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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Python-EPICS RF Conditioning Automatic Control System at the Spallation Neutron Source

The RF Test Facility (RFTF) at the Spallation Neutron Source (SNS) is used for the conditioning of RF compo-nents such as ceramic vacuum windows and power cou-plers prior to their installation in the H- ion linear accel-erator. This process exposes components to high-power RF fields and thermal cycling to improve performance and remove surface impurities. To automate and optimize this process, a Python-based EPICS control system was developed alongside targeted hardware upgrades. The system enables real-time monitoring and control of RF power levels, temperature, and vacuum pressure. A user-friendly graphical interface was implemented using CS-Studio (Phoebus), allowing operators to adjust parameters and collect data efficiently. The system integrates a High-Power Protection Module (HPM) for interlocks based on vacuum and arc detection, ensuring safe operation. These upgrades have significantly improved the efficiency, accuracy, and safety of RF conditioning at the SNS RFTF. This paper describes the updated RF conditioning sys-tem, highlighting the software and hardware develop-ments and their application in support of the Proton Pow-er Upgrade (PPU) project.

Lee, Sung-Woo [ORNL] (ORCID:000000030915835X)↗
DOE OSTI2025

jaxhps: An elliptic PDE solver built with machine learning in mind

Elliptic partial differential equations (PDEs) can model many physical phenomena, such as electrostatics, acoustics, wave propagation, and diffusion. In scientific machine learning settings, a high-throughput PDE solver may be required to generate a training dataset, run in the inner loop of an iterative algorithm, or interface directly with a deep neural network. To provide value to machine learning users, such a PDE solver must be compatible with standard automatic differentiation frameworks, scale efficiently when run on graphics processing units (GPUs), and maintain high accuracy for a large range of input parameters. We have designed the jaxhps package with these use-cases in mind by implementing a highly efficient and accurate solver for elliptic problems with native hardware acceleration and automatic differentiation support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Fiats: Functional inference and training for surrogates

Fiats provides a platform for research on the training and deployment of neural-network surrogate models for computational science. Fiats also supports exploring, advancing, and combining functional, object-oriented, and parallel programming patterns in Fortran 2023. As such, the Fiats name has dual expansions: “Functional Inference And Training for Surrogates” or “Fortran Inference And Training for Science.” Fiats inference and training procedures are pure and therefore satisfy a language constraint imposed on procedure invocations inside Fortran’s parallel loop construct: do concurrent. Furthermore, the Fiats training procedures are built around a do concurrent parallel reduction. Several compilers can automatically parallelize do concurrent on Central Processing Units (CPUs) or Graphics Processing Units (GPUs). Fiats thus aims to achieve performance portability through standard language mechanisms.

Rouson, Damian [Lawrence Berkeley National Laborat↗
DOE OSTI2025

High-Resolution Simulations of Geological CO 2 Injection: Application to the SPE11 Benchmark

Geological carbon sequestration (GCS) will play a critical role in decarbonization and in facilitating the transition to clean energy systems. Because CO 2 is highly mobile, ensuring its safe and permanent injection into subsurface geological formations involves monitoring over larger spatial domains and longer time periods than is typical for hydrocarbon reservoirs. This can benefit from simulation tools capable of modeling key CO 2 trapping mechanisms, particularly those optimized for speed and scalability on high-performance computing systems. Using isothermal versions of the SPE11B and SPE11C benchmark cases, we conduct a mesh refinement study simulating CO 2 injection into kilometer-scale rock formations at centimeter resolution with the GEOS open-source simulation framework. We focus on how mesh refinement improves the accuracy of convective mixing in both 2D and 3D simulations. The computational costs associated with achieving a converged solution highlight the need for predictive upscaling techniques. A systematic performance scaling analysis—including both central processing unit (CPU) and graphics processing unit (GPU) architectures—complements the “Results” section.

Geosciences↗
DOE OSTI2025

Vidyut3d: A Gpu Accelerated Fluid Solver for Non-Equilibrium Plasmas on Adaptive Grids

We present the numerical methods, programming methodology, verification, and performance assessment of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures, in this work. Our plasma fluid model solves the coupled conservation equations for species transport, electrostatic Poisson and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive-grid/particle management library, AMReX, and is portable over widely available vendor specific GPU architectures. We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth-order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on capacitive discharges and atmospheric pressure streamer propagation. We demonstrate the use of our solver on two 3D simulation cases: an atmospheric streamer propagation in Ar-H2 mixtures and a low pressure twin electrode radio frequency reactor. Our performance studies on three different CPU+GPU architectures indicate approximately 150-400X speed-up using AMD and NVIDIA GPUs per time step compared to a single CPU core for a 4 million cell simulation with 15 species.

Sitaraman, Hariswaran↗
DOE OSTI2024

Accuracy Enhancement of Nuclear Power Plant Simulators Utilizing High Accuracy Simulation Predictions

More recently, reactor core simulators for core designs associated with commercial nuclear power plants that utilize what is believed to be higher fidelity models have been developed. Features such as neutronics models that utilize transport equation solvers with fine spatial meshes and many energy-groups, thermal-hydraulic models that utilize sub-channel solvers with fine spatial mesh and capable of treating a wide range of fluid conditions, and fuel-coolant chemistry interaction models capable of treating CRUD deposition are to be found in these higher fidelity core simulators. These reactor core simulators require access to higher performance computers, characterized by many processors, cores and large memory. So associated with utilization of these simulators is access to high performance computers and ability to accommodate in one’s workflow longer execution times. By contrast, currently used core simulators by the nuclear industry can execute on engineering workstations and have execution times of seconds to minutes. The desirability for having short execution times is not only desired for support of time critical tasks but supports the mental process of decision making by engineers. The goal of the work reported upon here has the objective of retaining the fidelity of higher fidelity models while retaining the ability to utilize engineering workstations. Beyond the core simulator goal, additional goals of this work include incorporating the just described core simulator capability into a Nuclear Steam Supply System (NSSS) simulator, and to incorporate the resulting capability into an environment supportive of design and operational decision making associated with nuclear power stations. The model selected for the core neutronics model is the NESTLE code, for the core thermal-hydraulic model is the CTF code utilizing coarse mesh, and for the NSSS model is the RELAP5-3D code. WSC’s proprietary 3KEYMASTERTM platform is being used to provide software coupling, user interface, visualization, and reporting. The NESTLE core neutronics simulator was first integrated with the CTF core thermal-hydraulic simulator using CTF developed communication commands which are also used for CTF to communicate with RELAP5-3D under WSC’s proprietary 3KEYMASTERTM platform. To assure NESTLE prediction consistency with higher fidelity core neutronic simulators, buffer codes have been created to automatically generate from output files written by the VERA core simulator the NESTLE nodal neutronic parameter’ library, geometry, and pin-power reconstruction input files, thereby avoiding a number of challenges associated with utilizing lattice physics codes and providing consistency with VERA predictions. To treat absorber rod effects a multi-set library is utilized, where a set refers to a specific absorber rod fully inserted pattern. A coarse spatial mesh CTF model was developed with features added that support using CTF as envisioned in the engineering quality simulator. A hybrid meshing approach was implemented to allow for automated construction of models with mixed levels of refinement. Specifically, a core model could resolve some assemblies at a nodal level (4 subchannels per assembly) and others at a pin-resolution (one subchannel per coolant subchannel in the assembly). The intention is that this will allow for better resolution of limiting conditions such as DNBR and PCT, which are based on local rod and subchannel conditions. Further development was done of features that enhance the capabilities for the envisioned engineering quality simulator that has been developed, but now for RELAP-3D. The RELAP5-3D code development includes ability to model more than 999 components and the addition of the cross-channels turbulence mixing model and the void drift model that are implemented in CTF, aiming to achieve closer prediction agreement of the two codes for transient simulations, specifically, more accurate matches of the overall mass, momentum, and energy exchanges of both the liquid and gas phases between the neighboring core assemblies. Graphics were also developed for the Instructor Station for this project under WSC’s proprietary 3KEYMASTERTM platform to facilitate design and operational decision making.

42 ENGINEERING↗
DOE OSTI2024

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

SYCL is a portable programming model for heterogeneous computing, so it is important to obtain reasonable performance portability of SYCL. Towards the goal of better understanding and improving performance portability of SYCL for machine learning workloads, we have been developing benchmarks for basic operators in deep neural networks (DNNs). These operators could be offloaded to heterogeneous computing devices such as graphics processing units (GPUs) to speed up computation. In this work, we introduce the benchmarks, evaluate the performance of the operators on GPU-based systems, and describe the causes of the performance gap between the SYCL and Compute Unified Device Architecture (CUDA) kernels. We find that the causes are related to the utilization of the texture cache for read-only data, optimization of the memory accesses with strength reduction, shared local memory accesses, and register usage per thread. We hope that the efforts of developing benchmarks for studying performance portability will stimulate discussion and interactions within the community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Automated Generation of Weather and Climate Analysis Products

Wind roses are an important part to site operations as they depict the wind speed and direction percentage over a time period. In this project, I automated the production of wind roses for SRS meteorological towers. I developed a script to sequence through the dataset by period and create a wind rose for each of those period sets. Graphics were generated for every 4-hour period of the day, for each of the 4 heights of the instruments, for every half of each month. A 10-year climatological period consisted of wind speed and directions measurements at 15-minute intervals. We used the years 2014-2024 as the wind instruments on the tower were upgraded to sonic anemometers in early 2014. I then compared these wind roses to those from a previous study done in 2003 to analyze the differences and similarities in the wind patterns. The wind roses are also used to understand environmental transport conditions at SRS. When comparing the different heights of the anemometers to the 2003 report, there is a similarity in the fact that the direction is relatively the same across the levels, with the wind speeds increasing as you get higher in the air. When comparing the season of our graphs against the 2003 report, we noticed that the winter and summer months appear to have very similar wind directions. However, in the spring we noticed that there were more southerly winds compared to the 2003 report which had more westerly winds. Finally, in the fall months, we noticed that there was a higher percentage of northeasterly winds, while the 2003 report showed more southeasterly winds. We can use these summaries to estimate the directional dependence of dose that the surrounding areas receive throughout the year according to time of day.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Monte Carlo Simulation with CAD Interface for Calculation of 3D Maps of Residual Dose (CRADA)

Objective: To develop an easy-to-use software application to predict and mitigate radiation effects in research environment, space instruments, nuclear plants and medical facilities and help nonproliferation and national security efforts. Tech-X will develop standalone software libraries and command-line tools for ( 1) translating CAD into tessellated surfaces and tetrahedral meshes in GDML (for Geant4 and MARS 15), ROOT (for MARS 15) and HDF5 (for compact representation and for the visualization) formats, (2) healing CAD geometries to make them suitable for Monte Carlo simulations; (3) creating uniform and variable Cartesian and cylindrical meshes for detailed scoring; and ( 4) efficient Monte Carlo navigation in CAD geometries. JLAB will finish automation of simulations of residual dose in CAD geometries and integrate Tech-X software into Geant4 and MARS15. Finally, Tech-X will develop a Graphical User Interface to set up and heal CAD geometries, create input files, run and visualize simulations for residual dose. This application will run on local desktops, local and remote clusters and supercomputers and will be made available through public clouds, such as Amazon Web Services.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

FEM Analysis of Hybrid LTS/HTS Cos-Theta Dipole Magnet

After the recent results on Bi-2212 superconductive magnets realized and tested in canted cosine-theta and solenoid designs, respectively, at Lawrence Berkeley National Laboratory (LBNL) and NHMFL, the first Bi-2212 stress-managed cosine-theta insert magnet is in the assembly phase at Fermilab. This insert will be part of the first hybrid cosine-theta magnet made of Nb3Sn outer layers within the US-MDP effort to reach 20 T bore field. This paper reports the analytical analysis of the cosine-theta Nb3Sn/Bi-2212 hybrid magnet. As an introduction, it shows the validation of the finalized HTS coils' design optimized using the ROXIE code. Subsequently, it reports the parameters, logic, and implementation method of the 2D electromagnetic and mechanical FEM analysis of the LTS/HTS hybrid magnet. Results from the ANSYS detailed model made with sub-modeling geometry are compared with the homogeneous model implemented in the past. Moreover, a Python code was implemented to simulate the current degradation due to stresses in the detail-modeled conductor areas. The current degradation is introduced in the simulation dynamics for both conductors as an iteration process during the energization load step only after applying pre-stress and thermal loads. The numerical and graphic results of the 2D cosine-theta LTS/HTS magnet cross-section will be described and analyzed.

D'Agliano, A.↗
DOE OSTI2024

Surveillance Workload Divinator (SWORD)

The LANL Surveillance Workload Divinator (SWORD) is a high-level decision support tool that reproduces and predicts the annual values for stockpile and production disassembly and inspections (D&I) and rebuilds. SWORD, a spreadsheet-based tool, can be used to assess the surveillance workload under various planning scenarios. Results are shown graphically and updated dynamically for each weapon system or for the entire stockpile. Surveillance workload is calculated from stockpile surveillance guidance1 and from Production and Planning Directive (P&PD) data.

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

An Overview of the Molten Salt Thermal Properties Database--Thermophysical, Version 3.1 (MSTDB-TP v.3.1)

This report presents the current status of the Molten Salt Thermal Properties Database–Thermophysical (MSTDB-TP). Information regarding version 3.1 is provided herein, which contains 820 individual salt entries (data from 180+ independent studies); the thermophysical properties contained in the database include density, viscosity, thermal conductivity, and heat capacity. The major updates to the database include a significant expansion of pseudobinary and higher-order chloride salt mixtures, many of which bearing actinides, and an incorporation of more recent literature data (i.e., that within the past 5 years). Also, modifications have been made to the pure compound data in the database as a consequence of an external quality assessment of duplicate datasets. The user-facing API for the MSTDB-TP, Saline, has been updated to include viscosity estimation capabilities based on the Redlich–Kister formalism; this is an advancement with respect to the existing density estimation capabilities. The graphical user interface was also updated to include a density estimation capability, backed by Saline. Finally, additional preliminary efforts to include surface tension into the database, as well as an investigation on formalisms that would be appropriate for thermal conductivity estimation, are reported herein.

36 MATERIALS SCIENCE↗
DOE OSTI2024

GADRAS-DRF Enhancements for Safeguards – Custom Peak Fitting to Enhance Model Fitting and Isotopics

One major software update was accomplished within the Gamma Detector Response and Analysis Software-Detector Response Function (GADRAS-DRF) package. This update allows users to adjust individual peak fits for use in subsequent analysis processes within GADRAS-DRF. A graphical user interface (GUI) was implemented so users can see the effect of their fit adjustments on the spectrum. This new feature will enhance the capability of the previously funded auto-enrichment and peak-based 1D model fit feature that was implemented in FY23 (Fiscal Year). Isotopic analysis was performed using M400 data obtained from uranium standards and the isotopic assessment is given with and without manual peak adjustments.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

FY24 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and data analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and crack formation in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), or,in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or more of: height, color, and 16-bit grayscale values as functions of position in a plane projection) to detect signs of surface corrosion and cracking after being trained on similar data, with the features to be detected. Although the initial scope included screening for broader indicators of corrosion, e.g., pitting, identification of potential cracks was prioritized for the past several years at the request of program leadership. Labeled training data is essential to developing the ML algorithm, and enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the large volume of data required to train ML algorithms and the relative rarity of cracks in the ICCWR data set. The updated program will read binary data from either LCM, WAMS or SEM files, interrogate data attributes, facilitate user labeling of data for training ML algorithms, execute ML algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. In FY24, hourglass neural networks (HNNs) that were initiated in FY22 were further developed and tested using available LCM data, and their performance was tested against that of the alternative U-Net Neural Network algorithm structure. HNNs along with previously developed Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) comprise a suite of ML tools for identification of cracks in the ICCWR

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Verification of RESRAD-OFFSITE Code (V.4)

This report documents the verification of RESRAD-OFFSITE Version 4.0 and describes, where necessary, the verification of the following: • The data comprising the standard dose and risk coefficient libraries in the RESRAD database files Master_dcf_ICRP07.mdb and Master_dcf_2k.mdb. • The extraction and transfer of the data from the selected database file to the computational code by the RESRAD-OFFSITE 4.0 interface, ResOWin.exe. • The different processes that are modeled by the main computational code in RESRAD OFFSITE 4.0, ResOMain.exe. • The data displayed in the graphical and text reports. Many verifications were performed as part of the quality assurance quality control program associated with the development and release of RESRAD-OFFSITE 4.0, namely: • developer testing, • internal independent testing, and • release testing. Some were also performed in response to questions from users regarding the performance of the code. The main text of the report focuses on summarizing a subset of those tests, both independent and developer tests that verified the computations performed by the code. The verifications included in this report served as the basis for the development of the release tests of the computational executables and provided the quantitative results to be compared with the code output. The input and output interfaces and the data transfers between the various executables of the code were tested while performing the verification testing. They were tested intentionally during release testing. This report also provides some basic information to help in understanding the activities that were verified. The report: • outlines the components of RESRAD-OFFSITE 4.0 and the interconnections between these components, • outlines the processes modeled by the computational code, • provides summary figures and tables to offer confirmation of the verification of the computational components of the code, • reproduces the verifiers’ reports, if available, in individual appendices, • refers to the previous verification report (Yu et al. 2011) for more details about some of the verifications, and • reproduces the test cases and the testers’ reports from the release testing in individual appendices, when possible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Celeritas Midterm SciDAC Report

Celeritas is a new Monte Carlo (MC) code that helps satisfy the increasing demand for high energy physics (HEP) detector simulation, using Graphics Processing Unit (GPU) hardware on high performance computing (HPC) systems to model Large Hadron Collider (LHC) experiments and beyond. This report details the project’s progress midway through its SciDAC funding period, highlighting the first complete implementation of standard electromagnetic (EM) physics on GPUs, initial results for performance and scalability on Leadership Computing Facilities (LCFs), and preliminary integration into the CMS and ATLAS experiments. By integrating HEP domain knowledge with expertise in MC transport, Celeritas has catalyzed a shift in the HEP community’s perception of GPU platforms as the future for HPC simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

DECOVALEX-2023: Task G, SAFENET Final Report

DECOVALEX Task G deals with fracture mechanics at several scales using a combined approach of experimental work, related model development, benchmarking and experimental analysis. Fig. 0.1 provides a graphical abstract for Task G. The experimental basis for the related mechanical (M), hydro-mechanical (HM), and thermo-mechanical (TM) processes comes from the rock mechanics laboratories of Universities of Freiberg (TUBAF) and Edinburgh, as well as the Korea Institute of Civil Engineering and Building Technology (KICT). The experimental work in the rock laboratories is closely linked to the underground research laboratories (URLs) Reiche Zeche (Germany), KURT (Korea), and Mont Terri (Switzerland). The scientific key questions are related to fracture permeability evolution under THM conditions, anisotropy effects on fracturing processes, and thermal fracture slip, which are being addressed in specific steps of the task. A large variety of numerical methods have been developed and applied for experimental analysis, ranging from continuum to discontinuum approaches. A detailed comparison of mechanical and hydro-mechanical processes is given in the section 3 via the benchmarking exercises. As a result of DECOVALEX-2023 Task G we further improved our understanding and predictability of fracturing processes under THM conditions. This was based on robust numerical simulation methods and in-depth experimental analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Training NuGraph2 for ICARUS

This presentation describes the process of training NuGraph2, a Graphical Neural Network for event reconstruction, on simulated ICARUS neutrino event data. This began with an investigation into filtering ICARUS spacepoint data. Then NuGraph2 was repeatedly trained on three event samples, which were used for finding optimized machine-learning parameters and to find and fix the causes of several crashes in NuGraph2 s preprocessing and training scripts.

43 PARTICLE ACCELERATORS↗