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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Block-Structured Adaptive Mesh Framework to Solve Radiation Transfer Equation in Irregular Embedded Geometries

Radiation transport arises in various scientific, industrial, and medical fields, and understanding its effect in applications is needed to make accurate predictions, safety assessments and performance optimizations. Solving the Radiation Transport Equation (RTE) is challenging due to its integro-differential nature, which involves both differential and integral terms. The differential term describes the change in radiation intensity due to absorption and emission, while the integral term accounts for scattering. The accurate modeling of radiation is further complicated in many applications due to the complex, irregular geometries. Various methods exist for solving the RTE, including the zonal, Monte Carlo, spherical harmonics, discrete ordinates, and finite volume methods. Traditional mesh-based approaches, which rely on structured or unstructured meshes, struggle with irregular geometries due to: a) the difficulty of conforming structured grids to irregular domains, b) challenges in enforcing boundary conditions correctly, and c) the additional computational cost of unstructured mesh methods. This work presents a second-order accurate method for solving the RTE in irregular geometries. The radiation intensity is discretized using the finite-volume method in both spatial and angular directions on regular Cartesian grid blocks. Leveraging the block-structured adaptive mesh refinement (AMR) framework provided by AMReX, our method refines the grid locally to reduce spatial discretization error, ensuring a converged numerical solution while minimizing computational costs elsewhere. A two-stage deferred correction approach is employed: First, a first-order discretization on grid blocks is solved using an algebraic multigrid method in HYPRE. Second, a correction term is applied explicitly to achieve second-order accuracy. The correction term is calculated by approximating the radiation flux on cell faces using a Total Variation Diminishing (TVD) scheme. This approach ensures quick convergence of the multigrid method while preserving higher-order accuracy of the numerical solution. Irregular geometries are resolved as embedded boundaries (EB), resulting in both cut cells and regular cells. In cut cells, we modify the fluxes using face fractions and incorporate additional contributions from EB boundary conditions. To ensure higher-order convergence near the EB interface, the correction term is modified by interpolating the radiation intensity to fictitious ghost points. The implementation takes advantage of modern supercomputers by leveraging AMReX’sMPI/X parallelization strategy where X can be MPI or a GPU accelerator including CUDA, HIP and DPC++. We validate our solver using classical test cases, both with and without EB, demonstrating accuracy and efficiency. Additionally, we analyze the impact of adaptive mesh refinement on solution accuracy and computational cost, highlighting the advantages of our approach for high-resolution radiation transport simulations.

computational fluid dynamics (CFD)↗
DOE OSTI2025

Hierarchical Bayesian Modeling for Cosmology: Can NPE reliably replace MCMC?

Hierarchical neural posterior estimation has its place Hierarchical Bayesian Modeling (HBM) combined with MCMC algorithms has been shown to provide more robust and accurate inference for real-world phenomena in which nature takes a nested form. However, MCMC-based inference can be computationally expensive, and its performance often suffers for complex posterior geometries. These costs are especially pertinent for HBM. Studies have recently demonstrated the potential for a flexible, expressive, and amortized hierarchical neural posterior estimator (HNPE) built on Normalizing Flows. These studies have mostly been performed on simple datasets, or they focus on a single parameter from each level of the hierarchy. A systematic study analyzing how both hierarchical methods compare for more complex and realistic datasets is necessary before applying HNPE for scientific measurements. Here, we re-explore the theory behind HNPE and conduct comparative numerical experiments of HNPE and MCMC-based HBM methods on real and synthetic data, including strong gravitational lensing simulations. In particular, we use a suite of diagnostics to show trade-offs in terms of accuracy, precision, time to train or sample, reproducibility, and the need for expert domain knowledge. Especially for higher dimensional and complex posteriors, HNPE is expected to drastically improve on time for inference, accuracy, and precision with an upfront training time cost.

Hur, Rachel [Chicago U.] (ORCID:000900089890445X)↗
DOE OSTI2021

The influence of preexisting host rock damage on fault network localization

The transition from stable to unstable fracture propagation occurs when fractures begin to interact and link. Thus, fracture network coalescence controls how rocks and engineered structures fail. Here, to constrain the factors that influence localization in shear zones under brittle conditions, we build discrete element method models with a rough fault embedded in a shear zone. We add varying numbers of diffuse, randomly-placed weaknesses to examine the influence of diffuse damage on fracture network localization. The number of weaknesses controls the localization behavior of the fault network and the final fault geometry. We quantify localization using the Gini coefficient of the fracture volume, which measures the nonuniformity in a population. Each model generally increases in localization toward failure. However, models with more diffuse damage experience delocalization phases that are superimposed on the overall trend of increasing localization. The observed link between delocalization and host rock damage may help explain the varying localization of low magnitude seismicity in southern California. Models with more diffuse damage produce more complex fault geometries comprised of several parallel strands of wing cracks. The propagation of these wing cracks reduces the shear stress acting on the model boundaries, indicating that this fracture development increases the mechanical efficiency of the system.

58 GEOSCIENCES↗
DOE OSTI2024

ASMS 2024 Investigation of Uranyl Perchlorate Anion Complexes in the Gas Phase via Infrared Multiphoton Dissociation and Collision Induced Dissociation

Investigation of Uranyl Perchlorate Anion Complexes in the Gas Phase via Infrared Multiphoton Dissociation and Collision Induced Dissociation Brittany D. M. Hodges, Christopher A. Zarzana, JungSoo Kim, Jonathan Martens, and W. C. M. Berden Introduction (120 words max) Effects of electronic structure on chemical bonding and reactivity play critical roles shaping the chemical bonding and reactivity behaviors of heavy elements. Understanding the role of f electrons in bond formation between the actinide-series elements like uranium with other ligands is critical for solving technical challenges associated with these heavy elements, important to nuclear fuel cycles, efficient separations of rare earth metals, and understanding the chemistry of stored nuclear fuels and related environmental management sites. In this study, we further examine the interactions between uranyl and the perchlorate ion in order to understand the structures of these ions through the use of IRMPD. Here we report the IRMPD spectra of [UO2(ClO4)3]-, [UO3(ClO4)2]-, and a proposed transition state. Methods (120 word max) IRMPD spectra and CID spectra were acquired using a Bruker amaZon QIT/MS instrument at the Free-Electron Lasers for Infrared eXperiments (FELIX) laboratory at Radboud University. The FELIX QIT/MS is modified to allow for the high-intensity tunable IR beam from FELIX to be directed into the ion packet, resulting in multiphoton dissociation that is measured only when the IR frequency is in resonance with an adequately high absorption vibrational mode of the mass-selected complex. DFT geometry optimizations and frequency calculations using the Gaussian suite of programs were performed using B3LYP, TPSSh, and PBE0 level of theory with 6-31+G(d) basis for the O, C, H, and N atoms and the SDD basis set for U. The SDD basis set employs the Stuttgart/Dresden effective core potential. Preliminary Data or Plenary Speakers Abstract (300 words max) Metal ion clusters of uranyl perchlorate were formed via direct electrospray ionization. For each metal ligand complex of interest, the parent ion was isolated and collision induced dissociation fragmentation and Infrared Multiphoton Dissociation (IRMPD) fragmentation spectra were acquired. Results presented here are the first look at the IRMPD spectra of [UO3(ClO4)2]-, [UO2(ClO4)3]-. Structures were examined using Gaussian at different levels of theory B3LYP level of theory, TPPSh and PBE0 levels, to reflect the behaviors of uranium metal ligand complexes most accurately. In these structures, we identified an overlap between each of these uranyl stretches resulting in their largely being obscured by a perchlorate mode. The CID product spectra agree with similar structures reported by Groenewold for uranyl nitrate in 2006 (10.1021/ja058106n).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine-Learning-Based High-Resolution Earthquake Catalog Reveals How Complex Fault Structures Were Activated during the 2016–2017 Central Italy Sequence

The 2016–2017 central Italy seismic sequence occurred on an 80 km long normal-fault system. The sequence initiated with the Mw 6.0 Amatrice event on 24 August 2016, followed by the Mw 5.9 Visso event on 26 October and the Mw 6.5 Norcia event on 30 October. We analyze continuous data from a dense network of 139 seismic stations to build a high-precision catalog of ~900,000 earthquakes spanning a 1 yr period, based on arrival times derived using a deep-neural-network-based picker. Our catalog contains an order of magnitude more events than the catalog routinely produced by the local earthquake monitoring agency. Aftershock activity reveals the geometry of complex fault structures activated during the earthquake sequence and provides additional insights into the potential factors controlling the development of the largest events. Activated fault structures in the northern and southern regions appear complementary to faults activated during the 1997 Colfiorito and 2009 L’Aquila sequences, suggesting that earthquake triggering primarily occurs on critically stressed faults. Delineated major fault zones are relatively thick compared to estimated earthquake location uncertainties, and a large number of kilometer-long faults and diffuse seismicity were activated during the sequence. These properties might be related to fault age, roughness, and the complexity of inherited structures. The rich details resolvable in this catalog will facilitate continued investigation of this energetic and well-recorded earthquake sequence.

58 GEOSCIENCES↗
DOE OSTI2022

Volumetric additive manufacturing of silica glass with microscale computed axial lithography

Glass is increasingly desired as a material for manufacturing complex microscopic geometries, from the micro-optics in compact consumer products to microfluidic systems for chemical synthesis and biological analyses. As the size, geometric, surface roughness, and mechanical strength requirements of glass evolve, conventional processing methods are challenged. We introduce microscale computed axial lithography (micro-CAL) of fused silica components, by tomographically illuminating a photopolymer-silica nanocomposite that is then sintered. We fabricated three-dimensional microfluidics with internal diameters of 150 micrometers, free-form micro-optical elements with a surface roughness of 6 nanometers, and complex high-strength trusses and lattice structures with minimum feature sizes of 50 micrometers. As a high-speed, layer-free digital light manufacturing process, micro-CAL can process nanocomposites with high solids content and high geometric freedom, enabling new device structures and applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Novel superposed kinklike and pulselike solutions for several nonlocal nonlinear equations

In this work, we show that a number of nonlocal nonlinear equations, including the Ablowitz–Musslimani and Yang variant of the nonlocal nonlinear Schrödinger (NLS) equation, the nonlocal modified Korteweg de Vries (mKdV) equation, and the nonlocal Hirota equation, admit novel kinklike and pulselike superposed periodic solutions. Furthermore, we show that the nonlocal mKdV equation also admits the superposed (hyperbolic) kink–antikink solution. In addition, we show that while the nonlocal Ablowitz–Musslimani variant of the NLS admits complex parity-time reversal-invariant kink and pulse solutions, neither the local NLS nor the Yang variant of the nonlocal NLS admits such solutions. Finally, except for the Yang variant of the nonlocal NLS, we show that the other three nonlocal equations admit both the kink and pulse solutions in the same model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A high accuracy/resolution spectral element/Fourier–Galerkin method for the simulation of shoaling non-linear internal waves and turbulence in long domains with variable bathymetry

A high-order hybrid continuous-Galerkin numerical method, designed for the simulation of non-linear, non -hydrostatic internal waves and turbulence in long computational domains with complex bathymetry, is presented. The spatial discretization in the non-periodic wave-propagating directions, utilizes the nodal spectral element method. Such a high-order element-based discretization allows the highly accurate representation of complex domain geometry along with the flexibility of concentrating resolution in areas of interest. Under the assumption of the normal-to-isobath propagation of non-linear internal waves, a third periodic direction is incorporated via a Fourier-Galerkin discretization. The distinct non-hydrostatic nature of non-linear internal waves and, any instabilities and turbulence therein, necessitates the numerically challenging solution of the pressure Poisson problem. A defining feature of this work is the application of a domain decomposition approach, combined with block-Jacobi/deflation-based preconditioning to the pressure Poisson problem. Such a combined approach is particularly suitable for the long high aspect-ratio complex domains of interest and enables the efficient high-accuracy reproduction of the non-hydrostatic dynamics of non-linear internal waves. Implementation details are also described in the context of the stability of the solver and its parallelization strategy. A series of benchmarks of increasing complexity demonstrate the robustness of the flow solver. The benchmarks culminate with the three-dimensional simulation of a convectively breaking mode-one non-linear internal wave over a realistic South-China-Sea bathymetric transect and background current/stratification profiles.

Deflation↗
DOE OSTI2025

COG11.3 Abstract

COG is a high-resolution code for the Monte Carlo simulation of coupled particle transport in arbitrary3-D geometry. COG will transport neutrons, protons, deuterons, alpha particles with energies up to hundreds of GeV, and photons with energy ranges limited by the available cross section sets and physics models. Electrons can be transported via the EGS5 electron transport kernel, electrons can also be transported. The COG code is a significant upgrade from earlier Monte Carlo transport codes and has been written specifically to makes it more versatile, accurate, and easy to use. COG has provisions for calculating deep penetration (shielding) problems, criticality problems, and neutron activation problems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Monodomain Liquid‐Crystal Elastomer Lattices for Broad Strain‐Rate Mechanical Damping

Designing structures that effectively dissipate energy across a broad range of mechanical loading rates, including those from compression, shock, and vibration, poses a significant engineering challenge. In this study, liquid‐crystal elastomers (LCEs), which possess anisotropic properties due to the alignment of their polymer backbone, are explored. As a result, LCEs exhibit a soft elastic response under mechanical loading, making them ideal for energy dissipation. Advances in additive manufacturing (AM) enable simple fabrication of foamlike dissipative structures with complex lattice geometries. Herein, direct ink write 3D printing, an extrusion AM method, is used to fabricate aligned, monodomain LCE lattice structures for broad strain‐rate mechanical damping. In this work, it is shown that these structures can dissipate strain energy in quasi‐static environments, comparable to traditional elastomeric lattices, and provide improved damping under high strain‐rate drop testing due to LCE soft elasticity. Additionally, under dynamic mechanical vibration, monodomain LCE lattices enhance damping at structural natural frequencies and provide high‐frequency attenuation. Finally, in these findings, a promising method is presented for fabricating mechanical damping devices that effectively dissipate energy across a broad range of loading rates.

3D printings↗
DOE OSTI2022

Electronic Properties of the Weyl Semimetals Co 2 MnX (X=Si, Ge, Sn)

Using first-principles electronic structure calculations, iwe show that ferromagnetic Heusler compounds Co2MnX (X = Si, Ge, Sn) present nontrivial topological characteristics and belong to the category of Weyl semimetals. These materials exhibit two topologically interesting band crossings near the Fermi level. These band crossings have complex 3D geometries in the Brillouin zone and are characterized by nontrivial topology as Hopf links and chain-like nodal lines that are protected by the perpendicular mirror planes. The spin–orbit interaction split these nodal lines into several 0D Weyl band crossings. Unlike previously known topologically nontrivial Heusler materials, these majority spin band crossings lie in or very near to the bandgap of minority spin bands, potentially facilitating experimental observation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Wire arc additive manufactured A36 steel performance for marine renewable energy systems

Additive manufacturing has established itself to be advantageous beyond small-scale prototyping, now supporting full-scale production of components for a variety of applications. Despite its integration across industries, marine renewable energy technology is one largely untapped application with potential to bolster clean energy production on the global scale. Wave energy converters (WEC) are one specific facet within this realm that could benefit from AM. As such, wire arc additive manufacturing (WAAM) has been identified as a practical method to produce larger scale marine energy components by leveraging cost-effective and readily available A36 steel feedstock material. The flexibility associated with WAAM can benefit production of WEC by producing more complex structural geometries that are challenging to produce traditionally. Additionally, for large components where fine details are less critical, the high deposition rate of WAAM in comparison to traditional wrought techniques could reduce build times by an order of magnitude. In this context of building and supporting WEC, which experience harsh marine environments, an understanding of performance under large loads and corrosive environments must be understood. Hence, WAAM and wrought A36 steel tensile samples were manufactured, and mechanical properties compared under both dry and corroded conditions. Here, the unique microstructure created via the WAAM process was found to directly correlate to the increased ultimate tensile and yield strength compared to the wrought condition. Static corrosion testing in a simulated saltwater environment in parallel with electrochemical testing highlighted an outperformance of corroded WAAM A36 steel than wrought, despite having a slighter higher corrosion rate. Ultimately, this study shows how marine energy systems may benefit from additive manufacturing components and provides a foundation for future applications of WAAM A36 steel.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A variational multiscale immersed meshfree method for heterogeneous materials

Abstract We introduce an immersed meshfree formulation for modeling heterogeneous materials with flexible non-body-fitted discretizations, approximations, and quadrature rules. The interfacial compatibility condition is imposed by a volumetric constraint, which avoids a tedious contour integral for complex material geometry. The proposed immersed approach is formulated under a variational multiscale based formulation, termed the variational multiscale immersed method (VMIM). Under this framework, the solution approximation on either the foreground or the background can be decoupled into coarse-scale and fine-scale in the variational equations, where the fine-scale approximation represents a correction to the residual of the coarse-scale equations. The resulting fine-scale solution leads to a residual-based stabilization in the VMIM discrete equations. The employment of reproducing kernel (RK) approximation for the coarse- and fine-scale variables allows arbitrary order of continuity in the approximation, which is particularly advantageous for modeling heterogeneous materials. The effectiveness of VMIM is demonstrated with several numerical examples, showing accuracy, stability, and discretization efficiency of the proposed method.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Segregated Approach for Modeling the Electrochemistry in the 3-D Microstructure of Li-Ion Batteries and Its Acceleration Using Block Preconditioners

Abstract Battery performance is strongly correlated with electrode microstructure. Electrode materials for lithium-ion batteries have complex microstructure geometries that require millions of degrees of freedom to solve the electrochemical system at the microstructure scale. A fast-iterative solver with an appropriate preconditioner is then required to simulate large representative volume in a reasonable time. In this work, a finite element electrochemical model is developed to resolve the concentration and potential within the electrode active materials and the electrolyte domains at the microstructure scale, with an emphasis on numerical stability and scaling performances. The block Gauss-Seidel (BGS) numerical method is implemented because the system of equations within the electrodes is coupled only through the nonlinear Butler–Volmer equation, which governs the electrochemical reaction at the interface between the domains. The best solution strategy found in this work consists of splitting the system into two blocks—one for the concentration and one for the potential field—and then performing block generalized minimal residual preconditioned with algebraic multigrid, using the FEniCS and the Portable, Extensible Toolkit for Scientific Computation libraries. Significant improvements in terms of time to solution (six times faster) and memory usage (halving) are achieved compared with the MUltifrontal Massively Parallel sparse direct Solver. Additionally, BGS experiences decent strong parallel scaling within the electrode domains. Last, the system of equations is modified to specifically address numerical instability induced by electrolyte depletion, which is particularly valuable for simulating fast-charge scenarios relevant for automotive application.

25 ENERGY STORAGE↗
DOE OSTI2026

An Anisotropic Yield and Damage Material Model to Improve the Contact Pressure Analysis in a Biomass Shredding System

Size reduction systems used in biomass processing break biomass into smaller pieces by utilizing the kinetic energy from the sharp rotating blades. Abrasive and/or erosive wear caused by biomass comminution results in blade wear of the sharp edged cutters, deteriorating the process efficiency. Here, this study aims to optimize the blade design and improve the system efficiency by attempting to understand the interactions between the blades and biomass particles. Since real-time monitoring of these interactions is impractical during operation, mechanical simulations offer a viable alternative for investigating the shredding process. Yet, the irregular geometry and complex mechanical properties of biomass—such as the anisotropic nature of woodchips and their nonlinear fracture behavior—pose significant challenges for accurately simulating contact pressure. In this work an anisotropic yield material model, along with a damage initiation and evolution function, is applied to the woodchip particle to study the contact pressure on shredder blade, offering a scientific basis for improved blade design and process efficiency. This approach can be extended to other biomass processing systems with similar anisotropic feedstocks, making it a valuable tool for advancing sustainable biomass utilization.

09 - BIOMASS FUELS↗
DOE OSTI2020

Non-destructive simulation of node defects in additively manufactured lattice structures

Additive Manufacturing (AM), commonly referred to as 3D printing, offers the ability to not only fabricate geometrically complex lattice structures but parts in which lattice topologies in-fill volumes bounded by complex surface geometries. However, current AM processes produce defects on the strut and node elements which make up the lattice structure. This creates an inherent difference between the as-designed and as-fabricated geometries, which negatively affects predictions (via numerical simulation) of the lattice’s mechanical performance. Although experimental and numerical analysis of an AM lattice’s bulk structure, unit cell and struts have been performed, there exists almost no research data on the mechanical response of the individual as-manufactured lattice node elements. Here we propose a methodology that, for the first time, allows non-destructive quantification of the mechanical response of node elements within an as-manufactured lattice structure. A custom-developed tool is used to extract and classify each individual node geometry from micro-computed tomography scans of an AM fabricated lattice. Voxel-based finite element meshes are generated for numerical simulation and the mechanical response distribution is compared to that of the idealised computer-aided design model. The method demonstrates compatibility with Uncertainty Quantification methods that provide opportunities for efficient prediction of a population of nodal responses from sampled data. Overall, the non-destructive and automated nature of the node extraction and response evaluation is promising for its application in qualification and certification of additively manufactured lattice structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Grain structure and texture selection regimes in metal powder bed fusion

Additive manufacturing (AM) offers opportunities to produce complex part geometries not possible with conventional processing and in some cases even improve part performance. However, adoption has been slowed by difficulties assessing microstructure variability and there is no straightforward approach to relate processing to grain structure characteristics. In this study, datasets from AdditiveFOAM heat transport simulations of laser powder bed fusion (LPBF) are used to drive ExaCA simulations of grain structure. The GPU utilization of ExaCA and an algorithmic update for modeling melt pool overlap region solidification enabled rapid and parallel simulation across a wider range of process conditions than previously explored with cellular automata-based solidification models. A texture selection angle $θ_s$ is defined based on melt pool overlap geometry, and the range of $θ_s$ over which a commonly observed texture transition occurs in characterized AM builds was well-reproduced by ExaCA simulations over a wide range of melt pool shape, hatch spacing, and layer height. ExaCA simulations with 90 degree rotation of the scan direction on every other layer reproduced a number of trends from the AM literature including grain refinement, the dominance of layers with larger melt pools on the final grain structure, and the weakening or strengthening of texture depending on odd and even layer melt pool overlap geometry. EBSD data from a benchmark AM part is used to validate the simulated mechanism of a layer rotation-induced texture strengthening effect. Importantly, these results expand the understanding of the mechanisms for texture selection in alloys with cubic crystal symmetry and offer an approach to easily evaluate processing conditions. With this new understanding, these modeling tools will enable anticipation of previously unexpected variations in grain structure and target specific microstructures and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗