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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

General framework for calculating spin–orbit couplings using spinless one-particle density matrices: Theory and application to the equation-of-motion coupled-cluster wave functions

Standard implementations of nonrelativistic excited-state calculations compute only one component of spin multiplets (i.e., Ms = 0 triplets); however, matrix elements for all components are necessary for deriving spin-dependent experimental observables. Wigner–Eckart’s theorem allows one to circumvent explicit calculations of all multiplet components. We generate all other spin–orbit matrix elements by applying Wigner–Eckart’s theorem to a reduced one-particle transition density matrix computed for a single multiplet component. In addition to computational efficiency, this approach also resolves the phase issue arising within Born–Oppenheimer’s separation of nuclear and electronic degrees of freedom. A general formalism and its application to the calculation of spin–orbit couplings using equation-of-motion coupled-cluster wave functions are presented. The two-electron contributions are included via the mean-field spin–orbit treatment. Intrinsic issues of constructing spin–orbit mean-field operators for open-shell references are discussed, and a resolution is proposed. The method is benchmarked by using several radicals and diradicals. The merits of the approach are illustrated by a calculation of the barrier for spin inversion in a high-spin tris(pyrrolylmethyl)amine Fe(II) complex.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Self-Consistent Charge Density-Functional Tight-Binding Parametrization for Pt–Ru Alloys

In this paper, we present a self-consistent charge density-functional tight-binding (SCC-DFTB) parametrization for PtRu alloys, which is developed by employing a training set of alloy cluster energies and forces obtained from Kohn–Sham density-functional theory (DFT) calculations. Extensive simulations of a testing set of PtRu alloy nanoclusters show that this SCC-DFTB scheme is capable of capturing cluster formation energies with high accuracy relative to DFT calculations. The new SCC-DFTB parametrization is employed within a genetic algorithm to search for global minima of PtRu clusters in the range of 13–81 atoms and the emergence of Ru-core/Pt-shell structures at intermediate alloy compositions, consistent with known results, is systematically demonstrated. Our new SCC-DFTB parametrization enables computationally inexpensive and accurate modeling of Pt–Ru clusters that are among the best-performing catalysts in numerous energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The many-body expansion for aqueous systems revisited: II. Alkali metal and halide ion – water interactions

We present a detailed study of the Many-Body Expansion (MBE) for alkali metal and halide ion-water interactions and quantify the effect of these ions on the strength of the surrounding aqueous hydrogen bonding environment. Building on our previous work on neutral water clusters [J. P. Heindel and S. S. Xantheas, J. Chem. Theor. Comput. 16 (11), 6843–6855 (2020)], we carry out the complete MBE for ion-water clusters, Z+/-(H2O)9, where Z = Li+, K+, Cs+, Cl-, Br-, I- and compare with the results for (H2O)10. The 2-B ion-water (I-W) interaction represents a larger percentage of the total cluster binding energy compared to a pure water cluster of the same size with the total 3-B term being smaller and of opposite sign (repulsive) whereas higher order terms are essentially negligible. The same oscillating behavior around zero for MBE terms higher than the 5-B with basis set that was reported for water clusters is also observed for the ion-water clusters considered with Basis Set Superposition Error (BSSE) corrections amending this like in the water cluster case. A remarkable, linear anti-correlation between the total 2-B ion-water and the total 2-B and 3-B water-water interactions is found, quantifying the effect of the different ions in disrupting and altering (weakening) the neighboring hydrogen bonded water network. Our results suggest a universal behavior of the two different families of ions (alkali metals and halides) for both the correlations of the various components of the total binding energies as well as the estimate of the 2-B BSSE correction which is reported to follow a common profile for ion-water and water-water interactions when cast in terms of reduced distances and energies. We expect our insights into the nature of BSSE will be important for future ab initio based, many-body molecular dynamics studies.

ion-water interactions, water-water interaction, m↗
DOE OSTI2014

Ab-initio coupled-cluster effective interactions for the shell model: Application to neutron-rich oxygen and carbon isotopes

We derive and compute effective valence-space shell-model interactions from ab initio coupled-cluster theory and apply them to open-shell and neutron-rich oxygen and carbon isotopes. Our shell-model interactions are based on nucleon-nucleon and three-nucleon forces from chiral effective-field theory. We compute the energies of ground and low-lying states, and find good agreement with experiment. In particular, our computed 2 + states are consistent with N=14,16 shell closures in 22,24 O, and a weaker N=14 shell closure in 20 C. We find good agreement between our coupled-cluster effective-interaction results with those obtained from standard single-reference coupled-cluster calculations for up to eight valence neutrons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Computational multiphysics modeling of radioactive aerosol deposition in diverse human respiratory tract geometries

The evaluation of aerosol exposure relies on generic mathematical models that assume uniform particle deposition profiles over the human respiratory tract and do not account for subject-specific characteristics. Here we introduce a hybrid-automated computational workflow that generates personalized particle deposition profiles in 3D reconstructed human airways from computed tomography scans using Computational Fluid and Particle Dynamics simulations. This is the first large-scale study to consider realistic airways variability, where 380 lower and 40 upper human respiratory tract 3D geometries are reconstructed and parameterized. The data is clustered into nine groups using random forest regression. Computational fluid and particle dynamics simulations are conducted on these representative geometries using a realistic heavy-breathing respiratory cycle and radioactive iodine-131 as a source term. Monte Carlo radiation transport simulations are performed to obtain detailed energy deposition maps. Our findings emphasize the importance of personalized studies, as minor respiratory tract variations notably influence deposition patterns rather than global parameters of the lower airways, observing more than 30% variance in the mass deposition fraction.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Single-size and cluster dynamics modeling of intra-granular fission gas bubbles in UO 2

For this work, we perform simulations of intra-granular fission gas bubble evolution in UO 2 using both a relatively simple, computationally inexpensive single-size model and a detailed cluster dynamics model. Simulations encompass 36 experimental cases from 4 different databases, covering various temperature and burnup levels. We systematically compare results from the two models to each other and to post-irradiation experimental data of bubble average size and number density. Overall, the model-to-model comparisons reveal an excellent agreement across the set of simulations. This outcome indicates that, in spite of the underlying assumptions, the single-size model provides a good approximation of the complex physical behavior that is more rigorously described by the cluster dynamics model. Qualitatively, both models reproduce the trends of the experimental data with temperature and burnup correctly. Quantitatively, calculated results are either in good agreement with the data or within errors that appear consistent with the inherent uncertainties. Moreover, for the single-size model, we demonstrate and assess a multiscale approach whereby values for the fission gas atom diffusion coefficient from separate atomistic calculations are used. Systematic comparisons to experimental data point out a credible accuracy of the multiscale model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

The velocity distribution function of galaxy clusters as a cosmological probe

We present a new approach for quantifying the abundance of galaxy clusters and constraining cosmological parameters using dynamical measurements. In the standard method, galaxy line-of-sight velocities, v, or velocity dispersions are used to infer cluster masses, M, to quantify the halo mass function (HMF), dn(M)/dlog(M), which is strongly affected by mass measurement errors. In our new method, the probability distributions of velocities for each cluster in the sample are summed to create a new statistic called the velocity distribution function (VDF), dn(v)/dv. The VDF can be measured more directly and precisely than the HMF and can be robustly predicted with cosmological simulations that capture the dynamics of subhalos or galaxies. We apply these two methods to realistic (ideal) mock cluster catalogs with (without) interlopers and forecast the bias and constraints on the matter density parameter Ω{sub m} and the amplitude of matter fluctuations σ{sub 8} in flat ΛCDM cosmologies. For an example observation of 200 massive clusters, the VDF with (without) interloping galaxies constrains the parameter combination σ{sub 8} Ω{sub m}{sup 0.29(0.29)}=0.589±0.014 (0.584±0.011) and shows only minor bias. However, the HMF with interlopers is biased to low Ω{sub m} and high σ{sub 8} and the fiducial model lies well outside of the forecast constraints, prior to accounting for Eddington bias. When the VDF is combined with constraints from the cosmic microwave background, the degeneracy between cosmological parameters can be significantly reduced. Upcoming spectroscopic surveys that probe larger volumes and fainter magnitudes will provide clusters for applying the VDF as a cosmological probe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Contributions to the NUCLEI SciDAC-3 Project

This is the Final Report for Michigan State University for the NUCLEI SciDAC-3 project. The NUCLEI project, as defined by the scope of work, has developed, implemented and run codes for large-scale computations of many topics in low-energy nuclear physics. Physics studied included the properties of nuclei and nuclear decays, nuclear structure and reactions, and the properties of nuclear matter. The computational techniques used included Configuration Interaction, Coupled Cluster, and Density Functional methods. The research program emphasized areas of high interest to current and possible future DOE nuclear physics facilities, including ATLAS at ANL and FRIB at MSU (nuclear structure and reactions, and nuclear astrophysics), TJNAF (neutron distributions in nuclei, few body systems, and electroweak processes), NIF (thermonuclear reactions), MAJORANA and FNPB (neutrinoless double-beta decay and physics beyond the Standard Model), and LANSCE (fission studies).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

VERA Benchmarking Results for Watts Bar Nuclear Plant Unit 1 Cycles 1-12

Among the most important accomplishments during Phase 1 of the Consortium for Advanced Simulation of Light Water Reactors (CASL) is the development and deployment of what is known as VERA-CS, the steady-state nuclear reactor core simulation capability of the Virtual Environment for Reactor Applications, VERA. With this product CASL now has the ability to perform and support analyses relating to common evolutions of operating commercial pressurized water reactors (PWRs), including startup testing, power escalation, fuel cycle depletion, and fuel assembly discharge, reinsert, and shuffling. VERA-CS is a high-fidelity, multi-physics engineering tool that utilizes modest high-performance computing (HPC) systems and engineering-scale clusters to simultaneously simulate the local fuel rod neutronics and coolant channel thermal-hydraulics over the life of the reactor. Though it is still under development, the results demonstrated in this report provide encouraging evidence that VERA-CS will become highly acclaimed for industrial, scientific, and educational applications alike.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Modeling Clustered DNA Damage by Ionizing Radiation Using Multinomial Damage Probabilities and Energy Imparted Spectra

Simple and complex clustered DNA damage represent the critical initial damage caused by radiation. In this paper, a multinomial probability model of clustered damage is developed with probabilities dependent on the energy imparted to DNA and surrounding water molecules. The model consists of four probabilities: (A) direct damage of sugar-phosphate moieties leading to SSB, (B) OH− radical formation with subsequent SSB and BD formation, (C) direct damage to DNA bases, and (D) energy imparted to histone proteins and other molecules in a volume not leading to SSB or BD. These probabilities are augmented by introducing probabilities for the relative location of SSB using a ≤10 bp criteria for a double-strand break (DSB) and for the possible success of a radical attack that leads to SSB or BD. Model predictions for electrons, 4He, and 12C ions are compared to the experimental data and show good agreement. Thus, the developed model allows an accurate and rapid computational method to predict simple and complex clustered DNA damage as a function of radiation quality and to explore the resulting challenges to DNA repair.

Biochemistry & Molecular Biology↗
DOE OSTI2024

The SRG/eROSITA All-Sky Survey: Exploring halo assembly bias with X-ray-selected superclusters

Numerical simulations indicate that the clustering of dark matter halos is not only dependent on the halo masses but has a secondary dependence on other properties, such as the assembly history of the halo. This phenomenon, known as the halo assembly bias (HAB), has been found mostly on galaxy scales; observational evidence on larger scales is scarce. In this work, we propose a novel method for exploring HAB on cluster scales using large samples of superclusters. Leveraging the largest-ever X-ray galaxy cluster and supercluster samples obtained from the first SRG/eROSITA all-sky survey, we constructed two subsamples of galaxy clusters that consist of supercluster members and isolated clusters, respectively. After correcting for the selection effects on redshift, mass, and survey depth, we computed the excess in the concentration of the intracluster gas of isolated clusters with respect to supercluster members, defined as δc gas ≡ c gas , ISO /c gas , SC –1 , to investigate the environmental effect on the concentration of clusters, a sign of HAB on cluster scales. We find that the average gas mass concentration of isolated clusters is a few percent higher than that of supercluster members, with a maximum significance of 2.8σ. The result for δc gas varies with the overdensity ratio, f, in supercluster identification, cluster mass proxies, and mass and redshift ranges but remains positive in almost all the measurements. We measure slightly larger δc gas when adopting a higher f for supercluster identification. The δc gas is also higher for low-mass and low-redshift clusters. We performed weak lensing analyses to compare the total mass concentration of the two classes and find a similar trend in total mass concentration as obtained from the gas mass concentration. Our results are consistent with the prediction of HAB on cluster scales, where halos located in denser environments are less concentrated; this trend is stronger for halos with lower masses and at lower redshifts. These phenomena can be explained by the fact that clusters in denser environments, such as superclusters, have experienced more mergers than isolated clusters in their assembling history. This work paves the way to explore HAB with X-ray superclusters and demonstrates that large samples of superclusters with X-ray and weak-lensing data can advance our understanding of the evolution of the large-scale structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

A Dynamical Model for Clustered Star Formation in the Galactic Disk

The clustered nature of star formation should produce a high degree of structure in the combined phase and chemical space in the Galactic disk. To date, observed structure of this kind has been mostly limited to bound clusters and moving groups. In this paper, we present a new dynamical model of the Galactic disk that takes into account the clustered nature of star formation. This model predicts that the combined phase and chemical space is rich in substructure and that this structure is sensitive to both the precise nature of clustered star formation and the large-scale properties of the Galaxy. The model self-consistently evolves 4 billion stars over the last 5 Gyr in a realistic potential that includes an axisymmetric component, a bar, spiral arms, and giant molecular clouds. All stars are born in clusters with an observationally motivated range of initial conditions. As direct N-body calculations for billions of stars are computationally infeasible, we have developed a method of initializing star cluster particles to mimic the effects of direct N-body effects, while the actual orbit integrations are treated as test particles within the analytic potential. We demonstrate that the combination of chemical and phase space information is much more effective at identifying truly conatal populations than either chemical or phase space alone. Furthermore, we show that comoving pairs of stars are very likely to be conatal if their velocity separation is <2 km s -1 and their metallicity separation is <0.05 dex. The results presented here bode well for harnessing the synergies between Gaia and spectroscopic surveys to reveal the assembly history of the Galactic disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

aphBO-2GP-3B: a budgeted asynchronous parallel multi-acquisition functions for constrained Bayesian optimization on high-performing computing architecture

High-fidelity complex engineering simulations are often predictive, but also computationally expensive and often require substantial computational efforts. The mitigation of computational burden is usually enabled through parallelism in high-performance cluster (HPC) architecture. Optimization problems associated with these applications is a challenging problem due to the high computational cost of the high-fidelity simulations. In this paper, an asynchronous parallel constrained Bayesian optimization method is proposed to efficiently solve the computationally expensive simulation-based optimization problems on the HPC platform, with a budgeted computational resource, where the maximum number of simulations is a constant. The advantage of this method are three-fold. Firstly, the efficiency of the Bayesian optimization is improved, where multiple input locations are evaluated parallel in an asynchronous manner to accelerate the optimization convergence with respect to physical runtime. This efficiency feature is further improved so that when each of the inputs is finished, another input is queried without waiting for the whole batch to complete. Second, the proposed method can handle both known and unknown constraints. Third, the proposed method samples several acquisition functions based on their rewards using a modified GP-Hedge scheme. The proposed framework is termed aphBO-2GP-3B, which means asynchronous parallel hedge Bayesian optimization with two Gaussian processes and three batches. The numerical performance of the proposed framework aphBO-2GP-3B is comprehensively benchmarked using 16 numerical examples, compared against other 6 parallel Bayesian optimization variants and 1 parallel Monte Carlo as a baseline, and demonstrated using two real-world high-fidelity expensive industrial applications. The first engineering application is based on finite element analysis (FEA) and the second one is based on computational fluid dynamics (CFD) simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Clustering of CODEX clusters

The clustering of galaxy clusters links the spatial nonuniformity of dark matter halos to the growth of the primordial spectrum of perturbations. The amplitude of the clustering signal is widely used to estimate the halo mass of astrophysical objects. The advent of cluster mass calibrations enables using clustering in cosmological studies. Aims. We analyze the autocorrelation function of a large contiguous sample of galaxy clusters, the Constrain Dark Energy with X-ray (CODEX) sample, in which we take particular care of cluster definition. These clusters were X-ray selected using the ROentgen SATellite All-Sky Survey and then identified as galaxy clusters using the code redMaPPer run on the photometry of the Sloan Digital Sky Survey. We develop methods for precisely accounting for the sample selection effects on the clustering and demonstrate their robustness using numerical simulations. Methods. Using the clean CODEX sample, which was obtained by applying a redshift-dependent richness selection, we computed the two-point autocorrelation function of galaxy clusters in the 0.1 < z < 0.3 and 0.3 < z < 0.5 redshift bins. We compared the bias in the measured correlation function with values obtained in numerical simulations using a similar cluster mass range. Results. By fitting a power law, we measured a correlation length r 0 = 18.7 ± 1.1 and slope γ = 1.98 ± 0.14 for the correlation function in the full redshift range. By fixing the other cosmological parameters to their nine-year Wilkinson Microwave Anisotropy Probe values, we reproduced the observed shape of the correlation function under the following cosmological conditions: Ω m0 = $0.22_{-0.03}^{+0.04}$ and S 8 = σ 8 (Ω m0 /0.3)0.5 = $0.85_{-0.08}^{+0.10}$ with estimated additional systematic errors of σ Ω m0 = 0.02 and σS 8 = 0.20. We illustrate the complementarity of clustering constraints by combining them with CODEX cosmological constraints based on the X-ray luminosity function, deriving Ωm = 0.25 ± 0.01 and σ 8 = $0.81_{-0.02}^{+0.01}$ with an estimated additional systematic error of σ Ω m0 = 0.07 and σ σ8 = 0.04. The mass calibration and statistical quality of the mass tracers are the dominant source of uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

PluginPlay: Enabling exascale scientific software one module at a time

For many computational chemistry packages, being able to efficiently and effectively scale across an exascale cluster is a heroic feat. Collective experience from the Department of Energy’s Exascale Computing Project suggests that achieving exascale performance requires far more planning, design, and optimization than scaling to petascale. In many cases, entire rewrites of software are necessary to address fundamental algorithmic bottlenecks. This in turn requires a tremendous amount of resources and development time, resources that cannot reasonably be afforded by every computational science project. It thus becomes imperative that computational science transition to a more sustainable paradigm. Key to such a paradigm is modular software. While the importance of modular software is widely recognized, what is perhaps not so widely appreciated is the effort still required to leverage modular software in a sustainable manner. The present manuscript introduces PluginPlay, https://github.com/NWChemEx-Project/PluginPlay, an inversion-of-control framework designed to facilitate developing, maintaining, and sustaining modular scientific software packages. Here this manuscript focuses on the design aspects of PluginPlay and how they specifically influence the performance of the resulting package. Although, PluginPlay serves as the framework for the NWChemEx package, PluginPlay is not tied to NWChemEx or even computational chemistry. We thus anticipate PluginPlay to prove to be a generally useful tool for a number of computational science packages looking to transition to the exascale.

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

Electromagnetic reactions from coupled-cluster theory

We review recent results for electromagnetic reactions and related sum rules in light and medium-mass nuclei obtained from coupled-cluster theory. In particular, we highlight our recent computations of the photodisintegration cross section of 40Ca and of the electric dipole polarizability for oxygen and calcium isotopes. We also provide new results for the Coulomb sum rule for 4He and 16O. For 4He we perform a thorough comparison of coupled-cluster theory with exact hyperspherical harmonics.

Bacca, Sonia↗
DOE OSTI2025

Multi-fidelity learning for interatomic potentials: low-level forces and high-level energies are all you need

The promise of machine learning interatomic potentials (MLIPs) has led to an abundance of public quantum mechanical (QM) training datasets. The quality of an MLIP is directly limited by the accuracy of the energies and atomic forces in the training dataset. Unfortunately, most of these datasets are computed with relatively low-accuracy QM methods, e.g. density functional theory with a moderate basis set. Due to the increased computational cost of more accurate QM methods, e.g. coupled-cluster theory with a complete basis set (CBS) extrapolation, most high-accuracy datasets are much smaller and often do not contain atomic forces. The lack of high-accuracy atomic forces is quite troubling, as training with force data greatly improves the stability and quality of the MLIP compared to training to energy alone. Because most datasets are computed with a unique level of theory, traditional single-fidelity (SF) learning is not capable of leveraging the vast amounts of published QM data. In this study, we apply multi-fidelity learning (MFL) to train an MLIP to multiple QM datasets of different levels of accuracy, i.e. levels of fidelity. Specifically, we perform three test cases to demonstrate that MFL with both low-level forces and high-level energies yields an extremely accurate MLIP—far more accurate than a SF MLIP trained solely to high-level energies and almost as accurate as a SF MLIP trained directly to high-level energies and forces. Therefore, MFL greatly alleviates the need for generating large and expensive datasets containing high-accuracy atomic forces and allows for more effective training to existing high-accuracy energy-only datasets. Indeed, low-accuracy atomic forces and high-accuracy energies are all that are needed to achieve a high-accuracy MLIP with MFL.

36 MATERIALS SCIENCE↗