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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Particle/Ray Interaction Simulation Manager (PRISM) Assessment Report

The Particle/Ray Interaction Simulation Manager (PRISM) is a software tool developed by Triple Ring Technologies (TRT), http://www.tripleringtech.com/, under a Small Business Innovation Research Award from the Department of Homeland Security (DHS) to investigate the utility of simulations in X-ray-based explosive detection systems. The PRISM tool is intended to provide a standardized and intuitive user interface to control and configure realistic simulations of X-ray imaging systems. It includes a command-line interface that enables the user to configure simulated X-ray radiography and computed tomography (CT) systems. It allows the import of computer-aided design (CAD) models of objects and it supports Monte Carlo simulation engines such as GEANT4. PRISM is designed to simulate realistic X-ray projection images including scatter, noise, and various detector effects such as quantum efficiency, lag, and veiling glare. At the request of DHS, the authors assessed PRISM’s capabilities to simulate data generated by a Micro-CT test-bed system (MCT-TB) housed at the Lawrence Livermore National Laboratory (LLNL). This document describes the results of that assessment.

42 ENGINEERING↗
DOE OSTI2024

Experimental Setup and Learning-Based AI Model for Developing Accurate PV Inverter Models [Slides]

The integration of power electronics-based interfaces presents challenges due to the absence of detailed models and the high computational complexity. Generic models used in system studies lack accuracy in capturing converter dynamics. This paper proposes a data-driven approach developed from experimental setup data. This approach enhances accuracy in photovoltaic inverter modeling. We used two types of PV inverters in the experiment. The recorded experimental data undergo processing through a machine learning model. Results from the model trained through machine learning is also presented.

14 SOLAR ENERGY↗
DOE OSTI2021

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal

In recent years, there has been a growing interest in profiling multiomic modalities within individual cells simultaneously. One such example is integrating combined single-cell RNA sequencing (scRNA-seq) data and single-cell transposase-accessible chromatin sequencing (scATAC-seq) data. Integrated analysis of diverse modalities has helped researchers make more accurate predictions and gain a more comprehensive understanding than with single-modality analysis. However, generating such multimodal data is technically challenging and expensive, leading to limited availability of single-cell co-assay data. Here, we propose a model for cross-modal prediction between the transcriptome and chromatin profiles in single cells. Our model is based on a deep neural network architecture that learns the latent representations from the source modality and then predicts the target modality. It demonstrates reliable performance in accurately translating between these modalities across multiple paired human scATAC-seq and scRNA-seq datasets. Additionally, we developed CrossMP, a web-based portal allowing researchers to upload their single-cell modality data through an interactive web interface and predict the other type of modality data, using high-performance computing resources plugged at the backend.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Snow Micro-Structure Model

PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations: the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.

Micah Johnson, Andrew Slaughter↗
DOE OSTI2019

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

Stalzer, Mark A.↗
DOE OSTI2021

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

Stalzer, Mark A.↗
DOE OSTI2017

An overview of the IEEE human factors standard development activities - 2017 - 230

Since 1980 the Institute of Electrical and Electronics Engineers (IEEE) has supported development of human factors (HF) standards. Within IEEE, Subcommittee 5 (SC5) of the Nuclear Power Engineering Committee develops and maintains HF standards applicable to nuclear facilities. These standards are structured in a hierarchical fashion. The top-level standard defines the HF tasks required to support the integration of human performance into the design process. Five lower tier documents expand upon the upper tier standard. Presently, two new HF standards projects are underway; one to provide HF guidance for the validation of the system interface design and integrated systems operation and another for designing and developing computer-based displays for monitoring and control of nuclear facilities. In addition to producing and maintaining HF standards, SC5 is also involved in outreach activities, including sponsorship of a series of conferences on human factors and nuclear power plants. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Emerging investigator series: methylmercury speciation and dimethylmercury production in sulfidic solutions

Alkylated mercury species (monomethylmercury, MeHg, and dimethylmercury, DMeHg) exhibit significant bioaccumulation, and pose significant risks to ecosystems and human health. Although decades of research have been devoted to understanding MeHg formation and degradation, little is known about the DMeHg formation in aquatic systems. Here, we combine complementary experimental and computational approaches to examine MeHg speciation and DMeHg formation in sulfidic aqueous solutions, with an emphasis on the formation and decomposition of the binuclear bis(methylmercuric(II)) sulfide complex (CH 3 Hg) 2 S. Experimental data indicate that the reaction 2CH 3 Hg + + HS- $→\atop{←}$ (CH 3 Hg) 2 S + H + has a log K = 26.0 ± 0.2. Thus, the binuclear (CH 3 Hg) 2 S complex is likely to be the dominant MeHg species under high MeHg concentrations typically used in experimental investigations of MeHg degradation by sulfate-reducing bacteria (SRB). Our finding of a significant abiotic removal mechanism for MeHg in sulfidic solutions through the formation of relatively insoluble (CH 3 Hg) 2 S suggests careful reexamination of reported “oxidative demethylation” of MeHg by SRB and perhaps other obligate anaerobes. We provide evidence for slow decomposition of (CH 3 Hg) 2 S to DMeHg and HgS, with a first-order rate constant k = 1.5 ± 0.4 × 10 -6 h -1 . Quantum chemical calculations suggest that the reaction proceeds by a novel mechanism involving rearrangement of the (CH 3 Hg) 2 S complex facilitated by strong Hg–Hg interactions that activate a methyl group for intramolecular transfer. Predictions of DMeHg formation rates under a variety of field and laboratory conditions indicate that this pathway for DMeHg formation will be significant in laboratory experiments utilizing high MeHg concentrations, favoring (CH 3 Hg) 2 S formation. Finally, in natural systems with relatively high MeHg/[H 2 S] T ratios (the oxic/anoxic interface, for example), DMeHg production may be observed, and warrants further investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

BioRT‐HBV 1.0: A Biogeochemical Reactive Transport Model at the Watershed Scale

Abstract Reactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed‐scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed‐scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT‐HBV 1.0, a watershed‐scale, hydro‐biogeochemical RTM that builds upon the widely used, bucket‐type HBV model known for its simplicity and minimal data requirements. BioRT‐HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT‐HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous‐to‐measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy‐to‐use graphical user interface, BioRT‐HBV can be a useful research tool for users without in‐depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community.

Sadayappan, Kayalvizhi↗
DOE OSTI2017

Probing low noise at the MOS interface with a spin-orbit qubit.

The silicon metal-oxide-semiconductor (MOS) material system is technologically important for the implementation of electron spin-based quantum information technologies. Researchers predict the need for an integrated platform in order to implement useful computation, and decades of advancements in silicon microelectronics fabrication lends itself to this challenge. However, fundamental concerns have been raised about the MOS interface (e.g. trap noise, variations in electron g-factor and practical implementation of multi-QDs). Furthermore, two-axis control of silicon qubits has, to date, required the integration of non-ideal components (e.g. microwave strip-lines, micro-magnets, triple quantum dots, or introduction of donor atoms). In this paper, we introduce a spin-orbit (SO) driven singlet- triplet (ST) qubit in silicon, demonstrating all-electrical two-axis control that requires no additional integrated elements and exhibits charge noise properties equivalent to other more model, but less commercially mature, semiconductor systems. We demonstrate the ability to tune an intrinsic spin-orbit interface effect, which is consistent with Rashba and Dresselhaus contributions that are remarkably strong for a low spin-orbit material such as silicon. The qubit maintains the advantages of using isotopically enriched silicon for producing a quiet magnetic environment, measuring spin dephasing times of 1.6 μs using 99.95% 28 Si epitaxy for the qubit, comparable to results from other isotopically enhanced silicon ST qubit systems. This work, therefore, demonstrates that the interface inherently provides properties for two-axis control, and the technologically important MOS interface does not add additional detrimental qubit noise. isotopically enhanced silicon ST qubit systems

Jock, Ryan Michael↗
DOE OSTI2018

A Digitally Interfaced Analog Correlation Filter System for Object Tracking Applications

This study reports a 24×57 correlation filter system for object tracking applications. While digital interfacing of the input and output data enabled a standard and flexible way of communication with pre- and post-processing digital blocks, the multiply-accumulate (MAC) operations were performed in the analog domain to save power and area. The proposed system utilizes non-volatile floating-gate memories to store filter coefficients. The chip was fabricated in a 0.13- μm CMOS process and occupies 3.23 mm 2 of silicon area. The system dissipates 388.4 μW of power at a throughput of 11.3 kVec/s, achieving an energy efficiency of 25.2 pJ/MAC. Finally, experimental results for a custom filter designed to detect vehicles are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Plasma transport in an Eulerian AMR code

A plasma transport model has been implemented in an Eulerian AMR radiation-hydrodynamics code, xRage, which includes plasma viscosity in the momentum tensor, viscous dissipation in the energy equations, and binary species mixing with consistent species mass and energy fluxes driven by concentration gradients, ion and electron baro-diffusion terms and temperature gradient forces. The physics basis, computational issues, numeric options, and results from several test problems are discussed. The transport coefficients are found to be relatively insensitive to the kinetic correction factors when the concentrations are expressed with the molar fractions and the ion mass differences are large. The contributions to flow dynamics from plasma viscosity and mass diffusion were found to increase significantly as scale lengths decrease in an inertial confinement fusion relevant Kelvin-Helmholtz instability mix layer. The mixing scale lengths in the test case are on the order of 100 μm and smaller for viscous effects to appear and 10 μm or less for significant ion species diffusion, evident over durations on the order of nanoseconds. The temperature gradient driven mass flux is seen to deplete a high Z tracer ion at the ion shock front. The plasma transport model provides the generation of the atomic mix per unit of interfacial area between two species with no free parameters. The evolution of the total atomic mix then depends also on an accurate resolution or estimate of the interfacial area between the species mixing by plasma transport. High resolution simulations or a more Lagrangian-like treatment of species interfaces may be required to distinguish plasma transport and numerical diffusion in an Eulerian computation of complex and dynamically evolving mix regions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Material and Interface Engineering Strategies to Mitigate Decoherence in Superconducting Qubits

While significant strides have been made to increase the coherence time of superconducting qubits, further advancements are essential for realizing scalable quantum computing. Decoherence is often a result of loss and noise stemming from two-level systems and excess quasiparticles, arising due to material defects, fabrication processes, and ambient exposure, particularly at surfaces and interfaces. Our recent efforts to mitigate these decoherence mechanisms have employed a variety of strategies, including low-loss surface encapsulation materials, advanced substrate preparation techniques, modifications to metal film growth, and the development of novel fabrication processes. The structural and chemical properties of materials, surfaces, and interfaces are studied using scanning probe microscopy, electron microscopy, photoelectron spectroscopy, mass spectrometry, and X-ray diffraction, which is correlated to device performance metrics, including superconducting resonator internal quality factor and qubit T1 time. This information is used to identify and understand material sources of loss and their origins in the device fabrication process. Through multi-institution efforts within SQMS we have identified the loss mechanism of interstitial hydrogen in niobium-based devices and shown how standard fabrication processes introduce these hydrides, developing strategies to mitigate their formation.1 Furthermore, we have characterized the metal-substrate interface, including the loss of niobium-silicides formed at that interface, and developed silicon surface treatments that reduce atomic scale roughness and oxygen content at the metal-substrate and Josephson junction interfaces.2-4 By developing the connection between materials properties and the overall performance of superconducting quantum circuitry, we can develop fabrication strategies to mitigate material losses, thus supporting the ongoing efforts to enhance coherence time in superconducting quantum devices. 1. Torres-Castanedo, C. G.*, Goronzy, D. P.*, et al., Adv. Funct. Mater., 2401365 (2024) 2. Lu, X., et al., Phys. Rev. Materials 6, 064402 (2022) 3. Berti, G., Appl. Phys. Lett. 122, 192605 (2023) 4. Kopas, C. J., Goronzy, D. P., et al., arXiv:2408.02863 (2024)

Goronzy, Dominic P.↗
DOE OSTI2022

Critical role of orbital hybridization in the Dzyaloshinskii-Moriya interaction of magnetic interfaces

Dzyaloshinskii-Moriya interaction (DMI), an interfacial spin-orbit coupling (ISOC)-related effect, has become foundational for spintronic research and magnetic memory and computing technologies. However, the underlying mechanism of DMI, including the quantitative role of ISOC, has remained a long-standing unsettled problem due to the great challenge in quantifying and widely tuning ISOC strength in a strong DMI material system. Here, we find that DMI, ISOC, and orbital hybridization at the model magnetic interface Au 1-x Pt x /Co can be quantified and tuned significantly at the same time through the composition of the Au 1-x Pt x , without varying the bulk SOC and the electronegativity. From this ability, we establish that the widespread expectation that DMI should scale in linear proportion to ISOC breaks down at the Au 1-x Pt x /Co interface where degree of orbital hybridization varies with the Au 1-x Pt x composition and that the unexpected DMI behaviors can be understood well by the critical role of orbital hybridization. Our study provides a quantitative frame for comprehensively understanding interfacial DMI of various magnetic interfaces and establishes orbital hybridization as a new degree of freedom for controlling DMI in high-performance chiral domain wall/skyrmion devices and ultrafast magnetic tunnel junctions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Preliminary Development of a Drift-Flux Model Based Pin-Resolved Core Thermal-Hydraulic Code for Dedicated Use in Efficient High-Fidelity Neutronics Coupled Calculations

As the high-fidelity multiphysics coupled core calculation becomes more practical with the advent of high-performance computing technology, efficient coupling of a neutronics code with a thermal-hydraulic (T/H) code at the pin level poses a new challenge. The COBRA-TF (CTF) code which is one of the well-known subchannel analysis codes based on the two-fluid, three-field model was coupled with many neutron transport codes such as MPACT, TORTTD, and nTRACER due to the easiness of coupling by its well-established coupling interface. Nevertheless, the calculation efficiency of such coupled codes is not satisfactory because of the heavy computational burden of CTF. The MATRA subchannel analysis code of KAERI which is based on the homogeneous equilibrium model (HEM) was coupled with neutronics codes as well. The choice of the HEM and the marching scheme in MATRA reduces the computational burden significantly. However, the applicability of the HEM for the two-phase flow conditions is limited to normal operating conditions of pressurized water reactors (PWRs) and therefore a better model which would allow wider applicability than HEM is necessary in order to deal with the core states involving nontrivial voiding. The drift-flux model (DFM) which uses 5 equations for two-fluid analyses by adopting the mixture velocity instead of two phasic velocities can be a good compromise between the two-fluid model and the HEM. With the DFM, the computational cost can be reduced and moreover the modeling of the interfacial area constitutive relations can be avoided. The phase separation for the mixture velocity can be incorporated by using the drift-flux parameters, C0 and Vgj, which can be obtained by using empirical formulas. Several subchannel codes such as WOSUB and ASSERT were developed based on the DFM. It was also adopted in some system analysis codes such as RETRAN3D. In the work here, the development of a DFM based pin-resolved T/H analysis code, ESCOT (Efficient Simulator of Core Thermal-hydraulics), is introduced for the use in efficient coupled calculations with a high-fidelity neutronics code. The field equations and the numerical methods are briefly described. Then the efficiency tests of various linear system solvers including the Krylov subspace methods (KSMs) are presented. A test problem is solved by ESCOT, MATRA and CTF for performance comparison and validation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

GPU Acceleration of Mean Free Path Based Kernel Density Estimators for Monte Carlo Neutronics Simulations

Kernel Density Estimators (KDEs) are a non-parametric density estimation technique that has recently been applied to Monte Carlo radiation transport simulations. Kernel density estimators are an alternative to histogram tallies for obtaining global solutions in Monte Carlo tallies. With KDEs, a single event, either a collision or particle track, can contribute to the score at multiple tally points with the uncertainty at those points being independent of the desired resolution of the solution. Thus, KDEs show potential for obtaining estimates of a global solution with reduced variance when compared to a histogram. Previously, KDEs have been applied to neutronics for one-group reactor physics problems and fixed source shielding applications. However, little work was done to obtain reaction rates using KDEs. This paper introduces a new form of the MFP KDE that is capable of handling general geometries. Furthermore, extending the MFP KDE to 2-D problems in continuous energy introduces inaccuracies to the solution. An ad-hoc solution to these inaccuracies is introduced that produces errors smaller than 4% at material interfaces.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗