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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Part-scale evolution of fine-scale microstructural heterogeneity in solid-state additive manufacturing

Current solid-state additive manufacturing methods, refined through costly and time-consuming trial and error, have spurred interest in computational models that replicate material behavior under typical thermomechanical conditions (e.g., strain-rate ~ 102 s−1). These models, however, struggle to capture time-dependent microstructural evolution. In this work, Additive Friction-Stir Deposition (AFSD) is used as a representative case study for part-scale quantification of microstructure evolution at a fine spatial resolution (200 μm) by examining a liquid-nitrogen-cooled stop-action build via energy-dispersive X-ray diffraction coupled with a multi-channel detector. These results inform modeling efforts by linking process asymmetry to stored plastic strain, residual elastic strain, and texture development, and unlike current state-of-the-art characterization methods (e.g., EBSD or neutron diffraction), this approach provides both the spatial resolution and collection efficiency necessary to quantify fine-scale microstructural heterogeneity over large component volumes. As such, this technique provides essential validation data for computational models, e.g., crystal plasticity, enabling future prediction of heterogeneous behavior in AFSD and other additive manufacturing processes.

Franz, Cole [ORNL] (ORCID:0000000213465881)↗
DOE OSTI2022

Toward the fabrication of a 5- μm -resolution Wolter microscope for the National Ignition Facility (invited)

Advancements in computer-controlled polishing, metrology, and replication have led to an x-ray mirror fabrication process that is capable of producing high-resolution Wolter microscopes. Here, we present the fabrication and test of a nickel–cobalt replicated full-shell x-ray mirror that was electroformed from a finely figured and polished mandrel. This mandrel was designed for an 8-m source-to-detector-distance microscope, with 10× magnification, and was optimized to reduce shell distortions that occur within 20 mm of the shell ends. This, in combination with an improved replication tooling design and refined bath parameters informed by a detailed COMSOL Multiphysics® model, has led to reductions in replication errors in the mirrors. Mandrel surface fabrication was improved by implementing a computer-controlled polishing process that corrected the low-frequency mandrel figure error and achieved <2.0 nm RMS convergence error. X-ray tests performed on a pair of mirror shells replicated from the mandrel have demonstrated <10 μm full-width at half-maximum (FWHM) spatial resolution. Here, we discuss the development process, highlight results from metrology and x-ray testing, and define a path for achieving a program goal of 5 μm FWHM resolution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A parallel strategy for density functional theory computations on accelerated nodes

Using the Löwdin orthonormalization of tall-skinny matrices as a proxy-app for wavefunction-based Density Functional Theory solvers, we investigate a distributed memory parallel strategy focusing on Graphics Processing Unit (GPU)-accelerated nodes as available on some of the top ranked supercomputers at the present time. Here we present numerical results in the strong limit regime, as it is particularly relevant for First-Principles Molecular Dynamics. We also examine how matrix product-based iterative solvers provide a competitive alternative to dense eigensolvers on GPUs, allowing to push the strong scaling limit of these computations to a larger number of distributed tasks. Our strategy, which relies on replicated Gram matrices and efficient collective communications using the NCCL library, leads to a time-to-solution under 0.5 s for the Löwdin orthonormalization of a tall-skinny matrix of 3000 columns on Summit at Oak Ridge Leadership Facility (OLCF). Given the similarity in computational operations between one iteration of a DFT solver and this proxy-app, this shows the possibility of solving accurately the DFT equations well under a minute for 3000 electronic wave functions, and thus perform First-Principles molecular dynamics of physical systems much larger than traditionally solved on CPU systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Assessment of Potential Dose and Environmental Impacts from Proposed Testing at the INL Radiological Response Training Range

This assessment uses screening-level models to calculate potential environmental impacts from proposed tests at the Idaho National Laboratory (INL) Radiological Response Training Range (RRTR) site. Proposed tests could be conducted using 11 different radioactive material types that include K2O, LaBr3, KBr, Cu, Zr, F, Ga, Ga2O3, NaNO2, Ga-68, and Tc-99m. The tests could potentially release radioactive material to the atmosphere and radionuclides and other contaminants to the soil, which could leach into the unsaturated zone and migrate to the aquifer. Atmospheric transport of radionuclides to potential human receptors and time-integrated air concentrations were calculated with a Gaussian plume model and three years of hourly meteorological data. Potential surface-soil impacts were calculated with the computer program mixing-cell model (MCM). Groundwater impacts were calculated with the computer programs MCM and GWSCREEN. Radiological doses from potential atmospheric releases were calculated for public receptors off the INL Site and for workers at nearby INL facilities. Results were compared to regulatory dose limits. Maximum potential groundwater concentrations were estimated in the aquifer below the NSTR site and compared to drinking water standards or risk-based screening levels for resident tap water. Soil concentrations were calculated and compared to risk-based screening levels for workers and potential future residents. All impacts were estimated assuming 12 tests are conducted annually using all 11 material types for a period of 15 years. This document provides the resources to enable a subject matter expert in the field of environmental assessments to replicate the modeling and calculations. The methodology and parameters are presented in the text. All electronic files, including computer-code input, output, executable files, batch files, scripts, and spreadsheet files are contained in a zip file that can be accessed by selecting “Additional Information” (select Native File) in the INL Electronic Document Management System (EDMS). It is highly unlikely the test scenarios evaluated in this ECAR will adversely impact human health based on comparisons of calculated dose and concentration against regulatory standards and risk-based screening levels. Conservative estimates of dose to workers and the public from atmospheric transport of possible radionuclide releases are far below federal radiation protection standards. Conservative estimates of potential contaminant concentrations in groundwater are less than federal drinking water standards or screening levels. Predicted radionuclide concentrations in surface soils are below risk-based screening levels, except for Ge-68 (material Ga-68) for the worker. The Ge-68 soil concentration can be made less than the worker PRG, if the number of annual tests using Ga-68 is reduced from 12 to 6. However, the sum of ratios still exceeds one because of the high K-40 ratio. If the EF of the worker (number of days the worker is in the contaminated testing area) is reduced from 225 days/yr (default value for full time worker) to 112 days/yr, the Ge-68 ratio is less than one and the sum of ratios is less than one. Actual radiation doses and groundwater and surface-soil concentrations are likely to be much less than those calculated because of the conservative assumptions and parameters employed in the modeling. For example, atmospheric-transport calculations assume the entire inventory of each material type is readily released to the atmosphere and no plume deposition, depletion, or radioactive decay occurs during transport. The calculations also assume the same meteorological conditions (e.g., wind velocity, wind direction, stability class) that produce the maximum 95th percentile concentration (i.e., concentration representing the 95th percentile of a distribution of concentrations derived from 3 years of hourly meteorological data) at each receptor location are the same for all 12 tests during the year, and each receptor is assumed to be present during all 12 tests. The surface-soil assessment assumes the entire inventory of each test is deposited in the top 5 cm of soil. No atmospheric dispersal is assumed, and the radionuclides are subject only to leaching and radioactive decay. The groundwater-pathway modeling is conservative in that it is one-dimensional in the unsaturated zone (no lateral spreading/dilution) and assumes the entire inventory of contaminants infiltrates into the ground at the same location for every test. This is especially conservative for particulate radionuclides because they would have to dissolve or corrode first and some would be dispersed into the atmosphere. The groundwater receptor is also assumed to consume water directly from a hypothetical well positioned in the location of maximum concentration. In addition, conservative degradation rates were used, and volatilization was not considered for the nonradioactive chemical

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessment of Potential Dose and Environmental Impacts from Proposed Testing at the INL National Security Test Range

This assessment uses screening level models to calculate potential environmental impacts from proposed tests at two locations at the Idaho National Laboratory (INL) National Security Test Range (NSTR) site. Proposed tests could be conducted using 11 different radioactive material types that include K 2 O, LaBr 3 , KBr, Cu, Zr, F, Ga, Ga 2 O 3 , NaNO 2 , Ga-68, and Tc-99m. The tests could potentially release radioactive material to the atmosphere and radionuclides and other contaminants to the soil, which could leach into the unsaturated zone and migrate to the aquifer. Atmospheric transport of radionuclides to potential human receptors and time-integrated air concentrations were calculated with a Gaussian plume model and three years of hourly meteorological data. Potential surface soil impacts were calculated with the computer program Mixing-Cell Model (MCM). Groundwater impacts were calculated with the computer programs MCM and GWSCREEN. Radiological doses from potential atmospheric releases were calculated for public receptors off the INL Site and for workers at nearby INL facilities. Results were compared to regulatory dose limits. Maximum potential groundwater concentrations were estimated in the aquifer below the NSTR site and compared to drinking water standards or risk-based screening levels for resident tap water. Soil concentrations were calculated and compared to risk-based screening levels for workers and potential future residents. All impacts were estimated based on the assumption that 12 tests are conducted annually using all 11 material types for 15 years. This document provides the resources to enable a subject matter expert in the field of environmental assessments to replicate the modeling and calculations. The methodology and parameters are presented in the text. All electronic files, including computer code input, output, executable files, batch files, scripts, and spreadsheet files, are contained in a zip file that can be accessed by selecting “Additional Information” (select Native File) in the INL Electronic Document Management System (EDMS).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Assessment of Potential Dose and Environmental Impacts from Proposed Testing at the INL National Security Test Range

This assessment uses screening-level models to calculate potential environmental impacts from proposed tests at two locations at the Idaho National Laboratory (INL) National Security Test Range (NSTR) site. Proposed tests could be conducted using 11 different radioactive material types that include K 2 O, LaBr 3 , KBr, Cu, Zr, F, Ga, Ga 2 O 3 , NaNO 2 , Ga-68, and Tc-99m. The tests could potentially release radioactive material to the atmosphere and radionuclides and other contaminants to the soil, which could leach into the unsaturated zone and migrate to the aquifer. Atmospheric transport of radionuclides to potential human receptors and time-integrated air concentrations were calculated with a Gaussian plume model and three years of hourly meteorological data. Potential surface-soil impacts were calculated with the computer program mixing-cell model (MCM). Groundwater impacts were calculated with the computer programs MCM and GWSCREEN. Radiological doses from potential atmospheric releases were calculated for public receptors off the INL Site and for workers at nearby INL facilities. Results were compared to regulatory dose limits. Maximum potential groundwater concentrations were estimated in the aquifer below the NSTR site and compared to drinking water standards or risk-based screening levels for resident tap water. Soil concentrations were calculated and compared to risk-based screening levels for workers and potential future residents. All impacts were estimated based on the assumption that 12 tests are conducted annually using all 11 material types for 15 years. This document provides the resources to enable a subject matter expert in the field of environmental assessments to replicate the modeling and calculations. The methodology and parameters are presented in the text. All electronic files, including computer-code input, output, executable files, batch files, scripts, and spreadsheet files, are contained in a zip file that can be accessed by selecting “Additional Information” (select Native File) in the INL Electronic Document Management System (EDMS). It is highly unlikely the test scenarios evaluated in this ECAR will adversely impact human health based on comparisons of calculated dose and concentration against regulatory standards and risk-based screening levels. Conservative estimates of dose to workers and the public from atmospheric transport of possible radionuclide releases are far below federal radiation protection standards. Conservative estimates of potential contaminant concentrations in groundwater are less than federal drinking water standards or screening levels. Predicted radionuclide concentrations in surface soils are below risk-based screening levels, except for Ge-68 (material Ga-68) for the worker. The Ge-68 soil concentration can be made less than the worker PRG, if the number of annual tests using Ga-68 is reduced from 12 to 6. However, the sum of ratios still exceeds one because of the high K-40 ratio. If the EF of the worker (number of days the worker is in the contaminated testing area) is reduced from 225 days/yr (default value for full time worker) to 112 days/yr, the Ge-68 ratio is less than one and the sum of ratios is less than one. Actual radiation doses and groundwater and surface-soil concentrations are likely to be much less than those calculated because of the conservative assumptions and parameters employed in the modeling. For example, atmospheric-transport calculations assume the entire inventory of each material type is readily released to the atmosphere and no plume deposition, depletion, or radioactive decay occurs during transport. The calculations also assume the same meteorological conditions (e.g., wind velocity, wind direction, stability class) that produce the maximum 95th percentile concentration (i.e., concentration representing the 95th percentile of a distribution of concentrations derived from 3 years of hourly meteorological data) at each receptor location are the same for all 12 tests during the year, and each receptor is assumed to be present during all 12 tests. The surface-soil assessment assumes the entire inventory of each test is deposited in the top 5 cm of soil. No atmospheric dispersal is assumed, and the radionuclides are subject only to leaching and radioactive decay. The groundwater-pathway modeling is conservative in that it is one-dimensional in the unsaturated zone (no lateral spreading/dilution) and assumes the entire inventory of contaminants infiltrates into the ground at the same location for every test. This is especially conservative for particulate radionuclides because they would have to dissolve or corrode first and some would be dispersed into the atmosphere. The groundwater receptor is also assumed to consume water directly from a hypothetical well positioned in the location of maximum concentration. In addition, conservative degradation rates were used, and volatilization was not considered for the nonradradioactive chemicals modeled. And finally, the calculations assume all 12 tests will be performed at the same place at both locations, and all 11 radioactive material types will be used for each test. This is conservative because it is anticipated that no more than two material types will be used per test.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Measurement Error and Resolution in Quantitative Stable Isotope Probing: Implications for Experimental Design

Quantitative stable isotope probing (qSIP) estimates isotope tracer incorporation into DNA of individual microbes and can link microbial biodiversity and biogeochemistry in complex communities. As with any quantitative estimation technique, qSIP involves measurement error, and a fuller understanding of error, precision, and statistical power benefits qSIP experimental design and data interpretation. We used several qSIP data sets—from soil and seawater microbiomes—to evaluate how variance in isotope incorporation estimates depends on organism abundance and resolution of the density fractionation scheme. We assessed statistical power for replicated qSIP studies, plus sensitivity and specificity for unreplicated designs. As a taxon’s abundance increases, the variance of its weighted mean density declines. Nine fractions appear to be a reasonable trade-off between cost and precision for most qSIP applications. Increasing the number of density fractions beyond that reduces variance, although the magnitude of this benefit declines with additional fractions. Our analysis suggests that, if a taxon has an isotope enrichment of 10 atom% excess, there is a 60% chance that this will be detected as significantly different from zero (with alpha 0.1). With five replicates, isotope enrichment of 5 atom% could be detected with power (0.6) and alpha (0.1). Finally, we illustrate the importance of internal standards, which can help to calibrate per sample conversions of %GC to mean weighted density. These results should benefit researchers designing future SIP experiments and provide a useful reference for metagenomic SIP applications where both financial and computational limitations constrain experimental scope.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A guideline to document occupant behavior models for advanced building controls

The availability of computational power, and a wealth of data from sensors have boosted the development of model-based predictive control for smart and effective control of advanced buildings in the last decade. More recently occupant-behavior models have been developed for including people in the building control loops. However, while important objectives of scientific research are reproducibility and replicability of results, not all information is available from published documents. Therefore, the aim of this paper is to propose a guideline for a thorough and standardized occupant-behavior model documentation. For that purpose, the literature screening for the existing occupant behavior models in building control was conducted, and the occupant behavior modeling processes were studied to extract practices and gaps for each of the following phases: problem statement, data collection, and preprocessing, model development, model evaluation, and model implementation. Here, the literature screening pointed out that the current state-of-the-art on model documentation shows little unification, which poses a particular burden for the model application and replication in field studies. In addition to the standardized model documentation, this work presented a model-evaluation schema that enabled benchmarking of different models in field settings as well as the recommendations on how OB models are integrated with the building system.

Building control↗
DOE OSTI2024

Assessment of Potential Dose and Environmental Impacts from Proposed Testing at the INL Radiological Response Training Range

This assessment uses screening level models to calculate potential environmental impacts from proposed tests at the Idaho National Laboratory (INL) Radiological Response Training Range (RRTR) site. Proposed tests could be conducted using 11 different radioactive material types that include K 2 O, LaBr 3 , KBr, Cu, Zr, F, Ga, Ga 2 O 3 , NaNO 2 , Ga-68, and Tc-99m. The tests could potentially release radioactive material to the atmosphere and radionuclides and other contaminants to the soil, which could leach into the unsaturated zone and migrate to the aquifer. Atmospheric transport of radionuclides to potential human receptors and time-integrated air concentrations were calculated with a Gaussian plume model and three years of hourly meteorological data. Potential surface-soil impacts were calculated with the computer program Mixing-Cell Model (MCM). Groundwater impacts were calculated with the computer programs MCM and GWSCREEN. Radiological doses from potential atmospheric releases were calculated for public receptors off the INL Site and for workers at nearby INL facilities. Results were compared to regulatory dose limits. Maximum potential groundwater concentrations were estimated in the aquifer below the NSTR site and compared to drinking water standards or risk-based screening levels for resident tap water. Soil concentrations were calculated and compared to risk-based screening levels for workers and potential future residents. All impacts were estimated based on the assumption that 12 tests are conducted annually using all 11 material types for a period of 15 years. This document provides the resources to enable a subject matter expert in the field of environmental assessments to replicate the modeling and calculations. The methodology and parameters are presented in the text. All electronic files, including computer code input, output, executable files, batch files, scripts, and spreadsheet files are contained in a zip file that can be accessed by selecting “Additional Information” (select Native File) in the INL Electronic Document Management System (EDMS).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Surrogate models for development of unconventional shale reservoirs by an integrated numerical approach of hydraulic fracturing, flow and geomechanics, and machine learning

We develop well-completion surrogate models by taking an integrated workflow of hydraulic fracturing, flow, geomechanics, and machine learning simulation. There are three steps in the proposed workflow. First, history-matching processes are conducted with the field data including pumping and production data for characterization. Second, full-physics simulation is performed with various parameters of the field development (e.g., cluster spacing, clusters per stage, pumping rates and times, amount of proppant, and well spacing) to generate multiple simulation results by changing the parameters of the completion design with well-known hydraulic fracturing, reservoir, geomechanics simulators to calculate fracture geometry, reservoir depressurization, induced stress changes. The workflow is demonstrated over a field in the Southern Midland Basin. Here, we take two completion scenarios: a single well case followed by a multi-well case. Finally, a Long Short-Term Memory (LSTM) machine learning algorithm is employed to create surrogate models that can replicate the full-physics simulation results. Furthermore, results show that the trained models applied in the single well and multi-well cases for a particular geological system can provide good accuracy close to those provided by full-physics simulations. Specifically, the site-specific surrogate models can predict fracture parameters (length, height, and surface area) and cumulative production accurately with computational efficiency, suggesting our proposed workflow can be used as a pragmatic tool for expediting the well completion optimization process.

Geomechanics↗
DOE OSTI2020

Mesoscale informed parameter estimation through machine learning: A case-study in fracture modeling

Scale bridging is a critical need in computational sciences, where the modeling community has developed accurate physics models from first principles, of processes at lower length and time scales that influence the behavior at the higher scales of interest. However, it is not computationally feasible to incorporate all of the lower length scale physics directly into upscaled models. This is an area where machine learning has shown promise in building emulators of the lower length scale models, which incur a mere fraction of the computational cost of the original higher fidelity models. We demonstrate the use of machine learning using an example in materials science estimating continuum scale parameters by emulating, with uncertainties, complicated mesoscale physics. Additionally, we describe a new framework to emulate the fine scale physics, especially in the presence of microstructures, using machine learning, and showcase its usefulness by providing an example from modeling fracture propagation. Our approach can be thought of as a data-driven dimension reduction technique that yields probabilistic emulators. Our results show well-calibrated predictions for the quantities of interests in a low-strain simulation of fracture propagation at the mesoscale level. Furthermore, on average, we achieve ~10% relative errors on time-varying quantities like total damage and maximum stresses. Successfully replicating mesoscale scale physics within the continuum models is a crucial step towards predictive capability in multi-scale problems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software (Extended Analysis)

Tensor decomposition models play an increasingly important role in modern data science applications. One problem of particular interest is fitting a low-rank Canonical Polyadic (CP) tensor decomposition model when the tensor has sparse structure and the tensor elements are nonnegative count data. SparTen is a high-performance C++ library which computes a low-rank decomposition using different solvers: a first-order quasi-Newton or a second-order damped Newton method, along with the appropriate choice of runtime parameters. Since default parameters in SparTen are tuned to experimental results in prior published work on a single real-world dataset conducted using MATLAB implementations of these methods, it remains unclear if the parameter defaults in SparTen are appropriate for general tensor data. Furthermore, it is unknown how sensitive algorithm convergence is to changes in the input parameter values. This report addresses these unresolved issues with large-scale experimentation on three benchmark tensor data sets. Experiments were conducted on several different CPU architectures and replicated with many initial states to establish generalized profiles of algorithm convergence behavior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

New Results on Communication- and Memory-Aware Load Balancing Model and Algorithms

While load balancing in distributed-memory computing has been well-studied, we present an innovative approach to this problem: a unified, reduced-order model that combines three key components to describe “work” in a distributed system: computation, communication, and memory. Our model enables an optimizer to explore complex tradeoffs in task placement, such as augmented parallelism, at the expense of data replication increasing memory usage. We propose a fully distributed, heuristic-based load balancing optimization algorithm, and demonstrate that it quickly finds close-to-optimal solutions. We formalize the complex optimization problem as a mixed-integer linear program, and compare it to our strategy. Finally, we show that when applied to an electromagnetics code, our approach obtains up to 2.3x speedups for the imbalanced execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Fast Reactor Physics Model Verification Studies using ARC and PyARC Workflows

PyARC was recently developed at Argonne National Laboratory to automate many of the tasks required in the ARC (Argonne Reactor Computation) fast reactor simulation workflow, from input file generation, code execution, data transfer between ARC codes, and output postprocessing. PyARC will likely be the path forward to train new users of the ARC codes with the goal of wide adoption by the national laboratories, academia, and industry. In particular, for the ANL-JAEA collaboration under the Civil Nuclear Working Group (CNWG) project agreement NE-01, PyARC will be used to model the Joyo and EBR-II reactors for comparisons with measured data and calculated results from JAEA (Task 3: Fast Reactor Fuel and Core). As an additional avenue for verification and validation, this report investigates the use of PyARC towards a variety of existing ARC-based reactor models, in order to understand its efficacy in replicating the behavior of base ARC codes and better understand any limitations within modeling realistic fast reactor problems. To this end, PyARC was used to model the Joyo MKI, RBEC Benchmark-M, PRISM Mod-B, and EBR-II Run 138B cores, and its results were compared to those from existing ARC-based models. It was found that for hexagonal-based geometries PyARC was able to replicate the behavior of ARC codes to within 10 pcm for small reactor cores, and ~150pcm difference in eigenvalue for larger cores. These discrepancies are attributed primarily to differences in local mesh refinement options between ARC and PyARC, which currently cannot be resolved with PyARC’s latest version (1.6.0). In some of these cases, PyARC was used to model steady-state problems with initial core compositions originating from a prior REBUS depletion calculation. While PyARC was not designed to support such steady-state calculations, workarounds were applied to replicate the behavior of ARC-based calculations as closely as possible. Thus, these results demonstrate the wide extent to which they can be applied to fast reactor problems while still providing immense benefit to the user in terms of automating and standardizing common routines within the fast reactor analysis workflow. This study concluded that PyARC will be suitable for modeling the steady-state conditions of the EBR-II and Joyo fast reactors as part of the CNWG project agreement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

New insights into backbending in the symmetry-adapted shell-model framework

Here we provide insights into the backbending phenomenon within the symmetry-adapted framework which naturally describes the intrinsic deformation of atomic nuclei. For 20 Ne, the canonical example of backbending in light nuclei, the ab initio symmetry-adapted no-core shell model shows that while the energy spectrum replicates the backbending from experimental energies under the rotor-model assumption, there is no change in the intrinsic deformation or intrinsic spin of the yrast band around the backbend. For the traditional example of 48 Cr, computed in the valence shell with empirical interactions, we confirm a high-spin nucleus that is effectively near-spherical, in agreement with previous models. However, we find that this spherical distribution results, on average, from an almost equal mixing of deformed prolate shapes with deformed oblate shapes. Microscopic calculations confirm the importance of spin alignment and configuration mixing, but surprisingly unveil no anomalous increase in moment of inertia. Furthermore, this finding opens the path toward further understanding the rotational behavior and moment of inertia of medium-mass nuclei.

20 ≤ A ≤ 38↗
DOE OSTI2023

Neural network model of neutral beam injection in the EAST tokamak to enable fast transport simulations

The neutral beam injection (NBI) system in EAST produces energetic neutral particles, which collide with electrons and ions in tokamak plasmas and heat the plasmas through Coulomb collisions. Moreover, it drives a non-inductive source of current, due to the charge-exchange collision between neutral particles and ions, and injects toroidal torque, which generates a toroidal rotation of the plasma. The effect caused by the NBI system, such as plasma heating, current drive, total neutron rate, momentum transfer, and shine-through, are modeled by a comprehensive module called NUBEAM. However, NUBEAM is computationally intensive since it relies on Monte Carlo methods. In this work, a neural network model has been developed as a surrogate model for NUBEAM in EAST. The database for neural-network model training, validation and testing is generated by running TRANSP for experimental discharges from recent EAST campaigns (after the latest NBI upgrade) while using the NUBEAM module. Simulation results illustrate that the trained neural network has the capability of replicating the predictions made by NUBEAM while demanding a significantly shorter execution time. Finally, these results indicate that surrogate models like the one proposed in this work could enable fast transport simulations for EAST after integrating them into a control-oriented predictive code such as COTSIM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Molecular characterization of ebselen binding activity to SARS-CoV-2 main protease

There is an urgent need to repurpose drugs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Recent computational-experimental screenings have identified several existing drugs that could serve as effective inhibitors of the virus’ main protease, M pro , which is involved in gene expression and replication. Among these, ebselen (2-phenyl-1,2-benzoselenazol-3-one) appears to be particularly promising. Here, we examine, at a molecular level, the potential of ebselen to decrease Mpro activity. We find that it exhibits a distinct affinity for the catalytic region. Our results reveal a higher-affinity, previously unknown binding site localized between the II and III domains of the protein. A detailed strain analysis indicates that, on such a site, ebselen exerts a pronounced allosteric effect that regulates catalytic site access through surface-loop interactions, thereby inducing a reconfiguration of water hotspots. Together, these findings highlight the promise of ebselen as a repurposed drug against SARS-CoV-2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗