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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

How can a diverse set of integral and semi-integral measurements inform identification of discrepant nuclear data?

Nuclear data are used for a variety of applications, including criticality safety, reactor performance, and material safeguards. Despite the breadth of use-cases, the effective neutron multiplication factor, keff, of ICSBEP critical assemblies are primarily used for nuclear data validation; these are sensitive to specific energy regions and nuclides and are unable to uniquely constrain nuclear data. As a consequence, general-purpose nuclear data libraries, such as ENDF/B-VIII.0, may have deficiencies that, while not apparent in criticality applications, negatively impact other applications, such as non-destructive analysis of special nuclear material and neutron diagnosed subcritical experiments. Recent work by the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project developed a machine learning tool, RAFIEKI, which uses random forests and the SHAP metric to determine which nuclear data contribute most to predicted bias between measured and simulated responses (e.g. keff). This paper contrasts RAFIEKI analysis applied to keff only against RAFIEKI analysis with keff paired with either LLNL pulsed sphere measurements or subcritical benchmarks. Two examples show that a) including pulsed sphere measurements substantially increases 9Be nuclear data importance to bias between 2 and 15 MeV, and b) including subcritical benchmarks has the potential for disentangling compensating errors between 240Pu (n,el) and (n,il) cross-sections between 0.1 and 10 MeV. These results show that RAFIEKI analysis applied to response sets that include, but go beyond, keff can aid nuclear data evaluators in identifying issues in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Impact of CH 4 addition on the electron properties and electric field dynamics in a Ar nanosecond-pulsed dielectric barrier discharge

Non-equilibrium plasmas derive their low temperature reactivity from producing and driving energetic electrons and active species under large electric fields. Therefore, the impact of reactants on the plasma properties including electron number density, electric field, and electron temperature is critical for applications such as plasma CH 4 reforming. Due to experimental complexity, electron properties and the electric field are rarely measured together in the same discharge. Here, we combine time-resolved Thomson scattering and electric field induced second harmonic generation (EFISH) to probe electron temperature, electron density, and electric field strength in a 60 Torr CH 4 /Ar nanosecond-pulsed dielectric barrier discharge (ns-DBD) while varying the CH 4 mole fraction from 0 to 8%. These measurements are compared to a 1-D numerical model to benchmark its predictions and identify areas of uncertainty. Nonlinear coupling between CH 4 addition, electron temperature, electron density, and the electric field was directly observed. Contrary to previous measurements in He, the electron temperature increased with CH 4 mole fraction. This rise in electron temperature is identified as electron heating by residual electric fields that increased with larger CH 4 mole fraction. Moreover, the electron number density has been found to decrease rapidly with the increase of methane mole fraction. Comparison of these measurements with the model yielded better agreement at higher CH 4 mole fractions and with the usage of ab initio calculated Ar electron-impact cross-sections from the B-spline R-matrix (BSR) database. Furthermore, the calculated plasma properties are shown to be sensitive to the residual surface charge implanted on the quartz dielectric surfaces. Without considering surface charge in the simulations, the calculated electric field profiles agreed well with the measurements, but the electron properties were underpredicted by more than a factor of three. Therefore, measurements of either the electric field or electron properties measurements alone are insufficient to fully validate modelling predictions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

IER-297: TEX-HEU Baseline Assemblies Benchmark and Results [Slides]

The pending resolution of comments was accepted by the ICSBEP TRG in December 2021. Subgroup includes Catherine Percher, Dave Heinrichs, Michael Zerkle (NNL), and Jeffrey Favorite (LANL). The full resolution of comments is anticipated by March 31, 2022. Plans to execute TEX-HEU-Hf variant of experiment design are anticipated for FY22.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Data-Driven PMU Noise Emulation Framework using Gradient-Penalty-Based Wasserstein GAN

Availability of phasor measurement unit (PMUs) data has led to research on data-driven algorithms for event monitoring, control and ensuring stability of the grid. Unavailability of infrequent critical event field PMU data with component failures is driving the need to generate realistic synthetic PMU data for research. The synthetic data from power system simulation software often neglect noise profiles of received phasors, thus creating some discrepancies between real PMU data and synthetic ones. To address this issue, this work presents an initial study on the noise characteristics of PMUs, as well as presenting models for recreating their unique noise signatures. The proposed method, utilizing the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) architecture, provides an excellent benchmark for matching the noise distribution. One can use a well-learned GAN model to draw noise signatures from a distribution that seemingly mirrors the real PMU noise distribution, while also being able to be detached from the PMU data once the training is done. Based on the observed results and employed data-driven methodology, it is expected that the proposed methods can be adapted to replicate the behavior of other sensors, providing research and other applications with a tool for data synthesis and sensor characterization.

PMU↗
DOE OSTI2025

Vertical canopy gradients of respiration drive plant carbon budgets and leaf area index

Despite its importance for determining global carbon fluxes, leaf respiration remains poorly constrained in land surface models (LSMs). We tested the sensitivity of the Energy Exascale Earth System Model Land Model – Functionally Assembled Terrestrial Ecosystem Simulator (ELM-FATES) to variation in the canopy gradients of leaf maintenance respiration (R dark ). We ran global and point simulations varying the canopy gradient of R dark to explore the impacts on forest structure, composition, and carbon cycling. In global simulations, steeper canopy gradients of R dark lead to increased understory survival and leaf biomass. Leaf area index (LAI) increased up to 77% in tropical regions compared with the default parameterization, improving alignment with remotely sensed benchmarks. Global vegetation carbon varied from 308 Pg C to 449 Pg C across the ensemble. In tropical forest simulations, steeper gradients of R dark had a large impact on successional dynamics. Results show the importance of canopy gradients in leaf traits and fluxes for determining plant carbon budgets and emergent ecosystem properties such as competitive dynamics, LAI, and vegetation carbon. The high-model sensitivity to canopy gradients in R dark highlights the need for more observations of how leaf traits and fluxes vary along light micro-environments to inform critical dynamics in LSMs.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Cyclic creep analysis from elastic finite-element solutions

A uniaxial approach was developed for calculating cyclic creep and stress relaxation at the critical location of a structure subjected to cyclic thermomechanical loading. This approach was incorporated into a simplified analytical procedure for predicting the stress-strain history at a crack initiation site for life prediction purposes. An elastic finite-element solution for the problem was used as input for the simplified procedure. The creep analysis includes a self-adaptive time incrementing scheme. Cumulative creep is the sum of the initial creep, the recovery from the stress relaxation and the incremental creep. The simplified analysis was exercised for four cases involving a benchmark notched plate problem. Comparisons were made with elastic-plastic-creep solutions for these cases using the MARC nonlinear finite-element computer code.

Kaufman, A.↗
DOE OSTI2026

Radiative strength functions from the energy-localized Brink-Axel hypothesis

Radiative strength functions (RSFs) model the bulk electromagnetic response of highly excited nuclei and are critical inputs for statistical reaction codes. In this paper, we present a definition of the RSF that is consistent with Hauser-Feshbach reaction codes and that can be efficiently computed with the shell model using the Lanczos strength-function (LSF) method. Here, we introduce a variant of the shell-model LSF method that exploits the energy-localized Brink-Axel hypothesis, which makes it possible to compute both electric and magnetic RSFs across all energies relevant to capture reactions. We verify agreement with the conventional definition of RSFs with benchmark calculations of 24 Mg and then present novel results for 56 Fe. For 56 Fe we find that (i) the 𝑀⁢1 RSF shape evolves smoothly with excitation energy, consistent with the energy-localized Brink-Axel hypothesis; (ii) both 𝑀⁢1 and 𝐸⁢1 transitions contribute significantly to the radiative strength below the photoabsorption threshold; and (iii) within the sdpf model space, the strength below 3 MeV observed in Oslo-type experiments cannot be fully reproduced. These results pave the way for a coherent microscopic description of RSFs and further motivate the use of energy-dependent RSFs in modern reaction codes.

Physics - Nuclear physics and radiation physics↗
DOE OSTI2018

Fracture Toughness Characterization of Highly irradiated Reactor Pressure Weld from the ATR-2 Experiment

The UCSB ATR-2 irradiation experiment is designed to generate a new database on a wide variety of irradiated reactor pressure vessel (RPV) steels to fill a critical gap in predicting high fluence embrittlement for extended plant operation up to 80 years. A major focus in this experiment is to characterize the effects of irradiation temperature, neutron flux and fluence, and alloy chemistry on MNSP evolution, and model how these features impact hardening and embrittlement, manifested as shifts in ductile-to-brittle transition temperature. As part of these efforts, disk compact tension (DCT) specimens of three representative materials were included in the ATR-2 experiment to have direct measurement of transition fracture toughness shift and, thus, to have some benchmark data to compare outcoming predictive models with actual fracture toughness shifts. In addition, the attempts would be made to use these fracture toughness data to address the potential effect of high dose irradiation on the shape of the Master Curve for highly embrittled RPV material.This report provides data for the fracture toughness characterization of highly embrittled weld from Palisades steam generator.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Scaling and performance portability of the particle-in-cell scheme for plasma physics applications through mini-apps targeting exascale architectures

We perform a scaling and performance portability study of the particle-in-cell scheme for plasma physics applications through a set of mini-apps we name "Alpine", which can make use of exascale computing capabilities. The mini-apps are based on Independent Parallel Particle Layer, a framework that is designed around performance portable and dimension independent particles and fields. We benchmark the simulations with varying parameters such as grid resolutions (5123 to 20483) and number of simulation particles (109 to 1011) with the following mini-apps: weak and strong Landau damping, bump-on-tail and two-stream instabilities, and the dynamics of an electron bunch in a charge-neutral Penning trap. We show strong and weak scaling and analyze the performance of different components on several pre-exascale architectures such as Piz-Daint, Cori, Summit and Perlmutter. While the scaling and portability study helps identify the performance critical components of the particle-in-cell scheme in the current state-of-the-art computing architectures, the mini-apps by themselves can be used to develop new algorithms and optimize their high performance implementations targeting exascale architectures.

Muralikrishnan, Sriramkrishnan↗
DOE OSTI2025

Optimizing cost-effective and benchmarked industry standards to quantify nutrient bioextraction by seaweed

Interest in the utility of seaweed farms to mitigate coastal eutrophication, or nutrient loading, has grown commensurate with the recent rise of the farmed seaweed industry in the U.S. But economic valuation of this ecosystem service remains elusive in part because of challenges in quantifying this spatiotemporally variable biological process with reproducible and comparable metrics. Regulatory bodies that permit wastewater discharge or lease area for aquaculture farms require water quality testing and reporting of dissolved total nitrogen (N) in nearshore marine environments. These metrics must meet EPA standards for testing and reporting (e.g., Total Kjeldahl Nitrogen - TKN). However, these metrics are inherently highly variable over space and time in dynamic nearshore systems, and expensive to evaluate with sufficient breadth to constrain this variance, creating a critical bottleneck to direct quantification of farmed seaweed net uptake rates in situ.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

AFRL Additive Manufacturing Modeling Series: Challenge 1, Characterization of Residual Strain Distribution in Additively-Manufactured Metal Parts Using Energy-Dispersive Diffraction

A machine component fabricated by additive manufacturing (AM) of metal powders often possesses steep residual stress gradients with significant magnitudes due to large temperature gradients that transpire within a localized area during fabrication. These processing-induced residual stresses can cause distortion of the part, and if they are of significant magnitude, they could induce cracking of the component, degrade printability, and/or diminish subsequent mechanical performance. The ability to predict these residual stresses imparted by AM is an important step in permeating AM technology for advanced manufacturing. Calibration and validation of AM process models used for prediction are, therefore, a critical step in understanding the origin and mitigating the challenges associated with residual stresses inherent to the AM process. In the present work, the residual strain distributions in components with simple geometries fabricated by a laser powder bed fusion (LBPF) process were characterized non-destructively using energy-dispersive X-ray diffraction in support of the US Air Force Research Laboratory Additive Manufacturing Modeling Challenge Series Groeber et al. (JOM 70:441-448, 2018). The measurement setup and approach are described in detail so that the data can be used as a benchmark to calibrate and validate models for the prediction of macro-scale residual stresses due to the LPBF process.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Cost and Carbon Intensity Implications of Coprocessing Sustainable Aviation Fuel at Petroleum Refineries

Sustainable aviation fuel (SAF) will play a critical role in decarbonizing the aviation industry. Among SAF production pathways, alcohol-to-jet (ATJ) stands out for its scalability, supported by abundant feedstock availability and a well-established bioethanol industry. However, significant reductions in SAF carbon intensity (CI) require the use of future feedstocks (e.g., cellulosic) whose adoption is hindered by high capital costs for feedstock processing and ethanol upgrading. Here, we evaluate the financial viability and environmental implications of integrating an ATJ SAF biorefinery within a petroleum refinery, utilizing miscanthus and switchgrass as example feedstocks. Three scenarios are evaluated: standalone (benchmark), colocated, and repurposing (coprocessing SAF within the petroleum refinery). Results show repurposing reduces baseline capital costs by 36% and SAF minimum selling price (MSP) by 12% to 8.14 USD·gal −1 ; the superior performance of repurposing is consistent across both feedstocks. Integration has a limited effect on SAF CI, which remains stable across scenarios, whereas using cellulosic feedstocks reduces CI by over 70% relative to corn, with baseline values of 17.01 g CO 2 e· MJ −1 for miscanthus and 12.23 g CO 2 e·MJ −1 for switchgrass. Global sensitivity analysis reveals MSP declines with greater coprocessing levels.

09 BIOMASS FUELS↗
DOE OSTI2025

A hybrid calorimetry-simulation model of mixing enthalpy for molten salt

Calorimetric determination of enthalpies of mixing (ΔH mix ) in multicomponent molten salts is often interpreted using empirical models that lack physically meaningful parameters. However, for improving pyrochemical separation of spent nuclear fuel, where lanthanides are major fission products and critical elements, a deeper thermodynamic understanding of the link between excess thermodynamic properties and solvation structure is critically needed. In this work, we implement a hybrid and physics-informed framework, MIVM+Calorimetry+AIMD, which integrates experimentally measured ΔH mix (via high temperature drop calorimetry) with solvation structures from ab initio molecular dynamics (AIMD). This approach is demonstrated using LaCl 3 mixed with eutectic LiCl-KCl (58 mol% – 42 mol%) at 873 K and 1133 K. MIVM-derived parameters enable extrapolation of excess Gibbs energy and La 3+ activity across compositions. In contrast, direct ΔH mix predictions from AIMD and polarizable ion model simulations deviate significantly. By incorporating experimentally benchmarked solvation structures into an interpretable thermodynamic model, the MIVM+Calorimetry+AIMD formalism achieves higher accuracy and generalizable method for studying molten salts, offering a robust path for understanding and optimizing molten salt chemistry relevant to nuclear fuel cycles and separation science.

Goncharov, Vitaliy G. [Washington State Univ., Pul↗
DOE OSTI2023

Improving materials property predictions for graph neural networks with minimal feature engineering *

Graph neural networks (GNNs) have been employed in materials research to predict physical and functional properties, and have achieved superior performance in several application domains over prior machine learning approaches. Recent studies incorporate features of increasing complexity such as Gaussian radial functions, plane wave functions, and angular terms to augment the neural network models, with the expectation that these features are critical for achieving a high performance. Here, we propose a GNN that adopts edge convolution where hidden edge features evolve during training and extensive attention mechanisms, and operates on simple graphs with atoms as nodes and distances between them as edges. As a result, the same model can be used for very different tasks as no other domain-specific features are used. With a model that uses no feature engineering, we achieve performance comparable with state-of-the-art models with elaborate features for formation energy and band gap prediction with standard benchmarks; we achieve even better performance when the dataset size increases. Although some domain-specific datasets still require hand-crafted features to achieve state-of-the-art results, our selected architecture choices greatly reduce the need for elaborate feature engineering and still maintain predictive power in comparison.

42 ENGINEERING↗
DOE OSTI2012

The Ongoing Impact of the U.S. Fast Reactor Integral Experiments Program

The creation of a large database of integral fast reactor physics experiments advanced nuclear science and technology in ways that were unachievable by less capital intensive and operationally challenging approaches. They enabled the compilation of integral physics benchmark data, validated (or not) analytical methods, and provided assurance of future rector designs The integral experiments performed at Argonne National Laboratory (ANL) represent decades of research performed to support fast reactor design and our understanding of neutronics behavior and reactor physics measurements. Experiments began in 1955 with the Zero Power Reactor No. 3 (ZPR-3) and terminated with the Zero Power Physics Reactor (ZPPR, originally the Zero Power Plutonium Reactor) in 1990 at the former ANL-West site in Idaho, which is now part of the Idaho National Laboratory (INL). Two additional critical assemblies, ZPR-6 and ZPR-9, operated at the ANL-East site in Illinois. A total of 128 fast reactor assemblies were constructed with these facilities [1]. The infrastructure and measurement capabilities are too expensive to be replicated in the modern era, making the integral database invaluable as the world pushes ahead with development of liquid metal cooled reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

OpenACC Profiling Support for Clang and LLVM using Clacc and TAU

Since its launch in 2010, OpenACC has evolved into one of the most widely used portable programming models for accelerators on HPC systems today. Clacc is a project funded by the US Exascale Computing Project (ECP) to bring OpenACC support for C and C++ to the popular Clang and LLVM compiler infrastructure. In this paper, we describe Clacc's support for the OpenACC Profiling Interface, a critical component of the OpenACC specification that standardizes an interface that profiling tools and libraries can depend upon across OpenACC implementations. As part of Clacc's general strategy to build OpenACC support upon OpenMP, we describe how Clacc builds OpenACC Profiling Interface support upon an extended version of OMPT. We then describe how a major profiling and tracing toolkit within ECP, the TAU Performance System, takes advantage of this support. We also describe TAU's selective instrumentation support for OpenACC. Finally, using Clacc and TAU, we present example visualizations for several SPEC ACCEL OpenACC benchmarks running on an IBM AC922 node, and we show that the associated performance overhead is negligible.

Coti, Camille↗
DOE OSTI2022

Pulsed Sphere Time of Flight Neutron Spectrum Measurements: Blank Run and 1.8 Mean-Free-Path thick Polyethylene Moderating Sphere

From the late 1960s to 1985, Lawrence Livermore National Laboratory (LLNL) undertook a series of ‘pulsed sphere’ experiments for 32 materials involving 148 different experiments using 75 different spheres to measure the neutron leakage spectra for different materials from 14-MeV neutrons generated by 3 H(d, n) 4 He reactions induced by an incident D+ beam from the Insulated Core Transformer (ICT) accelerator at LLNL. This deuteron beam was focused to impinge on tritium loaded onto a titanium substrate within a low mass target assembly placed within the center of a spherical shell constructed from the material of interest. The neutron time of flight was measured at a detector outside a collimator. The program was intended to be comprehensive with numerous targets of various thicknesses spanning the periodic table from H to 239 Pu. Five different neutron detectors were utilized to avoid possible systematic errors due to differences in detector responses. Further, these measurements were designed with the aim that the simple geometry of the measurements could be easily simulated to validate Monte Carlo transport codes and nuclear data libraries. As a result, these benchmarks have been extensively used in the validation of ENDL, ENDF and other libraries. Two experiments selected as benchmark cases in this evaluation are: 1) target assembly without material sphere (blank run), and 2) target assembly with a hollow polyethylene sphere, 1.8 mean free path (mfp) or 16.56 cm thick.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗