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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Synthetic light-cone catalogues of modern redshift and weak lensing surveys with abacussummit

ABSTRACT The joint analysis of different cosmological probes, such as galaxy clustering and weak lensing, can potentially yield invaluable insights into the nature of the primordial Universe, dark energy, and dark matter. However, the development of high-fidelity theoretical models is a necessary stepping stone. Here, we present public high-resolution weak lensing maps on the light-cone, generated using the N-body simulation suite abacussummit, and accompanying weak lensing mock catalogues, tuned to the Early Data Release small-scale clustering measurements of the Dark Energy Spectroscopic Instrument. Available in this release are maps of the cosmic shear, deflection angle, and convergence fields at source redshifts ranging from z = 0.15 to 2.45 as well as cosmic microwave background convergence maps for each of the 25 base-resolution simulations ($L_{\rm box} = 2000\, h^{-1}\, {\rm Mpc}$ and Npart = 69123) as well as for the two huge simulations ($L_{\rm box} = 7500\, h^{-1}\, {\rm Mpc}$ and Npart = 86403) at the fiducial abacussummit cosmology. The pixel resolution of each map is 0.21 arcmin, corresponding to a healpix Nside of 16 384. The sky coverage of the base simulations is an octant until z ≈ 0.8 (decreasing to about 1800 deg2 at z ≈ 2.4), whereas the huge simulations offer full-sky coverage until z ≈ 2.2. Mock lensing source catalogues are sampled matching the ensemble properties of the Kilo-Degree Survey, Dark Energy Survey, and Hyper Suprime-Cam data sets. The mock catalogues are validated against theoretical predictions for various clustering and lensing statistics, such as correlation multipoles, galaxy–shear, and shear–shear, showing excellent agreement. All products can be downloaded via a Globus endpoint (see Data Availability section).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Single-Cell Universal Logic-in-Memory Using 2T-nC FeRAM: An Area and Energy-Efficient Approach for Bulk Bitwise Computation

This work presents a novel approach to configure 2T-nC ferroelectric RAM (FeRAM) for performing single cell logic-in-memory operations, highlighting its advantages in energy-efficient computation over conventional DRAM-based approaches. Unlike conventional 1T-1C dynamic RAM (DRAM), which incurs refresh overhead, 2T-nC FeRAM offers a promising alternative as a non-volatile memory solution with low energy consumption. Our key findings include the potential of quasi-nondestructive readout (QNRO) sensing in 2T-nC FeRAM for logic-in-memory (LiM) applications, demonstrating its inherent capability to perform inverting logic without requiring external modifications, a feature absent in traditional 1T-1C DRAM. We successfully implement the MINORITY function within a single cell of 2T-nC FeRAM, enabling universal NAND and NOR logic, validated through SPICE simulations and experimental data. Additionally, the research investigates the feasibility of 3D integration with 2T-nC FeRAM, showing substantial improvements in storage and computational density, facilitating bulk-bitwise computation. Our evaluation of eight real-world, data-intensive applications reveals that 2T-nC FeRAM achieves 2× higher performance and 2.5× lower energy consumption compared to DRAM. Furthermore, the thermal stability of stacked 2T-nC FeRAM is validated, confirming its reliable operation when integrated on a compute die. These findings emphasize the advantages of 2T-nC FeRAM for LiM, offering superior performance and energy efficiency over conventional DRAM.

36 MATERIALS SCIENCE↗
DOE OSTI2026

202508 HAIIC IR Images with Attitude Data at BNF

This campaign aims to collect infrared imagery using a custom data acquisition system to improve and validate a previously developed attitude estimation algorithm, with a focus on ensuring reliable performance at higher altitudes. The system integrates a Boson+320 infrared camera, a VN-200 IMU for recording attitude data synchronized with image acquisition, and a Raspberry Pi 4B+ for onboard processing and storage. Image orientation was controlled using a Gremsy T7 gimbal. The primary dataset spans roll angles from −40° to 40° and pitch angles from −20° to 40°, sampled at 1° increments. Additional, smaller datasets were also collected at 2.5° angular intervals.

Boson+320↗
DOE OSTI2020

K-space algorithmic reconstruction (KAREN): a robust statistical methodology to separate Bragg and diffuse scattering

Diffuse scattering occurring in the Bragg diffraction pattern of a long-range-ordered structure represents local deviation from the governing regular lattice. However, interpreting the real-space structure from the diffraction pattern presents a significant challenge because of the dramatic difference in intensity between the Bragg and diffuse components of the total scattering function. In contrast to the sharp Bragg diffraction, the diffuse signal has generally been considered to be a weak expansive or continuous background signal. In this paper, using 1D and 2D models, it is demonstrated that diffuse scattering in fact consists of a complex array of high-frequency features that must not be averaged into a low-frequency background signal. To evaluate the actual diffuse scattering effectively, an algorithm has been developed that uses robust statistics and traditional signal processing techniques to identify Bragg peaks as signal outliers which can be removed from the overall scattering data and then replaced by statistically valid fill values. This method, described as a 'K-space algorithmic reconstruction' (KAREN), can identify Bragg reflections independent of prior knowledge of a system's unit cell. KAREN does not alter any data other than that in the immediate vicinity of the Bragg reflections, and reconstructs the diffuse component surrounding the Bragg peaks without introducing discontinuities which induce Fourier ripples or artifacts from underfilling `punched' voids. The KAREN algorithm for reconstructing diffuse scattering provides demonstrably better resolution than can be obtained from previously described punch-and-fill methods. The superior structural resolution obtained using the KAREN method is demonstrated by evaluating the complex ordered diffuse scattering observed from the neutron diffraction of a single plastic crystal of CBr 4 using pair distribution function analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

NeuDiff Agent: a governed AI workflow for single-crystal neutron crystallography

Large-scale facilities increasingly face analysis and reporting latency as a limiting step in scientific throughput, particularly for structural studies that require iterative reduction, integration, refinement and validation. To improve the time to result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source. NeuDiff Agent takes instrument data through reduction, integration, refinement and validation to a validated crystal structure and a publication-ready CIF. NeuDiff Agent coordinates established crystallographic tools under explicit governance by restricting actions to allowlisted tools, enforcing fail-closed verification gates at key workflow boundaries, and capturing complete provenance for inspection, auditing and controlled replay. The present benchmark is limited to structural crystallography for periodic structures; magnetic structure analysis and incommensurate or superspace refinement are outside the scope of the current workflow. Performance is assessed using a fixed prompt protocol and repeated end-to-end runs with two large language model backends, with user and machine time partitioned and intervention burden and recovery behaviors quantified under gating. In a reference-case benchmark, NeuDiff Agent reduces wall time from 435 min (manual) to 86.5 ± 4.7 to 94.4 ± 3.5 min (4.6–5.0× faster) while producing a validated CIF with no checkCIF level A or B alerts. These results establish a practical route to deploy agentic AI in facility crystallography while preserving traceability and publication-facing validation requirements.

Xiao, Zhongcan [ORNL] (ORCID:0000000220761961)↗
DOE OSTI2020

Verification and Validation of MFiX-PIC

This work is aimed at verification and validation (V&V) of particle-in-cell (PIC) approach in the National Energy Technology Laboratory’s (NETL) Multiphase Flow with Interphase eXchanges (MFiX-PIC) which was officially released in April 2019. Under verification, the results from MFiX-PIC are compared with exact or analytical solutions, while experimental results are used for benchmarking under validation. The test suite consists of the following cases: Terminal velocity. Particle advection in time-varying flow field. Particle settling in a dense medium. Evaporation. Rayleigh-Taylor instability. Minimum fluidization. Mini-circulating fluidized bed. The cases reported in a format consistent with the existing Verification and Validation Manual (Musser et al., 2018) explore a wide range of flow velocities and concentration regimes. Only one case considered in this work verifies the implementation of heat and mass transfer routines in MFiX-PIC, while a few other studies are currently underway to further expand the validation space in reacting flows. This study highlights the need for a rigorous analysis to objectively quantify the effect of model parameters. In addition, there is a scarcity of high-quality experimental data in the literature suitable for validating PIC methodology. Future efforts would include performing experiments which provide results for a valuable database. While designing such experiments, particle count should be significant to have sufficient particles per parcel while maintaining an optimal parcel to cell volume ratio. Also, datasets should have objectively assessed experimental uncertainty whereby confidence interval in those measurements become more explicit.

42 ENGINEERING↗
DOE OSTI2024

Application of research reactor environments for validation of the IRDFF-II dosimetry cross section library

Activation data from seven different reactor-based reference neutron fields are examined to provide enhanced validation evidence for the newly released IRDFF-II library. A least-squares based spectrum adjustment methodology is used and rigorous statistical metrics demonstrate the consistency of the set of IRDFF-II dosimetry cross sections. The use of these reactor-based neutron fields provides validation evidence for nine more reactions than have been addressed in the 252 Cf(sf) and 235 U(th) benchmark validation testing. The use of covers to shift their energy response increases the power of the response validation but makes it challenging to properly capture response correlations.

Griffin, Patrick↗
DOE OSTI2024

Self‐Potential Tomography Preconditioned by Particle Swarm Optimization—Application to Monitoring Hyporheic Exchange in a Bedrock River

Abstract A self‐potential (SP) data‐inversion algorithm was developed and tested on an analytical model of electrical‐potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP‐monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock‐lined riverbed. The algorithm combined stochastic source‐localization by particle‐swarm‐optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least‐squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical‐model data to evaluate the algorithm performance. Results indicated that true parameters of single‐source models were inverted and approximated with small residual error, whereas inversion of analytical‐model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non‐uniqueness of the inverse‐model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point‐scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP‐monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

First Measurement of Inclusive Muon Neutrino Charged Current Triple Differential Cross Section on Argon

The field of accelerator neutrino experiments is entering an era of precision oscillation measurements where the remaining unknown neutrino measurements will be determined. The upcoming DUNE and Hyper-K experiments aim to determine the neutrino mass hierarchy and degree of Charge-Parity (CP) violation in the neutrino sector, providing potential insight on the matter-antimatter imbalance observed in the universe. However, these experiments require highly accurate measurements, and neutrino cross section modeling uncertainties may limit their capabilities. Cross section measurements at current- generation experiments can aid the development of neutrino interaction models to reduce these uncertainties. This is especially true for measurements of neutrino energy, as it drives neutrino oscillations and is of key importance to oscillation experiments. The MicroBooNE experiment uses a Liquid Argon Time Projection Chamber (LArTPC) to produce neutrino-argon cross sections as one of its physics goals. The MicroBooNE detector’s fully active volume, precision reconstruction, and calorimetry information are leveraged in the Wire-Cell analysis to produce a muon neutrino selection that is 92% pure while maintaining 68% efficiency. A reconstruction chain featuring a fully 3D charge reconstruction and a graph-based particle trajectory fit are used to produce accurate measurements of lepton kinematics as well as visible hadronic energy produced in a neutrino interaction. This thesis presents the first neutrino-argon triple-differential cross section measurement, targeting inclusive charged-current final states. Wiener SVD unfolding is used to produce a measurement over neutrino energy, muon momentum, and muon scattering angle. A series of constrained goodness of fit tests are used to demonstrate the validity of MicroBooNE’s model in describing the distribution of reconstructed kinematics seen in data to ensure the accuracy of unfolding. The validated unfolding to neutrino energy represents a step forward in the field of neutrino cross sections, and demonstrates the capabilities of the LArTPC detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Toward predictive permeabilities: Experimental measurements and multiscale simulation of methanol transport in Nafion

A polymer membrane's permeability to solutes determines its suitability for various applications: a permeability value is essential for predicting performance in diverse contexts. Using aqueous methanol permeation through Nafion as an example, we describe a methodology for determining membrane permeability that accounts for boundary layer effects and the possibility of swelling. For the materials and apparatus used herein, analysis of a permeance measurement and computational fluid dynamics simulations show that the mass transfer boundary layer is on the order of ones to tens of microns. Additionally, the data are used to develop and validate a multiscale model describing solute permeation through a hydrated membrane as a series of physical mechanistic steps: reversible adsorption from solution at the membrane interface, diffusion driven by a concentration gradient within the membrane, and reversible desorption into solution at the opposite membrane interface. The validated model is used to predict methanol transport across a solar-driven CO 2 reduction device and to assess the impact of polymer changes on the measured value. The approach of combining experimental data, computational fluid dynamics, and the mechanistic multiscale model is expected to provide more accurate analysis of membrane permeation data in cases with polymer swelling or unusual device geometries, among others.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Separate Effects Validation for Subcooled Boiling in CTF

In 2010, the U.S. Department of Energy created its first Energy Innovation Hub, which is focused on developing high-fidelity and high-resolution modeling and simulation (M&S) tools for modeling of light water reactors (LWRs). This hub, the Consortium for Advanced Simulation of LWRs (CASL), has developed an LWR simulation tool called the Virtual Environment for Reactor Applications (VERA). The multi-physics capability of VERA is achieved through the coupling of single-physics codes, including CTF (the CASL version of Coolant Boiling in Rod Arrays— Three Field (COBRA-TF)), Michigan Parallel Characteristics Transport (MPACT), BISON, and Materials Performance and Optimization (MPO) Advanced Model for Boron Analysis (MAMBA). As part of its M&S efforts, CASL has identified various challenge problems, including Crud Induced Power Shift (CIPS), Crud-Induced Localized Corrosion (CILC), Pellet-Cladding Interaction (PCI), and Departure from Nucleate Boiling (DNB). This work addresses CASL milestone L2:VVI.P19.03, which focuses on uncertainty quantification of crud, which is relevant to both CIPS and CILC. This is achieved through an analysis and separate effects validation of the thermal hydraulic phenomenon known as subcooled boiling. As part of this work, various sources of experimental data are examined and compared to different options for empirical modeling of subcooled boiling. Through this analysis, a complete understanding of the underlying models and their implementation details are understood. A subset of these data are incorporated into a separate effects validation study of CTF. The Westinghouse Advanced Loop Tester (WALT) and Rohsenow experiments are modeled, and it is shown that the newly-implemented Gorenflo correlation is more accurate than the existing Chen and Thom correlations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Documentation, assessment, and improvements of fission gas modeling capabilities in BISON

Fission gas behavior critically affects nuclear fuel performance, influencing thermal conductivity, microstructure, swelling, and fuel-cladding interactions. The Simple Integrated Fission Gas Release and Swelling (Sifgrs) model, implemented within the BISON fuel performance code, provides advanced capabilities for modeling these phenomena. This manuscript reviews and assesses Sifgrs’ modular structure and submodels describing intragranular, intergranular, and release mechanisms. The modular implementation enables rapid improvements as our understanding advances and new fuel forms emerge. After an overview of capabilities, we present a comprehensive validation suite, comparing predictions to experimental data from tests under normal and transient conditions, including reproduction of the Vitanza curve. Results demonstrate Sifgrs’ accuracy, robustness, and applicability. Current limitations and ongoing efforts are discussed, including mechanistic, multiscale modeling, uncertainty quantification, and validation within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, supporting the safe and efficient use of nuclear fuels.

BISON↗
DOE OSTI2026

An ultra-fast method for generating synthetic down-scattered neutron data for inertial confinement fusion implosions

In inertial confinement fusion experiments at the National Ignition Facility, asymmetries are probed by a variety of neutron diagnostics, including neutron imaging systems, real-time neutron activation diagnostics (RTNADs), and neutron spectrometers. It is often useful to generate synthetic data based on these diagnostics to validate and tune models. However, current methods of doing so using Monte Carlo particle tracing are time-consuming. In this paper, an ultra-fast method is presented for generating synthetic neutron images, RTNAD data, and spectrometry data using line integrals and 3D convolutions. While it does not contain as much physics as particle tracing codes, it is thousands of times faster and produces nearly identical data. This enables analysis techniques that depend on generating large amounts of synthetic data, which will prove very useful for the study of asymmetries going forward.

Deuterium↗
DOE OSTI2023

RAAW

High-fidelity wind turbine modeling advances necessitate model validation datasets of equally high fidelity. The Rotor Aerodynamics, Aeroelastics & Wake (RAAW) project was designed to address this need. This three-year project runs from October 2021 through October 2024 starting with a field data collection period followed by model validation activities. RAAW is a partnership between GE Renewable Energy and the United States Department of Energy (DOE) through the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories. The field experiment is designed to make detailed measurements of the inflow, wind turbine response, and the resulting wake. The experimental dataset will be suitable for validating wind turbine models across the fidelity spectrum from actuator disk methods to blade-resolved codes.

17 WIND ENERGY↗
DOE OSTI2023

Release of ENDF/B-VIII.1β1-Based ACE Data Files

On March 1 st , 2023, the National Nuclear Data Center (NNDC) released the ENDF/B-VIII.1β1 nuclear data library, which contained neutron, spontaneous and neutron-induced fission yield, and alpha sublibraries. The library was released in the standard Evaluated Nuclear Data File (ENDF) format. The files can be accessed on Brookhaven National Laboratory’s GitLab. The thermal scattering law (TSL) sublibrary will be released at a later date. The files provided in the neutron sublibrary were processed into A Compact ENDF (ACE)-formatted files, verified, and validated by the XCP-5 Nuclear Data Team. The resulting collection of ACE files will be referred to as the “e81b1” library. This report details the processing of these files and the quality assurance approach taken. This is not intended to be a full validation effort; rather, this library is intended to simply reproduce the released files for further validation testing by the community. The e81b1 ACE library will be released to the NNDC for access through GitLab and hosted locally on LANL computing resources. This library is only intended for analysis to support the future ENDF/B-VIII.1 release and should not be used for production results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

ChemEcho v1.0

ChemEcho is a tool that converts tandem mass spectra into embeddings used to build machine learning (ML) models with fully explainable predictions. It provides an API for transforming raw tandem mass spectral data into embeddings, along with functions for training and validating ML models. Additionally, it includes utilities for retrieving and cleaning training data. ChemEcho is broadly applicable in ML pipelines that use tandem mass spectra for a variety of tasks, such as chemical classification or bioactivity mining. While there are existing methods to generate embeddings from fragmentation data, ChemEcho's approach ensures that predictions remain interpretable, enabling experts to evaluate results and generate hypotheses about the underlying data.

Harwood, Thomas [Lawrence Berkeley National Labora↗
DOE OSTI2020

A Predictive Model for Survival of Escherichia coli O157:H7 and Generic E. coli in Soil Amended with Untreated Animal Manure

Abstract This study aimed at developing a predictive model that captures the influences of a variety of agricultural and environmental variables and is able to predict the concentrations of enteric bacteria in soil amended with untreated Biological Soil Amendments of Animal Origin (BSAAO) under dynamic conditions. We developed and validated a Random Forest model using data from a longitudinal field study conducted in mid‐Atlantic United States investigating the survival of Escherichia coli O157:H7 and generic E. coli in soils amended with untreated dairy manure, horse manure, or poultry litter. Amendment type, days of rain since the previous sampling day, and soil moisture content were identified as the most influential agricultural and environmental variables impacting concentrations of viable E. coli O157:H7 and generic E. coli recovered from amended soils. Our model results also indicated that E. coli O157:H7 and generic E. coli declined at similar rates in amended soils under dynamic field conditions.The Random Forest model accurately predicted changes in viable E. coli concentrations over time under different agricultural and environmental conditions. Our model also accurately characterized the variability of E. coli concentration in amended soil over time by providing upper and lower prediction bound estimates. Cross‐validation results indicated that our model can be potentially generalized to other geographic regions and incorporated into a risk assessment for evaluating the risks associated with application of untreated BSAAO. Our model can be validated for other regions and predictive performance also can be enhanced when data sets from additional geographic regions become available.

Pang, Hao↗