite cylinders with embedded defects was conducted with an objective to assess and validate a modeling approach using two available cohesive material models. The study included experimental and simulation evaluations of initiation of crack growth and progression. Interrupted thermal experiments used acoustic emissions monitoring to identify the onset of crack progression during each cooling interval and ultrasonic scanning provided images of defect growth. Verification, validation, and uncertainty quantification (VVUQ) processes were performed in the assessment of the simulation predicted temperature at which crack propagation begins (quantity of interest). The Sobol sensitivity analysis identified the hoop direction elastic modulus in the carbon fiber reinforced polymer (CFRP) plies as the most influential parameter for simulations using both cohesive models, accounting for at least 70% of the variation in the temperature at crack propagation. The UQ temperature range for the Tvergaard-Hutchinson model was higher (more conservative) than the experimental acoustic measurement indicators of crack progression, while the temperature range for the Thouless-Parmigiani model enveloped the experimental data points for the primary defect size of 0.75 x 1 in. The simulations could not capture the stable crack growth indicated in the experiments. This is likely due to the models’ inability to represent anisotropic fracture toughness attributed to the structure of the orthotropic fiber weave in a woven composite laminate.

42 ENGINEERING↗
DOE OSTI2024

Discovery of genes that positively affect biomass and stress associated traits in poplar

Woody biomass serves as a renewable resource for various industries, including pulp and paper production, construction, biofuels, and electricity generation. However, the molecular mechanisms behind biomass traits are poorly understood, which significantly curtails the speed and efficiency of their improvement. We used activation tagging to discover genes that can positively affect tree biomass-associated traits. We generated and screened under greenhouse conditions a population of 2,700 independent activation tagging lines. A total of 761 lines, which had significantly and positively affected at least one biomass-associated trait, were discovered. The tag was positioned in the genome for forty lines which were affected in multiple traits and activation of proximal genes validated for a subset. For two lines we fully recapitulated the phenotype of the original lines through overexpression. Moreover, the overexpression led to more pronounced and additional improvements, not observed in the original lines. Importantly, the overexpression of a Fasciclin-like gene (PtaFLA10) and a Patatin-like gene (PtaPAT) was found to substantially improve biomass, with a 40% increase in dry-stem weight, and enhance drought tolerance, respectively. Additionally, PtaPAT overexpression increased cellulose content, which is crucial for biofuel production. Our work shows that the activation tagging approach applied even on a non-genome saturation scale in a poplar tree can be successfully used for the discovery of genes positively modify biomass productivity. Such dominant forward genetics approaches can aid in biotechnological manipulation of woody biomass traits and help unravel the functions and mechanisms of individual genes, gene families, and regulatory modules.

Plant Sciences↗
DOE OSTI2026

Decreases in polyunsaturated fatty acid content improve heat stress tolerance during flowering and silicle development in pennycress (Thlaspi arvense L.)

Introduction: Pennycress (Thlaspi arvense L.) is an emerging intermediate oilseed crop grown in the offseason between primary summer crops to produce three cash crops in two years. Previous efforts to improve seed oil quality produced Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) genome-edited lines with decreased polyunsaturated fatty acids (PUFAs) levels, through loss of function of the FATTY ACID DESATURASE 2 (FAD2), REDUCED OLEATE DESATURATION1 (ROD1), and FATTY ACID ELONGASE1 (FAE1) genes. While seed oil compositions were previously characterized, it remains unknown how vegetative and reproductive tissue compositions might differ and affect tolerance to high temperature (HT) conditions.Methods: In four growth chamber experiments, we explored HT tolerance during flowering and silicle development. Plants were subjected to a 34 °C day/28 °C night regime and compared to control plants maintained at 20 °C. Pollen grain viability at a range of temperatures, lipid peroxidation and proline content in leaves and silicles following HT, and seed yield were measured.Results: Both fad2 and rod1 mutant lines had relatively higher pollen viability (71% and 54% respectively) under moderately elevated temperature (28 °C) compared to wild-type controls (37%). They also showed smaller decreases in seed yield (0% and 40% for fad2 and rod1 respectively, compared to 61% for wild type), following HT exposure during late flowering and early silicle development. Silicles of fad2 plants experienced 65% less lipid peroxidation under HT and 55% less buildup of proline, signifying less stress.Discussion: The differential results of fad2 and rod1 are likely due to the role of FAD2 in membranes in all tissues, whereas ROD1 predominantly affects triacylglycerol (TAG) composition in oil-accumulating tissues including pollen. Our results indicate that decreasing PUFAs, through gene editing, can increase heat tolerance in reproductive tissues as an auxiliary benefit accompanying improved seed oil quality.

59 BASIC BIOLOGICAL SCIENCES↗