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At least 253 records · Page 14

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↗

SIMULATIONS OF A DYNAMIC SOLAR CYCLE AND ITS EFFECTS ON THE INTERSTELLAR BOUNDARY EXPLORER RIBBON AND GLOBALLY DISTRIBUTED ENERGETIC NEUTRAL ATOM FLUX

Since 2009, observations by the Interstellar Boundary Explorer (IBEX) have vastly improved our understanding of the interaction between the solar wind (SW) and local interstellar medium through direct measurements of energetic neutral atoms (ENAs), which inform us about the heliospheric conditions that produced them. An enhanced feature of flux in the sky, the so-called IBEX ribbon, was not predicted by any global models before the first IBEX observations. A dominating theory of the origin of the ribbon, although still under debate, is a secondary charge-exchange process involving secondary ENAs originating from outside the heliopause. According to this mechanism, the evolution of the solar cycle should be visible in the ribbon flux. Therefore, in this paper we simulate a fully time-dependent ribbon flux, as well as globally distributed flux from the inner heliosheath (IHS), using time-dependent SW parameters from Sokół et al. as boundary conditions for our time-dependent heliosphere simulation. After post-processing the results to compute H ENA fluxes, our results show that the secondary ENA ribbon indeed should be time dependent, evolving with a period of approximately 11 yr, with differences depending on the energy and direction. Our results for the IHS flux show little periodic change with the 11 yr solar cycle, but rather with short-term fluctuations in the background plasma. While the secondary ENA mechanism appears to emulate several key characteristics of the observed IBEX ribbon, it appears that our simulation does not yet include all of the relevant physics that produces the observed ribbon.

79 ASTRONOMY AND ASTROPHYSICS↗

An efficient algorithm for simulating ensembles of parameterized flow problems

Abstract Many applications of computational fluid dynamics require multiple simulations of a flow under different input conditions. In this paper, a numerical algorithm is developed to efficiently determine a set of such simulations in which the individually independent members of the set are subject to different viscosity coefficients, initial conditions and/or body forces. The proposed scheme, when applied to the flow ensemble, needs to solve a single linear system with multiple right-hand sides, and thus is computationally more efficient than solving for all the simulations separately. We show that the scheme is nonlinearly and long-term stable under certain conditions on the time-step size and a parameter deviation ratio. A rigorous numerical error estimate shows the scheme is of first-order accuracy in time and optimally accurate in space. Several numerical experiments are presented to illustrate the theoretical results.

Mathematics↗

The DESI N -body Simulation Project – II. Suppressing sample variance with fast simulations

ABSTRACT Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches $\sim 20\, h^{-3}\, \mathrm{Gpc}^{3}$. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. AbacusSummit is a suite of high-resolution dark-matter-only simulations designed for this purpose, with $200\, h^{-3}\, \mathrm{Gpc}^{3}$ (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi-N-body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. $k \lt 0.3\, h\, \mathrm{Mpc}^{-1}$ for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in AbacusSummit suite to extend the effective volume ∼20 times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data.

cosmology: theory↗

The DESI N -body simulation project – I. Testing the robustness of simulations for the DESI dark time survey

ABSTRACT Analysis of large galaxy surveys requires confidence in the robustness of numerical simulation methods. The simulations are used to construct mock galaxy catalogues to validate data analysis pipelines and identify potential systematics. We compare three N-body simulation codes, abacus, gadget-2, and swift, to investigate the regimes in which their results agree. We run N-body simulations at three different mass resolutions, 6.25 × 108, 2.11 × 109, and 5.00 × 109 h−1 M⊙, matching phases to reduce the noise within the comparisons. We find systematic errors in the halo clustering between different codes are smaller than the Dark Energy Spectroscopic Instrument (DESI) statistical error for $s\ \gt\ 20\ h^{-1}$ Mpc in the correlation function in redshift space. Through the resolution comparison we find that simulations run with a mass resolution of 2.1 × 109 h−1 M⊙ are sufficiently converged for systematic effects in the halo clustering to be smaller than the DESI statistical error at scales larger than $20\ h^{-1}$ Mpc. These findings show that the simulations are robust for extracting cosmological information from large scales which is the key goal of the DESI survey. Comparing matter power spectra, we find the codes agree to within 1 per cent for k ≤ 10 h Mpc−1. We also run a comparison of three initial condition generation codes and find good agreement. In addition, we include a quasi-N-body code, FastPM, since we plan use it for certain DESI analyses. The impact of the halo definition and galaxy–halo relation will be presented in a follow-up study.

79 ASTRONOMY AND ASTROPHYSICS↗

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. II. cosmological results

Here, we present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven 𝑤 Cold Dark Matter (𝑤⁢ CDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (𝑆 8 , Ω m ) is improved by 70% (Λ ⁢CDM) and 90% (𝑤 ⁢CDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter 𝑆 8 ≡ 𝜎 8 ⁢(Ω m /0.3) 0.5 , obtaining 𝑆 8 = 0.794 ±0.017 (Λ⁢ CDM) and 𝑆 8 = 0.817 ±0.021 (𝑤 ⁢CDM), and a ∼10% constraint on Ω m , obtaining Ω m =0.259 ±0.025 (Λ ⁢CDM) and Ω m = 0.273 ±0.029 (𝑤⁢ CDM). In the context of the 𝑤⁢ CDM scenario, these statistics also strengthen the constraints on the parameter 𝑤, obtaining 𝑤 <−0.72. The constraints from different statistics are shown to be internally consistent (with a 𝑝-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2⁢𝜎.

79 ASTRONOMY AND ASTROPHYSICS↗