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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
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 OSTI2014

Precipitation of calcium carbonate and calcium phosphate under diffusion controlled mixing

Multi-component mineral precipitation in porous, subsurface environments is challenging to simulate or engineer when in situ reactant mixing is controlled by diffusion. In contrast to well-mixed systems, the conditions that favor mineral precipitation in porous media are distributed along chemical gradients, which evolve spatially due to concurrent mineral precipitation and modification of solute transport in the media. The resulting physical and chemical characteristics of a mixing/precipitation zone are a consequence of coupling between transport and chemical processes, and the distinctive properties of individual chemical systems. We examined the spatial distribution of precipitates formed in “double diffusion” columns for two chemical systems, calcium carbonate and calcium phosphate. Polyacrylamide hydrogel was used as a low permeability, high porosity medium to maximize diffusive mixing and minimize pressure- and density-driven flow between reactant solutions. In the calcium phosphate system, multiple, visually dense and narrow bands of precipitates were observed that were reminiscent of previously reported Liesegang patterns. In the calcium carbonate system, wider precipitation zones characterized by more sparse distributions of precipitates and a more open channel structure were observed. In both cases, formation of precipitates inhibited, but did not necessarily eliminate, continued transport and mixing of the reactants. A reactive transport model with fully implicit coupling between diffusion, chemical speciation and precipitation kinetics, but where explicit details of nucleation processes were neglected, was able to qualitatively simulate properties of the precipitation zones. The results help to illustrate how changes in the physical properties of a precipitation zone depend on coupling between diffusion-controlled reactant mixing and chemistry-specific details of precipitation kinetics.

54 ENVIRONMENTAL SCIENCES↗
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↗
NASA NTRS1981

Performance deterioration based on simulated aerodynamic loads test, JT9D jet engine diagnostics program

An engine was specially prepared with extensive instrumentation to monitor performance, case temperatures, and clearance changes. A special loading device was used to apply known loads on the engine by the use of cables placed around the flight inlet. These loads simulated the estimated aerodynamic pressure distributions that occur on the inlet in various segments of a typical airplane flight. Test results indicate that the engine lost 1.3 percent in take-off thrust specific fuel consumption (TSFC) during the course of the test effort. Permanent clearance changes due to the loads accounted for 1.1 percent; increase in low pressure compressor airfoil roughness and thermal distortion in the high pressure turbine accounted for 0.2 percent. Pretest predicted performance loss due to clearance changes was 0.9 percent in TSFC. Therefore, the agreement between measurement and prediction is considered to be excellent.

Stromberg, W. J.↗
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 OSTI2015

Optimal Ge/SiGe nanofin geometries for hole mobility enhancement: Technology limit from atomic simulations

We use first principles simulations to engineer Ge nanofins for maximum hole mobility by controlling strain tri-axially through nano-patterning. Large-scale molecular dynamics predict fully relaxed, atomic structures for experimentally achievable nanofins, and orthogonal tight binding is used to obtain the corresponding electronic structure. Hole transport properties are then obtained via a linearized Boltzmann formalism. This approach explicitly accounts for free surfaces and associated strain relaxation as well as strain gradients which are critical for quantitative predictions in nanoscale structures. We show that the transverse strain relaxation resulting from the reduction in the aspect ratio of the fins leads to a significant enhancement in phonon limited hole mobility (7× over unstrained, bulk Ge, and 3.5× over biaxially strained Ge). Maximum enhancement is achieved by reducing the width to be approximately 1.5 times the height and further reduction in width does not result in additional gains. These results indicate significant room for improvement over current-generation Ge nanofins, provide geometrical guidelines to design optimized geometries and insight into the physics behind the significant mobility enhancement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
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 OSTI2016

Modeling the Resilience of Nuclear Power Plant for Unexpected Reactor Trip

Resilience can be defined as the intrinsic ability of a system to adjust to its functioning prior to, during, or following changes and disturbances, so that it can sustain required operations under both expected and unexpected conditions. Resilience engineering is a relatively new paradigm for safety management that focuses on how to cope with complexity under pressure or disturbance to achieve success. A resilient system combines inherent human abilities with engineered safety features and organizational features in a controlled and flexible manner both in expected and in unexpected situations. The concept of resilience has been suggested to complement conventional safety analyses. Conventional safety analysis methods such as PSA have several limitations: 1) they primarily focus on technical dimension, 2) the analysis are linear and sequential, 3) they are dominated by static models, 4) they do not take a systemic view into account, and 5) they focus primarily on why accidents happen and not how success is achieved. The concept of resilience provides a more integrated view for the safety analysis in safety-critical systems, e.g., nuclear power plants. The concept of resilience in the organization of NPPs has been highlighted since the Fukushima Daiichi Nuclear Power Plant accident. An IAEA report addresses that a resilient organization is one that quickly realizes deviation from normal operations and has the ability to make even the toughest and least popular decisions and to manage the margins in which it can maneuver. While traditional strategy to safety in NPPs is to identify what could go or has gone wrong, the concept of resilience is focused on what the organization does well and what it does to maintain its successful operation and to capitalize on those processes in the event of an unexpected situation. This study attempts to model the resilience of NPP dynamically, based on the operating experiences in Korean NPPs. First, this study revised the characterization of NPP. Then, a survey on the literature was conducted to identify the influences between the elements in the model of resilience in NPPs. These works provide a qualitative model for the resilience in NPPs. Then, this study reviewed 168 licensee events reports submitted to the Korean regulatory body since 2004 and quantified the relation between the attributes in the model by performing a Pearson correlation analysis. Finally, a few simulations using the System Dynamics were conducted to discuss which factors are most influencing the resilience. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
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 OSTI2017

TC2015: Life cycle analysis of co-formed coal fines and hydrochar produced in twin-screw extruder (TSE)

Life cycle analysis (LCA) is a quantitative tool that evaluates the environmental performance of a process or system. The main objective of this LCA study is to assess the greenhouse gas (GHG) emissions and life cycle energy use associated with solid fuels produced by co-forming coal fines and hydrochar. The hydrochar is derived from loblolly pine wood via hydrothermal carbonization (HTC) conducted in a reactive twin-screw extruder (TSE). The final product is a drop-in replacement for coal. The life cycle impacts of the co-formed end products are quantified from ‘cradle-to-grave’. Model input parameters are collected from life cycle databases, literature, experimental measurements and simulations by engineering software. Results show that electricity generated from the co-formed products has significantly lower GHG intensity and slightly higher life cycle energy use than coal-generated electricity. The most carbon-intensive component in the overall hydrochar system is the HTC plant. However, this could be improved in the future by plant re-design to recover and recycle thermal energy for more efficient operation.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2017

A near-stationary subspace for ridge approximation

Response surfaces are common surrogates for expensive computer simulations in engineering analysis. However, the cost of fitting an accurate response surface increases exponentially as the number of model inputs increases, which leaves response surface construction intractable for high-dimensional, nonlinear models. Here we describe ridge approximation for fitting response surfaces in several variables. A ridge function is constant along several directions in its domain, so fitting occurs on the coordinates of a low-dimensional subspace of the input space. We review essential theory for ridge approximation – e.g., the best mean-squared approximation and an optimal low-dimensional subspace – and we prove that the gradient-based active subspace is near-stationary for the least-squares problem that defines an optimal subspace. Motivated by the theory, we propose a computational heuristic that uses an estimated active subspace as an initial guess for a ridge approximation fitting problem. We show a simple example where the heuristic fails, which reveals a type of function for which the proposed approach is inappropriate. We then propose a simple alternating heuristic for fitting a ridge function, and we demonstrate the effectiveness of the active subspace initial guess applied to an airfoil model of drag as a function of its 18 shape parameters.

42 ENGINEERING↗
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 OSTI2017

Collimation study for LCLS

In this study we investigate the power deposition along the undulator section of the SLAC Linac Coherent Light Source (LCLS) due to the primary e¯ -beam but also due to potential secondary particles. The expected beam distribution after the LCLS injector is deliberately broadened as an approximated representation of the beam halo. Secondary particles, as e + , e¯ and photons, are generated as a result of tracking the intercepted beam through a dense material. This process is carried out by means of GEANT-4, which has been convoluted into our main tracking engine, LUCRETIA. Simulations show no losses along the undulator section when assuming the nominal primary beam and collimator gaps. However when opening the gaps of collimators located at the first collimator section, by 25%, the fattened beam is partially intercepted by the second collimator section, which is aligned to the undulators. Secondary particles, mostly photons generated at the second collimator section, deposit their energy along the undulator section, at a rate of the order of a milliwatt.

43 PARTICLE ACCELERATORS↗
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↗