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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Construction and simulation of a novel continuous traffic flow model

In this paper, we aim to propose a novel mathematical model for traffic flow and apply a newly developed characteristic particle method to solve the associate governing equations. As compared with the existing non-equilibrium higher-order traffic flow models, the present one is put forward to satisfy the following three conditions: 1.Preserve the equilibrium state in the smooth region. 2.Yield an anisotropic propagation of traffic flow information. 3.Expressed with a conservation law form for traffic momentum. These conditions will ensure a more practical simulation in traffic flow physics: The current traffic will not be influenced by the condition in the behind and result in unambiguous condition across a traffic shock. Through analyses of characteristics, stability condition and steady-state solution adherent to the equation system, it is shown that the proposed model actually conform to these conditions. Furthermore, this model can be cast into its characteristic form which, incorporated with the Rankine-Hugoniot relation, is appropriate to be simulated by the characteristic particle method to obtain accurate computational results. - Highlights: • The traffic model expressed with the momentum conservation law. • Traffic flow information propagate anisotropically and preserve the equilibrium state in the smooth region. • Computational particles of two families are invented to mimic forward-running and backward-running characteristics. • Formation of shocks will be naturally detected by the intersection of computational particles of same family. • A newly developed characteristic particle method is used to simulate traffic flow model equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

An iterative particle filter approach for coupled hydro-geophysical inversion of a controlled infiltration experiment

The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to both measurement and model errors. Geophysical methods such as Electrical Resistivity Tomography (ERT) can provide useful indirect information on the hydrological processes occurring in the vadose zone. In this paper, we propose and test an iterated particle filter method to solve the coupled hydrogeophysical inverse problem. We focus on an infiltration test monitored by time-lapse ERT and modeled using Richards equation. The goal is to identify hydrological model parameters from ERT electrical potential measurements. Traditional uncoupled inversion relies on the solution of two sequential inverse problems, the first one applied to the ERT measurements, the second one to Richards equation. This approach does not ensure an accurate quantitative description of the physical state, typically violating mass balance. To avoid one of these two inversions and incorporate in the process more physical simulation constraints, we cast the problem within the framework of a SIR (Sequential Importance Resampling) data assimilation approach that uses a Richards equation solver to model the hydrological dynamics and a forward ERT simulator combined with Archie's law to serve as measurement model. ERT observations are then used to update the state of the system as well as to estimate the model parameters and their posterior distribution. The limitations of the traditional sequential Bayesian approach are investigated and an innovative iterative approach is proposed to estimate the model parameters with high accuracy. The numerical properties of the developed algorithm are verified on both homogeneous and heterogeneous synthetic test cases based on a real-world field experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Deep operator network surrogate for phase-field modeling of metal grain growth during solidification

A deep operator network (DeepONet) has been constructed that generates accurate representations of phase-field model simulations for evolving two dimensional metal grain morphology growing from melt. These representations serve as lower resolution, computationally efficient stand-ins for quick parameter space exploration of solutions to the the Allen-Cahn equations that dictate the phase-field model simulations. The experimental target for the phase-field model is a uranium casting system cooling a 434 g uranium charge from a maximum temperature of 1400° C at an average rate of 30° C / min , traversing the crystallographic phases of the pure metal. Experimental parameters inform the phase-field model, whose higher resolution computational model solutions are used to train the DeepONet in a given parameter space with the aim of developing a faster, more efficient method for predicting the solidifying metal's microstructure at different potential experimental values. The final DeepONet generates high accuracy, lower resolution predictions with cumulative relative approximation error over all timesteps of less than 0.5%, while ensuring solutions remain within physically feasible ranges. Further, these relative error values are comparable with other state-of-the-art DeepONet models for microstructure evolution, while significantly reducing the amount of training data required. Training a convolutional neural network simultaneously with the DeepONet, enforcing realistic values at the complex metal grain boundaries, and mathematically encoding boundary conditions into the structure of the DeepONet improved prediction accuracy and computational efficiency over a standard DeepONet model.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Triple Plate Mold Final Report: Optimization of the Mold Design and Casting Parameters for a Thin U-10mo Fuel Casting

This work describes the experiments and modeling that have been performed to improve and try to optimize the simultaneous casting of three plates of U-10wt%Mo in a single coil vacuum induction melting (VIM) furnace. The plates of interest are 280 mm wide by 203 mm tall by 5 mm thick (11" x 8" x 0.2"). The initial mold design and processing parameters were supplied by Y-12. The mold and casting cavity were instrumented with a number of thermocouples, and the casting performed to determine the thermal history of the mold and casting. The resulting cast plates were radiographed and numerous defects identified. Metallography was performed to help identify the nature of the radiographically observed defects. This information was then used to validate a mold filling and solidification model of that casting. Based on the initial casting, good casting design practice, and process simulation of several design alternatives, a revised design was developed with the goal of minimizing casting defects such as porosity. The redesigned mold had a larger hot-top and had its long axis along the horizontal direction. These changes were to try to develop a strong thermal gradient conducive to good feeding and minimization of micro- and macroporosity in the cast plates. An instrumented casting was then performed with the revised mold design and a linear distributor. This design yielded cast plates with significantly less radiographically identified defects. Unfortunately, there was significant variation in plate weight and metal content in their hot-tops. Fluid flow simulations were then performed on this mold/distributor design. This helped identify the issue with this linear distributor design. Additional simulations were then performed on candidate distributor redesigns and a preferred distributor annular design was identified. This improved annular design was used to produce a third instrumented casting with favorable results. These refined designs and their radiographic characterization are compared to the initial design.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Application of Selected Artificial Intelligence Methods in a System Predicting the Microstructure of Compacted Graphite Iron

Intelligent computing tools such as artificial neural network and fuzzy logic are used as predictive modeling tools. The use of these methods, combined with model experimental results, may be an excellent predictive tool, allowing us to forecast the microstructure of the tested cast iron at the level of computer simulation. In this study, the reference training cases collected in one database were used to determine the parameters of the neuro-fuzzy ANFIS model. They mainly include the results of observations and measurements of the content of individual microstructural constituents of the compacted graphite iron, examined as a function of the content of individual alloy additives (molybdenum, nickel and copper introduced in various proportions). The training process of such a fuzzy inference system is done by constantly changing its parameters (parameters of the membership function) and determining new rule conclusions as a result of presenting individual case examples from the training sample. The conducted research has shown the possibility of applying the ANFIS model as a tool to control the chemical composition of compacted graphite iron in the production of castings with high-strength parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Testing the conservative character of particle simulations: I. Canonical and noncanonical guiding center model in Boozer coordinates

The guiding center (GC) Lagrangian in Boozer coordinates for toroidally confined plasmas can be cast into canonical form by eliminating terms containing the covariant component B Ψ P of the magnetic field vector with respect to the poloidal flux function Ψ P . In an unperturbed plasma, B Ψ P can be eliminated via exact coordinate transformations, but, in general, one relies on approximations, assuming that the effect of B Ψ P is small. In this work, we are interested in the question whether Hamiltonian conservation laws are still satisfied when B Ψ P is retained in the presence of fluctuations. Considering fast ions in the presence of a shear Alfvén wave field with fixed amplitude, fixed frequency, and a single toroidal mode number n, we show that simulations using the code ORBIT with and without B Ψ P yield practically the same resonant and nonresonant GC orbits. The numerical results are consistent with theoretical analyses (presented in the appendix), which show that the unabridged GC Lagrangian with B Ψ P retained yields equations of motion that possess two key properties of Hamiltonian flows: (i) phase space conservation and (ii) energy conservation. As counter-examples, we also show cases where energy conservation (ii) or both conservation laws (i) and (ii) are broken by omitting certain small terms. When testing the conservative character of the simulation code, it is found to be beneficial to apply perturbations that do not resemble normal (eigen) modes of the plasma. The deviations are enhanced and, thus, more easily spotted when one inspects wave-particle interactions using nonnormal modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Modeling of Dendritic Evolution of Continuously Cast Steel Billet with Cellular Automaton

In order to predict the dendritic evolution during the continuous steel casting process, a simple mechanism to connect the heat transfer at the macroscopic scale and the dendritic growth at the microscopic scale was proposed in the present work. As the core of the across-scale simulation, a two-dimensional cell automaton (CA) model with a decentered square algorithm was developed and parallelized. Apart from nucleation undercooling and probability, a temperature gradient was introduced to deal with the columnar-to-equiaxed transition (CET) by considering its variation during continuous casting. Based on the thermal history, the dendritic evolution in a 4 mm × 40 mm region near the centerline of a SWRH82B steel billet was predicted. The influences of the secondary cooling intensity, superheat, and casting speed on the dendritic structure of the billet were investigated in detail. The results show that the predicted equiaxed dendritic solidification of Fe-5.3Si alloy and columnar dendritic solidification of Fe-0.45C alloy are consistent with in situ experimental results [Yasuda et al. Int J Cast Metals Res 22:15–21 (2009); Yasuda et al. ISIJ Int 51:402–408 (2011)]. Moreover, the predicted dendritic arm spacing and CET location agree well with the actual results in the billet. The primary dendrite arm spacing of columnar dendrites decreases with increasing secondary cooling intensity, or decreasing superheat and casting speed. Meanwhile, the CET is promoted as the secondary cooling intensity and superheat decrease. However, the CET is not influenced by the casting speed, owing to the adjusting of the flow rate of secondary spray water. Compared with the superheat and casting speed, the secondary cooling intensity can influence the cooling rate and temperature gradient in deeper locations, and accordingly exerts a more significant influence on the equiaxed dendritic structure.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Mechanism of Macrosegregation Formation in Continuous Casting Slab: A Numerical Simulation Study

Solidified shell bulging is supposed to be the main reason for slab center segregation, while the influence of thermal shrinkage rarely has been considered. In this article, a thermal shrinkage model coupled with the multiphase solidification model is developed to investigate the effect of the thermal shrinkage, solidification shrinkage, grain sedimentation, and thermal flow on solute transport in the continuous casting slab. In this model, the initial equiaxed grains contract freely with the temperature decrease, while the coherent equiaxed grains and columnar phase move directionally toward the slab surface. The results demonstrate that the center positive segregation accompanied by negative segregation in the periphery zone is mainly caused by thermal shrinkage. During the solidification process, liquid phase first transports toward the slab surface to compensate for thermal shrinkage, which is similar to the case considering solidification shrinkage, and then it moves opposite to the slab center near the solidification end. It is attributed to the sharp decrease of center temperature and the intensive contract of solid phase, which cause the enriched liquid to be squeezed out. With the effect of grain sedimentation and thermal flow, the negative segregation at the external arc side (zone A1) and the positive segregation near the columnar-to-equiaxed transition at the inner arc side (position B1) come into being. Besides, it is found that the grain sedimentation and thermal flow only influence solute transport before equiaxed grains impinge with each other, while the solidification and thermal shrinkage still affect solute redistribution in the later stage.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Scale-Adaptive Simulation of Transient Two-Phase Flow in Continuous-Casting Mold

Scale-adaptive simulation (SAS) of the transient gas–liquid two-phase flow in a laboratory-scale continuous-casting mold is presented. The main objective is to investigate the applicability of the scale-adaptive unsteady Reynolds-averaged Navier–Stokes turbulent model (URANS SAS) for predicting the transient multiscale turbulent structures in a two-phase flow. Good quantitative agreements with the experimental data and the large eddy simulation (LES) results are obtained both for the time-averaged velocity field and for the transient turbulent characteristics. The introduction of the von Karman length-scale into the turbulence-scale equation allows the SAS model to dynamically adjust to the resolved turbulent structures. The LES-like pulsating behavior of the air gas and the large-scale liquid eddy magnitudes in the unsteady regions of flow field are captured by the SAS model. The classical − 5/3 law of power spectrum density (PSD) of the axial velocity is kept properly for the single-phase turbulent flow. For two-phase flow, the decay of PSD is too steep at the high-frequency region; the predicted PSD obtained with SAS is damped stronger than that estimated by LES. The SAS model offers an attractive alternative to the existing LES approach or to the other hybrid RANS/LES models for strongly unsteady flows.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Modeling and Computation of Casting Process by Particle Method

Since particle-based computational methods, such as smoothed particle hydrodynamics (SPH) method, are suitable to treat free surfaces and moving boundaries, it is expected that the simulation with particle methods can represent more accurate molten metal flow. Hence, we apply the SPH method to some casting processes and validate the numerical results by comparing with experiments. While fluid behaviors of the transportation and the mold filling processes are expressed sufficiently, ladle pouring process of aluminum alloy is not reproduced by the existing scheme. So we developed a new numerical model of surface oxide film, and our numerical results show good agreement with the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Application of Al-Cu-W-Ta graded density impactors in dynamic ramp compression experiments

Graded density impactors (GDIs) are utilized to dynamically compress materials to extreme conditions. Two modifications to a previously developed Mg-Cu-W GDI are made in this work before using it in a dynamic compression experiment: Mg is replaced with Al and a Ta disk is glued to the back. The Mg phase is replaced by Al because FCC Al remains solid to higher pressure along its Hugoniot compared to Mg. The addition of the Ta disk creates a constant particle velocity regime and facilitates a definition of peak pressure states. Microstructure analysis, profilometry, and ultrasonic C-scans of the Al-Cu-W GDI all confirm excellent uniformity. We evaluated signal variation in the radial direction of a dynamically compressed Al-LiF bilayer target to evaluate the contribution of spatial nonuniformity to errors. Velocity traces from five photon Doppler velocimetry (PDV) probes located at different radial distances from the center of the target varied at most by 1.1% with a root mean square of 0.3% during the compression ramp, demonstrating low PDV measurement error over a relatively large experimental area. The experimental PDV data additionally agrees well with 1D simulations that use inputs from predictive characterization models developed for the material properties resulting from tape casting, laminating, and powder consolidation processes. Low measurement error during quasi-isentropic compression, leading to better precision, promises a robust platform to reach extreme compression and low-temperature recovery states and facilitates discovery via synthesis, quenching, and preservation of new high-pressure phases.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electron cyclotron drift instability and anomalous transport: two-fluid moment theory and modeling

In the presence of a strong electric field perpendicular to the magnetic field, the electron cross-field (E × B) flow relative to the unmagnetized ions can cause the so-called electron cyclotron drift instability (ECDI) due to resonances of the ion acoustic mode and the electron cyclotron harmonics. This occurs in, for example, collisionless shock ramps in space, and in E × B discharge devices such as Hall thrusters. A prominent feature of ECDI is its capability to induce an electron flow parallel to the background >E field at a speed greatly exceeding predictions by classical collision theory. Such anomalous transport is important due to its role in particle thermalization at space shocks, and in causing plasma flows towards the walls of E × B devices, leading to unfavorable erosion and performance degradation, etc. The development of ECDI and anomalous transport is often considered requiring a fully kinetic treatment. In this work, however, we demonstrate that a reduced variant of this instability, and more importantly, the associated anomalous transport, can be treated self-consistently in a collisionless two-fluid framework without any adjustable collision parameter. By treating both electron and ion species on an equal footing, the free energy due to the inter-species velocity shear allows the growth of an anomalous electron flow parallel to the background E field. We will first present linear analyses of the instability in the two-fluid five- and ten-moment models, and compare them against the fully-kinetic theory. At low temperatures, the two-fluid models predict the fastest-growing mode in good agreement with the kinetic result. Also, by including more (> = 10) moments, secondary (and possibly higher) unstable branches can be recovered. The dependence of the instability on ion-to-electron mass ratio, plasma temperature, and background B field strength is also thoroughly explored. We then carry out direct numerical simulations of the cross-field setup using the five-moment model. The development of the instability, as well as the anomalous transport, is confirmed and in excellent agreement with theoretical predictions. The force balance properties are also studied using the five-moment simulation data. Here this work casts new insights into the nature of ECDI and the associated anomalous transport and demonstrates the potential of the two-fluid moment model in efficient modeling of E × B plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Formation Mechanism of Surface Crack in Low Pressure Casting of A360 Alloy

A surface crack defect is normally found in low pressure castings of Al alloy with a sudden contraction structure. To further understand the formation mechanism of the defect, the mold filling process is simulated by a two-phase flow model. The experimental results indicate that the main reason for the defect deformation is the mismatching between the height of liquid surface in the mold and pressure in the crucible. In the case of filling, a sudden contraction structure with an area ratio smaller than 0.5 is obtained, and the velocity of the liquid front increases dramatically with the influence of inertia. Meanwhile, the pressurizing speed in the crucible remains unchanged, resulting in the pressure not being able to support the height of the liquid level. Then the liquid metal flows back to the crucible and forms a relatively thin layer solidification shell on the mold wall. With the increasing pressure in the crucible, the liquid level rises again, engulfing the shell and leading to a surface crack. As the filling velocity is characterized by the damping oscillations, surface cracks will form at different heights. The results shed light on designing a suitable pressurizing speed for the low pressure casting process.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An Ab Initio Molecular Dynamics Study of Key Thermodynamic Input Parameters for Computer Simulation of U-6Nb Solidification

The key to metallic fuel development is the fabrication of uranium metal and alloys into fuel forms. U-Nb alloys are one of the best candidates for a metallic fuel alloy with high-temperature strength sufficient to support the core, acceptable nuclear properties, good fabricability, and compatibility with usable coolant media. Melt processing has been a key component of the metallic fuel cycle, and process models require thermophysical parameters at elevated temperatures, particularly above the melting temperatures, regarding which experimental data are scarce, for accurate simulations and process development. By means of ab initio density-functional theory (DFT) quantum molecular dynamics (QMD), we have calculated the main thermophysical parameters—the density, thermal expansion coefficient, specific heat, thermal conductivity, melting temperature, latent heat of fusion, and viscosity—used in the modeling of the U-6 wt.% Nb alloy casting. The melting temperature of the U-6 wt.% Nb alloy at ambient pressure is obtained by means of QMD simulations using the Z-method. The ambient volume change and latent heat of melting of U-6 wt.% Nb are also derived from QMD simulations in conjunction with analytical fitting for the energy and pressure. The thermal conductivity for the solid U-Nb alloy is calculated from the semi-classical Boltzmann transport equation combined with an estimate of the electron relaxation time obtained from DFT simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

High-Throughput Study of Diffusion and Phase Transformation Kinetics of Magnesium-Based Systems for Automotive Cast Magnesium Alloys

The objective of the proposed study is to establish a scientific foundation on kinetic modeling of diffusion, phase precipitation, and casting/solidification, in order to accelerate the design and optimization of cast magnesium (Mg) alloys for weight reduction of U.S. automotive fleet. The team has performed the following tasks: 1) study diffusion kinetics of various Mg-containing binary systems using high-throughput diffusion multiples to establish reliable diffusivity and mobility databases for the Mg-aluminum (Al)-zinc (Zn)-tin (Sn)-calcium (Ca)-strontium (Sr)-manganese (Mn) systems; 2) study the precipitation kinetics (nucleation, growth and coarsening) using both innovative dual-anneal diffusion multiples and cast model alloys to provide large amounts of kinetic data (including interfacial energy) and microstructure atlases to enable implementation of the Kampmann-Wagner numerical model to simulate phase transformation kinetics of non-spherical/non-cuboidal precipitates in Mg alloys; 3) implement a micromodel to take into account back diffusion in the solid phase in order to predict microstructure and microsegregation in multicomponent Mg alloys during dendritic solidification especially under high pressure die-casting (HPDC) conditions; and, 4) widely disseminate the data, knowledge and information using the Materials Genome Initiative infrastructure (http://www.mgidata.org) as well as publications and digital data sharing to enable researchers to identify new pathways/routes to better cast Mg alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructure-process relationships in monolithic U-10Mo fuel foil single-pass rolling: A parametric simulation study

In this work, a previously validated coupling of Kinetic Monte Carlo (KMC) Potts Model and finite element method (FEM) simulations was implemented to investigate the effects of microstructural features in as-cast and homogenized monolithic U-10Mo foils on the emergent microstructure after rolling and reheating. Parameters that could potentially affect recrystallization behavior of the rolled U-10Mo foils were considered: grain size distribution, uranium carbide (UC) size distribution, UC volume fraction, spatial distribution of UC, and rolling reduction magnitude. Grain structure and the magnitude of rolling reduction have the strongest influence on recrystallization kinetics and the fabricated grain size distribution. The UC distribution had only a weak effect on the recrystallization kinetics and final microstructures. While particle-stimulated nucleation (PSN) occurred in simulation more frequently as grain size increased, its incidence did not appear to considerably affect the recrystallization kinetics or grain size distribution.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Metal plasticity and ductile fracture modeling for cast aluminum alloy parts

Here in this study, plasticity and ductile fracture properties were characterized by performing various tension, shear, and compression tests. A series of 10 experiments were performed using notched round bars, flat-grooved plates, in-plane shear plates, and cylindrical bars. Two cast aluminum alloys used in automotive suspension systems were selected. Plasticity modelling was performed and the results were compared with experimental and corresponding simulation results; further, the relationships among the stress triaxiality, Lode angle parameter, and equivalent plastic strain at the onset of failure were determined to calibrate a ductile fracture model. Finally, the proposed ductile fracture model shows good agreement with experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2016

ON THE MISALIGNMENT BETWEEN CHROMOSPHERIC FEATURES AND THE MAGNETIC FIELD ON THE SUN

Observations of the upper chromosphere show an enormous amount of intricate fine structure. Much of this comes in the form of linear features, which are most often assumed to be well aligned with the direction of the magnetic field in the low plasma β regime that is thought to dominate the upper chromosphere. We use advanced radiative magnetohydrodynamic simulations, including the effects of ion-neutral interactions (using the generalized Ohm’s law) in the partially ionized chromosphere, to show that the magnetic field is often not well aligned with chromospheric features. This occurs where the ambipolar diffusion is large, i.e., ions and neutral populations decouple as the ion-neutral collision frequency drops, allowing the field to slip through the neutral population; where currents perpendicular to the field are strong; and where thermodynamic timescales are longer than or similar to those of ambipolar diffusion. We find this often happens in dynamic spicule or fibril-like features at the top of the chromosphere. This has important consequences for field extrapolation methods, which increasingly use such upper chromospheric features to help constrain the chromospheric magnetic field: our results invalidate the underlying assumption that these features are aligned with the field. In addition, our results cast doubt on results from 1D hydrodynamic models, which assume that plasma remains on the same field lines. Finally, our simulations show that ambipolar diffusion significantly alters the amount of free energy available in the coronal part of our simulated volume, which is likely to have consequences for studies of flare initiation.

79 ASTRONOMY AND ASTROPHYSICS↗