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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Simultaneous enhancement of the coercivity and remanence at high temperatures in a sintered Nd-Fe-B magnet after grain boundary diffusion with Dy60Co40 alloy

Highlights: • Dy and Co enriched shells were formed on the Nd{sub 2}Fe{sub 14}B grain boundaries. • Coercivity and remanence were increased simultaneously at high temperatures. • Remanence stability was improved with little change of the Curie temperature. - Abstract: The grain boundary diffusion process (GBDP) using Dy{sub 60}Co{sub 40} alloy was applied to a sintered Nd-Fe-B magnet. After GBDP the temperature stability of remanence was improved greatly with the remanence temperature coefficient improving from −0.140%/°C to −0.095%/°C while the Curie temperature increased marginally. Both the coercivity and remanence were increased simultaneously at high temperatures. Microstructure and composition analysis revealed that Dy and Co enriched shells were formed on Nd{sub 2}Fe{sub 14}B grain boundaries after GBDP. The Dy enriched shell increased the coercivity while the Co enriched shell decreased the temperature sensitivity of remanence and then increased the remanence at high temperatures.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Spiking Neurons for Analysis of Patterns

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological neurons). These features enable the neurons to adapt their responses to high-rate inputs from sensors, and to adapt their firing thresholds to mitigate noise or effects of potential sensor failure. The mathematical derivation of the SVM starts from a prior model, known in the art as the point soma model, which captures all of the salient properties of neuronal response while keeping the computational cost low. The point-soma latency time is modified to be an exponentially decaying function of the strength of the applied potential. Choosing computational efficiency over biological fidelity, the dendrites surrounding a neuron are represented by simplified compartmental submodels and there are no dendritic spines. Updates to the dendritic potential, calcium-ion concentrations and conductances, and potassium-ion conductances are done by use of equations similar to those of the point soma. Diffusion processes in dendrites are modeled by averaging among nearest-neighbor compartments. Inputs to each of the dendritic compartments come from sensors. Alternatively or in addition, when an affected neuron is part of a pool, inputs can come from other spiking neurons. At present, SVM neural networks are implemented by computational simulation, using algorithms that encode the SVM and its submodels. However, it should be possible to implement these neural networks in hardware: The differential equations for the dendritic and cellular processes in the SVM model of spiking neurons map to equivalent circuits that can be implemented directly in analog very-large-scale integrated (VLSI) circuits.

Huntsberger, Terrance↗
NASA NTRS2012

Fermi Large Area Telescope Observations of the Supernova Remnant GS.7-0.1

We present a detailed analysis of the GeV gamma-ray emission toward the supernova remnant (SNR) G8.7-0.1 with the Large Area Telescope (LAT) onboard the Fermi Gamma-ray Space Telescope. An investigation of the relationship among G8.7-0.1 and the TeV unidentified source HESS J1804-216 provides us with an important clue on diffusion process of cosmic rays if particle acceleration operates in the SNR. The GeV gamma-ray emission is extended with most of the emission in positional coincidence with the SNR G8.7-0.1 and a lesser part located outside the western boundary of G8.7-0.1. The region of the gamma-ray emission overlaps spatially-connected molecular clouds, implying a physical connection for the gamma-ray structure. The total gamma-ray spectrum measured with LAT from 200 MeV-100 GeV can be described by a broken power-law function with a break of 2.4 +/- 0.6 (stat) +/- 1.2 (sys) GeV, and photon indices of2.10 +/- 0.06 (stat) +/- 0.10 (sys) below the break and 2.70 +/- 0.12 (stat) +/- 0.14 (sys) above the break. Given the spatial association among the gamma rays, the radio emission ofG8.7-0.1, and the molecular clouds, the decay of pions produced by particles accelerated in the SNR and hitting the molecular clouds naturally explains the GeV gamma-ray spectrum. We also find that the GeV morphology is not well represented by the TeV emission from HESS Jl804-2l6 and that the spectrum in the Ge V band is not consistent with the extrapolation of the TeV gamma-ray spectrum. The spectral index of the TeV emission is consistent with the particle spectral index predicted by a theory that assumes energy-dependent diffusion of particles accelerated in an SNR. We discuss the possibility that the TeV-spectrum originates from the interaction of particles accelerated in G8.7-0.l with molecular clouds, and we constrain the diffusion coefficient of the particles.

Ferrara, E. C.↗
NASA NTRS2011

Fermi Large Area Telescope Observations of the Supernova Remnant GS.7-0.1

We present a detailed analysis of the GeV gamma-ray emission toward the supernova remnant (SNR) G8.7-0.1 with the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope. An investigation of the relationship among G8.7-0.l and the TeV unidentified source HESS J1804-216 provides us with an important clue on diffusion process of cosmic rays if particle acceleration operates in the SNR. The GeV gamma-ray emission is extended with most of the emission in positional coincidence with the SNR G8.7-0.l and a lesser part located outside the western boundary of G8.7-0.l. The region of the gamma-ray emission overlaps spatially-connected molecular clouds, implying a physical connection for the gamma-ray structure. The total gamma-ray spectrum measured with LAT from 200 MeV-100 GeV can be described by a broken power-law function with a break of 2.4 +/- 0.6 (stat) +/- 1.2 (sys) GeV, and photon indices of 2.10 +/- 0.06 (stat) +/- 0.10 (sys) below the break and 2.70 +/- 0.12 (stat) +/- 0.l4 (sys) above the break. Given the spatial association among the gamma rays, the radio emission of G8.7-0.1, and the molecular clouds, the decay of 1IoS produced by particles accelerated in the SNR and hitting the molecular clouds naturally explains the GeV gamma-ray spectrum. We also find that the GeV morphology is not well represented by the TeV emission from HESS J1804-216 and that the spectrum in the GeV band is not consistent with the extrapolation of the TeV gamma-ray spectrum. The spectral index of the TeV emission is consistent with the particle spectral index predicted by a theory that assumes energy-dependent diffusion of particles accelerated in an SNR. We discuss the possibility that the TeV spectrum originates from the interaction of particles accelerated in G8.7-0.1 with molecular clouds, and we constrain the diffusion coefficient of the particles.

Ajello, M.↗
DOE OSTI2018

Effects of Calcite Impurities in Bentonite Buffer Systems on Uranium(VI) Solution Speciation and Sorption Behavior

In many nuclear waste disposal scenarios, bentonite is the proposed buffer material surrounding nuclear waste containers. Its main mineralogical component, Na-montmorillonite clay, is expected to limit radionuclide mobility to slow diffusion processes due to the clay’s low porosity and permeability, and the high sorption affinity of clay surface complexation and cation exchange sites for many radionuclides. Given its mineral structure, montmorillonite provides two types of porosities that can be accessible to radioactive contaminants: macropores between clay particles and interlayer spaces within clay particles, which become dominant at increasing degrees of bentonite compaction. Despite the fact that bentonite naturally contains a variety of mineral impurities (e.g., quartz, feldspars and calcite), most previous studies have only focused on radionuclide interactions with pure Na-montmorillonite phases. Hence, in this study, we will investigate the influence of calcite impurities on uranium(VI) (U(VI)) solution speciation and sorption behavior in bentonite systems. In the presence of water, calcite impurities are expected to lead to milli-molar concentrations of dissolved calcium over a wide range of pH conditions. Consequently, Ca 2+ could – at least partially – replace Na + on clay cation exchange sites, with further implications for exchange reactions of cationic U(VI) species. In addition, ternary U(VI)-Ca-carbonate solution species (CaUO 2 (CO 3 ) 3 2- and Ca 2 UO 2 (CO 3 ) 3 ) will largely replace U(VI)-carbonate species (UO 2 (CO 3 ) 3 4- and UO 2 (CO 3 ) 2 2- ) at alkaline pH. These larger, but lower-charged U(VI) species, may show different sorption and diffusion characteristics, e.g. if their access to negatively-charged clay interlayer spaces is different from binary U(VI)-carbonate complexes. In this presentation, we will first demonstrate the impacts of calcite impurities on U(VI) solution speciation based on PHREEQC simulations. We will then discuss first results from U(VI) sorption studies in these systems. This research is being performed using funding received from the DOE Office of Nuclear Energy's Nuclear Energy University Program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2011

Observation of Hydrological Processes Using Remote Sensing: Volume 2: The Science of Hydrology - Chapter 2.14

Improving water management can make a significant contribution to achieving most of the Millennium Development Goals established by the UN General Assembly in 2000, especially those related to poverty, hunger, and major diseases. The World Summit on Sustainable Development (WSSD) in 2002 recognized this need. Water and sanitation in particular received great attention from the Summit. The Johannesburg Plan of Implementation recommended to improve water resources management and scientific understanding of the water cycle through joint cooperation and research. For this purpose, it is recommended to promote knowledge sharing, provide capacity building, and facilitate the transfer of technology including remote-sensing (RS) and satellite technologies, especially to developing countries and countries with economies in transition, and to support these countries in their efforts to monitor and assess the quantity and quality of water resources, for example, by establishing and/or further developing national monitoring networks and water resources databases and by developing relevant national indicators. The Johannesburg Plan also adopted integrated water resources management as the overarching concept in addressing and solving water-related issues. As a result of the commitments made in the Johannesburg Plan of Implementation, several global and regional initiatives have emerged. Current international initiatives such as the Global Monitoring for Environment and Security (GMES) program of the European Commission and the European Space Agency (ESA), and the Global Earth Observation System of Systems (GEOSS) 10-Year Implementation Plan, have all identified Earth observation (EO) of the water cycle as the key in helping to solve the world s water problems. The availability of spatial information on water quantity and quality will also enable closure of the water budget at river basin and continental scales to the point where effective water management is essential (e.g., as requested by the European Union s Water Framework Directive (WFD), as well as national policies). Geo-information science and EO are vital in achieving a better understanding of the water cycle and better monitoring, analysis, prediction, and management of the world s water resources. The major components of the water cycle of the Earth system and their possible observations are presented. Such observations are essential to understand the global water cycle and its variability, both spatially and temporally, and can only be achieved consistently by means of EOs. Additionally, such observations are essential to advance our understanding of coupling between the terrestrial, atmospheric, and oceanic branches of the water cycle, and how this coupling may influence climate variability and predictability. Water resources management directly interferes with the natural water cycle in the forms of building dams, reservoirs, water transfer systems, and irrigation systems that divert and redistribute part of the water storages and fluxes on land. The water cycle is mainly driven and coupled to the energy cycle in terms of phase changes of water (changes among liquid, water vapor, and solid phases) and transport of water by winds in addition to gravity and diffusion processes. The water-cycle components can be observed with in situ sensors as well as airborne and satellite sensors in terms of radiative quantities. Processing and conversion of these radiative signals are necessary to retrieve the water-cycle components.

Wilder, Peter↗
DOE OSTI2018

Electrochemical Behavior of Sn-9Zn-xTi Lead-Free Solders in Neutral 0.5M NaCl Solution

Electrochemical techniques were employed to study the electrochemical corrosion behavior of Sn-9Zn-xTi (x = 0, 0.05, 0.1, 0.2 wt.%) lead-free solders in neutral 0.5M NaCl solution, aiming to figure out the effect of Ti content on the corrosion properties of Sn-9Zn, providing information for the composition design of Sn-Zn-based lead-free solders from the perspective of corrosion. EIS results reveal that Ti addition was involved in the corrosion product layer and changed electrochemical interface behavior from charge transfer control process to diffusion control process. The trace amount of Ti addition (0.05 wt.%) can refine the microstructure and improve the corrosion resistance of Sn-9Zn solder, evidenced by much lower corrosion current density (i{sub corr}) and much higher total resistance (R{sub t}). Excess Ti addition (over 0.1 wt.%) led to the formation of Ti-containing IMCs, which were confirmed as Sn{sub 3}Ti{sub 2} and Sn{sub 5}Ti{sub 6}, deteriorating the corrosion resistance of Sn-9Zn-xTi solders. The main corrosion products were confirmed as Sn{sub 3}O(OH){sub 2}Cl{sub 2} mixed with small amount of chlorine/oxide Sn compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Unraveling Shuttle Effect and Suppression Strategy in Lithium/Sulfur Cells by In Situ/Operando X-ray Absorption Spectroscopic Characterization

The polysulfides shuttle effect represents a great challenge in achieving high capacity and long lifespan of lithium/sulfur (Li/S) cells. A comprehensive understanding of the shuttle-related sulfur speciation and diffusion process is vital for addressing this issue. Herein, we employed in situ/operando X-ray absorption spectroscopy (XAS) to trace the migration of polysulfides across the Li/S cells by precisely monitoring the sulfur chemical speciation at the cathodic electrolyte-separator and electrolyte-anode interfaces, respectively, in a real-time condition. After we adopted a shuttle-suppressing strategy by introducing an electrocatalytic layer of twinborn bismuth sulfide/bismuth oxide nanoclusters in a carbon matrix (BSOC), we found the Li/S cell showed greatly improved sulfur utilization and longer life span. The operando S K-edge XAS results revealed that the BSOC modification was bi-functional: trapping polysulfides and catalyzing conversion of sulfur species simultaneously. We elucidated that the polysulfide trapping-and-catalyzing effect of the BSOC electrocatalytic layer resulted in an effective lithium anode protection. Finally, our results could offer potential stratagem for designing more advanced Li/S cells.

25 ENERGY STORAGE↗
DOE OSTI2023

Parasitic Effects in Impedance Spectrum of PEM Water Electrolysis Cells: Case Study of High-Frequency Inductive Effects

Electrochemical impedance spectroscopy (EIS) is a powerful tool to characterize and distinguish electrochemical, electrical, and diffusive processes in an electrolysis cell. The EIS response with small impedance (mΩ) depends on components and materials of the cell, but often also on the electrical setup, cables, and connectors, leading to incorrect conclusions about the performance of the electrolysis cells. These parasitic effects are assessed via a short-circuit measurement and confirmed to be external from the membrane electrode assembly (MEA). In the setup, the inductive characteristic is described by a modified inductive reactance and must be included in the equivalent circuit model (ECM) which is fitting the cell EIS spectra in operation (in situ). If points of the spectra showing inductive characteristic (below x-axis in Nyquist plot) are excluded from the ECM evaluation, an artificially increased ohmic resistance at high frequencies is obtained. In addition, considerations on other components of the ECM can be misleading and significantly incorrect. The only way to avoid that inductive behavior caused by the external setup is incorrectly assigned to the ECM describing properties of the MEA is to include the inductive effects in the ECM analysis of in situ EIS measurements.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

A New Electrode Paradigm Enabled by Co-Axial Electrospinning

A conventional electrode in a polymer electrolyte membrane fuel cell (PEMFC) often imposes competing requirements on the ionomer, which must enable efficient proton conduction while allowing sufficient oxygen transport. To address these material-level requirements, a co-axial electrospun electrode comprising of a pristine ionomer core and a multifunctional platinum-carbon-ionomer shell is introduced. By decoupling proton and oxygen transport pathways, this architecture enables independent tailoring of core and shell chemistries and their interfaces. The core-shell structure of the electrospun fibers is confirmed by microscopy, while electrochemical and transport properties are quantified using electrochemical impedance spectroscopy and limiting-current diagnostics. The co-axial fibers in their current version meet or exceed the performance of conventional ultrasonically sprayed electrode at relative humidities above 75%, enabled by improvements in non-Fickian diffusion processes. This work establishes co-axial electrospun electrodes as a versatile platform for advanced PEMFC electrodes and a wide range of electrochemical applications, including CO2 electrolysis, water electrolysis, and critical mineral separations.

08 HYDROGEN↗
DOE OSTI2019

Amorphization kinetics in strontium titanate at 16 and 300 K under argon ion irradiation

Here, the accumulation of irradiation-induced disorder in SrTiO 3 single crystals irradiated at 16 K with 200 keV Ar ions has been investigated using Rutherford backscattering spectrometry along the < 100 > channeling direction and compared with previous results obtained at 300 K under identical irradiation conditions. As expected, amorphization at 16 K occurs at a much lower fluence than at 300 K due to dynamic recovery of irradiation-induced defects at 300 K. Utilizing a comprehensive damage accumulation model for analysis of the data, irradiation at 16 K results only in the formation of point defects and amorphous pockets, while defect clusters are also formed at 300 K. High defect mobility under irradiation at 300 K tends to promote recombination and clustering of point defects. These results suggest that defect diffusion processes in SrTiO 3 are not thermally active at 16 K.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Investigation of Molecular Diffusion at Block Copolymer Thin Films Using Maximum Entropy Method-Based Fluorescence Correlation Spectroscopy and Single Molecule Tracking

Fluorescence correlation spectroscopy (FCS) has been widely used to investigate molecular diffusion behavior in various samples. The use of the maximum entropy method (MEM) for FCS data analysis provides a unique means to determine multiple distinct diffusion coefficients without a priori assumption of their number. Comparison of the MEM-based FCS method (MEM-FCS) with another method will reveal its utility and advantage as an analytical tool to investigate diffusion dynamics. Herein, we measured diffusion of fluorescent probes doped into nanostructured thin films using MEM-FCS, and validated the results with single molecule tracking (SMT) data. The efficacy of the MEM code employed was first demonstrated by analyzing simulated FCS data for systems incorporating one and two diffusion modes with broadly distributed diffusion coefficients. The MEM analysis accurately afforded the number of distinct diffusion modes and their mean diffusion coefficients. These results contrasted with those obtained by fitting the simulated data to conventional two-component and anomalous diffusion models, which yielded inaccurate estimates of the diffusion coefficients. Subsequently, the MEM analysis was applied to FCS data acquired from hydrophilic dye molecules incorporated into microphase-separated polystyrene-block-poly(ethylene oxide) (PS-b-PEO) thin films characterized under a water-saturated nitrogen atmosphere. The MEM analysis revealed distinct fast and slow diffusion components attributable to molecules diffusing on the film surface and inside the film, respectively. SMT studies of the same materials yielded trajectories for mobile molecules that appear to follow the curved PEO microdomains. Diffusion coefficients obtained from the SMT data were consistent with those obtained for the slow diffusion component detected by MEM-FCS. Furthermore, these results highlight the utility of MEM-FCS and SMT for gaining complementary information on molecular diffusion processes in heterogeneous material systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Deformation Mechanism Map of Cu/Nb Nanoscale Metallic Multilayers as a Function of Temperature and Layer Thickness

The mechanical properties and deformation mechanisms of Cu/Nb nanoscale metallic multilayers (NMMs) manufactured by accumulative roll bonding are studied at 25°C and 400°C. Cu/Nb NMMs with individual layer thicknesses between 7 nm and 63 nm were tested by in situ micropillar compression inside a scanning electron microscope. Yield strength, strain-rate sensitivities and activation volumes were obtained from the pillar compression tests. The deformed micropillars were examined under scanning and transmission electron microscopy in order to examine the deformation mechanisms active for different layer thicknesses and temperatures. The paper suggests that room temperature deformation was determined by dislocation glide at larger layer thicknesses and interface-related mechanisms at the thinner layer thicknesses. The high-temperature compression tests, in contrast, revealed superior thermo-mechanical stability and strength retention for the NMMs with larger layer thicknesses with deformation controlled by dislocation glide. A remarkable transition in deformation mechanism occurred as the layer thickness decreased, to a deformation response controlled by diffusion processes along the interfaces, which resulted in temperature-induced softening. Finally, a deformation mechanism map, in terms of layer thickness and temperature, is proposed from the results obtained in this investigation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Phase-Field Study on Internal to External Oxidation Transition in High-Temperature Structural Alloys

Structural alloys applied at high temperatures rely on an external dense layer of oxide scale for protection. As some reactive alloy components are selectively oxidized internally, understanding how these dispersed metal oxide particles reach the surface to form a protective scale—the so-called internal to external oxidation transition—is crucial for designing these alloys. While the literature is replete with experimental studies on oxidation of alloys, there is a lack of computational studies in this realm due to the complex nature of coupled reaction and diffusion processes in multicomponent multi-phase alloy systems. In this work, we apply a recently developed phase-field model to simulate the oxidation processes under different compositions and nucleation scenarios to gain insights into how a continuous oxide scale can be established. The results show that while alloy composition is critical for internal to external oxidation transition, the oxide nuclei size, shape and distribution also have significant impact on the transition kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Valuing catastrophe bonds involving correlation and CIR interest rate model

Natural catastrophes lead to problems of insurance and reinsurance industry. Classic insurance mechanisms are often inadequate for dealing with consequences of catastrophic events. Therefore, new financial instruments, including catastrophe bonds (cat bonds), were developed. In this paper we price the catastrophe bonds with a generalized payoff structure, assuming that the bondholder’s payoff depends on an underlying asset driven by a stochastic jump-diffusion process. Simultaneously, the risk-free spot interest rate has also a stochastic form and is described by the multi-factor Cox–Ingersoll–Ross model. We assume the possibility of correlation between the Brownian part of the underlying asset and the components of the interest rate model. Using stochastic methods, we prove the valuation formula, which can be applied to the cat bonds with various payoff functions. We use adaptive Monte Carlo simulations to analyze the numerical properties of the obtained pricing formula for various settings, including some similar to the practical cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Universal aging characteristics of macroscopically and microscopically dissimilar metallic glasses

Supercooled liquids and glasses, due to their intrinsically unstable nature, are known to relax continuously until an equilibrium state is reached. By exploring atomic relaxation, aging and microscopic structure of chemically similar but physically dissimilar metallic glasses, we find that neither the relaxation time nor aging correlate with the free volume or density of the glasses. Furthermore, atomic relaxation time in these metallic glasses does not depend on the microscopic structure of the systems. The activation energy for the diffusion process indicates a completely different microscopic mechanism governing the atomic transport process. Nevertheless, the age-dependent relaxation time surprisingly exhibits a universal time-waiting time-temperature superposition. In conclusion, our results provide a convincing proof of the universality in the aging of out-of-equilibrium materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Formation of helium-bubble networks in tungsten

The nucleation and subsequent growth of helium bubbles in bulk tungsten is investigated using molecular dynamics simulations. By considering a setting that includes the diffusion process of helium clusters, we study their attachment to existing bubbles and their interaction with tungsten crowdion structures generated in the bubble growth process. Here, we find that incoming helium atoms, and especially small helium clusters, can become trapped in the crowdion structures, providing nucleation sites for new helium bubbles, and leading to a distributed network of bubbles rather than a single, growing bubble. The nature of this network depends on both the temperature and the implantation flux of helium. Our results indicate that the kinetic interaction of He with generated dislocations is a key factor dictating the evolution of bubble distributions in plasma-exposed tungsten.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A physics-informed operator regression framework for extracting data-driven continuum models

The application of deep learning toward discovery of data-driven models requires careful application of inductive biases to obtain a description of physics which is both accurate and robust. We present here a framework for discovering continuum models from high fidelity molecular simulation data. Our approach applies a neural network parameterization of governing physics in modal space, allowing a characterization of differential operators while providing structure which may be used to impose biases related to symmetry, isotropy, and conservation form. Here, we demonstrate the effectiveness of our framework for a variety of physics, including local and nonlocal diffusion processes and single and multiphase flows. For the flow physics we demonstrate this approach leads to a learned operator that generalizes to system characteristics not included in the training sets, such as variable particle sizes, densities, and concentration.

42 ENGINEERING↗