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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Reduced diffusion and enhanced retention of multiple radionuclides from pore structure characterization of barrier materials for enhanced repository performance

Fluid flow and chemical transport in porous media are the macroscopic consequences of pore structure, which integrates geometry (e.g., pore size and surface area, pore-size distribution) and topology (e.g., pore connectivity). Low-permeability geological media whose pores are poorly interconnected will exhibit the characteristics of anomalous diffusion and sample size-dependent effective porosity, which will strongly impact long-term net diffusion and retention of radionuclides in geological repository settings involving different host rocks and barrier materials. A suite of innovative and complementary experimental approaches is utilized to study the microscopic pore structure and macroscopic fluid flow & chemical transport for a range of host rocks and barrier materials, in addition to standard clay minerals and reference rocks. With a particular focus on quantifying the presence and magnitude of “isolated” pores for a reduced effective porosity in low-permeability geomedia, the integrated methodologies for basic properties and pore structure characterization of these geomedia include X-ray diffraction, thin section petrography, grain size distribution, water immersion porosimetry after vacuum-pulling for full saturation, mercury intrusion porosimetry, nitrogen physisorption, scanning electron microscopy, X-ray computed tomography, and (ultra-)small angle neutron (X-ray) scattering. In addition, custom-designed gas diffusion, tracer recipe involving a range of anionic and cationic chemicals with subsequent analyses by laser ablation and inductively coupled plasma-mass spectrometry, along with batch sorption, column transport, and imbibition tests were conducted for coupled effects of pore structure and chemical retention/transport. From the perspectives of pore structure in conjunction with multiple and complementary approaches to examining a range of sample sizes under different observational scales, we find that the poor pore connectivity is prevalent in low-permeability media (mudstone and crystalline rock) that is related to geological processes (e.g., compaction, diagenesis and thermal maturation). For example, the deep and organic matter-rich mudstones have a much smaller effective porosity than the total porosity (as a result of poor pore connectivity) and associated diffusion coefficient, and the effective porosity & diffusion coefficients are also dependent upon the sample sizes used in the measurement. Similarly, most of the pore space in the shallow mudstone is also controlled by pore-throat diameters in the 5-50 nm range of intergranular pore types from its fine-grained nature, but with an overall good pore connectivity. However, the nm-sized pore space (physically pore-network architecture) and strong sorption capacities (chemical retention from clay minerals) of both shallow and deep mudstones lead to the synergistic retention of cationic radionuclides and their utilities as effective host rocks and barrier materials. Our unique approaches of studying how the micro-scale pore structure affect macro-scale fluid flow, diffusion & retention, and chemical transport produce improved mechanistic understanding, and realistic quantification, of diffusion and retention of typical radionuclides in a range of generic host rocks and barrier materials (clay/shale, salt, crystalline rock, and tuff), with the overall results leading to scientifically-based understanding of enhanced isolation (from both diffusion and retention) of radionuclides and improved confidence on the long-term performance of geological repository to store high-level radioactive wastes. In addition to the training of 25 undergraduates, graduates, and postdocs of UTA, the scientists (organizations) involved in performing this work (e.g., discussion, sample sharing, and operation of SANS and SAXS instruments) include Ed Matteo, Yifeng Wang, and Kristopher Kuhlman (Sandia National Laboratories), Jens Birkholzer, Liange Zheng, Tim Kneafsey, and Sharon Borglin (Lawrence Berkeley National Laboratory), Mavrik Zavarin (Lawrence Livermore National Laboratory), Yukio Tachi and Yuta Fukatsu (Japan Atomic Energy Agency), Mieke de Craen (Euridice, Belgium), Markus Bleuel (NIST), Wei-Ren Chen, Gergely Nagy, Changwoo Do, William Heller, Larry Anovitz, and Kenneth Littrell (ORNL), as well as Jan Illvsky, Ivan Kuzmenko, Ju-Sang Park and Jon Almers (ANL). Key deliverables include a total of 13 peer-reviewed journal articles (nine published and three under review), 23 presentations at scientific conferences (AAPG, AAPG Southwest Section, AGU, Asian Clay Conference, GSA, GSA South-Central Section, IHLRWM, InterPore, International Conference on Chemistry and Migration Behavior of Actinides and Fission Products in the Geosphere, International Conference on Coupled Processes in Fractured Geological Media: Observation, Modeling and Application), and academic institutions (UTA, New Mexico State University; University of Poitiers, France; University of Helsinki, Finland; Uppsala University, Sweden; Istanbul Technical University, Turkey) and other organizations (Andra, France; Posiva Oy, Finland).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Creation of Multiple Effect Evaporator and Combined Cycle Modelica Modules, and Optimization of Potable Water Generation from Saltwater Sources (Final Technical Report)

Modelica models for a Heat Recovery Steam Generator (HRSG) and Multiple Effect Evaporator have been developed. These models have been validated against results from literature and from an actual cogeneration system on the campus of NC State University. The models are capable of connecting to other components to create multi-input, multi-output energy systems with storage, also known as integrated energy systems. An existing 35 MW gas turbine model is connected to the HRSG model created for this project to produce 9 bar steam. The high pressure steam feeds a backpressure steam turbine from the library to generate additional electric power. 2 bar steam leaves the turbine to supply an 8 effect MEE to generate water for a community. As part of the effort, three research papers were submitted (two published in ANS Proceedings and one submitted to Applied Energy).

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Update of the Cesium-136 Cumulative Fission Yields at Multiple Neutron Energies

Nuclear data is foundational to several fields, including nuclear forensics. Nuclear forensics investigations of fission events, relies heavily on the cumulative fission yields, however several highly useful fission products suffer from very poor nuclear data including cumulative fission yields or associated uncertainties in that value. Cesium-136 is a highly relevant example of this issue, where the cumulative fission yield may be accurate but its uncertainty high enough to preclude its usefulness. In this work we evaluate and calculate an updated cumulative fission yield for 136 Cs for 235 U, 238 U, and 239 Pu at multiple neutron energies or sources using data obtained from irradiation campaigns. In all cases these newly determined cumulative fission yields provided small changes to the actual fission yields but had dramatic improvements to the uncertainty in those yields. These improvements in uncertainty will enable nuclear forensics end users to use 136 Cs data with more confidence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Generalizing HEPCloud Split Starter for Multiple Sites and Experiments

This talk discusses changes we made to the HEPCloud Split Starter to be able to reuse the software in multiple HPC sites across different experiments. I will explain the changes we made to the configuration system, how we generalized the project’s scripts, and the steps we took to reduce the application’s footprint on HPC shared storage, among other details.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Working with Multiple MPIs: Overcoming ABI Incompatibility

Scientific applications rely on third-party libraries, which may have multiple implementations. While sharing an application programming interface (API), many of these implementations do not have a shared application binary interface (ABI) and require recompiling. Recompiling can be a long and complex process and sometimes not even an option when the application is shipped binary only. ABI incompatibility strikes at the heart of portability, productivity, and performance by (1) impeding application execution across different HPC and Cloud systems; (2) adding developer hours rebuilding an application; and (3) not taking advantage of host-optimized libraries. This tutorial teaches attendees a portable way to address ABI incompatibility in MPI using the Wi4MPI library. Wi4MPI translates the ABI dynamically from the MPI library used to build the application to a different MPI library available at run time. With Wi4MPI, HPC practitioners can break the portability barrier imposed by ABI incompatibility, potentially increase performance, and increase user productivity. The tutorial is broken down in three components: (1) Understanding ABI compatibility in MPI; (2) Translating MPI libraries dynamically; and (3) Applying dynamic translation to key use cases in HPC, including Containers. If you use more than one MPI library or supercomputer, this tutorial is for you.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

BISON: A Flexible Code for Advanced Simulation of the Performance of Multiple Nuclear Fuel Forms [Slides]

As fuel vendors and designers pursue the development of advanced reactors or the increase in burnup limits for existing reactors, advanced computational tools are necessary to understand the fuel performance. BISON, a fuel performance code developed primarily at Idaho National Laboratory, which is built upon the Multiphysics Object-Oriented Simulation Environment (MOOSE), provides capabilities to analyze multiple nuclear fuel forms in a wide variety of dimensions. Since its inception, BISON has been used to investigate the performance of light-water reactor fuel rods, accident tolerant fuel concepts, metallic and mixed-oxide (MOX) fuels for fast reactors, plate fuels for research reactors, and tri-structural isotropic (TRISO) fuel particles. This talk will provide a history of BISON, highlights of major development milestones, tributes to key contributors, and applications of its use to various fuel forms in one-, two-, and three-dimensions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Developing ML/AI Methods for High-Throughput Characterization of Multiple-Sensor Streams of Tokamak Dynamics for High-Speed Control (Final Report)

This project evaluated and developed new mathematical and algorithmic techniques capable of handling (in real-time) the growing amounts of data generated by modern fusion research. While existing numerical linear algebra (NLA) methods provide the backbone to classical data analysis and algorithms, these methods fundamentally do not port to distributed architectures nor do they allow low-latency data reduction for control. Motivated by the needs for modern fusion reactors, this project explored and implemented new numerical methods to characterize plasma dynamics, respond in real-time to discharge evolution, and to process massive-scale data accurately and rapidly more fully. This project links expertise in multiple-sensor diagnostics of tokamak plasma dynamics from Columbia University’s Plasma Physics Laboratory with expertise in massive-scale data reduction and extreme data control algorithms at Columbia University’s Data Science Institute. This interdisciplinary project (i) applied machine learning methods, (ii) implemented a properly-trained neural-network for very fast processing of high-speed plasma videography, and (ii) developed the applied mathematical methods, based on randomized-NLA (rNLA) routines, for data analysis, reduction, and real-time control. The Columbia University High Beta Tokamak-Extended Pulse (HBT-EP) facility provided data to test new algorithms and partnership with Columbia University's Data Sciences Institute evaluated the broader use of new algorithms for many challenging control applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

CO2 Plume Imaging with Accelerated Deep Learning-based Data Assimilation Considering Multiple Realizations: Application to the Illinois Basin-Decatur Carbon Sequestration Project

We propose a fast and efficient deep learning workflow for near real-time data assimilation, forecasting and visualization of CO2 plume evolution in saline aquifer and demonstrate its application at a field site. Unlike the previous work, this study incorporates the impact of spatial heterogeneity using multiple realizations. In the proposed workflow, a neural network model utilizes available monitoring data such as downhole pressure measurements as input and predicts the propagating pressure ‘front’ using the diffusive time of flight (DTOF) map which is considered as representative reservoir image of the flow field. The DTOF is the arrival time of pressure front propagation, which can be computed by the Fast Marching Method rapidly without flow simulations. Reservoir model calibration can be implemented by selecting the training data samples that describe the predicted DTOF map based on observed data. The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project.

CO2 plume imaging↗
DOE OSTI2025

Closure and transport theory for plasmas with multiple ion species

This report summarizes a DOE-funded research project on closure and transport theory for plasmas with multiple ion species. The work developed accurate moment-based closure models across the full range of collisionality, incorporating both kinetic and collisional effects. Key contributions include high-fidelity closure relations, multi-temperature models, and transport coefficients applicable to fusion, space, and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Completion of Transport Property Measurements on Multiple Actinide Fluoride Mixtures

One of the missions of the US Department of Energy’s Office of Nuclear Energy (DOE-NE) Molten Salt Reactor (MSR) Campaign under the Advanced Reactor Technology program has been to experimentally measure thermophysical properties of MSR-relevent salt systems, with the intent of supporting the development of the Molten Salt Thermal Properties Database (MSTDB). This database is jointly funded by the DOE-NE Nuclear Energy Advanced Modeling and Simulation Program and the MSR Campaign. Multiple DOE national laboratories, including Oak Ridge National Laboratory (ORNL), have been conducting measurements of thermophysical properties to support MSTDB development and provide MSR developers with access to new data that has been measured using modern methodologies and more advanced sample characterization techniques. These data may either fill gaps in the database or provide updated higher quality data to replace legacy data. Researchers at ORNL have recognized significant gaps in the transport property data of actinide-bearing fluoride salt systems of MSR industry interest. Moreover, for the data present in MSTDB in this category, the uncertainty margins are generally high, leading to questionability in our current understanding of the thermophysical characterization of actinide fluoride mixtures. As such, the focus of this study has been to generate new transport property data of actinide fluoride mixtures that are of immediate interest to MSR developers. Specifically, the mixtures NaF-UF 4 (78 - 22 mol%) and NaF-KF-UF 4 (57-16.04-26.91 mol%) have been studied—NaF-UF 4 for thermal conductivity and viscosity and NaF-KF-UF 4 for viscosity. Thermal conductivity measurements have been conducted with a variable gap apparatus, whereas viscosity has been measured with a rolling ball viscometer. Methodological and calibration details are provided for both measurement processes, along with measurement system updates that have enabled easier manufacturing of components and fewer challenges associated with conducting the measurements themselves. The resultant data collected for NaF-UF 4 (78–22 mol%) and NaF-KF-UF 4 (57-16.04-26.91 mol%) have been compared with relevant mixture data within the thermophysical arm of the MSTDB (MSTDB-TP).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

24.1.3.4 Upgraded Fixed Energy Response Function Analysis with Multiple Efficiencies (FRAM) Software for U/Pu/MOX Mass Measurements

Fixed-energy Response-function Analysis with Multiple efficiency (FRAM) is a software code designed primarily for plutonium and uranium isotopic analysis. It is widely used in both the domestic and international safeguards community. FRAM can quickly and accurately determine the isotopic compositions of plutonium, uranium, and mixed oxides (MOX) when measuring with a high-purity germanium (HPGe), cadmium zinc telluride (CZT), or lanthanum bromide (LaBr 3 ) detector. The capabilities of FRAM have been enhanced to analyze the data of the pixelated CZT detector (made by H3D) and to measure the mass of plutonium, uranium, and MOX. Both the isotopic composition and mass of the item can be quickly determined with one measurement using a gamma detector with FRAM v.7.1.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Characterizing IHE Response to Multiple Shock Loading

The response of high explosives to shock loading is traditionally measured with a steady loading pressure. In many accident scenarios involving fragment impact, however, a loading duration that is shorter than the build up to detonation may occur. Fragments passing through multiple materials before reaching a high explosive charge may produce loading that is comprised of more than one shock wave. Additionally, the build up to detonation in high explosive corner turning loads the explosive a short duration pressure pulse, since rarefactions can often rapidly overtake the reactive wave. For these reasons, we have studied the response of the insensitive high explosive (IHE) materials PBX 9502 and LX-17 to complex loadings of varied intensity and duration. We refer to a single loading of limited duration as a “thin pulse”, whereas more complex scenarios were studied with an impactor that produces a double shock in the explosive. The following report presents experimental data and analyses of thin pulse shock initiation and double shock experiments designed to guide development of models of Insensitive High Explosives (IHEs) under controlled one-dimensional conditions relevant to accident scenarios and corner turning. Thin pulse shock initiation data on PBX 9502 and LX-17 were obtained under varied pulse duration, pressed density, and temperature conditions in order to probe various parameters essential for the development of a physics-based Cheetah reactive flow hotspot model. In situ pressure gauges provide insight into the degree of reaction in the explosive that are not obtainable with optical PDV measurements or distance measurements such as run to detonation. Double shock data was obtained to inform a Composition Aware Cheetah model which can be applied to any TATB-based IHEs. This model supports efforts to find a new IHE formulation and potentially incorporate new binders into IHE formulations. Simulations of each experiment are included to demonstrate the utility of these focused experiments to developing models of HE behavior. One-dimensional gas gun experiments are essential for characterizing shocked HE behavior and informing HE models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Timing reconstruction utilising multiple detection subsystems at the Short-Baseline Near Detector experiment

The Short-Baseline Near Detector (SBND) is the near detector of the Short-Baseline Neutrino Program, located only 110 m away from the Booster Neutrino Beam (BNB) target at Fermilab (Illinois, USA). SBND employs key detection technologies: a 112-ton Liquid Argon Time Projection Chamber for ionisation electrons, an advanced Photon Detection System (PDS) made up of photomultiplier tubes and X-ARAPUCAs for scintillation light, and a 4π coverage of Cosmic Ray Taggers (CRTs) for cosmic muons. This setup offers an exceptional energy, spatial and timing reconstruction of neutrino interactions. In this poster, we present ongoing timing reconstruction efforts of the PDS and CRTs, as well as combining complementary information across multiple detection subsystems to improve the timing resolution. This results in nanosecond level timing information that can be leveraged as an analysis tool, including the reconstruction of the BNB substructure to accept or reject signals detected in-between neutrino bunches as well as a timing-based discrimination for cosmic rejection.

Corallo, Annalea [INFN, Ferrara]↗
DOE OSTI2026

Prong Segmentation using Point Set Transformers in Multiple View Neutrino Detectors

NOvA is a long-baseline neutrino experiment studying neutrino oscillations by detecting neutrinos from the NuMI beam at Fermilab. Its physics analysis relies on accurate prong segmentation, which involves matching each hit to its source particle and identifying the particle type. This task has commonly been addressed using a combination of traditional clustering algorithms and convolutional neural networks (CNNs). However, NOvA’s detector design presents data as two sparse and decoupled 2D images (XZ and YZ views) rather than a native 3D representation, posing a significant challenge for traditional CNN-based models. In this talk, we propose a novel neural network based on the Point Set Transformer. By treating detector hits as sparse point clouds and implementing a cross-view attention mechanism, our model enables efficient information mixing between both views. Evaluated on NOvA simulated data, our model achieves superior accuracy while requiring significantly fewer computational resources compared to other models. Furthermore, the model demonstrates great performance when applied to Liquid Argon Time Projection Chamber (LArTPC) data, which shows its potential as a universal prong segmentation algorithm for multiple view neutrino detectors.

Liu, Jiaxi [UC, Irvine]↗
DOE OSTI2026

Improved Muon Energy Estimation Using a Detailed Model of Multiple Coulomb Scattering in the MicroBooNE LArTPC

We present an improved technique for estimating a muon's energy by measuring the deflections along its path inside the MicroBooNE detector from multiple Coulomb scattering (MCS). This approach implements several innovations that better capture detector non-idealizations compared to previous MCS-based muon energy estimators. As a result, it achieves improved resolution, reduced bias, and better data-model agreement. Using model simulation, for fully contained events the estimated bias is within 1\% and the estimated resolution narrows from 10\% to 4.3\% as muon energy increases from 0.1\,GeV to 2\,GeV. For events with particles exiting the detector volume, at least a meter of reconstructed muon track, and a muon energy below 2\,GeV, the estimated bias is less than 2\% and the estimated resolution varies from 7\% to 17\% over muon energy. These demonstrate significant improvements over the performance of previous work using an MCS-based energy estimator at MicroBooNE~\cite{mcs_2017}, which exhibited approximately twice worse resolution and a bias of 20\% over the same energy region. Data-model goodness-of-fit studies are used to validate the estimator's performance on data, showing good agreement within model uncertainties.

Cooper-Troendle, London [U. Pittsburgh (main); Fer↗
DOE OSTI2023

Simultaneous estimation of multiple eigenvalues with short-depth quantum circuit on early fault-tolerant quantum computers

We introduce a multi-modal, multi-level quantum complex exponential least squares (MM-QCELS) method to simultaneously estimate multiple eigenvalues of a quantum Hamiltonian on early fault-tolerant quantum computers. Our theoretical analysis demonstrates that the algorithm exhibits Heisenberg-limited scaling in terms of circuit depth and total cost. Notably, the proposed quantum circuit utilizes just one ancilla qubit, and with appropriate initial state conditions, it achieves significantly shorter circuit depths compared to circuits based on quantum phase estimation (QPE). Numerical results suggest that compared to QPE, the circuit depth can be reduced by around two orders of magnitude under several settings for estimating ground-state and excited-state energies of certain quantum systems.

97 MATHEMATICS AND COMPUTING↗