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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Standardized Analysis Process Using Digital Image Correlation to Calculate In Situ Cladding Strain from Modified Burst Tests for Fuel Performance Code Validation

Historical data collection on nuclear fuel cladding materials has focused on generating a statistically significant amount of data to assess the material and its failure behavior. Furthermore, data generated to support material model and failure criteria development were previously posttest evaluations, so a large number of tests was required to gain new understanding. A way to expedite this process is to develop techniques capable of generating large, high-fidelity data sets from a single test with lower uncertainty or quantified uncertainty. One such example of this approach is Oak Ridge National Laboratory’s use of modified burst tests (MBTs) to analyze the mechanical behavior and failure conditions of cladding during a simulated reactivity-initiated accident (RIA). Each test incorporates digital image correlation (DIC) analysis techniques that are used to assess the accumulated strain in situ, as well as eventual cladding failure. This work has been fruitful in defining strain-to-failure conditions for materials like silicon carbide (SiC) fiber–reinforced/SiC matrix composite tubes (SiC/SiC), iron-chromium-aluminum (FeCrAl) alloy tubes, and chromium-coated Zircaloy-4 tubes. However, there are numerous DIC software available, including open-source and proprietary software. The different DIC software use various algorithms to process images and calculate displacement values. Using these different software and algorithms can lead to varying results, and perhaps larger-than-expected uncertainties. In the present study, previously published MBT data encompassing a variety of test conditions were reanalyzed with two different DIC software to assess the variance in the calculated strain results. The data consisted of SiC/SiC, FeCrAl, and chromium-coated Zircaloy-4 tubes. Plots of the calculated strains during the transient revealed good agreement between the two DIC software. The average root-mean-square errors between the two software was 0.20% strain, which is slightly larger than a previously reported error value for these tests. In conclusion, this variance in results is low enough that this analysis method can be used for code validation.

Reactivity-initiated accident↗
DOE OSTI2022

Covariance matrices for variance-suppressed simulations

ABSTRACT Cosmological N-body simulations provide numerical predictions of the structure of the Universe against which to compare data from ongoing and future surveys, but the growing volume of the Universe mapped by surveys requires correspondingly lower statistical uncertainties in simulations, usually achieved by increasing simulation sizes at the expense of computational power. It was recently proposed to reduce simulation variance without incurring additional computational costs by adopting fixed-amplitude initial conditions. This method has been demonstrated not to introduce bias in various statistics, including the two-point statistics of galaxy samples typically used for extracting cosmological parameters from galaxy redshift survey data, but requires us to revisit current methods for estimating covariance matrices of clustering statistics for simulations. In this work, we find that it is not trivial to construct covariance matrices analytically for fixed-amplitude simulations, but we demonstrate that ezmock (Effective Zel’dovich approximation mock catalogue), the most efficient method for constructing mock catalogues with accurate two- and three-point statistics, provides reasonable covariance matrix estimates for such simulations. We further examine how the variance suppression obtained by amplitude-fixing depends on three-point clustering, small-scale clustering, and galaxy bias, and propose intuitive explanations for the effects we observe based on the ezmock bias model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

guppy i : a code for reducing the storage requirements of cosmological simulations

ABSTRACT As cosmological simulations have grown in size, the permanent storage requirements of their particle data have also grown. Even modest simulations present a major logistical challenge for the groups which run these boxes and researchers without access to high performance computing facilities often need to restrict their analysis to lower quality data. In this paper, we present guppy, a compression algorithm and code base tailored to reduce the sizes of dark matter-only cosmological simulations by approximately an order of magnitude. guppy is a ‘lossy’ algorithm, meaning that it injects a small amount of controlled and uncorrelated noise into particle properties. We perform extensive tests on the impact that this noise has on the internal structure of dark matter haloes, and identify conservative accuracy limits which ensure that compression has no practical impact on single-snapshot halo properties, profiles, and abundances. We also release functional prototype libraries in C, Python, and Go for reading and creating guppy data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Biased degenerate ground-state sampling of small Ising models with converged quantum approximate optimization algorithm

The quantum alternating operator ansatz, a generalization of the quantum approximate optimization algorithm (QAOA), is a quantum algorithm used for approximately solving combinatorial optimization problems. QAOA typically uses the transverse field mixer as the driving Hamiltonian. One of the interesting properties of the transverse field driving Hamiltonian is that it results in nonuniform sampling of degenerate ground states of optimization problems. In this study, we numerically examine the fair sampling properties of the transverse field mixer QAOA, and Grover mixer QAOA (GM-QAOA), which provides theoretical guarantees of fair sampling of degenerate optimal solutions, up to a large enough p such that the mean expectation value converges to an optimal approximation ratio of 1. This comparison is performed with high-quality heuristically computed, but not necessarily optimal, QAOA angles, which give strictly monotonically improving solution quality as p increases. These angles are computed using the Julia based numerical simulation software JuliQAOA. Fair sampling of degenerate ground states is quantified using the Shannon entropy of the ground-state amplitudes distribution. The fair sampling properties are reported on several quantum signature Hamiltonians from previous quantum annealing fair sampling studies. Small random fully connected spin glasses are shown, which exhibit exponential suppression of some degenerate ground states with transverse field mixer QAOA. The transverse field mixer QAOA simulations show that some problem instances clearly saturate the Shannon entropy of 0 with a maximally biased distribution that occurs when the learning converges to an approximation ratio of 1 while other problem instances never deviate from a maximum Shannon entropy (uniform distribution) at any p step. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Reduced Order Modeling for Accelerating Numerical Simulations (ROMANS)

SAND2021-15064 O ROMANS, or Reduced Order Modeling for Accelerating Numerical Simulations, is an open source software for accelerating numerical simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Martin, Shawn↗
DOE OSTI2023

Semi-Analytical Leakage Solutions for Aquifers (SALSA) v1

SALSA is a semi-analytical modeling tool that can provide assessments of pressure perturbations and brine leakage because of fluid injection and extraction activities in sedimentary basins. Sedimentary basins typically contain vertical sequences of near-horizontal aquifers separated by less-permeable aquitards. In the context of geologic carbon sequestration (GCS), while aquitards are relied upon to contain injected buoyant free-phase CO2 and limit inter-aquifer brine flow, the large number of leaky wells (e.g., unused/unsuccessful exploration wells, or improperly plugged water or oil/gas wells) that are present in sedimentary basins creates concerns for potential leakage and groundwater contamination. The mathematical theory and solution method included in SALSA is presented in our recent manuscript under review. SALSA is the first to account for the coupled leakage through aquitards and leaky wells, with geologic pressurization sources. SALSA based on semi-analytical solutions can be computationally very efficient for problems containing many injection and leaky wells in multilayered sedimentary systems, compared to any numerical simulation software requiring local mesh refinement around each well to obtain accurate results. Therefore, stakeholders (e.g., regulators, operators) for site screening, injection and post-injection pressure behavior and assessing leakage risks can use SALSA as a fast-predictive tool in GCS applications in multilayered aquifer systems.

Cihan, Abdullah↗
DOE OSTI2023

BaseBuddy v1

The software "BaseBuddy" (basebuddy.lbl.gov) is a user-friendly web app designed for codon optimization of heterologous genes. Codon optimization is a widely used technique to enhance the expression levels of non-native genes. Our app is built on the DNA Chisel Python library (Zulkower and Rosser, 2020), which offers highly customizable and transparent gene optimization. Unlike DNA Chisel, which is a command-line interface software with numerous optional functions, our web app simplifies the process for users. Additionally, while DNA Chisel relies on the outdated Kazusa codon usage database, our app introduces the option to utilize the most recent version of the CoCoPUTs database (Athey et al., 2017). By incorporating CoCoPUTs, we also expand the range of target organisms and maintain up-to-date sequencing data for more accurate codon optimization results.

Schmidt, Matthias↗
DOE OSTI2022

Fast BLT Code

This note discusses numerical algorithmic software design considerations and performance estimates for a fast BLT coupling code [1] written in c++. The aim of this code is to conduct faster parameter studies over line orientations. The original matlab code was written by Mike Rivera. Art Barnes ported this code to julia. I rewrote portions of the code for speed improvement, mainly to eliminate some redundant computation when calculating many line orientations. But this code is still far from optimal.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

2.1.1.1.401 - Wave Energy Converter Modeling

The Wave Energy Converter (WEC) Modeling Project began in 2013 with the aim of driving innovation and advancing the state of the wave energy industry by developing publicly available, easy to use software that's customizable to meet end user needs. This project is primarily focused on development of open source software for numerical design and analysis of wave energy converters (WEC), and it also supports international collaboration on standards (IEC TC 114), code verification and validation (IEA OES Task 10) and a competition (WECCCOMP).

MATHEMATICS AND COMPUTING,TIDAL AND WAVE POWER↗
DOE OSTI2022

Toward a Unified Framework for WEC Numerical Modeling

This presentation is about moving toward a united framework for WEC numerical modeling. A unified framework for WEC numerical modeling could help device developers on three fronts: 1) optimization; 2) more accurate load estimates; 3) validation.

modeling↗
DOE OSTI2022

Hexagonal Distributed Embedded Energy Converters (HexDEECs)

The HexDEEC is a small, characteristic length approximating a centimeter, energy transducer that converts the dynamic deformations of its elastomer housing into electricity through a variable capacitance charging-discharging cycle. This device is a type of Distributed Embedded Energy Converter Technology (DEEC-Tec), a new domain for marine renewable energy research that utilizes a conglomeration of small distributed embedded energy converters (DEECs) that, in aggregate, form larger metamaterial frameworks. These resulting DEEC-Tec metamaterials can then, in turn, be used to construct flexible ocean wave energy converters called flexWECs, which can utilize a broad band of ocean wave frequencies and lack highly loaded rigid bodies. These systems also provide new avenues of wave energy harvesting such as actively transforming topologies (e.g., shape and form) and morphologies (e.g., stiffness and damping throughout its entire structure) in real time. Presented, is one specific type of DEEC: the HexDEEC, which is currently being developed by the United States National Renewable Energy Laboratory. This transducer shows promise in aiding the adoption and further development of the DEEC-Tec domain. The following presentation focuses on the promise of this technology and current work being done to analyze the performance of an individual HexDEEC design. The HexDEEC is composed of a hyperelastic hexagonal housing, nominally silicon rubber, with six electrodes on its inner faces. The upper three electrodes share the same charge while the lower three electrodes oppose the upper electrode charges. Externally, the HexDEEC has two arms extending away from the middle vertices of the hexagon. Via principles governing the relationship between electrical capacitance and electrical potential (voltage and charge), electricity is generated when the HexDEEC's arms are dynamically pulled or released under tensile loading, as doing so causes the distance between the upper and lower sets of electrodes to change - varying the energy converter's overall capacitance. Analytical and numerical modeling is being used to evaluate the mechanics and electrical energy generated by the HexDEEC. Equations to describe the capacitance and electrostatic forces acting on this unique system have been developed and implemented into the numerical modeling software STAR-CCM+, along with models to describe its hyperelastic material, such as the Mooney-Rivlin 3-parameter model. So far, an initial design has been analyzed and we plan to further optimize it to increase power production. Individual HexDEECs have been fabricated by drawing uncured liquid silicon rubber into molds via vacuum pressure. To simplify manufacturing, HexDEEC sub-components - e.g., electrodes, wires - can be placed within those molds such that they are directly embedded into the hexagonal housing during the curing process. Furthermore, DEEC-Tec metamaterials can be created by interweaving or sequentially layering multiple HexDEEC strands together. The HexDEEC based metamaterial could then generate electricity through its gross deformations. Ultimately, HexDEECs represent a specific type of energy transducer that can be leveraged, by the DEEC-Tec domain, to create metamaterials used to construct novel flexWECs.

DEEC-Tec↗
DOE OSTI2024

Building and Sustaining a Community Resource for Best Practices in Scientific Software: The Story of BSSw.io

The development of scientific software—a cornerstone of long-term collaboration and scientific progress—parallels the development of other types of software but still poses distinct challenges, especially in high-performance computing. Although web searches yield numerous resources on software engineering, there is still a scarcity specifically for scientific software development. Here, this article introduces the Better Scientific Software site (https://bssw.io), a platform that hosts a community of researchers, developers, and practitioners who share their experiences and insights on scientific software development. Since 2017, this collaborative hub has gained traction within the scientific computing community, attracting a growing number of readers and contributors eager to share ideas and elevate their software development practices. In sharing the BSSw.io site’s story, we hope to encourage further growth of the BSSw.io community through both readership and contributors, with a long-term goal of fostering culture change by increasing emphasis on best practices in scientific software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

MAGMA: Enabling exascale performance with accelerated BLAS and LAPACK for diverse GPU architectures

MAGMA (Matrix Algebra for GPU and Multicore Architectures) is a pivotal open-source library in the landscape of GPU-enabled dense and sparse linear algebra computations. With a repertoire of approximately 750 numerical routines across four precisions, MAGMA is deeply ingrained in the DOE software stack, playing a crucial role in high-performance computing. Notable projects such as ExaConstit, HiOP, MARBL, and STRUMPACK, among others, directly harness the capabilities of MAGMA. In addition, the MAGMA development team has been acknowledged multiple times for contributing to the vendors’ numerical software stacks. Looking back over the time of the Exascale Computing Project (ECP), we highlight how MAGMA has adapted to recent changes in modern HPC systems, especially the growing gap between CPU and GPU compute capabilities, as well as the introduction of low precision arithmetic in modern GPUs. We also describe MAGMA’s direct impact on several ECP projects. Maintaining portable performance across NVIDIA and AMD GPUs, and with current efforts toward supporting Intel GPUs, MAGMA ensures its adaptability and relevance in the ever-evolving landscape of GPU architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Status of SPCA-ANL Software Development, Software Quality Assurance, and Application (FY2025)

SPCA-ANL is a simulation tool used to perform deterministic analyses of sodium spray and pool fires. Development of the SPCA-II (Spray Pool Combustion Analysis) code began in the mid- 1980s as part of the Clinch River Breeder Reactor (CRBR) Project. At that time, development of SPCA-II, which was led by Rockwell International, was focused on treatment of large-scale sodium spray, stream, and pool fires that were anticipated to be prototypic of the steam generator building cells in CRBR. Under more recent DOE NE programmatic activities, the SPCA-II code was recovered from existing literature and underwent minor modifications to generate a stable executable. This recovered version of the code was not formally released. As part of the Versatile Test Reactor (VTR) Project in the 2010s, the SPCA-II code underwent key modifications to improve stability, address modeling deficiencies, improve consistency between the code manual and software, and address numerous bugs. At this point, SPCA-II was renamed SPCA-ANL. Given that SPCA-II served as the original basis for SPCA-ANL, both codes share an integrated history. Following termination of the VTR Project, the DOE NE Fast Reactor Program resumed support of the software with the goal of building and maintaining software infrastructure that can enable commercial-grade dedication of SPCA-ANL by an end user. Version 1.0, the first external release of SPCA-ANL, was generated in June 2024. This report summarizes the development and maintenance activities completed for SPCAANL in FY2025. This year’s work was focused on improving quality and usability of the code. The provisional Software Quality Assurance (SQA) program has been established and was used to test the procedures for infrastructure improvements, code development, bug fixes, and code releases, as described in the following sections of this report. A code Version 1.0.1 was released in FY25, as described in Chapter 4.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

SAM: A Modern System Code for Advanced Non-LWR Safety Analysis

The System Analysis Module (SAM), developed at Argonne National Laboratory and by collaborators at other organizations, is for advanced non–light water reactor safety analysis. SAM aims to provide fast-running, modest-fidelity, whole-plant transient analysis capabilities that are essential for fast-turnaround design scoping and engineering analyses of advanced reactor concepts. To facilitate code development, SAM utilizes the MOOSE object-oriented application framework, its underlying finite element library, and linear and nonlinear solvers to leverage modern advanced software environments and numerical methods. SAM aims to solve tightly coupled physical phenomena, including fission reaction, heat transfer, fluid dynamics, and thermal-mechanical responses in advanced reactor structures, systems, and components with high accuracy and efficiency. Finally, this paper gives an overview of the SAM code development, including goals and functional requirements, physical models, current capabilities, verification and validation, software quality assurance, and examples of simulations for advanced nuclear reactor applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Hermes-3: Multi-component plasma simulations with BOUT++

A new open source tool for fluid simulation of multi-component plasmas is presented, based on a flexible software design that is applicable to scientific simulations in a wide range of fields. Hermes-3 is built on plasma simulation framework BOUT++, consolidating earlier SD1D and Hermes models into a single code that can be configured at run-time to solve plasma models in 1D, 2D or 3D, either for transport (steady-state) or turbulent (time-evolving) problems, with an arbitrary number of ion and neutral species. Here, we describe the improved numerical algorithms and software design that have been implemented in Hermes-3. To demonstrate the capabilities of this tool, applications relevant to the boundary of tokamak plasmas are presented: 1D simulations of diveror plasmas evolving equations for all charge states of neon and deuterium; 2D transport simulations of tokamak equilibria in single-null X-point geometry with plasma ion and neutral atom species; and simulations of the time-dependent propagation of plasma filaments (blobs). Hermes-3 is publicly available on Github under the GPL-3 open source license. The repository includes documentation and a suite of unit, integrated and convergence tests.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Feasibility Study on Implementing a Staggered-Grid Finite Volume Method for System Analysis Code Development Under the MOOSE Framework

Here, this work summarizes a feasibility study on testing numerical algorithms that are suitable and efficient for advanced system analysis code development under the mutli-physics framework, MOOSE. The key to the test bed is the implementation of high-order one-dimensional staggered-grid finite volume method (SG-FVM), and its direct interaction with the linear/nonlinear solver, PETSc. The test bed utilized a more flexible code structure to enable the finite volume method implementation and direct interacting with the solver package, instead of using the natively supported finite element method by the framework. Using a suite of selected test problems with different problem sizes and levels of complexity, the implemented SG-FVM demonstrated superior performance improvement against a direct finite element method implementation through MOOSE. On two computer systems, the speedup was observed to be significant, with at least one order of magnitude of solving time reduction. For a complex reactor model, transient simulation was performed using the newly developed finite volume method code, the results of which agree very well with the reference results from the finite element method code. Overall, this study demonstrates a successful feasibility study on the proposed numerical algorithms and software structure to support advanced system analysis tool development.

MOOSE↗
DOE OSTI2025

TensorID v1.0

This Python software package includes new and efficient algorithms for satellite and core interpolative decomposition of tensor data. In general, these algorithms target high-dimensional data reduction and compression. The software is purely numerical and can be applied by others to many important sources of tensor data generated by computation or experiment.

Zhang, Yifan [Lawrence Berkeley National Laborator↗