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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Relationship between Surface Self-Diffusion and Bubble Mobility in Solids: Theory and Atomistic Simulation

Diffusion processes in solids are characterized by complex mechanisms occurring at the atomistic level. The relevant theoretical concepts are sufficiently developed in the case of the diffusion of point defects. At the same time, the diffusion of objects such as clusters of vacancies or nanometer-size cavities in the crystal lattice is described only in terms of continuous-medium approximation. This paper attempts to link the existing theory of diffusion of bubbles in a crystalline matrix with the atomistic description of the process on the basis of the molecular dynamics method. For simplicity, the diffusion of cavities in a two-dimensional Lennard-Jones lattice is considered. A controlled molecular dynamics method is proposed to speed up the direct computation of the diffusion rate of bubbles. Based on the results of simulation, a practical interpretation is given to a parameter of the continuum theory such as the rate of surface self-diffusion. The applicability range of the continuum theory is demonstrated, and principles for the refinement of the theory in the case of minimum-size bubbles are formulated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A Graphics Processing Unit–Based, Industrial Grade Compositional Reservoir Simulator

Summary Recently, graphics processing units (GPUs) have been demonstrated to provide a significant performance benefit for black-oil reservoir simulation, as well as flash calculations that serve an important role in compositional simulation. A comprehensive approach to compositional simulation based on GPUs has yet to emerge, and the question remains as to whether the benefits observed in black-oil simulation persist with a more complex fluid description. We present a positive answer to this question through the extension of a commercial GPU-based black-oil simulator to include a compositional description based on standard cubic equations of state (EOSs). We describe the motivations for the selected nonlinear formulation, including the choice of primary variables and iteration scheme, and support for both fully implicit methods (FIMs) and adaptive implicit methods (AIMs). We then present performance results on an example sector model and simplified synthetic case designed to allow a detailed examination of runtime and memory scaling with respect to the number of hydrocarbon components and model size, as well as the number of processors. We finally show results from two complex asset models (synthetic and real) and examine performance scaling with respect to GPU generation, demonstrating that performance correlates strongly with GPU memory bandwidth. NOTE: This paper is also published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.

Engineering↗
DOE OSTI2021

Estimating outflow masses and velocities in merger simulations: Impact of r -process heating and neutrino cooling

Here, the determination of the mass, composition, and geometry of matter outflows in black hole-neutron star and neutron star-neutron star binaries is crucial to current efforts to model kilonovae and to understand the role of neutron star merger in r-process nucleosynthesis. In this manuscript, we review the simple criteria currently used in merger simulations to determine whether matter is unbound and what the asymptotic velocity of ejected material will be. We then show that properly accounting for both heating and cooling during r-process nucleosynthesis is important to accurately predict the mass and kinetic energy of the outflows. These processes are also likely to be crucial to predict the fall-back timescale of any bound ejecta. We derive a model for the asymptotic velocity of unbound matter and binding energy of bound matter that accounts for both of these effects and that can easily be implemented in merger simulations. We show, however, that the detailed velocity distribution and geometry of the outflows can currently only be captured by full three-dimensional fluid simulations of the outflows, as nonlocal effect ignored by the simple criteria used in merger simulations cannot be safely neglected when modeling these effects. Finally, we propose the introduction of simple source terms in the fluid equations to approximately account for heating/cooling from r-process nucleosynthesis in future seconds-long three-dimensional simulations of merger remnants, without the explicit inclusion of out-of-nuclear statistical equilibrium reactions in the simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Bayesian stability and force modeling for uncertain machining processes

Accurately simulating machining operations requires knowledge of the cutting force model and system frequency response. However, this data is collected using specialized instruments in an ex-situ manner. Bayesian statistical methods instead learn the system parameters using cutting test data, but to date, these approaches have only considered milling stability. This paper presents a physics-based Bayesian framework which incorporates both spindle power and milling stability. Initial probabilistic descriptions of the system parameters are propagated through a set of physics functions to form probabilistic predictions about the milling process. The system parameters are then updated using automatically selected cutting tests to reduce parameter uncertainty and identify more productive cutting conditions, where spindle power measurements are used to learn the cutting force model. The framework is demonstrated through both numerical and experimental case studies. Results show that the approach accurately identifies both the system natural frequency and cutting force model.

42 ENGINEERING↗
DOE OSTI2017

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averaging methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.

Dai, Heng↗
DOE OSTI2025

The R -process Alliance: Enrichment of r -process Elements in a Simulated Milky Way–like Galaxy

We study the formation of stars with varying amounts of heavy elements synthesized by the rapid neutron-capture process (r-process) based on our detailed cosmological zoom-in simulation of a Milky Way–like galaxy with an N-body/smoothed particle hydrodynamics code, asura. Most stars with no overabundance in r-process elements, as well as the strongly r-process-enhanced (RPE) r-II stars ([Eu/Fe] > +0.7), are formed in dwarf galaxies accreted by the Milky Way within the 6 Gyr after the Big Bang. In contrast, over half of the moderately enhanced r-I stars (+0.3 < [Eu/Fe] ≤ +0.7) are formed in the main in situ disk after 6 Gyr. Our results suggest that the fraction of r-I and r-II stars formed in disrupted dwarf galaxies is larger the higher their [Eu/Fe] is. Accordingly, the most strongly enhanced r-III stars ([Eu/Fe] > +2.0) are formed in accreted components. These results suggest that non-r-process-enhanced stars and r-II stars are mainly formed in low-mass dwarf galaxies that hosted either none or a single neutron star merger, while the r-I stars tend to form in the well-mixed in situ disk. We compare our findings with high-resolution spectroscopic observations of RPE metal-poor stars in the halo and dwarf galaxies, including those collected by the R-Process Alliance. We conclude that observed [Eu/Fe] and [Eu/Mg] ratios can be employed in chemical tagging of the Milky Way’s accretion history.

Chemical enrichment↗
DOE OSTI2021

Fast Emulation of Expensive Simulations using Approximate Gaussian Processes [Slides]

Nuclear Computational Low-Energy Initiative (NUCLEI) collaboration uses Density Functional Theory (DFT) simulations to predict the structure and binding energies of nuclei over a wide range of proton (Z) and neutron (N) numbers. The DFT simulations utilize a particular parameterization of a Skyrme energy density functional called UNEDF1 which depends on 12 free parameters that must be fit to data (M Kortelainen et al 2014). Fitting involves comparing (e.g.) predicted binding energies of nuclei to experimentally measured values. We use only binding energies as observables, but DFT with UNEDF1 will predict structure (shape) observables as well. In this work, assessing the capability of approximate GP emulators to balance emulator accuracy with computational speed to facilitate improved UNEDF1 calibration. Sparse GPs are straightforward to train and accurate. Calibration is not straightforward with MCMC (using MH or HMC/NUTS). We produced reusable software for continuing and building on this work as well as accessing and using Darwin cluster compute resources

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Permanganate Oxidation of Defense Waste Processing Facility (DWPF) Recycle Collection Tank (RCT) Simulants – Protocol Runs for Nominal and Chemical Process Cell (CPC) Foamover Conditions

Savannah River National Laboratory (SRNL) has completed a work scope in support of the Savannah River Remediation (SRR) Nitric-Glycolic flowsheet. Glycolic acid will replace formic acid as a reducing agent in the pre-processing of High-Level Waste sludge performed at the Defense Waste Processing Facility (DWPF). Glycolic acid will perform the same function as formic acid, namely reduction of mercury and adjustment of feed rheology and melter oxidation/reduction potential, while significantly reducing the potential for hydrogen generation in DWPF processing. Development testing has demonstrated glycolic acid virtually eliminates hydrogen production in the pre-processing steps. The Nitric-Glycolic flowsheet significantly improves DWPF’s ability to address one of the Savannah River Site’s key challenges - the incorporation of effluent received from the Salt Waste Processing Facility (SWPF). SWPF will deliver significant effluent volume to DWPF, resulting in a concurrent increase in DWPF effluent returned to the Concentration, Storage and Transfer Facilities (CSTF). This work scope demonstrates that glycolate can be destroyed under the Nitric-Glycolic flowsheet prior to returning the DWPF recycle stream to CSTF. To avoid potential flammability issues due to thermolysis of glycolate in CSTF, SRR tasked SRNL to quantify and mitigate glycolate returns via DWPF’s recycle stream. The development of a strategy for glycolic mitigation was initiated with a system’s engineering workshop. Various chemical and/or physical solutions for how and where to destroy glycolate were considered – consistent with DWPF’s operational capabilities and process requirements. The workshop identified chemical oxidation of glycolate within the DWPF Recycle Collection Tank (RCT) as the most promising option. (The RCT collects offgas condensate from pre-processing, vitrification, and other unit operations performed in DWPF and is the singular return vessel delivering recycle effluent back to CSTF.) A series of down-select experimental tests were performed that showed sodium permanganate was the most effective oxidant. This work was performed to identify an appropriate operational protocol for DWPF implementation. Building upon the downselect experiments, the work targeted an improved description of suitable RCT conditions prior to the strike (pH, etc.), permanganate addition rate, and destruction reaction kinetics. Data collected were also used to determine the best expression of reaction stoichiometry and the effective minimum permanganate addition required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Parallel point defect identification in molecular dynamics simulations without post-processing: A compute and dump style for LAMMPS

Two classes for the molecular dynamics program LAMMPS – one compute style and one dump style – are presented that are designed to identify, count, and output point defects in cascade damage and related molecular dynamics simulations. The calculations are done in parallel across multiple MPI processes, and can be done at the same time as the original simulation. This drastically reduces storage requirements by eliminating the need to post-process every atom in the system. Non-cubic lattices, free surfaces, and large voids can be eliminated from the output by suitable choices of the reference lattice. The classes are derived from LAMMPS’s Dump and Compute classes, and pose no additional overhead to LAMMPS if they are not used.

42 ENGINEERING↗
DOE OSTI2021

Performance-based simulants for Hanford radioactive waste treatment process testing

Radioactive wastes from nuclear fuel processing are stored in large underground storage tanks at the Hanford Nuclear Reservation. Treatment and remediation require that waste feed from the storage tanks be delivered to the Hanford Tank Waste Treatment and Immobilization Plant continually for the duration of the treatment mission. Furthermore, the complex physical and chemical processes required for this mission, the significant scale, and the hazardous nature of the waste necessitate the use of simulants in process testing. A new class of simulants, “performance-based simulants,” has been developed to match the process performance of the simulant to actual waste performance data.

Hanford tank waste treatment↗
DOE OSTI2018

Microwave sintering of complex shapes: From multiphysics simulation to improvements of process scalability

The microwave sintering homogeneity of large and complex shape specimens is analyzed. A new approach enabling the fabrication of complex shapes ceramics via 3D printing and microwave sintering is presented. The use of a dental microwave cavity is shown to enable a substantial level of densification of complex shape components while restricting the grain growth. The homogeneity of the processed samples during microwave sintering is studied by an electromagnetic-thermal-mechanical simulation. The realistic densification behavior, that phenomenologically takes into account the microwave effect, is included in the modeling framework. We observe that the simulation indicates the sharp correlation between the microwave field distribution in the cavity, the temperature profile, and the specimen's shape distortion.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Biological Mechanisms May Contribute to Soil Carbon Saturation Patterns: Modeling Archive

This Modeling Archive is in support of a TES-SFA publication “Biological Mechanisms May Contribute to Soil Carbon Saturation Patterns” (Craig et al., 2021). We ran and evaluated a multi-assumption soil organic carbon (SOC) model to investigate whether alternative assumptions regarding constraints on soil microbial biomass could lead to soil carbon saturation patterns. We developed this model in the Multi-Assumption Architecture and Testbed (MAAT, https://github.com/walkeranthonyp/MAAT, tag: v1.2.1_Craig2021; Walker et al. 2018). Using MAAT, we embedded three alternative hypotheses in a microbially explicit three-pool SOC model: 1) the efficiency of mineral-associated SOC formation decreases as mineral-associated SOC approaches a maximum value (“Mineral saturation”), 2) the microbial biomass turnover rate increases with increasing microbial biomass (“Density-dependent turnover”), and 3) community carbon use efficiency decreases as microbial biomass increases toward an upper limit (“Density-dependent growth”). We ran a factorial combination of these hypotheses resulting in eight models for three different classes of model (linear decay, Michaelis-Menten decay, or reverse Michaelis-Menten decay), resulting in 24 models, 12 of which are presented or discussed in the related publication. Models were parameterized using values from previous studies with similar models (Wang et al. 2013, Wieder et al. 2014, Li et al. 2014, Georgiou et al. 2017, Hassink and Whitmore 1997) and ran to an approximate steady state (200 years) at six (6) different C input rates corresponding to 0.5, 1, 2, 4, 7, and 10 times the default input value. Further model details are available in the related publication. This archive contains output from three MAAT simulations, and scripts to run these simulations and process and plot the data. Simulations are labeled “lin”, “MM_highKm”, and “RMM_highKm” reflecting factorial runs for linear, Michealis-Menten, and reverse Michaelis-Menten models, respectively. This archive contains: • 3 R scripts prepended with “init_MAAT_” to initialize runs (1 for each simulation), • 1 csv file containing years over which to run simulations (“met_year.csv”), • 1 bash script (.bs) to run MAAT, • 6 XML files that are output from MAAT describing a run (2 for each simulation), • 3 model output csv files prepended by “out_” (1 for each simulation), and • 1 analysis R script for reproducing figures 3 and 4 in Craig et al. 2021. See included user guide (Craig_2021_modeling_archive_20210315.pdf) for file organization details.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dynamic modeling and simulation of pressure swing adsorption processes using toPSAil

Pressure swing adsorption (PSA) has attracted significant recent interest for chemical process intensification due to its potential for high energy efficiency and amenability to small, modular designs. However, the lack of simulation tools that are readily available, transparent, and trusted, has been identified as a serious impediment to widespread adoption of PSA, as well as to further research on PSA modeling, numerical solution, optimization, and control. This paper presents a complete framework for dynamic modeling and simulation of PSA processes and its implementation in an open-source simulator called toPSAil. Further, the presentation is tutorial and includes many modeling and implementation details often overlooked in existing literature. Novel methods are presented for handling flow reversals and implementing various pressure–flow relationships, along with controlled boundary conditions. Finally, the code contains several innovations designed to improve efficiency and reduce the extensive trial-and-error tuning often required to produce a working PSA cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Plasma Energization in Colliding Magnetic Flux Ropes

Magnetic flux ropes are commonly observed throughout the heliosphere, and recent studies suggest that interacting flux ropes are associated with some energetic particle events. In this work, we carry out 2D particle-in-cell (PIC) simulations to study the coalescence of two magnetic flux ropes (or magnetic islands), and the subsequent plasma energization processes. The simulations are initialized with two magnetic islands embedded in a reconnecting current sheet. The two islands collide and eventually merge into a single island. Particles are accelerated during this process as the magnetic energy is released and converted to the plasma energy, including bulk kinetic energy increase by the ideal electric field, and thermal energy increase by the fluid compression and the nonideal electric field. We find that contributions from these different energization mechanisms are all important and comparable with each other. Fluid shear and a nongyrotropic pressure tensor also contribute to the energy conversion process. For simulations with different box sizes ranging from $L_x$ ~ 25–100$d_i$ and ion-to-electron mass ratios $m_i /m_e$ = 25,100, and 400, we find that the general evolution is qualitatively the same for all runs, and the energization depends only weakly on either the system size or the mass ratio. The results may help us understand plasma energization in solar and heliospheric environments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A 1D–0D–3D coupled model for simulating blood flow and transport processes in breast tissue

In this work, we present mixed dimensional models for simulating blood flow and transport processes in breast tissue and the vascular tree supplying it. These processes are considered, to start from the aortic inlet to the capillaries and tissue of the breast. Large variations in biophysical properties and flow conditions exist in this system necessitating the use of different flow models for different geometries and flow regimes. In total, we consider four different model types. First, a system of 1D nonlinear hyperbolic partial differential equations (PDEs) is considered to simulate blood flow in larger arteries with highly elastic vessel walls. Second, we assign 1D linearized hyperbolic PDEs to model the smaller arteries with stiffer vessel walls. The third model type consists of ODE systems (0D models). It is used to model the arterioles and peripheral circulation. Finally, homogenized 3D porous media models are considered to simulate flow and transport in capillaries and tissue within the breast volume. Sink terms are used to account for the influence of the venous and lymphatic systems. Combining the four model types, we obtain two different 1D–0D–3D coupled models for simulating blood flow and transport processes: The first model results in a fully coupled 1D–0D–3D model covering the complete path from the aorta to the breast combining a generic arterial network with a patient specific breast network and geometry. The second model is a reduced one based on the separation of the generic and patient specific parts. The information from a calibrated fully coupled model is used as inflow condition for the patient specific sub-model allowing a significant computational cost reduction. Several numerical experiments are conducted to calibrate the generic model parameters and to demonstrate realistic flow simulations compared to existing data on blood flow in the human breast and vascular system. Moreover, we use two different breast vasculature and tissue data sets to illustrate the robustness of our reduced sub-model approach.

multiscale blood flow models↗
DOE OSTI2017

Drying Model for Fukushima Fuel Debris - 17489

The FATE{sup TM} code is a well-established software tool for simulation of processing, shipping, and interim storage of damaged spent nuclear fuel (SNF) that was used for process design and safety analysis for the Hanford Spent Nuclear Fuel Program (SNFP). This paper describes new model developments that allow FATE to be used for simulation of drying of damaged LWR fuel and, in particular, for simulation of processing, shipping, and interim storage of Fukushima fuel debris. The model is capable of quantifying important tradeoffs in the debris chunk size, process conditions such as temperature and pressure, container size, etc. to optimize process design. The model is also capable of demonstrating proof-of-dryness and to demonstrate the link between observed quantities such as pressure and the amount of residual water. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Characterization of muon and electron beams in the Paul Scherrer Institute PiM1 channel for the MUSE experiment

The MUon Scattering Experiment, MUSE, at the Paul Scherrer Institute, Switzerland, investigates the proton charge radius puzzle, lepton universality, and two-photon exchange, via simultaneous measurements of elastic muon-proton and electron-proton scattering. The experiment uses the PiM1 secondary beam channel, which was designed for high precision pion scattering measurements. We review the properties of the beam line established for pions. We discuss the production processes that generate the electron and muon beams, and the simulations of these processes. Simulations of the π/μ/e beams through the channel using TURTLE and G4beamline are compared. The G4beamline simulation is then compared to several experimental measurements of the channel, including the momentum dispersion at the intermediate focal plane and target, the shape of the beam spot at the target, and timing measurements that allow the beam momenta to be determined. Finally, we conclude that the PiM1 channel can be used for high precision π, μ, and e scattering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗