Robust Bayesian calibration of a RANS model for jet-in-crossflow simulations.
Abstract not provided.
Ray, Jaideep↗
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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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Improving Representation of Convective Transport for Scale-Aware Parameterization – Part I: Convection and Cloud Properties Simulated with Spectral Bin and Bulk Microphysics
The ultimate goal of this study is to improve representation of convective transport by cumulus parameterization for meso-scale and climate models. As Part I of the study, we perform extensive evaluations of cloud-resolving simulations of a squall line and mesoscale convective complexes in mid-latitude continent and tropical regions using the Weather Research and Forecasting (WRF) model with spectral-bin microphysics (SBM) and with two double-moment bulk microphysics schemes: a modified Morrison (MOR) and Milbrandt and Yau (MY2). Compared to observations, in general, SBM gives better simulations of precipitation, vertical velocity of convective cores, and the vertically decreasing trend of radar reflectivity than MOR and MY2, and therefore will be used for analysis of scale-dependence of eddy transport in Part II. The common features of the simulations for all convective systems are (1) the model tends to overestimate convection intensity in the middle and upper troposphere, but SBM can alleviate much of the overestimation and reproduce the observed convection intensity well; (2) the model greatly overestimates radar reflectivity in convective cores (SBM predicts smaller radar reflectivity but does not remove the large overestimation); and (3) the model performs better for mid-latitude convective systems than tropical system. The modeled mass fluxes of the mid latitude systems are not sensitive to microphysics schemes, but are very sensitive for the tropical case indicating strong microphysics modification to convection. Cloud microphysical measurements of rain, snow and graupel in convective cores will be critically important to further elucidate issues within cloud microphysics schemes.
Fan, Jiwen↗
Improving representation of convective transport for scale‐aware parameterization: 2. Analysis of cloud‐resolving model simulations
Abstract Following Part I, in which 3‐D cloud‐resolving model (CRM) simulations of a squall line and mesoscale convective complex in the midlatitude continental and the tropical regions are conducted and evaluated, we examine the scale dependence of eddy transport of water vapor, evaluate different eddy transport formulations, and improve the representation of convective transport across all scales by proposing a new formulation that more accurately represents the CRM‐calculated eddy flux. CRM results show that there are strong grid‐spacing dependencies of updraft and downdraft fractions regardless of altitudes, cloud life stage, and geographical location. As for the eddy transport of water vapor, updraft eddy flux is a major contributor to total eddy flux in the lower and middle troposphere. However, downdraft eddy transport can be as large as updraft eddy transport in the lower atmosphere especially at the mature stage of midlatitude continental convection. We show that the single‐updraft approach significantly underestimates updraft eddy transport of water vapor because it fails to account for the large internal variability of updrafts, while a single downdraft represents the downdraft eddy transport of water vapor well. We find that using as few as three updrafts can account for the internal variability of updrafts well. Based on the evaluation with the CRM simulated data, we recommend a simplified eddy transport formulation that considers three updrafts and one downdraft. Such formulation is similar to the conventional one but much more accurately represents CRM‐simulated eddy flux across all grid scales.
Liu, Yi‐Chin↗
Exploring a Variable-Resolution Approach for Simulating Regional Climate in the Rocky Mountain Region Using the VR-CESM: VR-CESM Simulation in the Rocky Mountains
The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. Here, we evaluate the variable-resolution Community Earth System Model (VR-CESM) with a high-resolution (0.125°) refinement over the Rocky Mountain region. The VR-CESM results are compared with observations, as well as CESM simulation at a quasi-uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR-CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR-CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR-CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR-CESM. VR-CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10–40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR-CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR-CESM captures the observed occurrence frequency and seasonal variation of rain-on-snow days and performs better than UNIF and CRCM5. Lastly, these results demonstrate the VR-CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.
54 ENVIRONMENTAL SCIENCES↗
Microstructure selection in thin-sample directional solidification of an Al-Cu alloy: In situ X-ray imaging and phase-field simulations
We study microstructure selection during directional solidification of a thin metallic sample. We combine in situ X-ray radiography of a dilute Al-Cu alloy solidification experiments with three-dimensional phase-field simulations. We explore a range of temperature gradient G and growth velocity V and build a microstructure selection map for this alloy. We investigate the selection of the primary dendritic spacing Lambda and tip radius rho. While rho shows a good agreement between experimental measurements and dendrite growth theory, with rho similar to V-1/2, Lambda is observed to increase with V (partial derivative Lambda/partial derivative V > 0), in apparent disagreement with classical scaling laws for primary dendritic spacing, which predict that partial derivative Lambda/partial derivative V <0. We show through simulations that this trend inversion for Lambda(V) is due to liquid convection in our experiments, despite the thin sample configuration. We use a classical diffusion boundary-layer approximation to semi-quantitatively incorporate the effect of liquid convection into phase-field simulations. This approximation is implemented by assuming complete solute mixing outside a purely diffusive zone of constant thickness that surrounds the solid-liquid interface. This simple method enables us to quantitatively match experimental measurements of the planar morphological instability threshold and primary spacings over an order of magnitude in V. We explain the observed inversion of partial derivative Lambda/partial derivative V by a combination of slow transient dynamics of microstructural homogenization and the influence of the sample thickness.
36 MATERIALS SCIENCE↗
Simulations of ecosystem hydrological processes using a unified multi-scale model
This paper presents a unified multi-scale model (UMSM) that we developed to simulate hydrological processes in an ecosystem containing both surface water and groundwater. The UMSM approach modifies the Navier–Stokes equation by adding a Darcy force term to formulate a single set of equations to describe fluid momentum and uses a generalized equation to describe fluid mass balance. The advantage of the approach is that the single set of the equations can describe hydrological processes in both surface water and groundwater where different models are traditionally required to simulate fluid flow. This feature of the UMSM significantly facilitates modelling of hydrological processes in ecosystems, especially at locations where soil/sediment may be frequently inundated and drained in response to precipitation, regional hydrological and climate changes. In this paper, the UMSM was benchmarked using WASH123D, a model commonly used for simulating coupled surface water and groundwater flow. Disney Wilderness Preserve (DWP) site at the Kissimmee, Florida, where active field monitoring and measurements are ongoing to understand hydrological and biogeochemical processes, was then used as an example to illustrate the UMSM modelling approach. The simulations results demonstrated that the DWP site is subject to the frequent changes in soil saturation, the geometry and volume of surface water bodies, and groundwater and surface water exchange. All the hydrological phenomena in surface water and groundwater components including inundation and draining, river bank flow, groundwater table change, soil saturation, hydrological interactions between groundwater and surface water, and the migration of surface water and groundwater interfaces can be simultaneously simulated using the UMSM. Overall, the UMSM offers a cross-scale approach that is particularly suitable to simulate coupled surface and ground water flow in ecosystems with strong surface water and groundwater interactions.
Environmental Molecular Sciences Laboratory↗
Equation-based object-oriented modeling and simulation of data center cooling systems
In this paper, we introduce a newly developed open source data center package in the Modelica Buildings library to support modeling and simulation of cooling and control systems of data centers. The data center package contains major thermal and control component models, such as Computer Room Air Handler, Computer Room Air Conditioner, models of different subsystem configurations such as chillers with differently configured waterside economizers, as well as templates for different systems. Two case studies based on this package are performed to investigate the performances of the cooling and electrical system under normal conditions and emergency situations such as a blackout: one is for a data center powered by conventional energy, and the other is for a data center powered by renewable energy. Simulation results show that the dynamic modeling and multi-domain simulation in the Modelica-based tool make it convenient for users to investigate both normal and emergent operations for conventional and renewable data centers.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Phase-field simulations of fission gas bubbles in high burnup UO2 during steady-state and LOCA transient conditions
To improve the economics of commercial nuclear energy generation, U.S. utilities are currently seeking licensing approval to operate UO2 fuel to higher burnups. One significant safety issue that must be addressed to obtain approval is the potential for fine fragmentation/pulverization of the fuel during a loss-of-coolant accident (LOCA). It has been hypothesized this is caused by the rapid increase of pressure in fission gas bubbles in the high burnup region of the fuel. To better understand this phenomenon, a novel phase-field model of the fission gas bubble microstructure in UO2 has been developed and implemented in Idaho National Laboratory's Marmot application for phase-field simulation of nuclear materials. Simulations of bubble growth in the high burnup region during steady-state conditions showed that initially overpressurized bubbles decreased in pressure during growth, but still remained above equilibrium pressure. During a LOCA transient, simulations of bubbles in the high burnup region showed that bubble size did not change significantly, and the pressure increase due to the transient was calculated and passed to a phase-field model of fracture.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
A prospect for computing in porous materials research: Very large fluid flow simulations
Properties of porous materials, abundant both in nature and industry, have broad influences on societies via, e.g. oil recovery, erosion, and propagation of pollutants. The internal structure of many porous materials involves multiple scales which hinders research on the relation between structure and transport properties: typically laboratory experiments cannot distinguish contributions from individual scales while computer simulations cannot capture multiple scales due to limited capabilities. Thus the question arises how large domain sizes can in fact be simulated with modern computers. This question is here addressed using a realistic test case; it is demonstrated that current computing capabilities allow the direct pore-scale simulation of fluid flow in porous materials using system sizes far beyond what has been previously reported. The achieved system sizes allow the closing of some particular scale gaps in, e.g. soil and petroleum rock research. Specifically, a full steady-state fluid flow simulation in a porous material, represented with an unprecedented resolution for the given sample size, is reported: the simulation is executed on a CPU-based supercomputer and the 3D geometry involves 16,3843 lattice cells (around 590 billion of them are pore sites). Using half of this sample in a benchmark simulation on a GPU-based system, a sustained computational performance of 1.77 PFLOPS is observed. These advances expose new opportunities in porous materials research. The implementation techniques here utilized are standard except for the tailored high-performance data layouts as well as the indirect addressing scheme with a low memory overhead and the truly asynchronous data communication scheme in the case of CPU and GPU code versions, respectively.
Computer Science↗
Near-continuum, hypersonic oxygen flow over a double cone simulated by direct simulation Monte Carlo informed from quantum chemistry
A large-scale, fully resolved direct simulation Monte Carlo (DSMC) computation of a non-equilibrium, reactive flow of pure oxygen over a double cone is presented. Under the simulated near-continuum conditions, the computational demands are shown to be significant because of the wide range of length scales that must be resolved. Therefore, robust grid adaption capabilities and efficient parallelization of the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code that is utilized in this work are essential. The thermochemical and transport collision models were selected for efficiency and simplicity. First-principles data, obtained from the highly accurate direct molecular simulation method, were used to inform the collision models’ parameters. Importantly, because SPARTA implements molecular collision models using collision-specific energies, the resulting macroscopic relaxation rates were evaluated a posteriori via zero-dimensional heat bath simulations. The comparisons of surface properties, namely heat flux and pressure, show very close agreement with previous computational fluid dynamics (CFD) results. Differences with the measurements were found to be similar to the CFD simulations. The unresolved discrepancy with the measurements could be due to inconsistent free stream conditions with the actual experimental data or missing physical phenomena altogether, for example atomic and molecular oxygen electronically excited states, three-dimensional effects, or more complex gas–surface interactions. As shown in this work, the advantages of obtaining a DSMC particle solution for these flows reside in the method's ability to be directly informed from first principles and to seamlessly describe internal energy non-equilibrium for all modes. With the advent of exascale computing and beyond, particle methods will be an increasingly important tool to verify the validity of physical assumptions in reduced-order models via fully resolved, experimental-scale simulations, down to the level of molecular-level distributions.
Mechanics↗
Ab Initio Molecular Dynamics Simulations of Amorphous Calcium Carbonate: Interpretation of Pair Distribution Function and X-Ray Absorption Spectroscopy Data
The structure and transformation of hydrous amorphous calcium carbonate (ACC) are key to understanding biomineralization pathways and their relationship with the properties of the resulting material. Quantitative interpretation of scattering experiments aimed at elucidating the structure of ACC is challenging, due to the amorphous nature of this material, and, therefore, requires models for the structure and the scattering physics. Here, we generate physically realistic ensembles of hydrated ACC structures and their vibrational disorder from ab initio molecular dynamics (AIMD) simulations with an emphasis on enabling the consistent interpretation of the finer details of three complementary structural probes: neutron and x-ray pair distribution experiments and x-ray absorption spectroscopy (XAS). In each case, we simulate the signal directly in reciprocal space and then manipulate it into the real-space pair distribution function (PDF) or spectrum using the same procedures for the experimental and theoretical data. Good agreement with experiment was obtained across the three techniques with the simulations accounting well for all features in the spectra. Remaining small discrepancies pointed to differences between real samples and the idealized simulated systems such as deviations from the nominal CaCO3·nH2O stoichiometry. Additionally, the simulations offered a more accurate description of the local coordination environment of calcium than previous shell-by-shell fits to spectra of synthetic ACC and classical molecular dynamics simulations. This work demonstrates that AIMD is a powerful approach for extracting detailed structural information from neutron PDF, x-ray PDF, and XAS of amorphous carbonate phases.
Prange, Micah P.↗
Clay Swelling in Dry Supercritical Carbon Dioxide: Effects of Interlayer Cations on the Structure, Dynamics, and Energetics of CO 2 Intercalation Probed by XRD, NMR, and GCMD Simulations
In situ X-ray diffraction (XRD) and nuclear magnetic resonance (NMR) experiments combined with molecular dynamics simulations using the grand canonical ensemble [grand canonical molecular dynamics (GCMD)] show that the cation size, charge, and solvation energy play critical roles in determining the interlayer expansion of smectite clay minerals when exposed to dry supercritical scCO2 (scCO2) under conditions relevant to petroleum reservoirs and geological CO2 sequestration conditions. The GCMD results show that the smectite mineral, hectorite, containing interlayer alkali and alkaline earth cations with small ionic radii and high solvation energies (e.g., Na+ and Ca2+) does not intercalate CO2 and that the fully collapsed interlayer structure is the most energetically stable configuration. With Cs+ and Ba2+, the monolayer structure is the stable configuration, and CO2 should spontaneously enter the interlayer. With Cs+, there is not even an energy barrier for CO2 intercalation, in agreement with the XRD and NMR results. 13C NMR and simulations show that the average orientation of the intercalated CO2 is with their O-C-O axes parallel to the basal clay surface and that they undergo a rapid rotation about an axis perpendicular to the main molecular axis. The simulations show that the strength of the interaction between the exchangeable cation and the clay structure dominates the intercalation energetics in dry scCO2.
Loganathan, Narasimhan (ORCID:0000000302515430)↗
Insights into Spontaneous Solid Electrolyte Interphase Formation at Magnesium Metal Anode Surface from Ab Initio Molecular Dynamics Simulations
Spontaneous chemical reactivity at multivalent (Mg, Ca, Zn, Al) electrode surfaces is critical to solid electrolyte interphase (SEI) formation, and hence, directly affects the longevity of batteries. Here, we report an investigation of the reactivity of 0.5 M Mg(TFSI)2 in 1,2-dimethoxyethane (DME) solvent at a Mg(0001) surface using ab initio molecular dynamics (AIMD) simulations and detailed Bader charge analysis. Based on the simulations, the initial degradation reactions of the electrolyte strongly depend on the structure of the Mg(TFSI)2 species near the anode surface. At the surface, the dissociation of Mg(TFSI)2 species occurs via cleavage of the N-S bond for the solvent separated ion pair (SSIP) and via cleavage of the C-S bond for the contact ion pair (CIP) configuration. In the case of the CIP, both TFSI anions undergo spontaneous bond dissociation reactions to form atomic O, C, S, F, and N species adsorbed on the surface of the Mg anode. These products indicate that the initial SEI layer formed on the surface of the pristine Mg anode consists of a complex mixture of multiple components such as oxides, carbides, sulfides, fluorides, and nitrides. We believe that the atomic level insights gained from these simulations will lay the groundwork for the rational design of tailored and functional interphases that are critical for the success of multivalent battery technology.
Agarwal, Garvit↗
Bayesian force fields from active learning for simulation of inter-dimensional transformation of stanene
Abstract We present a way to dramatically accelerate Gaussian process models for interatomic force fields based on many-body kernels by mapping both forces and uncertainties onto functions of low-dimensional features. This allows for automated active learning of models combining near-quantum accuracy, built-in uncertainty, and constant cost of evaluation that is comparable to classical analytical models, capable of simulating millions of atoms. Using this approach, we perform large-scale molecular dynamics simulations of the stability of the stanene monolayer. We discover an unusual phase transformation mechanism of 2D stanene, where ripples lead to nucleation of bilayer defects, densification into a disordered multilayer structure, followed by formation of bulk liquid at high temperature or nucleation and growth of the 3D bcc crystal at low temperature. The presented method opens possibilities for rapid development of fast accurate uncertainty-aware models for simulating long-time large-scale dynamics of complex materials.
Chemistry↗
Cognitive simulation models for inertial confinement fusion: Combining simulation and experimental data
The design space for inertial confinement fusion (ICF) experiments is vast, and experiments are extremely expensive. Researchers rely heavily on computer simulations to explore the design space in search of high-performing implosions. However, ICF multiphysics codes must make simplifying assumptions, and thus deviate from experimental measurements for complex implosions. For more effective design and investigation, simulations require input from past experimental data to better predict future performance. In this work, we describe a cognitive simulation method for combining simulation and experimental data into a common, predictive model. This method leverages a machine learning technique called “transfer learning,” the process of taking a model trained to solve one task, and partially retraining it on a sparse dataset to solve a different, but related task. In the context of ICF design, neural network models are trained on large simulation databases and partially retrained on experimental data, producing models that are far more accurate than simulations alone. Here, we demonstrate improved model performance for a range of ICF experiments at the National Ignition Facility and predict the outcome of recent experiments with less than 10% error for several key observables. We discuss how the methods might be used to carry out a data-driven experimental campaign to optimize performance, illustrating the key product—models that become increasingly accurate as data are acquired.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
How numerical simulations helped to achieve breakeven on the NIF
The inertial confinement fusion program relies upon detailed simulations with inertial confinement fusion (ICF) codes to design targets and to interpret the experimental results. These simulations treat as much physics from essential principles as is practical, including laser deposition, cross beam energy transfer, x-ray production and transport, nonlocal thermal equilibrium kinetics, thermal transport, hydrodynamic instabilities, thermonuclear burn, and transport of reaction products. Improvements in radiation hydrodynamic code capabilities and vast increases in computing power have enabled more realistic, accurate 3D simulations that treat all known asymmetry sources. We describe how numerical simulations helped to guide the program, assess the impediments to breakeven, and optimize every aspect of target design. A preshot simulation of the first National Ignition Facility experiment that surpassed breakeven predicted an increased yield that matches the experimental result, within the preshot predicted uncertainty, with a target gain of 1.5. We will cover the key developments in Lawrence Livermore National Laboratory ICF codes that enabled these simulations and give specific examples of how they helped to guide the program.
Marinak, M. M. (ORCID:0009000331127696)↗
Electronic structure simulations in the cloud computing environment
The transformative impact of modern computational paradigms and technologies, such as high-performance computing, quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages, such as NWChem, NWChemEx, SPEC, ExaChem, and FLOSIC codes on the Azure Quantum Element (AQE) Microsoft cloud services. We pay particular attention to the intricate workflows for performing composite chemistry simulations, associated data curation, and mechanisms for accuracy assessment, as defined by the enabling cloud Computational Chemistry as a Service (CCaaS). Our focus also extends to Arrows' automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities (LCFs).
computational chemistry, electronic structure, Clo↗
MAGNETOHYDRODYNAMIC EFFECTS ON PULSED YOUNG STELLAR OBJECT JETS. I. 2.5D SIMULATIONS
In this paper, we explore the dynamics of radiative axisymmetric magnetohydrodynamic (MHD) jets at high resolution using adaptive mesh refinement methods. The goal of the study is to determine both the dynamics and emission properties of such jets. To that end, we have implemented microphysics enabling us to produce synthetic maps of Hα and [S II]. The jets are pulsed either sinusoidally or randomly via a time-dependent ejection velocity which leads to a complicated structure of internal shocks and rarefactions as has been seen in previous simulations. The high resolution of our simulations allows us to explore in great detail the effect of pinch forces (due to the jet's toroidal magnetic field) within the ''working surfaces'' where pulses interact. We map the strong Hα emission marking shock fronts and the strong [S II] emission inside cooling regions behind shocks as observed with high-resolution images of jets. We find that pinch forces in the stronger field cases produce additional emission regions along the axis as compared with purely hydrodynamic runs. These simulations are a first step to understanding the full three-dimensional emission properties of radiative MHD jets.
79 ASTRONOMY AND ASTROPHYSICS↗