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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

CHMMPP: A c++ library for constrained Hidden Markov Models

SAND2024-13027O The CHMMPP: A c++ Library for Constrained Hidden Markov Models (HMM) software supports the analysis of multivariate time series data to detect patterns using HMM. Many applications involve the detection and characterization of hidden or latent states in a complex system using observable states and variables. This software supports inference of latent states integrating both an HMM and application-specific constraints that reflect known relationships in hidden states. The CHMMPP software supports application-specific and generic methods for constrained inference. This includes a framework for customized Viterbi methods, constrained inference of hidden states with A* and integer programming methods, and various constraint-informed methods for learning HMM model parameters. CHMMPP focuses on supporting generic methods that enable the agile expression of complex sets of constraints that naturally arise in many real-world applications.

Hart, William↗
DOE OSTI2024

Wind Turbine Airfoil Design Tools

SAND2025-11738O Wind Turbine Airfoil Design Tools is a software tool that connects existing open-source airfoil analysis tools with optimization software to produce modern airfoil design for wind turbine applications. 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.

Maniaci, David↗
DOE OSTI2025

Abbreviated Report for 25-FS-011: Switch and Stitch Similar Subgraph Synthesizer

Government institutions utilize software from a wide array of development sources, including those written by large software companies, government contractors, and open-source repositories. Avoiding installation of malicious software components is an important national security endeavor. Automated analysis of previously unseen software is an active research area, and there is much research in the design of systems that compare new software artifacts to a large set of previously seen software records organized by various behaviors they contain. One attractive approach is to turn each compiled software binary into a graph representation and apply a graph similarity model that scores pairs of binaries by their relative similarity. When a pair is deemed similar, it is useful to know why, in the sense of providing explanations to security analysts regarding which portions of the software they should look into further.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

ReactionMechanismSimulator.jl: A modern approach to chemical kinetic mechanism simulation and analysis

Abstract We present ReactionMechanismSimulator.jl (RMS), a modern differentiable software for the simulation and analysis of chemical kinetic mechanisms, including multiphase systems. RMS has already been applied to problems in combustion, pyrolysis, polymers, pharmaceuticals, catalysis, and electrocatalysis. RMS is written in Julia, making it easy to develop and allowing it to take advantage of Julia's extensive numerical computing ecosystem. In addition to its extensive library of optimized analytic Jacobians, RMS can generate and use Jacobians computed using automatic differentiation and symbolically generated analytic Jacobians. RMS is demonstrated to be faster than Cantera and Chemkin in several benchmarks. RMS also implements an extensive set of features for analyzing chemical mechanisms, including a library of easy‐to‐call plotting functions, molecular structure resolved flux diagram generation, crash analysis, traditional sensitivity analysis, transitory sensitivity analysis, and an automatic mechanism analysis toolkit. RMS implements efficient adjoint and parallel forward sensitivity analyses. We also demonstrate the ease of adding new features to RMS.

Johnson, Matthew S.↗
DOE OSTI2024

Nucleus++ : a new tool bridging AME and NUBASE for advancing nuclear data analysis

The newly developed software, Nucleus++ , is an advanced tool for displaying basic nuclear physics properties from NUBASE and integrating comprehensive mass information for each nuclide from Atomic Mass Evaluation. Additionally, it allows users to compare experimental nuclear masses with predictions from different mass models. Building on the success and learning experiences of its predecessor, Nucleus , this enhanced tool introduces improved functionality and compatibility. With its user-friendly interface, Nucleus++ was designed as a valuable tool for scholars and practitioners in the field of nuclear science. Finally, this article offers an in-depth description of Nucleus++ , highlighting its main features and anticipated impacts on nuclear science research.

AME↗
DOE OSTI2024

Synthetic Biology PacBio/JAWS QC Analysis (PBJ) v3.0

This software was designed as a sequence validation tool for the assembly of synthetic constructs. It analyzes FASTQ files against a list of reference sequences, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time, and assumes that each construct sequence in the reference will be in each pool, however, this is not a requirement. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.

Simirenko, Lisa↗
DOE OSTI2024

Prefeasibility Assessment for Solar PV and Storage for Critical Community Facilities in Chernihiv, Ukraine [Slides]

A prefeasibility analysis is performed for integrating solar photovoltaics and battery energy storage at four critical facilities in Chernihiv, Ukraine. The facilities were identified by Chernihiv city officials and include Hospital No. 2, the Maternity Hospital, Secondary School No. 11, and Preschool No. 4. The analyses were performed using NREL's REopt decision-support software tool. The analysis identifies potential capacities for PV and battery energy storage to provide both economic and resilience benefits. The conceptual architecture and estimates of key summary financial and performance metrics are presented.

14 SOLAR ENERGY↗
DOE OSTI2023

Catalyst: Fast and flexible modeling of reaction networks

We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Transportation analysis and related design optimization of the Fermilab high-beta 650 MHz cryomodule

The Proton Improvement Plan-II (PIP-II) at Fermi National Accelerator Laboratory (FNAL) will create a new and vastly improved accelerator, which will be the source of high-energy particles for the experiments taking place at FNAL. The new linear accelerator (LINAC) contains several types of cryomodules, which are individual particle accelerators. The last cryomodule in the LINAC will be the High-Beta 650 (HB650), which will operate at 650 MHz. Each module is approximately 15 meters in length and 1.5 meters wide, weighs 13 tonnes, and shares many design features with three of the other cryomodules. The HB650 consists of two primary sections, the outer vacuum vessel and the components that reside within it, which will be cooled to cryogenic temperatures – the cold mass. Once assembly is complete at FNAL, it will be transported to one of three places: another location at FNAL, another national laboratory within the continental United States, or to a scientific partner in Europe. Any excitation the module experiences, such as going over rough roads when on a semitrailer, can create high stresses in components and cause failure if severe enough. Additionally, any delicate components with low resonant frequencies that match the excitation spectrum could achieve resonance, potentially causing a fatigue failure by repeated flexing. To ensure the successful transportation of the HB650, a transport analysis utilizing ANSYS simulation software has been performed on major subassemblies, as well as analysis of the subassemblies as a combined system. The optimization of components, design of support structures, and overall increasing of the lowest resonant frequencies have resulted in a cryomodule that will be better equipped to handle transportation and any large impact loads that come with it.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

GSAS-II (GENERAL STRUCTURE AND ALAYSIS SYSTEM-II)

GSAS-II is a comprehensive data analysis and simulation software package for determining atomistic structures from single-crystal and powder diffraction data. X-ray, neutron and electron data may be used. Constant-wavelength, time-of-flight and pink-beam sources may be employed and analyses may combine different types of data. The package is oriented towards materials characterization problems, but protein crystallography, pair-distribution function analysis, small-angle scattering and reflectometry analysis are all included. GSAS-II provides tools for indexing and solving structures from powder diffraction data, in addition to structure, data and results visualization tools

TOBY, BRIANH↗
DOE OSTI2024

Generic and ML Workloads in an HPC Datacenter: Node Energy, Job Failures, and Node-Job Analysis

HPC datacenters offer a backbone to the modern digital society. Increasingly, they run Machine Learning (ML) jobs next to generic, compute-intensive workloads, supporting science, business, and other decision-making processes. However, understanding how ML jobs impact the operation of HPC datacenters, relative to generic jobs, remains desirable but understudied. In this work, we leverage long-term operational data, collected from a national-scale production HPC datacenter, and statistically compare how ML and generic jobs can impact the performance, failures, resource utilization, and energy consumption of HPC datacenters. Our study provides key insights, e.g., ML-related power usage causes GPU nodes to run into temperature limitations, median/mean runtime and failure rates are higher for ML jobs than for generic jobs, both ML and generic jobs exhibit highly variable arrival processes and resource demands, significant amounts of energy are spent on unsuccessfully terminating jobs, and concurrent jobs tend to terminate in the same state. We open-source our cleaned-up data traces on Zenodo (https://doi. org/10.5281/zenodo.13685426), and provide our analysis toolkit as software hosted on GitHub (https://github.com/atlarge-research/2024-icpads-hpc-workload-characterization). This study offers multiple benefits for data center administrators, who can improve operational efficiency, and for researchers, who can further improve system designs, scheduling techniques, etc.

crossanalysis↗
DOE OSTI2020

Dynamic PRA-Based Estimation of PWR Coping Time Using a Surrogate Model for Accident Tolerant Fuel

In this study, we propose an interpolation-based response surface surrogate methodology to manage a large number of scenarios in dynamic probabilistic risk assessment. It adopts the shape Dynamic Time Warping algorithm to cluster the interpolation neighborhood from time series sample data. The interpolation method was adapted from Taylor Kriging to allow a reduced-order model of the Taylor series. In order to demonstrate its applicability to complex issues in risk assessment for nuclear engineering, an example risk response surface to estimate emergency core cooling system (ECCS) criteria for triplex silicon carbide (SiC) accident-tolerant fuel was constructed. The response surface was exploited to estimate the cumulative failure probability of the fuel cladding structure due to the uncertainties in operator actions and safety systems. The functional failures were assessed based on a combination of individual layer failures computed by coupling Risk Analysis Virtual Environment software with a pressurized water reactor 1000-MW(electric) RELAP5 model and the in-house fuel performance assessment module. Results showed that SiC cladding failure probability spiked less than 1 min after a large-break loss-of- coolant accident whenever the current ECCS criteria for Zircaloy-4 (Zr-4) cladding was used. However, it still provides an increased safety margin of three orders of magnitude compared to Zr-4. This positive margin could be utilized to relax active ECCS requirements by allowing deviations of up to 450 s in its actuation time. The proposed surrogate methodology generated a response surface of SiC cladding failure probability reasonably well, with a significant savings of computation time. This methodology is expected to be useful in the analysis of system response with complex uncertainty sources.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Preliminary Feasibility of Printing, Microstructure Analysis and Mechanical Performance of a Down Selected Ni Alloy

This report is submitted as completion of a Milestone 3 deliverable under work package ORNL CT-23OR1304051 in support of the Advanced Materials and Manufacturing Technologies (AMMT) program. The AMMT program is aiming at the faster incorporation of new materials and manufacturing technologies into complex nuclear-related systems. An integrated approach, combining advanced characterization, high-throughput and accelerated testing, modeling and simulation including machine learning and artificial intelligence will be employed. While 316H (Fe-16-18Cr-10-14Ni-2-3Mo-0.04-0.1C) has been identified as a key alloy to be integrated into the AMMT accelerated alloy qualification approach due its relevance for many current and future nuclear energy reactors, many other alloys could be considered for the advanced fabrication of innovate high-performance nuclear components. ANL, INL, ORNL and PNNL are collaborating on identifying the most promising alloy candidates relevant for the AMMT program. A selection criteria matrix was established to evaluate the alloys considering their relative importance and technological readiness levels for nuclear energy applications, with a focus on laser powder bed fusion (LPBF). Due to the broad range of potential candidate alloys, ORNL and INL focused on Ni-based alloys, while ANL and PNNL mainly evaluated Fe-based alloys. PNNL previously published materials scorecards reports on several key alloys and this report is providing a broader overview of Ni-based candidate alloys, expending beyond alloys well-known to the nuclear community. Of particular interest are alloys that are currently commercially available in powder form due to the growing demand from other industries that have invested heavily in additive manufacturing. Among these alloys, Haynes 282 (Fe-20Cr-20Co-8Mo) was selected due to its superior strength at high temperature compared to the code-qualified alloy 617 (Ni-20-24Cr-10-15Co-8-10Mo). To assess the integration of this new alloy into the AMMT digital manufacturing framework, we performed the rapid optimization of alloy 282 printing parameters on a Renishaw 250 machine, the fabrication of sufficient materials for extensive characterization and mechanical testing both at ORNL and INL, and added the printing data into the digital platform via the Peregrine software. A detailed analysis of the LPBF 718 alloy was also conducted, with creep specimens being tested at 600-650°C and characterized by advanced electron microscopy. The alloy superior mechanical strength and great printability associated with the extensive database that has already been generated highlight the promising potential of LPBF 718 as a candidate alloy for the AMMT program. INL, ANL and PNNL have generated similar reports and all the information will be compiled into a final M2 milestone report to provide the AMMT leadership team with clear recommendations on the down selection of reactor materials, as well as establish a roadmap for the qualification of these selected alloys.

36 MATERIALS SCIENCE↗