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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Foundations for high-order, conservative cut-cell methods: Stable discretizations on degenerate meshes

Cut-cell methods for unsteady flow problems can greatly simplify the grid generation process and allow for high-fidelity simulations on complex geometries. However, cut-cell methods have been limited to low orders of accuracy. This is driven, largely, by the variety of procedures typically introduced to evaluate derivatives in a stable manner near the highly irregular embedded geometry. Here, a completely new approach, termed TEMO (truncation error matching and optimization), is taken to solve this problem. The approach is based on two simple and intuitive design principles. These principles directly allow for the construction of stable 8th To the best of the authors' knowledge, these are the highest orders ever achieved for a cut-cell discretization by a significant margin. This is done for both explicit and compact finite differences and is accomplished without any geometric transformations or artificial stabilization procedures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Efficient smoothed particle radiation hydrodynamics I: Thermal radiative transfer

This work presents efficient solution techniques for radiative transfer in the smoothed particle hydrodynamics discretization. Two choices that impact efficiency are how the material and radiation energy are coupled, which determines the number of iterations needed to converge the emission source, and how the radiation diffusion equation is solved, which must be done in each iteration. The coupled material and radiation energy equations are solved using an inexact Newton iteration scheme based on nonlinear elimination, which reduces the number of Newton iterations needed to converge within each time step. During each Newton iteration, the radiation diffusion equation is solved using Krylov iterative methods with a multigrid preconditioner, which abstracts and optimizes much of the communication when running in parallel. The code is verified for an infinite medium problem, a one-dimensional Marshak wave, and a two and three-dimensional manufactured problem, and exhibits first-order convergence in time and second-order convergence in space. For these problems, the number of iterations needed to converge the inexact Newton scheme and the diffusion equation is independent of the number of spatial points and the number of processors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Intersection-distribution-based remapping between arbitrary meshes for staggered multi-material arbitrary Lagrangian-Eulerian hydrodynamics

In this paper, we present a new intersection-distribution-based remapping method between arbitrary polygonal meshes for indirect staggered multi-material arbitrary Lagrangian-Eulerian hydrodynamics. All cell-centered material quantities are conservatively remapped using intersections between the Lagrangian (old, source) mesh and the rezoned (new, target) mesh. The new nodal masses are obtained by conservative distribution of all material masses in each new cell to the cell's corners and then collecting those corner masses at new nodes. This distribution is done using a local constrained optimization approach for each cell in the new mesh. In order to remap nodal momentum we first define cell-centered momentum for each cell in the old mesh, conservatively remap this to the new mesh and then conservatively distribute the new zonal momentum to each cell's bounding nodes, again using local constrained optimization. Our method also conserves total energy by applying a new nodal kinetic energy correction that relies on a process similar to that used for remapping nodal mass and momentum. Cell-centered kinetic energy is computed, conservatively remapped and then distributed to nodes. The discrepancy between this conservatively remapped and actual nodal kinetic energy is then conservatively distributed to the internal energies of the materials in the cells surrounding each node. Unlike conventional cell-based corrections of this type, this new nodal kinetic energy correction has not been observed to drive material internal energy negative in any of our testing. Unlike flux based remapping, our new intersection-distribution method can be applied to remapping between source and target meshes that are arbitrarily different, which provides superior flexibility in the rezoning strategy. Our method is accurate, essentially conservative and essentially bounds preserving.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Flow-driven spectral chaos (FSC) method for simulating long-time dynamics of arbitrary-order non-linear stochastic dynamical systems

Uncertainty quantification techniques such as the time-dependent generalized polynomial chaos (TD-gPC) use an adaptive orthogonal basis to better represent the stochastic part of the solution space (aka random function space) in time. However, because the random function space is constructed using tensor products, TD-gPC-based methods are known to suffer from the curse of dimensionality. Here, we introduce a new numerical method called the flow-driven spectral chaos (FSC) which overcomes this curse of dimensionality at the random-function-space level. The proposed method is not only computationally more efficient than existing TD-gPC-based methods but is also far more accurate. The FSC method uses the concept of enriched stochastic flow maps to track the evolution of a finite-dimensional random function space efficiently in time. To transfer the probability information from one random function space to another, two approaches are developed and studied herein. In the first approach, the probability information is transferred in the mean-square sense, whereas in the second approach the transfer is done exactly using a new theorem that was developed for this purpose. The FSC method can quantify uncertainties with high fidelity, especially for the long-time response of stochastic dynamical systems governed by ODEs of arbitrary order. Six representative numerical examples, including a nonlinear problem (the Van-der-Pol oscillator), are presented to demonstrate the performance of the FSC method and corroborate the claims of its superior numerical properties. Finally, a parametric, high-dimensional stochastic problem is used to demonstrate that when the FSC method is used in conjunction with Monte Carlo integration, the curse of dimensionality can be overcome altogether.

(nonlinear) stochastic dynamical systems↗
DOE OSTI2022

Efficient hybrid explicit-implicit learning for multiscale problems

Splitting method is a powerful method to handle application problems by splitting physics, scales, domain, and so on. Many splitting algorithms have been designed for efficient temporal discretization. Here, in this paper, our goal is to use temporal splitting concepts in designing machine learning algorithms and, at the same time, help splitting algorithms by incorporating data and speeding them up. We propose a machine learning assisted splitting scheme which improves the efficiency of the scheme meanwhile preserves the accuracy. We consider a recently introduced multiscale splitting algorithms, where the multiscale problem is solved on a coarse grid. To approximate the dynamics, only a few degrees of freedom are solved implicitly, while others explicitly. This splitting concept allows identifying degrees of freedom that need implicit treatment. In this paper, we use this splitting concept in machine learning and propose several strategies. First, the implicit part of the solution can be learned as it is more difficult to solve, while the explicit part can be computed. This provides a speed-up and data incorporation for splitting approaches. Secondly, one can design a hybrid neural network architecture because handling explicit parts requires much fewer communications among neurons and can be done efficiently. Thirdly, one can solve the coarse grid component via PDEs or other approximation methods and construct simpler neural networks for the explicit part of the solutions. We discuss these options and implement one of them by interpreting it as a machine translation task. This interpretation of the splitting scheme successfully enables us using the Transformer since it can perform model reduction for multiple time series and learn the connection between them. We also find that the splitting scheme is a great platform to predict the coarse solution with insufficient information of the target model: the target problem is partially given and we need to solve it through a known problem which approximates the target. Our machine learning model can incorporate and encode the given information from two different problems and then solve the target problems. We conduct four numerical examples and the results show that our method is stable and accurate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

One-sweep moment-based semi-implicit-explicit integration for gray thermal radiation transport

Thermal radiation transport (TRT) is a time dependent, high dimensional partial integro-differential equation. In practical applications such as inertial confinement fusion, TRT is coupled to other physics such as hydrodynamics, plasmas, etc., and the timescales one is interested in capturing are often much slower than the radiation timescale. As a result, TRT is treated implicitly, and due to its stiffness and high dimensionality, is often a dominant computational cost in multiphysics simulations. Here we develop a new approach for implicit-explicit (IMEX) integration of gray TRT in the deterministic SN setting, which requires only one sweep per stage, with the simplest first-order method requiring only one sweep per time step. The partitioning of equations is done via a moment-based high-order low-order formulation of TRT, where the streaming operator and first two moments are used to capture the asymptotic stiff regimes of the streaming limit and diffusion limit. Absorption-reemission is treated explicitly, and although stiff, is sufficiently damped by the implicit solve that we achieve stable accurate time integration without incorporating the coupling of the high order and low order equations implicitly. Due to nonlinear coupling of the high-order and low-order equations through temperature-dependent opacities, to facilitate IMEX partitioning and higher-order methods, we use a semi-implicit integration approach amenable to nonlinear partitions. In conclusion, results are demonstrated on thick Marshak and crooked pipe benchmark problems, demonstrating orders of magnitude improvement in accuracy and wallclock compared with the standard first-order implicit integration typically used.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗
DOE OSTI2021

High-precision measurement of U-Pu-Np-Am concentrations and isotope ratios in environmental reference materials by mass spectrometry

Herein, we report results of precise and sensitive mass spectrometric measurements of uranium, plutonium, neptunium, and americium concentrations and isotope ratios in a variety of environmental reference materials. Most of our work has been done on NIST SRM 4350b, River Sediment, but we also present results for NIST SRM 4354, Lake Sediment; NIST SRMs 4355 and 4355a, Peruvian Soil; NIST SRM 4357, Ocean Sediment; NIST SRM 1648a, Urban Particulate Material; NIST SRM 1649b, Urban Dust; IAEA CRM 385, Ocean Sediment; USGS BCR-2, Columbia River Basalt; and USGS BHVO-2, Hawaiian Volcanic Observatory Basalt. These materials reflect a wide range in long-lived actinide concentrations (e.g. 1E4 to 1E10 atoms 239 Pu/g) and isotope ratios. Measurements were performed in a clean laboratory by isotope dilution, multi-collector thermal ionization and multi-collector inductively coupled plasma mass spectrometry. In general, our results are in agreement with, but lower the uncertainty of, literature or certificate values for these reference materials. Our uranium results for the basalts also confirm previously reported high-precision mass spectrometric results from our laboratory. In many cases our measurements of U-Pu-Np-Am nuclides appear to be novel.

58 GEOSCIENCES↗
DOE OSTI2021

Measurements of Argon-39 from locations near historic underground nuclear explosions

Measurement of radioactive gas seepage from an underground nuclear explosion is one of the primary methods to confirm whether an event was nuclear in nature. Radioactive noble gas indicators that are commonly targeted by such measurements (e.g. 133Xe, 37Ar) have half-lives of 35 days or less. Argon-39, an activation product similar to 37Ar, is produced by the interaction between neutrons and potassium in the surrounding geology and has a half-life of 269 years. Measurements taken at three sites near three historic underground nuclear test locations at the Nevada National Security Site have all shown highly elevated levels of 39Ar in subsurface air decades after the test events. Elevated levels of 39Ar (30-50 times background) were also detected in atmospheric air collected roughly 30 cm above ground level near two of these sites, and outside the entrance of the one tunnel site. These measurements demonstrate that 39Ar has the potential to be a long-term signature of an underground nuclear event which can be reliably detected at the surface or in the shallow subsurface. This radionuclide detection of an underground nuclear event decades after the event takes place is in contrast to the commonly held assumption that detecting underground nuclear events via radionuclides at the surface needs to be done in a matter of months. Depending upon what further studies show about the robustness of this signature in a variety of geological settings, it may in fact be easy to detect underground nuclear events at the surface for a very long time post-detonation.

Johnson, Christine M.↗
DOE OSTI2022

Investigations of Association Among Atmospheric Radionuclide Measurements

Large networks producing frequent atmospheric radionuclide measurements have additional power in characterizing and localizing radionuclide release events over the analysis done with four or fewer samples. However, adding unrelated samples to an analysis dilutes that advantage, unless models are extended to account for this complexity. A key steppingstone to obtaining network power is to select a group of related sample measurements that are associated with a release event. Such collections of measurements can be assembled by an analyst, or perhaps they can be selected by algorithm. The authors explore, using a year of atmospheric transport calculations and realistic sensor sensitivities, the potential for a computed radionuclide association tool.

Eslinger, Paul W.↗
DOE OSTI2022

Projected network performance for next-generation xenon monitoring systems

Next-generation radioxenon monitoring systems are reaching maturity and are expected to improve certain aspects of performance in verifying the absence of nuclear tests. To predict the improvement in detecting and locating nuclear releases, thousands of releases all over the globe were simulated and the global detection probability was calculated. This was done for the International Monitoring System network of noble gas samplers as it currently exists (25 certified stations), and how it would be for potential future network sizes of 39 and 79 stations. The probability of detection was calculated for releases ranging from 10 10 Bq to 10 16 Bq of 133 Xe and presented as coverage maps and global integrals for both current and next-generation monitoring systems. Similarly, the number of detecting stations and the number of detecting samples were tabulated to elucidate the possibilities for enhanced location capability. Improvements in global detection coverage are maximized at different release sizes in a way that depends on the station density. For example, for releases of 3×10 14 Bq and 39 stations, the detection probability would rise from 60% to 70% with next-generation systems, while for releases of 10 13 Bq and 79 stations, it would rise from 37% to 52%. Achieving an average of two detecting stations requires a 1015 Bq release for a 39-station network and a 10 14 Bq release for a 79-station network. The largest impact of using next-generation systems may be the confidence, failure tolerance, and location capability that arise from obtaining multiple samples associated with a single release event.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Snowmass2021 theory frontier white paper: Astrophysical and cosmological probes of dark matter

While astrophysical and cosmological probes provide a remarkably precise and consistent picture of the quantity and general properties of dark matter, its fundamental nature remains one of the most significant open questions in physics. Obtaining a more comprehensive understanding of dark matter within the next decade will require overcoming a number of theoretical challenges: the groundwork for these strides is being laid now, yet much remains to be done. Chief among the upcoming challenges is establishing the theoretical foundation needed to harness the full potential of new observables in the astrophysical and cosmological domains, spanning the early Universe to the inner portions of galaxies and the stars therein. Identifying the nature of dark matter will also entail repurposing and implementing a wide range of theoretical techniques from outside the typical toolkit of astrophysics, ranging from effective field theory to the dramatically evolving world of machine learning and artificial-intelligence-based statistical inference. Through this work, the theory frontier will be at the heart of dark matter discoveries in the upcoming decade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Adsorptive denitrogenation of model aviation fuel using mesoporous silica in a packed bed adsorption system

This study aims to understand the effects of system process parameters such as flow rate, adsorbent particle size, and use of recycled adsorbent on denitrogenation performance of a model fuel using mesoporous silica gel. The goal is to reduce the nitrogen content of the model fuel from 1500 parts per million to single-digit ppm to meet ASTM specifications for drop-in fuels. This work was done with the intent of applying adsorptive denitrogenation to sustainable aviation fuel (SAF) product fractions produced via hydrothermal liquefaction (HTL). The adsorption performance of the silica is evaluated via packed column breakthrough data, with data generated from collecting from the column outlet and quantifying nitrogen content via gas chromatography. Select experiments use a significantly larger (2.5x column diameter and length) column to demonstrate linear scalability of the process. Thermogravimetric analysis data is collected to evaluate the effects of thermal calcination as a sorbent regeneration method. Effects of a more complex feed are also investigated using a known reference fuel with additional added nitrogen containing compounds. The results presented in this work successfully demonstrate up to 99.8 % removal of NCCs from a model fuel fraction at an original NCC concentration of approximately 1500 ppm to single-digit parts per million after treatment. We also examine calcination of sorbent materials to remove the adsorbed species to enable sorbent reuse and minimize waste generation and show that the calcined material can be reused up to 5 cycles with reduced adsorption capacity. Overall, this work indicates that adsorptive denitrogenation using silica gel is a viable solution to enable the integration of HTL-derived aviation fuels into existing fuel infrastructure.

Adsorption techniques↗
DOE OSTI2020

Magnetic anomalies associated with domain wall freezing and coupled electron hopping in magnetite nanorods

Magnetite has fascinated researchers for decades, due to its wide range of applications from spintronics to biomedicine. Despite a large body of works aimed at its magnetic properties, no consensus has been reached on the physical origin of the low temperature magnetic anomalies observed in magnetite. Although, a lot of work has been done in studying magnetite nanoparticles, but studies on the low temperature anomalies in those nanoparticles still remains unresearched. We report on the observation of the low temperature magnetic anomalies in highly crystalline, stoichiometric Fe 3 O 4 nanorods and relate them to the coupled electron hopping relaxation process and domain wall motion. Both DC and AC susceptibility show the presence of a hump around 35 K, which is associated with the relaxation of Fe +2 extra electrons. Radiofrequency transverse susceptibility (TS) measurements indicated a noticeable increase in anisotropy field below ~ 25 K, which is attributed to the rearrangement of Fe +2 electrons in the octahedral sites. TS experiments also revealed the domain wall freezing below ~35 K. Our combined DC, AC and TS susceptibility studies shed light on the complex nature of the lowtemperature magnetic behavior in nanostructured magnetite.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Phase-field modeling of dislocation–interstitial interactions

The mechanical behavior of body-centered cubic (BCC) materials can be dramatically affected by the presence of interstitial solute atoms. Here we present a new phase-field dislocation dynamics formulation to include the diffusion of interstitials. Short-range interactions are accounted for by a concentration-dependent lattice energy, and long-range interactions are accounted for by modifications to the elastic energy. The interstitial diffusion law introduces gradients that require methods for minimizing Gibbs oscillations, which is done via a modified Green’s function. The formulation is general to any solute-solvent system and is applied here to Nb-O as a model system, whose interstitial parameters are obtained from ab initio calculations. The effect of O on the core structures of Nb edge and screw dislocations is calculated. The diffusion of O to form interstitial atmospheres around dislocation cores is simulated, as well as the critical stresses required for dislocations to break away or cross slip from these atmospheres. Future applications of the method to simulate complex interstitial embrittlement mechanisms are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Grand potential sintering simulations of doped UO 2 accident-tolerant fuel concepts

Chromium-doped UO is a widely-studied near-term deployable accident-tolerant fuel concept because it results in a dense, large-grain structure that increases the fuel resistance to densification, swelling, and fission gas release. A new charged-interstitial mechanism was recently proposed to describe the behavior of dopants like chromium in sintered UO 2 . Based on that mechanism, manganese was suggested as an even stronger dopant than chromium. In the current work we use mesoscale sintering simulations in an effort to validate the new mechanism. We compare the relative behavior of Cr-doped and undoped UO 2 against experimental data in the literature. We also make predictions of the relative behavior of Mn-doped UO 2 . Simulations are done using the phase field-based grand potential sintering model. Dopants have two effects on sintered UO 2 . They marginally increase the densification rate and greatly increase the average grain size. Both of these effects are individually tested in small-scale simulations. Then large 3D sintering simulations are used to test the combined behavior of both effects. The results for the densification rate simulations are consistent with experiments for Cr-doped fuels. However, we note the grain growth rates are lower than what is found in the literature for Cr-doped fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Enhancing isotope mixing in U-10Mo downblend castings with electromagnetic stirring

Uranium alloyed with 10 wt percent molybdenum (U-10Mo) is the proposed fuel for use in the United States’ high-performance research reactors. The U-10Mo fuel is fabricated by a two-step casting process that downblends highly enriched uranium with depleted uranium (DU) and/or natural uranium (NU) and subsequently alloys the resulting high-assay low-enriched uranium (HALEU) with Mo. Currently, a two-step casting process is needed to meet the ingots’ U-235 enrichment homogeneity specifications. This work demonstrates the ability to provide more homogeneous U-235 distributions during downblend casting by using zirconia for crucibles rather than graphite. When graphite is used as a crucible, the electromagnetic field produced by the induction heater couples directly with the graphite. Zirconia is nonconducting in this study, and therefore does not couple with the field. The induction field couples directly with the metal, and causes electromagnetic stirring (EMS) in the molten metal pool. Eight downblend casting experiments were carried out in this work. Four were performed with zirconia crucibles and four with graphite crucibles. The U-235 enrichment was measured at nine discrete points in each casting using laser ablation multi-collector inductively coupled mass spectrometry (LA-MC-ICP-MS). The enrichment homogeneity was approximately eight times better in zirconia crucible castings than in graphite crucible castings as measured by the plate enrichment range and enrichment coefficient of variation. The results show a single casting step could be used to meet USHPRR enrichment specifications if electromagnetic stirring is present during casting. A related investigation was carried out to determine whether it is appropriate to measure enrichment on as-cast ingots or whether heat treated specimens should be used to accurately characterize enrichment. The results show that the as-cast microstructure plays a significant role in enrichment homogeneity. It is recommended that all enrichment measurements be done after the homogenization heat treatment typical of U-10Mo processing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Characterization and qualification of neutron radiation effects – Summary of Japan-USA Joint Projects for 40 years

The Joint Projects under the Japan-USA Fusion Cooperation Program started in 1981 and has continued for more than 40 years. In the Joint Projects, although a wide range of fusion materials and engineering issues were covered, neutron radiation effects on fusion reactor materials have always been the major research emphases, and the neutron irradiation facilities in the US were jointly used by Japanese and US researchers. Japanese test facilities including neutron and charged particle irradiation facilities were complementarily used. Here, the initial focus of the Joint Projects was on fundamental fusion neutron radiation effects and irradiation correlation. Systematic comparison of fission and fusion radiation effects in comparable damage levels and the effects of transmutation-induced helium were investigated. The collaboration was then focused on the effect of dynamic irradiation effects in variable conditions. In addition to the relatively fundamental studies, the Joint Projects contributed largely to development of candidate materials such as RAFM steels, vanadium alloys, SiC/SiC composites, and tungsten alloys, through a mechanism-oriented approach. The Joint Projects also covered issues specific to materials application to fusion blankets and plasma-facing components, including neutron radiation effects such as tritium retention and permeation of neutron-irradiated plasma-facing materials. Various irradiation technologies were developed and applied to the irradiation experiments, including those for in-situ testing.Considering that high energy neutron sources, such as A-FNS and IFMIF-DONES, now have high viability, the research supporting the neutron source programs is essential. The knowledge obtained through the Joint Projects is valuable and should be advanced for this purpose. To this end, it is of urgent necessity to launch an international scientific program accumulating knowledge of fusion neutron radiation effects, including their fundamental aspects.

36 MATERIALS SCIENCE↗