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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 433 records · Page 24

Measurement of $\nu_\mu/\bar\nu_\mu$ CC double-differential cross sections on MINERvA hydrocarbon target for the shallow inelastic scattering background region

Cross section measurements are essential for all neutrino oscillation experiments. In fact, uncertaintiesassociated to cross section model parameters constitute one of the dominant sources oferrors in current oscillation analyses. In particular, understanding neutrino-induced pion productionin the kinematic regime known as shallow inelastic scattering (SIS) is critical for improvingneutrino interaction modeling in event generators. In this study, 416,233 (237,468) muon neutrino(antineutrino) interactions are measured in a SIS background region, predominantly made ofbaryon resonances. The analyzed datasets were collected from 2013 to 2019, comprising neutrinosgenerated by the Fermilab NuMI facility, with mean energy of 6 GeV, and the interactions occurredon the MINERvA hydrocarbon target. The measurements are presented as double-differential crosssections in terms of the outgoing muon longitudinal and transverse momentum components, aswell as the Bjorken x and y variables. Comparisons between the extracted data and predictionsfrom several generators reveal significant discrepancies across most kinematic bins.

Souza Correia, Souza Correia, Daniel [Rio de Janei↗

Delineating the Impact of Weightlessness on Human Physiology Using Computational Models

Microgravity environment has profound effects on several important human physiological systems. The impact of weightlessness is usually indirect as mediated by changes in the biological fluid flow and transport and alterations in the deformation and stress fields of the compliant tissues. In this context, Fluid-Structural and Fluid-Solid Interaction models provide a valuable tool in delineating the physical origins of the physiological changes so that systematic countermeasures can be devised to reduce their adverse effects. In this presentation, impact of gravity on three human physiological systems will be considered. The first case involves prediction of cardiac shape change and altered stress distributions in weightlessness. The second, presents a fluid-structural-interaction (FSI) analysis and assessment of the vestibular system and explores the reasons behind the unexpected microgravity caloric stimulation test results performed aboard the Skylab. The last case investigates renal stone development in microgravity and the possible impact of re-entry into partial gravity on the development and transport of nucleating, growing, and agglomerating renal calculi in the nephron. Finally, the need for model validation and verification and application of the FSI models to assess the effects of Artificial Gravity (AG) are also briefly discussed.

Computational Models↗

Finite Difference Time Domain Electromagnetic Scattering from Frequency-Dependent Lossy Materials

During this effort the tasks specified in the Statement of Work have been successfully completed. The extension of Finite Difference Time Domain (FDTD) to more complicated materials has been made. A three-dimensional FDTD code capable of modeling interactions with both dispersive dielectric and magnetic materials has been written, validated, and documented. This code is efficient and is capable of modeling interesting targets using a modest computer work station platform. However, in addition to the tasks in the Statement of Work, a significant number of other FDTD extensions and calculations have been made. RCS results for two different plate geometries have been reported. The FDTD method has been extended to computing far zone time domain results in two dimensions. Finally, the capability to model nonlinear materials has been incorporated into FDTD and validated. The FDTD computer codes developed have been supplied, along with documentation, and preprints describing the other FDTD advances have been included with this report as attachments.

Luebbers, Raymond J.↗

Coupling Processes Between Atmospheric Chemistry and Climate

This is the final report. The overall objective of this project is to improve the understanding of coupling processes among atmospheric chemistry, aerosol and climate, all important for quantitative assessments of global change. Among our priority are changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The work emphasizes two important aspects: (1) AER's continued participation in preparation of, and providing scientific input for, various scientific reports connected with assessment of stratospheric ozone and climate. These include participation in various model intercomparison exercises as well as preparation of national and international reports. and (2) Continued development of the AER three-wave interactive model to address how the transport circulation will change as ozone and the thermal properties of the atmosphere change, and assess how these new findings will affect our confidence in the ozone assessment results.

Ko, Malcolm K. W.↗

High throughput, accurate gene annotation through AI and HPC-enabled structural analysis

With the advances in next generation sequencing technologies, the number of sequenced genomes is growing exponentially, resulting in a technology bottleneck for the translation of sequence information into usable hypotheses about the function of each gene. We have proposed leveraging our leadership high-performance computing (HPC) resources to help break this annotation bottleneck. Here we design an HPC-based framework to infer gene function from gene sequence by incorporating information about protein structure and interactions predicted by deep learning approaches. Accurate functional prediction and gene annotation using computational methods will facilitate breakthroughs in the genomic sciences essential to understanding and harnessing life processes in bacteria, fungi and plants. The development and applications of the state-of-the-art deep neural networks to protein structural modeling, interaction prediction, sequence comparison, and quality assessment of protein structural models will be made possible by leadership computational resources. These HPC-enabled bioinformatics and molecular modeling tools will provide powerful insights into molecular functions of genes.

59 BASIC BIOLOGICAL SCIENCES↗

Pion-decay radiation and two-phase acceleration in the June 3, 1982 solar flare

The June 3, 1982 flare is unique in the wealth of observed neutron, gamma-ray and energetic-particle emission that it produced. Using calculations of high-energy emissions to fit the various time-dependent gamma-ray fluxes, a self-consistent interaction model for the June 3 flare is constructed in which the observed fluxes are produced by two distinct particle populations with different acceleration and interaction time histories as well as different but time-independent energy spectra. The two populations are associated with first- and second-phase particle acceleration, respectively.

Ramaty, R.↗

Sea Ice Motion from Wavelet Analysis of Satellite Data

Wavelet analysis of NASA scatterometer (NSCAT) backscatter and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) radiance data can be used to obtain daily sea ice drift information for the Arctic region. This technique provides improved spatial coverage over the existing array of Arctic Ocean buoys and better temporal resolution over techniques utilizing data from satellite synthetic aperture radars. Comparisons with ice motion derived from ocean buoys give good quantitative agreement. Both comparison results from NSCAT and SSM/I are compatible, and the results from NSCAT can definitely complement that from SSM/I when there are cloud or surface effects. Then three sea-ice drift daily results from NSCAT, SSM/I, and buoy data can be merged as a composite map by some data fusion techniques. The ice flow streamlines are highly correlated with surface air pressure contours. Examples of derived ice-drift maps in December 1996 illustrate large-scale circulation reversals over a period of four days. A method for deriving divergence and shear at the large-scale has been developed and comparison between buoys and satellite results shows a good agreement. These calibrated/validated results indicate that NSCAT, SSM/I merged daily ice motion are suitably accurate to identify and closely locate sea ice processes, and to improve our current knowledge of sea ice drift and related processes through the data assimilation of ocean-ice numerical model. For demonstration purpose, the ice velocities derived from satellite data are compared with the ice velocities derived from a coupled ice-ocean interaction model. The comparison reveals that the general circulation patterns of the two are quite similar but the ice velocity differences between the two are quite significant. In order to quantify the wind effects on ice motion, empirical orthogonal functions (EOF) are used in the principal component analysis for both ice motion and pressure field. Some preliminary results of sea-ice motion from QuikScat will also be presented.

Liu, Antony K.↗

ChIMES: A Machine-Learned Interatomic Model Targeting Improved Description of Condensed Phase Chemistry in Energetic Materials

In this report we detail completion of a Physics and Engineering Model Level Two Milestone targeting improved reactive interatomic potentials (IAPs) for energetic materials (EM) through machine learning. The specific goals of this milestone were to develop, validate, and document a new reactive molecular dynamics method for EM, based on machine learning by (1) generating databases of first-principles-derived forces, stresses, and energies for HN3 and 3,4-bis(3-nitrofurazan- 4-yl)furoxan (DNTF) (2) generate atomistic force fields from these databases via ML, and (3) benchmark model performance against first principles calculations. These goals were achieved by (1) further developing a machine learned reactive IAP and generation approach (i.e. the Chebyshev Interaction Model for Efficient Simulation or “ChIMES”), for which resulting IAPs can approach the predictive power of quantum-mechanical approaches at a fraction of the computational expense, and (2) applying the ChIMES framework to develop models for HN3 and DNTF. We find that for simple energetic materials like HN3, high accuracy ChIMES models can be obtained through application of a fitting approach that does not use active machine learning. We demonstrate the suitability of ChIMES models for simulations involving EM by using the HN3 model in multiscale shock technique simulations to predict the HN3 Chapman-Jouguet detonation state and investigate chemical evolution out to 1 ns following shock compression. This model is then used in larger direct shock (DS) simulations for a preliminary investigation of how bubbles (i.e. voids) influence material response under shock compression. We find that more complex EM (i.e. DNTF) necessitate a more sophisticated fitting approach, and develop a new active learning method and python tool to meet this challenge. We demonstrate that this fitting approach yields ChIMES models that out-perform commonly used standard reactive IAPs as well as semi-empirical quantum methods, and discuss the systematic improvability of these actively learned ChIMES models. We also describe challenges related to model development for EM such as DNTF, for which few experimental or previous simulation data are available (e.g. which could otherwise inform generation of training data). To overcome this issue, we establish a semi-empirical quantum ChIMES capability which can be used to efficiently map out relevant thermodynamic and configurational space, and generate ChIMES-IAP training data in a multiscale manner. We also show that these semi-empirical quantum ChIMES models can be used to generate predictions for the shock Hugoniot (the Hugoniot is the locus of thermodynamic states found in a shocked material) equation of state, investigate related thermochemistry, and explore carbon condensation following shock compression. This work represents a substantial advance in our atomistic modeling capability for EM that will provide much needed information on the chemistry of detonation for continued development of continuum models based on the Cheetah thermochemical code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparisons of triple-differential cross sections for quasielastic-like $ν_μ$-hydrocarbon interactions using $\langle E_ν\rangle \sim$ 3~GeV versus $\sim$ 6~GeV beams in MINERvA

Neutrino charged-current quasielastic-like scattering, a reaction category extensively used in neutrino oscillation measurements, receives contributions from single nucleon knockout processes, multinucleon processes, and inelastic scattering with subsequent rescattering or absorption in the nucleus to produce only nucleons in the final state. In this article, comparisons are presented of the same measurement in two different wideband neutrino beams: one beam peaks near 3 GeV with few neutrinos above 6 GeV; the other peaks near 6 GeV with few neutrinos above 10 GeV. Comparisons of differential cross sections in muon and proton kinematics for these two exposures probe deviations from free-neutron scattering that arise from the processes involving the nuclear medium, and provide a test of neutrino interaction models used to infer neutrino energies in oscillation experiments. Discrepancies are observed between the data and predictions that point to overestimates of the final state interactions of both protons and charged pions in quasielastic-like events.

Ruterbories, D. [Rochester U.]↗

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

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

42 ENGINEERING↗

Self-Consistent Ring Current Modeling with Propagating Electromagnetic Ion Cyclotron Waves in the Presence of Heavy Ions

The self-consistent treatment of the RC ion dynamics and EMIC waves, which are thought to exert important influences on the ion dynamical evolution, is an important missing element in our understanding of the storm-and recovery-time ring current evolution. Under certain conditions, relativistic electrons, with energies 21 MeV, can be removed from the outer radiation belt by EMIC wave scattering during a magnetic storm. That is why the modeling of EMIC waves is critical and timely issue in magnetospheric physics. To describe the RC evolution itself this study uses the ring current-atmosphere interaction model (RAM). RAM solves the gyration and bounce-averaged Boltzmann-Landau equation inside of geosynchronous orbit. Originally developed at the University of Michigan, there are now several branches of this model currently in use as describe by Liemohn namely those at NASA Goddard Space Flight Center This study will generalize the self-consistent theoretical description of RC ions and EMIC waves that has been developed by Khazanov and include the heavy ions and propagation effects of EMIC waves in the global dynamic of self-consistent RC - EMIC waves coupling. The results of our newly developed model that will be presented at GEM meeting, focusing mainly on the dynamic of EMIC waves and comparison of these results with the previous global RC modeling studies devoted to EMIC waves formation. We also discuss RC ion precipitations and wave induced thermal electron fluxes into the ionosphere.

Khazanov, George V.↗

System Analysis Modeling and Intermodal Transportation for Commercial Spent Nuclear Fuel

The United States Department of Energy (DOE) Office of Nuclear Energy is applying knowledge and understanding in the areas of systems level engineering, analysis, and decision making to better inform the waste management pathways for U.S. spent nuclear fuel (SNF). Currently there are 93 operating and 23 shutdown commercial nuclear reactors in the United States. SNF at most of these locations is being stored in spent fuel pools, dry storage, or both [1, 2]. This paper initially goes over the basics of the agent-based simulation tool known as the Next Generation System Analysis Model (NGSAM) that has the capability to model interaction and movements of individual components or groups like casks, railcars etc. The next section covers some of the methods implemented in the Java Transportation Operations Model (JTOM) to facilitate the movement of assemblies, casks, railcars etc. and the various intermodal transfer options. This section also covers the current cask loading and intermodal transfer times implemented in NGSAM. The last section goes over the proposed values for intermodal transportation, and cask transfer/loading operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A simple model for the interaction between vertical eddy heat fluxes and static stability

A numerical model for studying the interaction of vertical eddy heat fluxes and vertical temperature structure in midlatitude regions is described. The temperature profile for the model was derived from calculations of the equilibrium among heating rates in simplified representations of large-scale vertical eddy heat flux, moist convection and radiation. An eddy flux profile is calculated based on the quasi-geostrophic, liner baroclinic instability of a single wave. Model equilibrium states for summer and winter conditions are compared with observations, and the results are discussed in detail.

Gutowski, W. J., Jr.↗

High‐Speed Embedded Ink Writing of Anatomic‐Size Organ Constructs

Embedded ink writing (EIW) is an emerging 3D printing technique that fabricates complex 3D structures from various biomaterial inks but is limited to a printing speed of ∼10 mm s −1 due to suboptimal rheological properties of particulate-dominated yield-stress fluids when used as liquid baths. In this work, a particle-hydrogel interactive system to design advanced baths with enhanced yield stress and extended thixotropic response time for realizing high-speed EIW is developed. In this system, the interactions between particle additive and three representative polymeric hydrogels enable the resulting nanocomposites to demonstrate different rheological behaviors. Accordingly, the interaction models for the nanocomposites are established, which are subsequently validated by macroscale rheological measurements and advanced microstructure characterization techniques. Filament formation mechanisms in the particle-hydrogel interactive baths are comprehensively investigated at high printing speeds. To demonstrate the effectiveness of the proposed high-speed EIW method, an anatomic-size human kidney construct is successfully printed at 110 mm s −1 , which only takes ∼4 h. This work breaks the printing speed barrier in current EIW and propels the maximum printing speed by at least 10 times, providing an efficient and promising solution for organ reconstruction in the future.

36 MATERIALS SCIENCE↗

Interaction strength and model geometry effects on the structure of crossing-shock wave/turbulent boundary-layer interactions

The flowfield structure of a range of symmetric crossing-shock wave/turbulent boundary-layer interactions of varying strength is presented. The test geometry, consisting of a symmetric pair of opposing sharp fins at angle of attack, alpha, mounted to a flat plate, is studied experimentally for a range of alpha from 7 to 15 degrees at Mach numbers of 3 and 4. Results reveal that the basic flowfield shock structure remains similar in nature over the range of interaction strengths examined, with the only changes being in the scale and location of the various features present. The separated flow regions are classified as being either completely or partially separated, the completely separated case being the one in which the entire incoming boundary layer separates from the plate surface. For the current experiments, all but the weakest of the interactions exhibited complete boundary layer separation. Finally, the effects of model geometry are analyzed by comparing data for shock generators of varying lengths, with the results showing no evidence of upstream influence due to the shock generator trailing edges.

Garrison, T. J.↗

Modeling Plant Nutrient Acquisition Strategies Alters Projections of Carbon and Nitrogen Dynamics in Bioenergy Agroecosystems

Plant strategies to acquire nutrients from limited environments help shape ecosystem carbon (C) and nitrogen (N) cycling and response to environmental change. The effects of plant strategies on ecosystem dynamics are largely uncharacterized in bioenergy agroecosystems, where the impacts could determine bioenergy's ability to meet its sustainability goals of storing C and reducing N loss. We used FUN-BioCROP (Fixation and Uptake of Nitrogen-Bioenergy Carbon, Rhizosphere, Organisms and Protection), a plant–microbe interaction model of coupled plant nutrient uptake and soil organic matter decomposition, to simulate the effects of nutrient acquisition strategies on soil microbial activity and ecosystem nutrient cycling in bioenergy feedstocks miscanthus (Miscanthus × giganteus) and sorghum (Sorghum bicolor (L.) Moench). We examined the model's ability to reproduce the relative effects of belowground nutrient uptake on microbial activity using a reanalysis of empirical data showing that miscanthus root exudation provoked a larger soil microbial response than sorghum. From baseline model simulations, we found that the ability of miscanthus to retranslocate N resulted in higher N uptake at a lower C cost than the sorghum/soybean rotation and that soil C and N pools increased under perennial (miscanthus) and decreased under annual (sorghum/soybean) cultivation. The model also predicted that greater root exudation increased soil C accumulation, highlighting the role of roots in forming stable soil C. Overall, the baseline model was unable to reproduce field observations of miscanthus root exudation stimulating microbial activity more than sorghum. To improve the model, we updated the soil microbial parameters in miscanthus to have faster decomposition, a higher C/N ratio, and greater carbon use efficiency. These changes improved the simulated soil microbial response to miscanthus root exudation, supporting the hypothesis that miscanthus soils foster a microbial community that is more responsive to root exudation than that of sorghum.

09 BIOMASS FUELS↗

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗

A Variational Formulation for the Finite Element Analysis of Sound Wave Propagation in a Spherical Shell

Development of design tools to furnish optimal acoustic environments for lightweight aircraft demands the ability to simulate the acoustic system on a workstation. In order to form an effective mathematical model of the phenomena at hand, we have begun by studying the propagation of acoustic waves inside closed spherical shells. Using a fully-coupled fluid-structure interaction model based upon variational principles, we have written a finite element analysis program and are in the process of examining several test cases. Future investigations are planned to increase model accuracy by incorporating non-linear and viscous effects.

Lebiedzik, Catherine↗