Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cluster computing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Inelastic rate coefficients for collisions of C 4 H - with H 2

Carbon-chain anions were recently detected in the interstellar medium. These very reactive species are used as tracers of the physical and chemical conditions in a variety of astrophysical environments. However, the local thermodynamic equilibrium conditions are generally not fulfilled in these environments. Therefore, collisional as well as radiative rates are needed to accurately model the observed emission lines. We determine in this work the state-to-state rate coefficients of C 4 H- in collision with both ortho- and para-H 2 . A new ab initio 4D potential energy surface was computed using explicitly correlated coupled-cluster procedures. This surface was then employed to determine rotational excitation and de-excitation cross-sections and rate coefficients for the first 21 rotational levels (up to rotational level j 1 = 20) using the close-coupling method, while the coupled-state approximation was used to extend the calculations up to j 1 = 30. State-to-state rate coefficients were obtained for the temperature range 2–100K. The differences between the ortho- and para-H 2 rate coefficients are found to be small.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Two-particle correlation functions in cluster perturbation theory: Hubbard spin susceptibilities

Cluster perturbation theory (CPT) is a computationally economic method commonly used to estimate the momentum- and energy-resolved single-particle Green's function. It has been used extensively in direct comparisons with experiments that effectively measure the single-particle Green's function, e.g., angle-resolved photoemission spectroscopy. However, many experimental observables are given by two-particle correlation functions. CPT can be extended to compute two-particle correlation functions by approximately solving the Bethe-Salpeter equation. We implement this method and focus on the transverse spin susceptibility, measurable via inelastic neutron scattering or with optical probes of atomic gases in optical lattices. Finally, we benchmark the method with the one-dimensional Fermi-Hubbard model by comparing with known results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Efficient Ab initio Modeling of Random Multicomponent Alloys

Here, we present in this Letter a novel small set of ordered structures (SSOS) method that allows extremely efficient ab initio modeling of random multi-component alloys. Using inverse II-III spinel oxides and equiatomic quinary bcc (so-called high entropy) alloys as examples, we also demonstrate that a SSOS can achieve the same accuracy as a large supercell or a well-converged cluster expansion, but with significantly reduced computational cost. In particular, because of this efficiency, a large number of quinary alloy compositions can be quickly screened, leading to the identification of several new possible high entropy alloy chemistries. Furthermore, the SSOS method developed here can be broadly useful for the rapid computational design of multi-component materials, especially those with a large number of alloying elements, a challenging problem for other approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2024

COSMIC DAWN: Distributed Analysis of Wireless at Nextscale

Distributed Analysis of Wireless at Nextscale (DAWN) is a novel simulation framework for large-scale design-space exploration (DSE) of unmodified software-defined radio (SDR) applications interacting in a scalable, high-fidelity, virtual physics environment. The software-defined nature of the coupled software-physics simulation leverages hardware emulation to permit in-depth examination and modification of not only the electromagnetic environment, including each signal in flight, but also the precise state of system software and components. DAWN supports modular, customizable physics environments allowing realistic propagation effects so that computationally efficient empirical models, reduced order/surrogate models, or large-scale, high-fidelity, site-specific simulations can be used as a propagation medium based on scenario requirements. This paper introduces DAWN’s design and initial implementation, detailing key architectural components, including the Physics Realization Engine (PhyRE), Runtime Infrastructure for Simulation Environments (RISE), and the design space exploration (DSE) suite. It concludes with demonstrations using unmodified 4G/LTE software available from srsRAN on computing resources ranging from a small cluster to ORNL’s Frontier Exascale system.

Wise, Mike [ORNL] (ORCID:0000000266120641)↗
DOE OSTI2016

Data Analysis Approaches for the Risk-Informed Safety Margins Characterization Toolkit

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, RELAP-7, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually called Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, “extracting information” means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Integrating Concentrating Solar Power Technologies into the Hybrid Optimization and Performance Platform (HOPP)

As the world increases renewable energy deployment, there is an increasing interest in hybridizing various generation and storage technologies to maximize net benefit to the developer and/or off-taker. A particularly interesting combination of renewable technologies is concentrating solar power (CSP) with thermal energy storage (TES), photovoltaics (PV), and electrochemical battery energy storage (BESS). Due to the system complexity of CSP technology, it is difficult to evaluate the technological and financial performance of a CSP-PV hybrid system without detailed modeling of annual operations. To address this challenge, we have developed a modeling framework for evaluating the performance and financial viability of CSP systems hybridized with PV and battery technologies. This modeling effort incorporates CSP tower and trough systems into an existing modeling tool recently developed by NREL referred to as the Hybrid Optimization and Performance Platform (HOPP). This report outlines the modeling methodology as well as preliminary results from example case studies conducted using the model. The methodology describes: (i) the integration of CSP tower and troughs into HOPP using python interfaces to access System Advisor Model (SAM) underlining technology models, (ii) the mathematical formulation of the mixed integer linear program dispatch optimization model which optimizes operations of storage asset to either maximize system revenue or minimize operating cost while load following, (iii) the design analysis methods implemented within HOPP, and (iv) simulation clustering for the purposes of reducing computational expense. We exercise the model using a case study of a future scenario where we assume (i) CSP and PV technologies achieve the 2030 cost targets provided by the Solar Energy Technologies Office (SETO), (ii) battery costs reduce to the 2030 mid cost projection presented by NREL. Lastly, (iii) electricity prices for southern California in 2030 are provided by NREL's Cambium database, and (iv) a capacity payment of $150/kW-yr based on the system capacity factor during the to 100 net-load hours.

14 SOLAR ENERGY↗
DOE OSTI2026

Ab Initio Many Body Quantum Embedding and Local Correlation in Crystalline Materials using Interpolative Separable Density Fitting

We present an efficient implementation of ab initio many-body quantum embedding and local correlation methods for infinite periodic systems through translational symmetry adapted interpolative separable density fitting, an approach which reduces the scaling of the calculations to only linear with the number of k-points. Employing this methodology, we compute correlated ground-state coupled cluster energies within density matrix embedding and local natural orbital correlation frameworks for both weakly and strongly correlated solids, using up to 1000 k-points. By extrapolating the local correlation domains and k-point sampling we further obtain estimates of the full coupled cluster with singles, doubles, and perturbative triples ground-state energies in the thermodynamic limit.

Chemical Physics (physics.chem-ph)↗
DOE OSTI2018

MONTE CARLO NEUTRONICS ANALYSIS OF THE SNS STS MONOLITH

Neutronics analysis for the Oak Ridge National Laboratory Spallation Neutron Source second target station monolith conceptual design was performed entirely with the Monte Carlo method. It has been demonstrated that even though the monolith provides ~peta-scale attenuation of the dose rates, Monte Carlo simulations are within reach of computing capabilities of relatively inexpensive Linux clusters. Several monolith configurations achieved or exceeded design requirements and provide basis for the final design.

Remec, Igor↗
DOE OSTI2019

Monte Carlo Neutronics Analysis of the SNS STS Monolith

The neutronics analysis for the Oak Ridge National Laboratory’s Spallation Neutron Source second target station monolith conceptual design was performed entirely with the Monte Carlo method. It has been demonstrated that even though the monolith provides approximately peta-scale attenuation of the dose rates, Monte Carlo simulations are within reach of computing capabilities of relatively inexpensive Linux clusters. Several monolith configurations achieved or exceeded design requirements and provide basis for the final design.

Remec, Igor↗
DOE OSTI2016

Computational and photoelectron spectroscopic study of the dipole-bound anions, indole(H{sub 2}O){sub 1,2}{sup −}

We report our joint computational and anion photoelectron spectroscopic study of indole-water cluster anions, indole(H{sub 2}O){sub 1,2}{sup −}. The photoelectron spectra of both cluster anions show the characteristics of dipole-bound anions, and this is confirmed by our theoretical computations. The experimentally determined vertical electron detachment (VDE) energies for indole(H{sub 2}O){sub 1}{sup −} and indole(H{sub 2}O){sub 2}{sup −} are 144 meV and 251 meV, respectively. The corresponding theoretically determined VDE values for indole(H{sub 2}O){sub 1}{sup −} and indole(H{sub 2}O){sub 2}{sup −} are 124 meV and 255 meV, respectively. The vibrational features in the photoelectron spectra of these cluster anions are assigned as the vibrations of the water molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Massively parallel GPU enabled third-order cluster perturbation excitation energies for cost-effective large scale excitation energy calculations

We present here a massively parallel implementation of the recently developed CPS(D-3) excitation energy model that is based on cluster perturbation theory. The new algorithm extends the one developed in Baudin et al. [J. Chem. Phys., 150, 134110 (2019)] to leverage multiple nodes and utilize graphical processing units for the acceleration of heavy tensor contractions. Furthermore, we show that the extended algorithm scales efficiently with increasing amounts of computational resources and that the developed code enables CPS(D-3) excitation energy calculations on large molecular systems with a low time-to-solution. More specifically, calculations on systems with over 100 atoms and 1000 basis functions are possible in a few hours of wall clock time. This establishes CPS(D-3) excitation energies as a computationally efficient alternative to those obtained from the coupled-cluster singles and doubles model.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2014

Giant and pigmy dipole resonances in 4 He, 16,22 O, and 40 Ca from chiral nucleon-nucleon interactions

We combine the coupled-cluster method and the Lorentz integral transform for the computation of inelastic reactions into the continuum. We show that the bound-state-like equation characterizing the Lorentz integral transform method can be reformulated based on extensions of the coupled-cluster equation-of-motion method, and we discuss strategies for viable numerical solutions. Starting from a chiral nucleon-nucleon interaction at next-to-next-to-next-to-leading order, we compute the giant dipole resonances of 4 He, 16,22 O, and 40 Ca, truncating the coupled-cluster equation-of-motion method at the two-particle–two-hole excitation level. Within this scheme, we find a low-lying E1 strength in the neutron-rich 22 O nucleus, which compares fairly well with data from Leistenschneider et al. [Phys. Rev. Lett. 86, 5442 (2001)]. We also compute the electric dipole polarizability in 40 Ca. Deficiencies of the employed Hamiltonian lead to overbinding, too-small charge radii, and a too-small electric dipole polarizability in 40 Ca.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Low oxidation state aluminum-containing cluster anions: Cp{sup ∗}Al{sub n}H{sup −}, n = 1–3

Three new, low oxidation state, aluminum-containing cluster anions, Cp*Al{sub n}H{sup −}, n = 1–3, were prepared via reactions between aluminum hydride cluster anions, Al{sub n}H{sub m}{sup −}, and Cp*H ligands. These were characterized by mass spectrometry, anion photoelectron spectroscopy, and density functional theory based calculations. Agreement between the experimentally and theoretically determined vertical detachment energies and adiabatic detachment energies validated the computed geometrical structures. Reactions between aluminum hydride cluster anions and ligands provide a new avenue for discovering low oxidation state, ligated aluminum clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Clustering and α-capture reaction rate from ab initio 20 Ne

We introduce a new framework for studying clustering and for calculating α partial widths using ab initio wave functions. We demonstrate the formalism for 20 Ne, by calculating the overlap between the 16 O + α cluster configuration and states in 20 Ne computed in the ab initio symmetry-adapted no-core shell model. We present spectroscopic amplitudes and spectroscopic factors, and compare those to no-core symplectic shell-model results in larger model spaces, to gain insight into the underlying physics that drives α clustering. Specifically, we report on the α partial width of the lowest 1 – resonance in 20 Ne, which is found to be in good agreement with experiment.We also present first no-core shell-model estimates for asymptotic normalization coefficients for the ground state, as well as for the first excited 4 + state in 20 Ne that lies in a close proximity to the α + 16 O threshold. This outcome highlights the importance of correlations for developing cluster structures and for describing α widths. The widths can then be used to calculate α-capture reaction rates for narrow resonances of interest to astrophysics. Finally, we explore the reaction rate for the α-capture reaction 16 O(α, γ ) 20 Ne at astrophysically relevant temperatures and determine its impact on simulated x-ray burst abundances.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis

As the market for cloud computing continues to grow, an increasing number of users are deploying applications as microservices. The shift introduces unique challenges in identifying and addressing performance issues, particularly within large and complex infrastructures. To address this challenge, we propose a methodology that unveils temporal performance deviations in microservices by clustering containers based on their performance characteristics at different time intervals. Showcasing our methodology on the Alibaba dataset, we found both stable and dynamic performance patterns, providing a valuable tool for enhancing overall performance and reliability in modern application landscapes.

Clustering↗
DOE OSTI2022

Computational Estimation by Scientific Data Mining with Classical Methods to Automate Learning Strategies of Scientists

Experimental results are often plotted as 2-dimensional graphical plots (aka graphs) in scientific domains depicting dependent versus independent variables to aid visual analysis of processes. Repeatedly performing laboratory experiments consumes significant time and resources, motivating the need for computational estimation. The goals are to estimate the graph obtained in an experiment given its input conditions, and to estimate the conditions that would lead to a desired graph. Existing estimation approaches often do not meet accuracy and efficiency needs of targeted applications. We develop a computational estimation approach called AutoDomainMine that integrates clustering and classification over complex scientific data in a framework so as to automate classical learning methods of scientists. Knowledge discovered thereby from a database of existing experiments serves as the basis for estimation. Challenges include preserving domain semantics in clustering, finding matching strategies in classification, striking a good balance between elaboration and conciseness while displaying estimation results based on needs of targeted users, and deriving objective measures to capture subjective user interests. These and other challenges are addressed in this work. The AutoDomainMine approach is used to build a computational estimation system, rigorously evaluated with real data in Materials Science. Our evaluation confirms that AutoDomainMine provides desired accuracy and efficiency in computational estimation. It is extendable to other science and engineering domains as proved by adaptation of its sub-processes within fields such as Bioinformatics and Nanotechnology.

Computer Science↗
DOE OSTI2018

Microscopic optical potentials for calcium isotopes

We construct nucleonic microscopic optical potentials by combining the Green's function approach with the coupled-cluster method for 40 Ca and 48 Ca. For the computation of the ground states of 40 Ca and 48 Ca, we use the coupled-cluster method in the singles-and-doubles approximation, while for the A = ±1 nuclei we use particle-attached and particle-removed equation-of-motion method truncated at two-particle–one-hole and one-particle–two-hole excitations, respectively. Our calculations are based on the chiral nucleon-nucleon and three-nucleon interaction NNLO sat , which reproduces the charge radii of 40 Ca and 48 Ca, and the chiral nucleon-nucleon interaction NNLO opt . In all cases considered here, we observe that the overall form of the neutron scattering cross section is reproduced for both interactions, but the imaginary part of the potential, which reflects the loss of flux in the elastic channel, is negligible. Furthermore, the latter points to neglected many-body correlations that would appear beyond the coupled-cluster truncation level considered in this work. We show that, by artificially increasing the parameter η in the Green's function, practical results can be further improved.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

The molecular dipole moment ( μ ) is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra as well as induction and long-range electrostatic interactions. Furthermore, it can be extracted directly—via the ground state electron density—from high-level quantum mechanical calculations, making it an ideal target for machine learning (ML). Here, we choose to represent this quantity with a physically inspired ML model that captures two distinct physical effects: local atomic polarization is captured within the symmetry-adapted Gaussian process regression framework which assigns a (vector) dipole moment to each atom, while the movement of charge across the entire molecule is captured by assigning a partial (scalar) charge to each atom. The resulting “MuML” models are fitted together to reproduce molecular μ computed using high-level coupled-cluster theory and density functional theory (DFT) on the QM7b dataset, achieving more accurate results due to the physics-based combination of these complementary terms. The combined model shows excellent transferability when applied to a showcase dataset of larger and more complex molecules, approaching the accuracy of DFT at a small fraction of the computational cost. We also demonstrate that the uncertainty in the predictions can be estimated reliably using a calibrated committee model. The ultimate performance of the models—and the optimal weighting of their combination—depends, however, on the details of the system at hand, with the scalar model being clearly superior when describing large molecules whose dipole is almost entirely generated by charge separation. These observations point to the importance of simultaneously accounting for the local and non-local effects that contribute to μ ; furthermore, they define a challenging task to benchmark future models, particularly those aimed at the description of condensed phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗