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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Guide to Using Sierra

Sierra is an engineering mechanics simulation code suite supporting the Nation's Nuclear Weapons mission as well as other customers. It has explicit ties to Sandia National Labs' workflow, including geometry and meshing, design and optimization, and visualization. Distinguishing strengths include "application aware" development, scalability, SQA and V&V, multiple scales, and multi-physics coupling. This document is intended to help new and existing users of Sierra as a user manual and troubleshooting guide.

42 ENGINEERING↗
DOE OSTI2018

Milestone Report: Grain growth and fission gas behaviour in doped UO 2 M2MS-18LA0201034

Here, the microstructure of UO 2 can be modified during nuclear fuel fabrication by using additives. Several dopants (e.g. Cr, Ti, V, Mg, Nb) are used to enhance grain growth and densification during sintering. In previous work, we used atomic scale simulation techniques to identify a common interstitial solution mechanism for a range of dopants that form positively charged defects at sintering temperatures. As a result, negatively/positively charged defect concentrations were enhanced/suppressed relative to undoped fuel under the same conditions (temperature and oxygen partial pressure). Importantly U and fission gas migration is vacancy mediated, such that the increase in the concentration uranium vacancies (which have negative charge), due to doping, causes an increase in U and fission gas diffusivity. This is important because U diffusivity is the rate limiting step in mass transport during sintering and bulk fission gas diffusivity is the underlying property that governs fission gas release. In this work, we implement analytical expressions for uranium vacancy concentrations in doped fuel (based on atomic scale results) into mesoscale and engineering scale simulations of sintering and fission gas release. It is shown that densification is dramatically enhanced at 1850 K and 1950 K due to dopant solution and that Mn-doping has a greater effect than the more widely used Cr-doping. The effect of both dopants is strongly temperature dependent and is negligible below approximately 1800 K. The effect of enlarged grain size and enhanced fission gas diffusivity has been included in BISON. Fuel temperatures under normal operating conditions are not sufficient to activate the enhanced fission gas diffusivity mechanism predicted by atomic scale calculations. Therefore, the benefits of enlarged grains for reduced fission gas release should not undermined by enhanced fission gas diffusivity for doped UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

The Effect of Pressure on NO x Entitlement and Reaction Timescales in a Premixed Axial Jet-In-Crossflow

This paper investigates the pressure dependency of a lean premixed jet injected into a lean vitiated crossflow with an experimentally verified detailed chemistry computational fluid dynamics (CFD) model and 53 species considered. Experimental data were taken in an axially staged combustor with an optically accessible test section, allowing the use of particle image velocimetry (PIV) and CH* chemiluminescence techniques as well as point measurement of species concentration, temperature, and pressure. The experimental data cases at one, three, and five atmospheres were selected to describe the flame stabilization dependency on pressure and gain the required knowledge for an extrapolation to engine condition. Simulated exit nitrogen oxide levels were validated with experimental emission data, and a global emission trend for the NO reduction at elevated pressure and constant turbine inlet temperature level was defined. The nitrogen oxide benefit at elevated operating pressure was justified with the significantly smaller flame surface area: the analysis of the simulated spanwise and top-view profiles showed a relatively short receded core flame with nitrogen oxide production in the center at high pressure relative to a longer and larger shear layer flame at atmospheric condition that produced NO toward the inner and outer side of the flame. Furthermore, decomposition of the Damköhler number revealed the strong influence of the reaction timescales with higher reaction rates at elevated pressure, along with a moderate influence of the turbulent timescales, showing higher turbulence intensity in the lee-side recirculation zone at lower pressure.

03 NATURAL GAS↗
DOE OSTI2022

Analytical homogenization techniques applied to the Fickian diffusion: Effective diffusivity coefficient

For multiple applications in nuclear energy, the ability to accurately represent material behavior with a simplified model is important to facilitate practical engineering-scale simulations. In this work, we focus on the homogenized thermal response of a medium containing spherical inclusions, similar to a fuel form (compact or pebble) containing TRISO particles. An extensive survey on effective thermal conductivity modeling was performed in our previous study, considering a random distribution of mono-sized spherical inclusions in a continuous matrix. Using the analogy between heat conduction and the simplified Fickian diffusion (or fission product species conservation), we can use the same analytical homogenization methods to obtain ETC as for the effective diffusivity coefficient (EDC). We performed several numerical experiments at varying conditions to assess the validity of our hypothesis for EDC calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

PREDICTION OF CYCLIC VARIABILITY AND KNOCK-LIMITED SPARK ADVANCE (KLSA) IN SPARK-IGNITION (SI) ENGINE

Engine knock remains one of the major barriers to further improve the thermal efficiency of spark-ignition (SI) engines. SI engine is usually operated at knock-limited spark advance (KLSA) to achieve possibly maximum efficiency with given engine hardware and fuel properties. Co-optimization of fuels and engines is promising to improve engine efficiency, and predictive computational fluid dynamics (CFD) models can be used to facilitate this process. However, cyclic variability of SI engine demands that multi cycle results are required to capture the extreme conditions. In addition, Mach Courant Friedrichs-Lewy (CFL) number of 1 is desired to accurately predict the knock intensity (KI), resulting in unaffordable computational cost. In this study, a new approach to numerically predict KLSA using large Mach CFL of 50 with ten consecutive cycle simulation is proposed. This approach is validated against the experimental data for a boosted SI engine at multiple loads and spark timings with good agreements in terms of cylinder pressure, combustion phasing, and cyclic variation. Engine knock is predicted with early spark timing, indicated by significant pressure oscillation and end-gas heat release. Maximum amplitude of pressure oscillation analysis is performed to quantify the KI, and the slope change point in KI extrema is used to indicate the KLSA accurately. Using a smaller Mach CFL number of 5 also results in the same conclusions, thus demonstrating that this approach is insensitive to the Mach CFL number. The use of large Mach CFL number allows us to achieve fast turn-around time for multicycle engine CFD simulations.

CCV↗
DOE OSTI2021

NEAMS-Multiphysics Technical Assistance in FY21

The Multiphysics Object Oriented Simulation Environment (MOOSE) [1] is a massively parallel finite-element/volume package for multiphysics simulation in science and engineering. The package focuses on providing rapid-development capabilities for engineering applications by leveraging well-built features from libMesh [2] and the Portable Extensible Toolkit for Scientific Computation (PETSc) [3]. Fiscal year 2021 (FY-21) was the first year with funding dedicated to supporting MOOSE-derived applications relevant to the Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program. In this report we outline the work done to support NEAMS applications such as BISON, Griffin, Pronghorn, and System Analysis Module (SAM).

42 ENGINEERING↗
DOE OSTI2020

General Correlations for Laminar Flow Friction Loss and Heat Transfer in Plain Rectangular Plate-Fin Cores

In this paper, new generalized correlations for predicting the average fanning friction factor f and average Nusselt number Nu for laminar flow in plain plate-fin compact cores of rectangular cross section are presented. These are based on extended experimental data, as well as three-dimensional computational simulations, obtained for a broad range of fin density and geometrical attributes. The results indicate that while the fully developed forced convection scales only with the interfin channel cross-sectional ratio α (fin spacing by fin height), the entrance region hydrodynamic and thermal performance is additionally a function of the fin-core length L, flow Reynolds number Re, and fluid Prandtl number Pr. The developing flow and convection is further shown to scale as: (fRe)~(L/d h Re) 1/2 , and Nu ~(L/d h Re) 1/2 Pr 1/3 Φ(α), where f, Re, and Nu are all based on the hydraulic diameter dh of the interfin flow channel. Generalized correlations for both (fRe) and Nu are developed by the corresponding scaling of the forced convection behavior and asymptotic matching of the entrance or developing flow (short fin-core flow length) and the fully developed flow (large fin-core flow length) region performance. Finally, the predictions from these correlations are found to be within ±15% of all available experimental data for air, water, and glycol (0.71 ≤ Pr ≤ 10), and fin cores with 0 < α ≤ 1.

36 MATERIALS SCIENCE↗
DOE OSTI2018

HELICS-HLA (Hierarchical Engine for Large-scale Infrastructure Co-Simulation High Level Architecture) [SWR-18-46]

The Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS) is a co-simulation platform that is currently under development as part of a GMLC project. The High Level Architecture (HLA) is a co-simulation standard, various implementations of which have been widely used for co-simulations for several years, particularly in the defense community. The objective of developing the HELICS-HLA interface is to provide the ability of making software connected with HLA implementations to work with software connected with HELICS. Since each HLA federation is dependent on the RTI being used, the HELICS-HLA interface developed here uses an implementation of the HLA, the Universal CPS Environment for Federation (UCEF), to create this interface. Both HELICS and UCEF are open source software. UCEF-gateway that enables the integration of HELICS and UCEF is also an open source software.

Jain, Himanshu↗
DOE OSTI2019

Partial relay selection in mixed RF/FSO dual-hop system over unified M-distributed fading channel with non-zero boresight pointing errors

In this paper, the performance of a partial relay selection-based amplify-and-forward mixed radio frequency/free space optical (RF/FSO) system with a direct RF link and outdated channel state information (CSI) is presented. The source-to-relay and source-to-destination RF links are subjected to Rayleigh distributions while the relay-to-destination FSO link experiences Malaga (M)-distribution with generalized non-zero boresight pointing errors. It is also assumed that selection combining diversity with heterodyne detection is considered for the signal reception at the destination. Moreover, the cumulative distribution functions of the end-to-end signal-to-noise under the influence of with/or without a direct link are then derived for the concerned system. Through this, the closed-form expressions for the system outage probability and average bit error rate are obtained. Thus, the influence of atmospheric turbulence, outdated CSI and relay selection are evaluated for the system under zero boresight and non-zero boresight displacement pointing errors scenarios. The results illustrated that the mixed RF/FSO system with a direct link offers better performance than the one without a direct link. The accuracy of the presented results is validated by Monte-Carlo simulation.

42 ENGINEERING↗
DOE OSTI2025

GPU-accelerated kinetic Hall thruster simulations in WarpX

Abstract Two-dimensional (axial-azimuthal) simulations of a Hall thruster are performed using the open-source particle-in-cell code WarpX. The simulation conditions are chosen to match those of the axial-azimuthal benchmark first reported by Charoy et al. in 2019. A range of numerical and solver parameters is investigated in order to find those which yield the best performance. It is found that WarpX completes the benchmark case in 3.8 days on an Nvidia V100 GPU, and in as low as 1.5 days on a more recent Nvidia H100 GPU. Of the numerical parameters investigated, it is determined that the field-solve tolerance and particle resampling thresholds have the largest effect on the simulation wall time and that particle resampling may artificially widen electron velocity distribution functions, leading to unphysical heating. A semi-implicit scheme for the electrostatic field solve is tested and is found to produce results consistent to within 10% of the benchmark in less than twelve hours. The scaling properties of the electrostatic solver to multiple GPUs are also assessed on a uniform plasma test problem. The results of this work are discussed in the context of advancements in GPU hardware and the suitability of kinetic Hall thruster simulations for engineering applications.

Marks, Thomas A.↗
DOE OSTI2022

Assessment of diffuse-interface methods for compressible multiphase fluid flows and elastic-plastic deformation in solids

This work describes three diffuse-interface methods for the simulation of immiscible, compressible multiphase fluid flows and elastic-plastic deformation in solids. The first method is the localized-artificial-diffusivity approach of Cook, Subramaniam et al., and Adler and Lele, in which artificial diffusion terms are added to the individual phase mass fraction transport equations and are coupled with the other conservation equations. The second method is the gradient-form approach that is based on the quasi-conservative method of Shukla et al., in which the diffusion and sharpening terms (together called regularization terms) are added to the individual phase volume fraction transport equations and are coupled with the other conservation equations. The third approach is the divergence-form approach that is based on the fully conservative method of Jain et al., in which the regularization terms are added to the individual phase volume fraction transport equations and are coupled with the other conservation equations. In the present study, all three diffuse-interface methods are used in conjunction with a four-equation, multicomponent mixture model, in which pressure and temperature equilibria are assumed among the various phases. The primary objective of this work is to compare these three methods in terms of their ability to: maintain constant interface thickness throughout the simulation; conserve mass, momentum, and energy; and maintain accurate interface shape for long-time integration. The second objective of this work is to consistently extend these methods to model interfaces between solid materials with strength. To assess and compare the methods, they are used to simulate a wide variety of problems, including (1) advection of an air bubble in water, (2) shock interaction with a helium bubble in air, (3) shock interaction and the collapse of an air bubble in water, and (4) Richtmyer–Meshkov instability of a copper–aluminum interface. The current work focuses on comparing these methods in the limit of relatively coarse grid resolution, which illustrates the true performance of these methods. In conclusion, this is because it is rarely practical to use hundreds of grid points to resolve a single bubble or drop in large-scale simulations of engineering interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Development and assessment of a reactor system prognosis model with physics-guided machine learning

Autonomous control systems provide recommendations to help operators in decision-making during plant operations ranging from normal operation to accident management. An important step of autonomous control is prognosis. In nuclear engineering domain, prognosis is the process of predicting future conditions of a system or equipment based on present signs and symptoms of a fault. The prognosis model allows predicting future reactor states for possible candidate control strategies so that the outcomes can be evaluated to determine the best control strategy. The prognosis model requires representing direct relationships between the symptoms and the predictions. In nuclear engineering, computational simulations are approximate representations of the operation of the real system. However, prognosis with computational simulations requires high computation power and time due to possible large number of scenarios. Necessary computation resources can be reduced with machine learning (ML) approach for fast predictions by building a surrogate function using the simulation data. A critical issue is, ML models are ignorant of physical knowledge, and these models approximate statistical relationships between the system variables. This ignorance can produce results that are inconsistent with physical laws, even if an optimal result is achieved from a mathematical point of view. Physics-guided machine learning (PGML) is an approach to tackle this issue. Here, this work formulates and illustrates a framework to guide development and assessment of the ML-based prognosis model for autonomous control systems. The development of the prognosis model considers the training of a ML model which consists of optimizing many aspects of the ML approach. The assessment of the prognosis model considers training data limitations and uncertainties of the ML approach. Prognosis models with standalone ML and PGML are developed and assessed on the loss-of-flow scenario of Experimental Breeder Reactor II. The results indicate that PGML based prognosis model has the best performance compared to other prognosis models.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Artificial Graphene Nanoribbons: A Test Bed for Topology and Low-Dimensional Dirac Physics

Here, we synthesize artificial graphene nanoribbons by positioning carbon monoxide molecules on a copper surface to confine its surface state electrons into artificial atoms positioned to emulate the low-energy electronic structure of graphene derivatives. We demonstrate that the dimensionality of artificial graphene can be reduced to one dimension with proper "edge" passivation, with the emergence of an effectively gapped one-dimensional nanoribbon structure. These one-dimensional structures show evidence of topological effects analogous to graphene nanoribbons. Guided by first-principles calculations, we spatially explore robust, zero-dimensional topological states by altering the topological invariants of quasi-one-dimensional artificial graphene nanostructures. The robustness and flexibility of our platform allow us to toggle the topological invariants between trivial and nontrivial on the same nanostructure. Ultimately, we spatially manipulate the states to understand fundamental coupling between adjacent topological states that are finely engineered and simulate complex Hamiltonians.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Structural basis of agonist specificity of α 1A -adrenergic receptor

α 1 -adrenergic receptors (α 1 -ARs) play critical roles in the cardiovascular and nervous systems where they regulate blood pressure, cognition, and metabolism. However, the lack of specific agonists for all α 1 subtypes has limited our understanding of the physiological roles of different α 1 -AR subtypes, and led to the stagnancy in agonist-based drug development for these receptors. Here we report cryo-EM structures of α 1A -AR in complex with heterotrimeric G-proteins and either the endogenous common agonist epinephrine or the α 1A -AR-specific synthetic agonist A61603. These structures provide molecular insights into the mechanisms underlying the discrimination between α 1A -AR and α 1B -AR by A61603. Guided by the structures and corresponding molecular dynamics simulations, we engineer α 1A -AR mutants that are not responsive to A61603, and α 1B -AR mutants that can be potently activated by A61603. Together, these findings advance our understanding of the agonist specificity for α 1 -ARs at the molecular level, opening the possibility of rational design of subtype-specific agonists.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

High-Order Qubit Dephasing at Sweet Spots by Non-Gaussian Fluctuators: Symmetry Breaking and Floquet Protection

Although the Gaussian noise assumption is widely adopted in studying qubit decoherence, non-Gaussian noise sources have been detected in many qubits. Further understanding and mitigating the distinctive decoherence effect of the non-Gaussian noise remain critical. Here, we study the qubit dephasing caused by non-Gaussian fluctuators, and predict a symmetry-breaking effect that is unique to non-Gaussian noise. This broken symmetry results in an experimentally measurable mismatch between the extremum points of the dephasing rate and qubit frequency, which demands extra carefulness in characterizing the noise and locating the optimal working point. To further enhance the coherence time, we propose suppressing the second-order derivative of the qubit frequency by Floquet engineering. Our simulation on a tunable and gapped two-level quantum system, with the parameters from a heavy fluxonium, shows an order-of-magnitude improvement of the dephasing time, even after including the drive noise.

Huang, Ziwen↗
DOE OSTI2018

2018 FEARCE Development: A Robust and Accurate Engine Modeling Software

Research and development of Fast, Easy, Accurate and Robust Continuum Engineering (FEARCE, formerly KIVA-hpFE) for turbulent reactive and multiphase flow, particularly as related to engine modeling, is relevant to the DOE Vehicle Technologies Office efforts at addressing national energy security. Less dependence on petroleum products leads to greater energy security. By Environmental Protection Agency standards, some vehicles are now reaching 42–50 mpg mark. These are conventional gasoline engines. With continued investment and research into new technical innovations, the potential exists to save more than 4 million barrels of oil per day or approximately 200 to 400 dollars million per day. This would be a significant decrease in emissions and use of petroleum and a very large stimulus to the U.S. economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗