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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Qubit coupled cluster singles and doubles variational quantum eigensolver ansatz for electronic structure calculations

Variational quantum eigensolver (VQE) for electronic structure calculations is believed to be one major potential application of near term quantum computing. Among all proposed VQE algorithms, the unitary coupled cluster singles and doubles excitations (UCCSD) VQE ansatz has achieved high accuracy and received a lot of research interest. However, the UCCSD VQE based on fermionic excitations needs extra terms for the parity when using Jordan–Wigner transformation. Here we introduce a new VQE ansatz based on the particle preserving exchange gate to achieve qubit excitations. The proposed VQE ansatz has gate complexity up-bounded to O ( n 4 ) for all-to-all connectivity where n is the number of qubits of the Hamiltonian. Numerical results of simple molecular systems such as BeH 2 , H 2 O, N 2 , H 4 and H 6 using the proposed VQE ansatz gives very accurate results within errors about 10 -3 Hartree.

Physics↗
DOE OSTI2024

Learning From User Behavior: A Survey-Assist Algorithm for Longitudinal Mobility Data Collection

GPS-based travel surveys are widely used in mobility studies to gather crucial qualitative data, like purpose, transportation mode and replaced mode. However, survey response still poses a burden to users, especially in long-term mobility studies, leading to response fatigue. We explore a survey-assist strategy to ease this burden by a novel, user-level modeling approach that leverages past responses from each user to predict responses for new trips, without relying on external data sources like GIS data. We investigate three main algorithms for predicting responses: (i) clustering trips and extrapolating responses for similar trips, (ii) using random forest classification, and (iii) clustering that uses a hybrid algorithm to determine spatial structure, which is then fed as input to a classic random forest classifier. The clustering approach can flexibly predict responses for even complex qualitative survey questions; it achieved F-scores of 65%. The random forest pipeline uses architecture that restricts it to predicting three predetermined survey questions: trip purpose, mode, and replaced mode. However, it achieved F-scores of 78%. While the survey-assist approach has been implemented by several proprietary systems, to our knowledge, this is the first exploration in the academic literature. It follows that this is also the first rigorous evaluation of multiple algorithms that can implement the approach. The evaluation uses a large scale, publicly available, longitudinal dataset consisting of ~ 92k trips from 235 users over a period of roughly one and a half years. With this approach, travel surveys can be pre-filled with the predicted responses for each trip, thus streamlining the survey process for users. Combined with an active learning system that requests user input on low-confidence predictions, models can be updated and improved over time to better support the long-term collection of longitudinal qualitative data.

clustering↗
DOE OSTI2016

Geometries, Binding Energies, Ionization Potentials, and Electron Affinities of Metal Clusters: Mg n 0, ± 1 , n = 1–7

Equilibrium geometries, binding energies, adiabatic ionization potentials, and adiabatic electron affinities for neutral and singly charged magnesium clusters, Mg n 0, ± 1 , n = 1–7, have been computed using 39 exchange-correlation (XC) functionals in Kohn–Sham density functional theory and several coupled-cluster methods with single, double, and triple excitations, including CCSD(T) for all species, CCSD(2)T and CR-CC(2,3) for species with n = 1–3, and CCSDt, CC(t;3), and CCSDT for species with n = 1 and 2. We have used augmented polarized–valence and polarized–core–valence correlation-consistent basis sets. We have found that the geometry and binding energy of the weakly bound Mg 2 dimer requires a robust treatment of connected triple excitations, represented in this work by the CR-CC(2,3), CC(t;3), and full CCSDT methods, which are more accurate than the popular quasi-perturbative CCSD(T) approximation, but CCSD(T) is sufficiently accurate to be applied to other Mg clusters. We have also demonstrated that for all Mg clusters examined in this study, hybrid XC functionals generally have higher accuracy than local ones, with PW6B95, SOGGA11-X, M11, and PWB6K being the most accurate, both for the geometries and for the binding energies, ionization potentials, and electron-detachment energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

The OSG Open Facility: an on-ramp for opportunistic scientific computing

The Open Science Grid (OSG) is a large, robust computing grid that started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero, but has evolved in recent years to a much larger user and resource platform. In addition to meeting the US LHC community’s computational needs, the OSG continues to be one of the largest providers of distributed high-throughput computing (DHTC) to researchers from a wide variety of disciplines via the OSG Open Facility. The Open Facility consists of OSG resources that are available opportunistically to users other than resource owners and their collaborators. In the past two years, the Open Facility has doubled its annual throughput to over 200 million wall hours. More than half of these resources are used by over 100 individual researchers from over 60 institutions in fields such as biology, medicine, math, economics, and many others. Over 10% of these individual users utilized in excess of 1 million computational hours each in the past year. The largest source of these cycles is temporary unused capacity at institutions affiliated with US LHC computational sites. An increasing fraction, however, comes from university HPC clusters and large national infrastructure supercomputers offering unused capacity. Such expansions have allowed the OSG to provide ample computational resources to both individual researchers and small groups as well as sizable international science collaborations such as LIGO, AMS, IceCube, and sPHENIX. Opening up access to the Fermilab FabrIc for Frontier Experiments (FIFE) project has also allowed experiments such as mu2e and NOvA to make substantial use of Open Facility resources, the former with over 40 million wall hours in a year. We present how this expansion was accomplished as well as future plans for keeping the OSG Open Facility at the forefront of enabling scientific research by way of DHTC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1987

Full CI benchmark calculations for several states of the same symmetry

Full CI (FCI) wave functions are used to compute energies for several electronic states of the same symmetry for SiH2, CH2, and CH2(+). It is found that CASSCF/multireference CI wave functions yield results very similar to FCI, irrespective of whether the CASSCF MOs are optimized independently for each state or using an average of the CASSCF energies for all desired states. The ionization potentials and excitation energies obtained from the FCI calculations should help calibrate methods (such as Green's function approaches, equations of motion and propagator methods, and cluster expansions) in which energy differences are computed directly.

Bauschlicher, Charles W., Jr.↗
DOE OSTI2015

Ternary alloy material prediction using genetic algorithm and cluster expansion

This thesis summarizes our study on the crystal structures prediction of Fe-V-Si system using genetic algorithm and cluster expansion. Our goal is to explore and look for new stable compounds. We started from the current ten known experimental phases, and calculated formation energies of those compounds using density functional theory (DFT) package, namely, VASP. The convex hull was generated based on the DFT calculations of the experimental known phases. Then we did random search on some metal rich (Fe and V) compositions and found that the lowest energy structures were body centered cube (bcc) underlying lattice, under which we did our computational systematic searches using genetic algorithm and cluster expansion. Among hundreds of the searched compositions, thirteen were selected and DFT formation energies were obtained by VASP. The stability checking of those thirteen compounds was done in reference to the experimental convex hull. We found that the composition, 24-8-16, i.e., Fe 3 VSi 2 is a new stable phase and it can be very inspiring to the future experiments.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Leveraging the Cloud for Robust and Efficient Lunar Image Processing

The Lunar Mapping and Modeling Project (LMMP) is tasked to aggregate lunar data, from the Apollo era to the latest instruments on the LRO spacecraft, into a central repository accessible by scientists and the general public. A critical function of this task is to provide users with the best solution for browsing the vast amounts of imagery available. The image files LMMP manages range from a few gigabytes to hundreds of gigabytes in size with new data arriving every day. Despite this ever-increasing amount of data, LMMP must make the data readily available in a timely manner for users to view and analyze. This is accomplished by tiling large images into smaller images using Hadoop, a distributed computing software platform implementation of the MapReduce framework, running on a small cluster of machines locally. Additionally, the software is implemented to use Amazon's Elastic Compute Cloud (EC2) facility. We also developed a hybrid solution to serve images to users by leveraging cloud storage using Amazon's Simple Storage Service (S3) for public data while keeping private information on our own data servers. By using Cloud Computing, we improve upon our local solution by reducing the need to manage our own hardware and computing infrastructure, thereby reducing costs. Further, by using a hybrid of local and cloud storage, we are able to provide data to our users more efficiently and securely. 12 This paper examines the use of a distributed approach with Hadoop to tile images, an approach that provides significant improvements in image processing time, from hours to minutes. This paper describes the constraints imposed on the solution and the resulting techniques developed for the hybrid solution of a customized Hadoop infrastructure over local and cloud resources in managing this ever-growing data set. It examines the performance trade-offs of using the more plentiful resources of the cloud, such as those provided by S3, against the bandwidth limitations such use encounters with remote resources. As part of this discussion this paper will outline some of the technologies employed, the reasons for their selection, the resulting performance metrics and the direction the project is headed based upon the demonstrated capabilities thus far.

Cloud Computing↗
DOE OSTI2015

A full-configuration-interaction nuclear orbital approach and application for small doped He clusters

An efficient full-configuration-interaction 'nuclear orbital' treatment was developed as a benchmark quantum-chemistry-like method to calculate, ground and excited, fermionic 'solvent' wave-functions and applied to {sup 3}He{sub N} clusters with atomic or molecular impurities [J. Chem. Phys. (Communication) 125, 221101 (2006)]. The main difficulty in handling doped {sup 3}He{sub N} clusters lies in the Fermi-Dirac nuclear statistics, the wide amplitudes of the He-dopant and He-He motions, and the hard-core He-He interaction at short distances. This paper overviews the theoretical approach and its recent applications to energetic, structural and spectroscopic aspects of different dopant-{sup 3}He{sub N} clusters. Preliminary results by using the latest version of the FCI-NO computational implementation, to bosonic Cl{sub 2}(X)-({sup 4}He){sub N} clusters, are also shown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Efficient Application of the Factorized form of the Unitary Coupled-Cluster Ansatz for the Variational Quantum Eigensolver Algorithm by Using Linear Combination of Unitaries

The variational quantum eigensolver is one of the most promising algorithms for near-term quantum computers. It has the potential to solve quantum chemistry problems involving strongly correlated electrons with relatively low-depth circuits, which are otherwise difficult to solve on classical computers. The variational eigenstate is constructed from a number of factorized unitary coupled-cluster terms applied onto an initial (single-reference) state. Current algorithms for applying one of these operators to a quantum state require a number of operations that scale exponentially with the rank of the operator. We exploit a hidden SU(2) symmetry to allow us to employ the linear combination of unitaries approach, Our Prepare subroutine uses n+2 ancilla qubits for a rank-n operator. Our Select (U) scheme uses O(n) Cnot gates. This results in a full algorithm that scales like the cube of the rank of the operator n 3 , a significant reduction in complexity for rank five or higher operators. This approach, when combined with other algorithms for lower-rank operators (when compared to the standard implementation), will make the factorized form of the unitary coupled-cluster approach much more efficient to implement on all types of quantum computers.

97 MATHEMATICS AND COMPUTING↗
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↗
NASA NTRS2013

Revisiting Scaling Relations for Giant Radio Halos in Galaxy Clusters

Many galaxy clusters host megaparsec-scale radio halos, generated by ultrarelativistic electrons in the magnetized intracluster medium. Correlations between the synchrotron power of radio halos and the thermal properties of the hosting clusters were established in the last decade, including the connection between the presence of a halo and cluster mergers. The X-ray luminosity and redshift-limited Extended GMRT Radio Halo Survey provides a rich and unique dataset for statistical studies of the halos. We uniformly analyze the radio and X-ray data for the GMRT cluster sample, and use the new Planck Sunyaev-Zel'dovich (SZ) catalog to revisit the correlations between the power of radio halos and the thermal properties of galaxy clusters. We find that the radio power at 1.4 GHz scales with the cluster X-ray (0.1-2.4 keV) luminosity computed within R(sub 500) as P(sub 1.4) approx. L(2.1+/-0.2) - 500). Our bigger and more homogenous sample confirms that the X-ray luminous (L(sub 500) > 5 × 10(exp 44) erg/s)) clusters branch into two populations-radio halos lie on the correlation, while clusters without radio halos have their radio upper limits well below that correlation. This bimodality remains if we excise cool cores from the X-ray luminosities. We also find that P(sub 1.4) scales with the cluster integrated SZ signal within R(sub 500), measured by Planck, as P(sub 1.4) approx. Y(2.05+/-0.28) - 500), in line with previous findings. However, contrary to previous studies that were limited by incompleteness and small sample size, we find that "SZ-luminous" Y(sub 500) > 6×10(exp −5) Mpc(exp 2) clusters show a bimodal behavior for the presence of radio halos, similar to that in the radio-X-ray diagram. Bimodality of both correlations can be traced to clusters dynamics, with radio halos found exclusively in merging clusters. These results confirm the key role of mergers for the origin of giant radio halos, suggesting that they trigger the relativistic particle acceleration.

radiation mechanisms↗
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↗
NASA NTRS1989

Transonic viscous flow computations about a complete aircraft using the Navier-Stokes equations

A numerical approach for simulating the viscous transonic flow about the complete F-16A fighter aircraft is presented using the Navier-Stokes equations. This finite difference approach utilizes a body conforming zonal grid system to provide appropriate viscous clustering near all body surfaces. A comparison between computational and experimental pressure coefficients is good, and integrated quantities such as lift and drag are within 2.6 percent and 1.6 percent, respectively. The versatility of the method is demonstrated by further modeling the flow inside the inlet up to the compressor face and the exhaust nozzle plume. Results for the F-16A in sideslip are also presented and indicate the proper trends.

Chaderjian, Neal M.↗
NASA NTRS2010

Understanding the Scalability of Bayesian Network Inference Using Clique Tree Growth Curves

One of the main approaches to performing computation in Bayesian networks (BNs) is clique tree clustering and propagation. The clique tree approach consists of propagation in a clique tree compiled from a Bayesian network, and while it was introduced in the 1980s, there is still a lack of understanding of how clique tree computation time depends on variations in BN size and structure. In this article, we improve this understanding by developing an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN s non-root nodes to the number of root nodes, and (ii) the expected number of moral edges in their moral graphs. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for the total size of each set. For the special case of bipartite BNs, there are two sets and two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, where random bipartite BNs generated using the BPART algorithm are studied, we systematically increase the out-degree of the root nodes in bipartite Bayesian networks, by increasing the number of leaf nodes. Surprisingly, root clique growth is well-approximated by Gompertz growth curves, an S-shaped family of curves that has previously been used to describe growth processes in biology, medicine, and neuroscience. We believe that this research improves the understanding of the scaling behavior of clique tree clustering for a certain class of Bayesian networks; presents an aid for trade-off studies of clique tree clustering using growth curves; and ultimately provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms.

Mengshoel, Ole J.↗
NASA NTRS2005

A Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations

A parallel Particle Swarm Optimization (PSO) algorithm is presented. Particle swarm optimization is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tied to swarming theory. Although PSO algorithms present several attractive properties to the designer, they are plagued by high computational cost as measured by elapsed time. One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. Previous parallel PSO algorithms were mostly implemented in a synchronous manner, where all design points within a design iteration are evaluated before the next iteration is started. This approach leads to poor parallel speedup in cases where a heterogeneous parallel environment is used and/or where the analysis time depends on the design point being analyzed. This paper introduces an asynchronous parallel PSO algorithm that greatly improves the parallel e ciency. The asynchronous algorithm is benchmarked on a cluster assembled of Apple Macintosh G5 desktop computers, using the multi-disciplinary optimization of a typical transport aircraft wing as an example.

Venter, Gerhard↗
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↗