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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Boride-based Ceramic Super-high Temperature Thermocouples in Harsh Environments (Final Scientific/Technical Report)

An electromotive force (emf) can be generated along a temperature gradient between the cold end and hot end of a thermoelectric material, termed the Seebeck effect. Based on the Seebeck effect, metallic alloys have been extensively employed to detect temperatures for centuries, named thermocouples. However, commercially available thermocouple alloys suffer from limitations, such as oxidation, chemical degradation, and poor long-term stability under high-temperature harsh environments. This DOE-funded project aimed to develop high-temperature, chemically tolerant thermocouples suitable for operation in extreme environments relevant to semiconducting thermoelectric materials. The research focused on boride-based semiconducting thermoelectric compounds as candidates for next-generation thermocouples with enhanced oxidation resistance, chemical stability, and thermal robustness under conditions representative of charcoal-fired electricity facilities. During the funded years, boride materials were synthesized using an arc-plasma technique under ambient air and argon atmospheres, enabling scalable and cost-effective production compared with conventional boride fabrication methods. The synthesized borides were processed into nanostructured powders, followed by consolidation into dense bulk materials using a spark plasma sintering (SPS) bottom-up approach. Comprehensive characterization was performed, including microstructural analysis, electrical transport measurements, and optical and thermal property evaluation. Both p-type and n-type boride electric legs were fabricated and integrated into boride-based thermocouples. The thermal and irradiation stabilities of the boride nanomaterials and bulk thermoelectric materials were systematically evaluated to assess suitability for long-term operation in harsh environments. Additionally, 12 students were broadly hands-on trained spanning the full research workflow, including word processing and technical editing (e.g., LATEX for manuscript and poster preparation), data collection and analysis (using Python and related libraries and hardware interfaces), sample preparation (including arc-plasma synthesis and spark plasma sintering), and advanced characterization techniques (such as X-ray diffraction, UV–vis spectroscopy, electron microscopy, differential thermal analysis (DTA), and Seebeck coefficient measurements, etc). Overall, this project demonstrated the feasibility of boride-based thermoelectric materials as durable high-temperature thermocouples, providing a promising pathway toward robust temperature sensing technologies aligned with DOE energy infrastructure and extreme-environment monitoring needs.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Powered By CADET

The Capacity Expansion Decision Support for Distribution Networks (CADET) is a Python-based library and framework for creating electrical distribution system capacity planning tools for cost-effective, reliable power delivery. It enables the creation of modular, scalable, and extensible distribution capacity planning tools by providing a high-level optimization interface, parameter and options data managers, optimization constraint and objective libraries, generalized nomenclature, a system for tracking and modifying distribution network changes, optimization solution validation, and other capabilities. This webinar will describe 1) the motivation for creating CADET, 2) key designs, and 3) several use cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Truchas Overview

Truchas and Truchas-PBF are two sister codes for part-scale multi-physics modeling of manufacturing processes. Both programs are open source and made publicly available. They’re designed for efficient use of HPC resources and can be programmatically driven from Python packages. This enables automatic execution and analysis of ensembles of simulations, in some cases allowing 1000s of simulations to be evaluated in a day on HPC. Beyond just giving engineers a window into the concealed internal state of a system, the goal of Truchas is to provide a framework for developing novel manufacturing processes by understanding how the entire space of engineering inputs affects thermal state. It often is used to explore combinations of capabilities uncommon in commercial software, or to scale up analyses beyond the capabilities of commercial software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Intrusive Uncertainty Quantification and Optimal Experiment Design in the Open-Source Pyomo Ecosystem

This contribution describes ParmEst and Pyomo.DoE, two pillars of the open-source Python-based Pyomo ecosystem for computational optimization with (partial differential) algebraic equation mathematical models. Specifically, ParmEst facilitates intrusive frequentist parameter estimation (PE) and uncertainty quantification (UQ) through built-in features, such as covariance matrix estimation, bootstrapping, and likelihood ratio tests. Complementary, Pyomo.DoE enables optimal experiment design by maximizing various metrics of the Fisher information matrix, such as A-optimality (trace), D-optimality (determinant), E-optimality (minimum eigenvalue), and ME-optimality (condition number). ParmEst and Pyomo.DoE can solve high-dimensional optimization problems by leveraging the model structure and exact derivative information. Finally, we will discuss future opportunities to integrate PE and UQ capabilities with optimization under uncertainty, including robust optimization with non-convex models via PyROS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Powered By ERAD [Slides]

Energy Resilience Analysis for Distribution Power System (ERAD) is a free, open-source Python toolkit for estimating the energy and service impacts of hazards like earthquakes and flooding. It uses a graph-based approach to capture high resolution connectivity among the grid, critical services, and customers and rapidly compute household level metrics and aggregated statistics across large distribution systems. It uses asset fragility curves that relate hazard severity to survival probability for power system equipment including cables, transformers, substations, etc. The tool is designed to be modular and extensible, allowing it to interface with third-party hazard simulators and integrate into broader resilience analysis workflows. ERAD enables researchers, students, communities, distribution utilities, and other stakeholders to understand hazard impacts and evaluate the effectiveness of different programs to improve energy resilience. The webinar was hosted by NLR researcher Aadil Latif.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Waveform Simulation Framework: User Manual with Tutorials

This manuscript describes the Waveform Simulation Framework (WSF), a Python-based framework that provides a unified, programmable interface for generating synthetic seismograms for applications such as seismic array design, method development, and special event analysis. WSF standardizes how users define sources, receivers, and velocity models while abstracting simulator-specific configuration details, enabling workflows that are largely independent of the underlying numerical engine. The document provides installation guidance and tutorial-driven examples for three WSF simulator wrappers—WSF PyFK, WSF SW4, and WSF SPECFEM2D—illustrating end-to-end workflows from forward waveform simulation to common post-processing tasks (e.g., visualization and backprojection) using consistent data products (e.g., ObsPy Stream objects and SAC files).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Implementation of a High-Mach Integral Boundary Layer Method for Arbitrary Streamlined Body Geometry

The Momentum-Energy Integral Technique (MEIT) is an integral boundary layer method for the high-Mach flow regime used to approximate heat transfer and viscous force quantities of interest along streamlines of an inviscid flow solution on the surface of a flight vehicle. This method allows rapid mid-fidelity estimation of these quantities which would otherwise require a much more expensive viscous flow solution to produce. Integral boundary layer methods like MEIT have been around for decades, though usually only formulated for simple geometries such as 2-dimensional wing shapes or axi-symmetric nose shapes. The implementation discussed herein has been generalized to apply to any 3-dimensional streamlined body geometry through correct treatment of the curvilinear axes (streamline attached) momentum and energy entrainment terms, and handling of arbitrary stagnation region geometry. This implementation is provided as a software package for the Python environment, along with readers for common inviscid flow solution providers such as NASA’s CART3D flow solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Aerosol Model Benchmarking Repository: A toolkit for model intercomparison

The Aerosol Model Benchmarking Repository and Standards (AMBRS) project was initiated to provide tools and to establish community standards for benchmarking aerosol models. This report describes a set of open-source tools for building, running, and analyzing aerosol box model simulations in a standardized framework. The framework consists of three core components: AMBuilder, a CMake-based build system that compiles supported models consistently; AMBRS, a Python module that defines unified numerical experiments and executes them with aligned inputs; and PyParticle, an aerosol analysis package that standardizes output, computes diagnostics, and visualizes simulation results. Together, these tools enable reproducible intercomparison of aerosol schemes and support process-level evaluation of how model simplifications affect predictions of size distributions, cloud condensation nuclei activity, and other relevant properties relevant for the Earth-Energy system. Beyond its role in benchmarking, AMBRS provides a platform for studying aerosol processes across scales and can be used to generate training data for AI/ML applications in support of a broader hierarchical aerosol modeling strategy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Identifying the Accuracy of Surface Roughness for Metal Additive Manufacturing Parts Captured with Computed Tomography Scanning

Conventional surface roughness measurement techniques require direct access to internal surfaces, often necessitating destructive sectioning of test articles. Computed tomography (CT) offers a non-destructive alternative for internal surface characterization, but its application in metrology remains unstandardized and sensitive to machine resolution and operator technique. This study investigates the feasibility of using CT scanning to quantify areal surface roughness in metal AM heat exchanger tubes with three distinct internal geometries: ribbed, discrete W, and featureless. CT-derived surface parameters were extracted using custom Python scripts and compared to measurements obtained from a focus variation microscope calibrated against a known standard. Results show that CT-based roughness measurements closely matched microscope values for the discrete W specimen, deviations between CT and microscope measurements were minimal—less than 1 µm—indicating reliable reconstruction. In contrast, the ribbed and featureless specimens, with lower roughness values showed greater discrepancies. The findings suggest that CT scanning can be a viable non-destructive metrology tool for AM parts with surface roughness above approximately 8 µm. For smoother surfaces, current CT capabilities may not provide sufficient accuracy, highlighting the need for resolution-aware workflows and further standardization in CT-based surface metrology.

36 MATERIALS SCIENCE↗
DOE OSTI2025

REDESIGNING A PERFORMANCE MONITORING SOFTWARE FOR SUPERCOMPUTERS

The objective of this project was to improve upon the existing Watchr software that charts performance test metrics from the Trilinos project run on supercomputers at Sandia and elsewhere across the DOE complex. Software was iteratively designed and developed using Python Pandas and Dash data visualization to improve the extensibility and user experience of Watchr. Documentation is being maintained for future developers who want to extend the application.

Camacho, Dane Joseph [Sandia National Laboratories↗
DOE OSTI2026

Draft Impacts: Modeling and Lab Validation (CRADA Final Report)

Chimney draft is a significant source of variability in real-world wood heater performance, yet laboratory tests conducted for certification do not capture this variability. Because draft varies with climate, chimney height, and home conditions, a heater that performs well in the lab can perform quite differently when installed in a home. Until now, wood heater manufacturers and installers have lacked the tools needed to anticipate how draft will vary across real installations or to advise on corrective measures when draft is too low or too high. The goal of this project was to develop and validate an open-source draft prediction tool for cordwood heater chimney systems. Over 18 months, Lawrence Berkeley National Laboratory (LBNL) and the Hearth, Patio & Barbecue Association (HPBA) collaborated to build a physics-based, Python tool that predicts how chimney draft evolves during operation, from ignition through steady burning. HPBA convened a stakeholder group of manufacturers and venting experts who provided feedback throughout development. LBNL validated the tool against laboratory measurements from a catalytic and a non-catalytic cordwood heater operated across a range of chimney heights and room-pressure conditions.

42 ENGINEERING↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗
DOE OSTI2026

Los Alamos National Laboratory R&D Intern

This report details the responsibilities, outcomes, and project details of a summer R&D internship at Los Alamos National Laboratory (LANL). LANL is a multidisciplinary laboratory that focuses on current cutting-edge research in many fields such as national security, engineering, materials science, computational modeling, and advanced manufacturing. The goal of the internship project was to work with lab engineers and resources to develop an energy absorbing structure for high-velocity impact applications. The successful development of this technology and methodology would not only positively impact future project funding but also contribute to the laboratory's commitment to solve national security challenges through simultaneous excellence. Such devices would also support efforts surrounding the research and development of energy absorbing structures and would provide new vital information backed by experimentation. Different computational and modeling methods were used to design these structures, in addition to qualitative background information provided by past literature. The resultant designs were successfully tested, and the test results were successfully quantified. From these results, new computational methods were developed through python programming and modeling to predict ideal materialistic properties for these structures given a sufficiently defined application.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Demonstration of Optimal Benchmark Selection Website and Validation of the q c Coverage Metric Using HEU-SOL-THERM-013-003 Experiment

In the work documented in this interim report, the experiment selection toolkit web site was demonstrated and q C coverage metric methodology was validated for IEU-MET-FAST-002-001, MIX-COMP-THERM 004-004, and HEU-SOL-THERM-013-003 experiments. 𝑞 𝐶 is an information-theoretic measure based on mutual information that quantifies the ability of candidate benchmark experiments to reduce the bias and uncertainty of a target criticality safety application. The metric and an accompanying open-source Python toolkit with a web-based interface were tested against a benchmark set of 425 experiments drawn from the International Criticality Safety Benchmark Evaluation Project Handbook. The interface is hosted at https://edim.covdef.com. It accepts sensitivity data files produced by the TSUNAMI-IP module of the SCALE code system and supports both (i) deterministic analysis using the ENDF/B-VII.0 covariance library and (ii) stochastic analysis based on user-supplied keff samples. Demonstrations on representative applications across a range of material composition, spectrum, and form show that q C -guided benchmark selection achieves greater uncertainty reduction with fewer experiments and yields more stable posterior bias and uncertainty estimates than traditional similarity coefficient ( c k )–based selection, while also capturing valuable low-ck experiments that one-to-one metrics overlook.

Abdel-khalik, Hany S. [Indiana Univ.-Purdue Univ. ↗
DOE OSTI2026

Developing a GUI for the Robotic Test Stand

The introduction of this poster explains the technology behind DUNE’s far and near detectors and how passing neutrinos generate electrons that drift into a wire grid. I then explain how 3 ASICs manage signals received from electron interception. Next, the poster states how COLDATA chips are undergoing quality control by a Robotic Test Stand using a state machine. I further explained how earlier tests were done via a command line script and the necessity to implement a user-friendly Graphical User Interface with new features a command line can’t implement. For the implementation section, tools and methods for implementation are listed such as Python, tkinter, and GitHub as well as how multithreading and queue implementation was necessary for GUI functionality. Then, I elaborated on the GUIs new features. Finally, I explain how the GUI will be distributed across multiple institutions and future changes planned for the GUI. Photos of the RTS, far detector cave, diagram of anode assembly plane, COLDATA chips, set up tab, result tab, and legacy command line interface are shown.

Gutierrez Villanueva, Jaziel [DuPage Coll.]↗
DOE OSTI2026

AutoSAC-Automated Sample Activation Calculation on VULCAN

AutoSAC is an automated python program to conduct sample activation calculation immediately after neutron scattering experiment on VULCAN. AutoSAC takes account of sample dimensions, compositions, forms, sample environments, neutron beam configurations, neutron scattering history, and proton charged resolved beam power etc., and uses a simplified method to rapidly estimate the radioactivity at end of beam or after. It generates a draft report per sample and repository of radioactivity per measurement and provides feedback of current radioactivity and decay time back to a neutron proposal Slack channel to inform users immediately on sample handling. It also utilizes either the sample note field in EPICS or sample composition or thickness correction and takes slack prompt or command to conduct post-beam SAC by demand. The program can be shared to be used in other beamlines at spallation neutron source with modified instrument configurations including instrument specific characteristic beam fluxes.

An, Ke [Oak Ridge National Laboratory (ORNL), Oak ↗
DOE OSTI2026

TRACE Input Modernization

This work presents a Tom’s Obvious Minimal Language (TOML)-based representation of input for the US Nuclear Regulatory Commission’s TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics code. Implemented using the Workbench Analysis Sequence Processor (WASP), the approach maps traditional TRACE input structures to a hierarchical format composed of named parameters, typed values, and native data collections. The resulting representation preserves TRACE’s existing modeling capabilities while providing a modern, structured interface for model development and management. WASP further extends TOML through a file import directive that supports modular model composition and reusable input organization. In addition, WASP provides extended array data entry convenience with various data repeat and interpolation capabilities. Examples of the new TOML syntax are provided for major TRACE input categories, including hydraulic components, heat structures, control systems, and trip logic. The TOML representation establishes a foundation for improved validation, tooling, automation, and model maintainability while remaining compatible with existing TRACE workflows. To facilitate migration to the TOML-based input format, the TRACE executable now supports conversion of native TRACE input into an intermediate JSON representation. A Python utility subsequently transforms the JSON data into an equivalent TOML model. Lastly, the TRACE executable now supports execution using TOML-formatted input.

Lefebvre, Robert A. [Oak Ridge National Laboratory↗
DOE OSTI2026

Modernizing GlideinWMS Factory Monitoring with Prometheus & Grafana

Large-scale scientific experiments like CMS and DUNE rely on the distributed workload management system GlideinWMS to efficiently utilize computing resources across heterogeneous computing environments. GlideinWMS currently records Factory statistics using Round Robin Databases (RRDBs), XML, and JSON files, and these statistics are displayed via custom monitoring Web pages, thereby limiting integration with modern observability platforms. This project investigates the use of Prometheus-based instrumentation to expose Factory metrics using OpenTelemetry principles. Factory statistics related to Glidein submission and job execution are exported as Prometheus metrics through the Prometheus Python Client Library and are served via an HTTP metrics endpoint. The collected metrics are inspected using the Prometheus web-based interface and are visualized through Grafana dashboards within the Landscape monitoring infrastructure at Fermilab. This project significantly streamlines the integration of modern monitoring technologies into GlideinWMS and establishes a framework for extending observability across additional system components.

Appiah, Gideon [Grambling State U.]↗