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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Validation of High-Fidelity Reactor Physics Models for Support of the KJRR Experimental Campaign in the Advanced Test Reactor

The Korea Atomic Energy Research Institute is currently in the process of qualifying a Low-Enriched Uranium fuel element design for the new Ki-Jang Research Reactor (KJRR). As part of this effort, a prototype KJRR fuel element was irradiated for several operating cycles in the Northeast Flux Trap of the Advanced Test Reactor (ATR) at the Idaho National Laboratory. The KJRR fuel element contained a very large quantity of fissile material (618g 235U) in comparison with historical ATR experiment standards (<1g 235U), and its presence in the ATR flux trap was expected to create a neutronic configuration that would be well outside of the approved validation envelope for the reactor physics analysis methods used to support ATR operations. Accordingly it was necessary, prior to high-power irradiation of the KJRR fuel element in the ATR, to conduct an extensive set of new low-power physics measurements with the KJRR fuel element installed in the ATR Critical Facility (ATRC), a companion facility to the ATR that is located in an immediately adjacent building, sharing the same fuel handling and storage canal. The new measurements had the objective of expanding the validation envelope for the computational reactor physics tools used to support ATR operations and safety analysis to include the planned KJRR irradiation in the ATR and similar experiments that are anticipated in the future. The computational and experimental results demonstrated that the neutronic behavior of the KJRR fuel element in the ATRC is well-understood, both in terms of its general effects on core excess reactivity and fission power distributions, its effects on the calibration of the core lobe power measurement system, as well as in terms of its own internal fission rate distribution and total fission power per unit ATRC core power. Taken as a whole, these results have significantly extended the ATR physics validation envelope, thereby enabling an entire new class of irradiation experiments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Full radiator-perturber interaction in computer simulations of hydrogenic spectral line broadening by plasmas

Spectral line broadening by plasmas can be computed by solving the equation of motion for the dipole of the radiating system perturbed by a fluctuating potential obtained from computer simulations. Such calculations have relied on the multipole expansion of the radiator-plasma interaction often keeping only the dipole term. With increasing density, however, higher multipoles as well as plasma perturbers overlapping the bound electron wave functions are expected to become important. For hydrogenic systems, the atomic matrix elements of the full Coulomb and screened Coulomb interactions are given by analytical formulas. Using these results, a computer simulation approach that accounts for the full radiator-plasma interaction is developed. One benefit is the removal of inherent strong collision divergences in the multipole expansion approximation. Furthermore, it yields the plasma polarization shift produced by perturbers penetrating the wave function of the radiator bound electrons. Here, the model was applied to hydrogenic argon Ly-α , Ly- β , and Ly-$\gamma$ spectral lines in a dense argon plasma at free electron densities of 10 24 or 10 25 cm ⁻3 and temperature of $800$ $eV$ relevant to plasma diagnostic techniques for inertial confinement fusion implosions.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Direct observation of dislocation structure evolution in SRF cavity niobium using electron channeling contrast imaging

Two major goals of superconducting radio frequency cavity research and development are achieving higher accelerating gradient and gaining the highest quality factor, a measure of efficiency. However, the consistent improvement of these performance metrics is restricted by many factors, one of which is microstructural defects, such as dislocation substructures within the material. In this work, dislocation evolution is compared in four samples extracted from a 2.8 mm thick large-grain niobium slice, with tensile axes chosen to generate specific dislocation structures during subsequent deformation. The four samples are (1) as-extracted, (2) extracted and annealed, (3) extracted and then deformed to 40% tensile strain, and (4) extracted, annealed at 800 °C 2 h, and then deformed to 40% strain. Electron channeling contrast imaging was performed on all samples to characterize initial dislocation density and dislocation structure evolution due to annealing and deformation, and related to the mechanical behavior observed in stress-strain curves. A fundamental understanding of dislocation evolution in niobium is necessary to develop computational models to simulate cavity forming, which could enable new processing methods for cavity fabrication to be identified that could lead to improved performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Mean Field Theory of Self‐Organizing Memristive Connectomes

Abstract Biological neuronal networks are characterized by nonlinear interactions and complex connectivity. Given the growing impetus to build neuromorphic computers, understanding physical devices that exhibit structures and functionalities similar to biological neural networks is an important step toward this goal. Self‐organizing circuits of nanodevices are at the forefront of the research in neuromorphic computing, as their behavior mimics synaptic plasticity features of biological neuronal circuits. However, an effective theory to describe their behavior is lacking. This study provides for the first time an effective mean field theory for the emergent voltage‐induced polymorphism of circuits of a nanowire connectome, showing that the behavior of these circuits can be explained by a low‐dimensional dynamical equation. The equation can be derived from the microscopic dynamics of a single memristive junction in analytical form. The effective model is tested on experiments of nanowire networks and show that it fits both the potentiation and depression of these synapse‐mimicking circuits. It is shown that this theory applies beyond the case of nanowire networks by formulating a general mean‐field theory of conductance transitions in self‐organizing memristive connectomes.

Caravelli, Francesco↗
DOE OSTI2021

Limitations of Hartree–Fock with quantum resources

The Hartree–Fock problem provides the conceptual and mathematical underpinning of a large portion of quantum chemistry. As efforts in quantum technology aim to enhance computational chemistry algorithms, the Hartree–Fock method, central to many other numerical approaches, is a natural target for quantum enhanced algorithms. While quantum computers and quantum simulation offer many prospects for the future of modern chemistry, the non-deterministic polynomial-complete Hartree–Fock problem is not a likely candidate. Here, we highlight this fact from a number of perspectives including computational complexity, practical examples, and the full characterization of energy landscapes for simple systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

TU-AB-BRC-02: Accuracy Evaluation of GPU-Based OpenCL Carbon Monte Carlo Package (goCMC) in Biological Dose and Microdosimetry in Comparison to FLUKA Simulations

Purpose: One of the most accurate methods for radiation transport is Monte Carlo (MC) simulation. Long computation time prevents its wide applications in clinic. We have recently developed a fast MC code for carbon ion therapy called GPU-based OpenCL Carbon Monte Carlo (goCMC) and its accuracy in physical dose has been established. Since radiobiology is an indispensible aspect of carbon ion therapy, this study evaluates accuracy of goCMC in biological dose and microdosimetry by benchmarking it with FLUKA. Methods: We performed simulations of a carbon pencil beam with 150, 300 and 450 MeV/u in a homogeneous water phantom using goCMC and FLUKA. Dose and energy spectra for primary and secondary ions on the central beam axis were recorded. Repair-misrepair-fixation model was employed to calculate Relative Biological Effectiveness (RBE). Monte Carlo Damage Simulation (MCDS) tool was used to calculate microdosimetry parameters. Results: Physical dose differences on the central axis were <1.6% of the maximum value. Before the Bragg peak, differences in RBE and RBE-weighted dose were <2% and <1%. At the Bragg peak, the differences were 12.5% caused by small range discrepancy and sensitivity of RBE to beam spectra. Consequently, RBE-weighted dose difference was 11%. Beyond the peak, RBE differences were <20% and primarily caused by differences in the Helium-4 spectrum. However, the RBE-weighted dose agreed within 1% due to the low physical dose. Differences in microdosimetric quantities were small except at the Bragg peak. The simulation time per source particle with FLUKA was 0.08 sec, while goCMC was approximately 1000 times faster. Conclusion: Physical doses computed by FLUKA and goCMC were in good agreement. Although relatively large RBE differences were observed at and beyond the Bragg peak, the RBE-weighted dose differences were considered to be acceptable.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Optimizing Simulation Fidelity in Direct-Drive Inertial Confinement Fusion with Cassio

Recently, the National Ignition Facility (NIF) demonstrated that inertial confinement fusion (ICF) is capable to achieve thermonuclear (TN) ignition in the laboratory, making it a crucial method on the path to replicate the Sun’s power production mechanism on Earth. However, the physics governing the high-energy density environments is very complex and remains a challenge to fully understand and model. For example, dopants in the TN fuel are important diagnostic tools to extract the thermodynamic conditions of the plasma. However, if their concentration is chosen too high, they can significantly degrade the performance of an ICF capsule. In this study, we use the Los Alamos National Laboratory radiation-hydrodynamics code Cassio to model ICF implosions of capsules which contain deuterium fuel with high-Z dopants like Krypton and Argon from the high-Z campaign conducted 15 years ago. We focus on how chosen computational and physics parameters influence the implosion outcomes. By systematically changing the resolution of the computational mesh and the photon energies as well as modifying settings for the laser drive and TN fuel pre-heat effects, we assess the impact on experimentally measured performance metrics like neutron production from TN burn and x-ray emission during the implosion. Our results will help to improve the fidelity of simulations and guide future numerical studies and experimental designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A classical model for three-body interactions in aqueous ionic systems

We present a classical induction model to evaluate the three-body ion–water–water (I–W–W) and water–water–water (W–W–W) interactions in aqueous ionic systems. The classical description of the induction energy is based on electrostatic distributed multipoles up to hexadecapole and distributed polarizabilities up to quadrupole–quadrupole on the O and H atoms of water. The monatomic ions were described by a point charge and a dipole–dipole polarizability, while for the polyatomic ions, distributed multipoles up to hexadecapole and distributed polarizabilities up to quadrupole–quadrupole were used. The accuracy of the classical model is benchmarked against an accurate dataset of 936 (I–W–W) and 2184 (W–W–W) three-body terms for 13 different monatomic and polyatomic cation and anion systems. The classical model shows excellent agreement with the reference second order Moller–Plesset and coupled-cluster single double and perturbative triple [CCSD(T)] three-body energies. The Root-Mean-Square-Errors (RMSEs) for monatomic cations, monatomic anions, and polyatomic ions were 0.29, 0.25, and 0.12 kcal/mol, respectively. The corresponding RMSE for 1744 CCSD(T)/aVTZ three-body (W–W–W) energies, used to train MB-pol, was 0.12 kcal/mol. The accuracy of the proposed classical model demonstrates that the three-body term for aqueous ionic systems can be accurately modeled classically. This approach provides a fast, efficient, and as-accurate path toward modeling the three-body term in aqueous ionic systems that is fully transferable across systems with different ions without the need to fit to tens of thousands of ab initio calculations for each ion to extend existing many-body force fields to interactions between water and ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Suppressing simulation bias in multi-modal data using transfer learning

Abstract Many problems in science and engineering require making predictions based on few observations. To build a robust predictive model, these sparse data may need to be augmented with simulated data, especially when the design space is multi-dimensional. Simulations, however, often suffer from an inherent bias. Estimation of this bias may be poorly constrained not only because of data sparsity, but also because traditional predictive models fit only one type of observed outputs, such as scalars or images, instead of all available output data modalities, which might have been acquired and simulated at great cost. To break this limitation and open up the path for multi-modal calibration, we propose to combine a novel, transfer learning technique for suppressing the bias with recent developments in deep learning, which allow building predictive models with multi-modal outputs. First, we train an initial neural network model on simulated data to learn important correlations between different output modalities and between simulation inputs and outputs. Then, the model is partially retrained, or transfer learned, to fit the experiments; a method that has never been implemented in this type of architecture. Using fewer than 10 inertial confinement fusion experiments for training, transfer learning systematically improves the simulation predictions while a simple output calibration, which we design as a baseline, makes the predictions worse. We also offer extensive cross-validation with real and carefully designed synthetic data. The method described in this paper can be applied to a wide range of problems that require transferring knowledge from simulations to the domain of experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

Global Sampling for Integrating Physics-Specific Subsystems and Quantifying Uncertainties of CO 2 Geological Sequestration

The risk of CO 2 leakage from a deep storage reservoir into a shallow aquifer through a fault is assessed and studied using physics-specific computer models. The hypothetical CO 2 geological sequestration system is composed of three subsystems: a deep storage reservoir, a fault in caprock, and a shallow aquifer, which are modeled respectively by considering sub-domain-specific physics. Supercritical CO 2 is injected into the reservoir subsystem with uncertain permeabilities of reservoir, caprock, and aquifer, uncertain fault location, and injection rate (as a decision variable). The simulated pressure and CO 2 /brine saturation are connected to the fault-leakage model as a boundary condition. CO 2 and brine fluxes from the fault-leakage model at the fault outlet are then imposed in the aquifer model as a source term. Moreover, uncertainties are propagated from the deep reservoir model, to the fault-leakage model, and eventually to the geochemical model in the shallow aquifer, thus contributing to risk profiles. To quantify the uncertainties and assess leakage-relevant risk, we propose a global sampling-based method to allocate sub-dimensions of uncertain parameters to sub-models. The risk profiles are defined and related to CO 2 plume development for pH value and total dissolved solids (TDS) below the EPA's Maximum Contaminant Levels (MCL) for drinking water quality. A global sensitivity analysis is conducted to select the most sensitive parameters to the risk profiles. The resulting uncertainty of pH- and TDS-defined aquifer volume, which is impacted by CO 2 and brine leakage, mainly results from the uncertainty of fault permeability. Subsequently, high-resolution, reduced-order models of risk profiles are developed as functions of all the decision variables and uncertain parameters in all three subsystems.

25 ENERGY STORAGE↗
DOE OSTI2022

Combining Physics and Machine Learning for the Next Generation of Molecular Simulation

Simulating molecules and atomic systems at quantum accuracy is a grand challenge for science in the 21 st century. Quantum-accurate simulations would enable the design of new medicines and the discovery of new materials. The defining problem in this challenge is that quantum calculations on large molecules, like proteins or DNA, are fundamentally impossible with current algorithms. In this work, we explore a range of different methods that aim to make large, quantum-accurate simulations possible. We show that using advanced classical models, we can accurately simulate ion channels, an important biomolecular system. We show how advanced classical models can be implemented in an exascale-ready software package. Lastly, we show how machine learning can learn the laws of quantum mechanics from data and enable quantum electronic structure calculations on thousands of atoms, a feat that is impossible for current algorithms. Altogether, this work shows that combining advances in physics models, computing, and machine learning, we are moving closer to the reality of accurately simulating our molecular world.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Remote Gamma Ray Spectrum Acquisition

An approach is presented that utilizes networking, hardware, and software components to allow data acquisition from Canberra's Osprey multi-channel analyzer (MCA) detector. The research has allowed researchers to remotely connect to Canberra's ProSpect gamma spectroscopy software and the detector by making use of Windows Server 2012 and a network connection. Gamma rays are ionizing, electromagnetic radiation of high energy and short wavelength. They are produced primarily by radioactive decay. Several undergraduate courses at Texas A and M University-Kingsville focus on teaching students to measure and research gamma rays while in the laboratory. Recent needs have motivated efforts to develop a network solution that allows authorized students and researchers to access the ProSpect software and Osprey MCA detectors remotely from multiple computers connected to the campus network. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Extension of the Advanced Test Reactor Operating Envelope Via Enhanced Reactor Physics Validation Techniques

The Korea Atomic Energy Research Institute is currently in the process of qualifying a low-enriched-uranium fuel element design for the new Ki-Jang Research Reactor (KJRR). As part of this effort, a prototype KJRR fuel element was irradiated in this paper for several operating cycles in the northeast flux trap of the Advanced Test Reactor (ATR) at the Idaho National Laboratory. The KJRR fuel element contained a very large quantity of fissile material (618 g 235 U) in comparison with historical ATR experiment standards (<1 g 235 U), and its presence in the ATR flux trap was expected to create a neutronic configuration that would be well outside of the approved validation envelope for the reactor physics analysis methods used to support ATR operations. Accordingly, it was necessary to conduct an extensive set of new low-power physics measurements in the ATR Critical Facility (ATRC), a companion facility to the ATR, located in an immediately adjacent building and sharing the same fuel storage canal. The new measurements included fission power distributions, reactivity, and measurements related to the calibration of the in-core online instrumentation. The effort was focused on the objective of expanding the validation envelope for the computational reactor physics tools used to support ATR operations and safety analysis to include the planned KJRR irradiation in the ATR and similar experiments that are anticipated in the future. The computational and experimental results have demonstrated that the neutronic behavior of the KJRR fuel element in the ATRC is well understood in terms of its general effects on ATRC core reactivity and fission power distributions and its effects on the calibration of the ATR Lobe Power Calculation and Indication System, as well as in terms of its own internal fission rate distribution and total fission power per unit ATRC core power. Finally, taken as a whole, these results have significantly extended the ATR physics validation envelope, thereby enabling an entire new class of irradiation experiments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Improving the stellarator through advances in plasma theory

Improvements to the stellarator concept can be realized through advancements in theoretical and computational plasma physics. Herein, recent advances are reported in the topical areas of: (1) improved energetic ion confinement, (2) the impact of three-dimensional (3D) shaping on turbulent transport, (3) reducing coil complexity, (4) novel optimization and design methods, and (5) computational magnetohydrodynamic tools. Furthermore, these advances enable the development of new stellarator configurations with improved confinement properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Building an AI-enhanced modeling framework to address multiscale predictability challenges

Focal Area(s): Build an AI-enhanced modeling framework that integrates the three focus areas in the solicitation. Science Challenge: The 4M-2N complexities (Multiscale, Multiphysics, Multibody, Multidimension, Non-linearity, and Non-Gaussianality) of atmospheric aerosol-cloud-precipitation-turbulence-radiation system poses physical and computational challenges to further advance predictive models; We plan to address the challenges by developing an AI-enhanced modeling framework that facilitates automated calibration and improvement of subgrid parameterizations, enhance data assimilation of measurements to improve initial and boundary conditions used to drive the physical model, and optimally blends data-driven and physics-based forecasting models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A primer on the energy efficiency of computing

The efficiency of computing at peak output has increased rapidly since the dawn of the computer age. This paper summarizes some of the key factors affecting the efficiency of computing in all usage modes. While there is still great potential for improving the efficiency of computing devices, we will need to alter how we do computing in the next few decades because we are finally approaching the limits of current technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗