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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Superfluid condensate fraction and pairing wave function of the unitary Fermi gas

The unitary Fermi gas is a many-body system of two-component fermions with zero-range interactions tuned to infinite scattering length. Despite much activity and interest in unitary Fermi gas and its universal properties, there have been great difficulties in performing accurate calculations of the superfluid condensate fraction and pairing wave function. In this paper, we present auxiliary-field lattice Monte Carlo simulations using a lattice interaction which accelerates the approach to the continuum limit, thereby allowing for robust calculations of these difficult observables. As a benchmark test, we compute the ground-state energy of 33 spin-up and 33 spin-down particles. As a fraction of the free Fermi gas energy $E_{\text{FG}}$, we find $E_0/E_{\text{FG}}$ = 0.369(2), 0.372(2), using two different definitions of the finite-system energy ratio, in agreement with the latest theoretical and experimental results. We then determine the condensate fraction by measuring off-diagonal long-range order in the two-body density matrix. We find that the fraction of condensed pairs is α = 0.43(2). Further, we also extract the pairing wave function and find the pair correlation length to be $ζ_pk_F$ = 1.8(3)ℏ, where $k_F$ is the Fermi momentum. Provided that the simulations can be performed without severe sign oscillations, the methods we present here can be applied to superfluid neutron matter as well as more exotic $\textit{P}$-wave and $\textit{D}$-wave superfluids.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

Correlation and relativistic effects in actinide ions

Wavelengths, line strengths, and transition rates are calculated for the multipole (E1, M1, E2, M2, E3, and M3) transitions between the excited 6s{sup 2}6p{sup 5}nl and 6s6p{sup 6}nl states and the ground 6s{sup 2}6p{sup 6} state in Ac{sup 3+}, Th{sup 4+}, and U{sup 6+} Rn-like ions. Relativistic many-body perturbation theory (RMBPT), including the Breit interaction, is used to evaluate energies and transition rates for multipole transitions in these hole-particle systems. The RMBPT method agrees with multiconfigurational Dirac-Fock (MCDF) calculations in lowest order, includes all second-order correlation corrections, and includes corrections from negative-energy states. The calculations start from a [Xe]4f{sup 14}5d{sup 10}6s{sup 2}6p{sup 6} Dirac-Fock potential. First-order perturbation theory is used to obtain intermediate-coupling coefficients, and second-order RMBPT is used to determine the matrix elements. Evaluated multipole matrix elements for transitions from excited states to the ground states are used to determine the line strengths, transition rates, and multipole polarizabilities. This work provides a number of yet unmeasured properties of these actinide ions for various applications and for benchmark tests of theory and experiment.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Relativistic configuration interaction plus linearized-coupled-cluster calculations of U 2 + energies, g factors, transition rates, and lifetimes

In this study, excitation energies, term designations, g factors, transition rates, and lifetimes of U 2+ are determined using a relativistic configuration interaction (CI) + linearized-coupled-cluster (LCC) approach. The CI-LCC energies are compared with CI + many-body-perturbation-theory (MBPT) and available experimental energies. Close agreement has been found with experiment, within hundreds of cm -1 . In addition, lifetimes of higher levels have been calculated for comparison with three experimentally measured lifetimes, and close agreement has been found within the experimental error. CI-LCC calculations constitute a benchmark test of the CI + all-order method in complex relativistic systems such as actinides and their ions with many valence electrons. The theory yields many energy levels, g factors, transition rates, and lifetimes of U 2+ that are not available from experiment. Lastly, the theory can be applied to other multivalence atoms and ions, which would be of interest to many applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Towards a quantitative description of tunneling conductance of superconductors: Application to LiFeAs

Since the discovery of iron-based superconductors, a number of theories have been put forward to explain the qualitative origin of pairing, but there have been few attempts to make quantitative, material-specific comparisons to experimental results. The spin-fluctuation theory of electronic pairing, based on first-principles electronic structure calculations, makes predictions for the superconducting gap. Within the same framework, the surface wave functions may also be calculated, allowing, e.g., for detailed comparisons between theoretical results and measured scanning tunneling topographs and spectra. We present such a comparison between theory and experiment on the Fe-based superconductor LiFeAs. Our results for the homogeneous surface as well as impurity states are presented as a benchmark test of the theory. For the homogeneous system, we argue that the maxima of topographic image intensity may be located at positions above either the As or Li atoms, depending on tip height and the setpoint current of the measurement. We further report the experimental observation of transitions between As- and Li-registered lattices as functions of both tip height and setpoint bias, in agreement with this prediction. Next, we give a detailed comparison between the simulated scanning tunneling microscopy images of transition-metal defects with experiment. Finally, we discuss possible extensions of the current framework to obtain a theory with true predictive power for scanning tunneling microscopy in Fe-based systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Quantum many-body calculations using body-centered cubic lattices

It is often computationally advantageous to model space as a discrete set of points forming a lattice grid. This technique is particularly useful for computationally difficult problems such as quantum many-body systems. For reasons of simplicity and familiarity, nearly all quantum many-body calculations have been performed on simple cubic lattices. Since the removal of lattice artifacts is often an important concern, it would be useful to perform calculations using more than one lattice geometry. In this paper we show how to perform quantum many-body calculations using auxiliary-field Monte Carlo simulations on a three-dimensional body-centered cubic (BCC) lattice. As a benchmark test we compute the ground state energy of 33 spin-up and 33 spin-down neutrons in the unitary limit, which is an idealized limit where the interaction range is zero and scattering length is infinite. As a fraction of the free Fermi gas energy E FG , we find that the ground state energy is E 0 /E FG =0.369(2),0.371(2), using two different definitions of the finite-system energy ratio. This is in excellent agreement with recent results obtained on a cubic lattice [He et al., Phys. Rev. A 101, 063615 (2020)]. We find that the computational effort and performance on a BCC lattice is approximately the same as that for a cubic lattice with the same number of lattice points. We discuss how the lattice simulations with different geometries can be used to constrain the size of lattice artifacts in simulations of continuum quantum many-body systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Modeling betatron radiation using particle-in-cell codes for plasma wakefield accelerator diagnostics

The analysis of plasma wakefield acceleration experimental measurements, particularly in the characterization of photons emitted through the betatron radiation mechanism, requires the development of accurate numerical models. These computational models are crucial for supporting modern instrumentation designed to measure the single-shot, double-differential angular-energy radiation spectra resulting from interactions between beams and plasmas. Motivated by the needs of such applications, this paper presents detailed numerical models of betatron radiation generated in beam-plasma acceleration experiments. These models are based on the integration of the Liénard-Wiechert (LW) potentials, applied to computed particle trajectories. The particle trajectories are generated using three distinct methods: first, by tracking particles through idealized fields in the blowout regime of PWFA; second, by obtaining trajectories using the fast quasistatic particle-in-cell (PIC) code quickpic; and third, obtaining trajectories from the fully self-consistent PIC code osiris. To ensure the accuracy and reliability of these models, the paper includes various benchmark tests using analytical expressions, as well as employing the PIC code epoch, which takes an alternative approach by using a Monte Carlo quantum electrodynamics (QED)-based radiation model. Additionally, the paper presents simulations of the expected experimental betatron radiation spectra, taking into account parameters relevant to PWFA and plasma photocathode experiments at the SLAC FACET-II facility.

Yadav, M. [University of California, Los Angeles, ↗
DOE OSTI2018

Quality Assessment of GPU Power Profiling Mechanisms

Accurate component-level power measurements are nowadays essential for the design and optimization of high-performance computing (HPC) systems and applications. Particularly, as more and more heterogeneous HPC systems are developed, the characterizations of GPU power profiles have become extremely crucial because, although GPUs provide exceptional performance, they do consume substantial amounts of power. Currently, there are various GPU power profiling mechanisms available; however, there is no standard way to assess the quality of such profiling schemes. To address this issue, in this paper, we develop an assessment methodology to rate the quality and performance of the profiling mechanism itself. Specifically, we present the assessments of four different GPU power profiling techniques: (i) Nvidia's NVML via Allinea MAP, (ii) Nvidia's NVML via direct reads, and (iii) Penguin Computing's PowerInsight (PI) via two vendor-provided drivers, and (iv) PowerInsight via Allinea MAP. In addition, we discuss the effects of moving-average filters to explain the slow variations of some of the measured power profiles. Based on our assessment, the GPU power profiling mechanism using PI device outperforms the other schemes by reliably measuring the ground-truth power profile generated by a GPU stress-test benchmark.

Sen, Satyabrata↗
DOE OSTI2021

Structural Controllability Assessment for Inverter-Based Microgrids

Enhanced inverter-based controls are considered for microgrids, which use additional actuation beyond a droop-like term. Shaping of the microgrid’s small-signal dynamics using such enhanced controls is posed as a structural controllability problem. A graph-theoretic characterization of structural controllability is obtained, in terms of the concept of zero-forcing sets.Two benchmark test systems are used to illustrate the selection of locations where enhanced controls should be applied, based on the graph-theoretic analysis. These examples indicate that small-signal characteristics can be shaped using a relatively small number of enhanced controls

microgrids, zero-forcing, structural controlabilit↗
DOE OSTI2015

Sub-second State Estimation Implementation and its Evaluation with Real Data

This paper describes the performance of a parallel state estimation (PSE) tool implemented using advanced computing techniques. The developed code is able to solve state estimation of large-size, practical power systems within one second. Benchmark tests against a commercial tool shows that the computational speed is 10 times faster. Benefits brought by the sub-second state estimation are also discussed.

EMS↗
DOE OSTI2023

Enhancing Cyber Resilience of Networked Microgrids using Vertical Federated Reinforcement Learning

This paper presents a novel federated reinforcement learning (Fed-RL) methodology to inject sufficient resiliency into the operations of the network of microgrids. We consider adversarial actions to the voltage and power control loop reference signals at the grid forming (GFM) inverters in the microgrids which are essential to integrate renewable resources. Therefore, we formulate a resilient reinforcement learning training setup that uses these adversarial injections to generate episodic trajectories and train the RL agents to alleviate their impact on performance. To circumvent the concerns about data-sharing and privacy for different owners of the microgrids in the networked setting, we bring in the aspects of the federated operation to propose novel Fed-RL algorithms. As the dynamics of each microgrid are coupled due to electrical interlinks, the conventional federated RL approaches using decoupled independent environments are not applicable, which leads us to propose a multi-agent vertically federated variation of actor-critic algorithms, namely federated soft actor-critic (FedSAC). We have performed numerical simulations on an IEEE 123-bus benchmark test feeder with three microgrids by creating a customized simulation setup by encapsulating the microgrid dynamic simulations in GridLAB-D/HELICS co-simulation platform with the OpenAI Gym environment and validated the proposed resilient and secured learning methodology.

Artificial Intelligence (AI), reinforcement learni↗
DOE OSTI2026

Accelerating Bilevel Optimization With Hierarchical Many-Threaded Parallel Differential Evolution

Bilevel optimization is encountered in many relevant real-world applications. The main feature of this type of problem is that an upper-level optimization problem is constrained by a nested lower-level optimization problem. Because of this nested structure, bilevel problems (BLPs) are usually computationally expensive to solve. Differential evolution (DE) has demonstrated promising results in solving BLPs of relatively small scales. As the problem scale increases, the decision space becomes intrinsically larger, requiring a growing number of function evaluations for the method to work properly. In this context, heavy parallelization and high-performance computing techniques are indispensable to enable the resolution of more complex and challenging optimization problems. Hence, we propose a hierarchical many-threaded parallel DE approach for BLPs, where both levels are parallelized. The computational experiments demonstrate that the parallel implementation achieved runtime speeds ranging from 44 to 2559 times faster than the sequential version on a well-known scalable SMD benchmark test problem when executed on an NVIDIA A100 GPU. The findings indicate that the algorithm’s convergence is strongly influenced by the number of both upper- and lower-level generations. Moreover, the success of experiments with large-scale problems is closely linked to the choice of small population sizes.

Dufek, Amanda S↗
DOE OSTI2018

P4: Portable Parallel Processing Pipelines for Interactive Information Visualization

We present P4, an information visualization toolkit that combines declarative design specification and GPU computing for building high-performance interactive systems. Most of the existing information visualization toolkits do not harness the power of parallel processors in today's mainstream computers. P4 leverages GPU computing to accelerate both data processing and visualization rendering for interactive visualization applications. P4's programming interface offers a declarative visualization grammar for rapid specifications of data transformations, visual encodings, and interactions. By simplifying the development of GPU-accelerated visualization systems while supporting a high degree of flexibility and customization for design specification, P4 narrows the gap between expressiveness and scalability in information visualization toolkits. Through a range of examples and benchmark tests, we demonstrate that P4 provides high efficiency for creating interactive visualizations and offers drastic performance improvement over current state-of-the-art toolkits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Maximum Likelihood Source Localization Using Elpasolite as a Dual Gamma Neutron Directional Detector

The problem of accurately detecting extremely low levels of nuclear radiation is rapidly increasing in importance in nuclear counter-proliferation, verification, and environmental and waste management. Because the 239Pu gamma signature may be weak, for instance, even when compared to the natural terrestrial background, coincidence counting with the 239Pu neutron signature may improve overall 239Pu detection sensitivity. However, systems with sufficient multiple-particle detectors require demonstration that the increased sensitivity be sufficiently high to overcome added cost and weight. We report the results of measurements and calculations to determine sensitivity that can be gained in detecting low levels of nuclear radiation from use of a relatively new detector technology based on elpasolite crystals. We have performed investigations exploring cerium (Ce3+)-doped elpasolites Cs2LiYCl6:Ce3+0.5% (CLYC) and Cs2LiLa(Br6)90%(Cl6)10%:Ce3+0.5% (CLLBC:Ce). These materials can provide energy resolution (r(E) = 2.35σ(E)/E) as good as 2.9% at 662 keV (FWHM). The crystals show an excellent neutron and gamma radiation response. The goals of the investigation were to set up the neutron/gamma pulse shape discrimination electronics for elpasolite detectors; perform limited static source benchmarking, testing, and evaluation to validate system performance; and explore application of a maximum likelihood algorithm for source location. Data were measured and processed through a maximum likelihood estimation algorithm, providing a direction to the radioactive source for each individual position. The estimated directions were good representations for the actual directions to the radioactive source. This paper summarizes the maximum likelihood results for our elpasolite system.

maximum likelihood, radiation detectors, neutron d↗
DOE OSTI2024

Progressive Dynamics for Cloth and Shell Animation

We propose Progressive Dynamics, a coarse-to-fine, level-of-detail simulation method for the physics-based animation of complex frictionally contacting thin shell and cloth dynamics. Progressive Dynamics provides tight-matching consistency and progressive improvement across levels, with comparable quality and realism to high-fidelity, IPC-based shell simulations [Li et al. 2021] at finest resolutions. Together these features enable an efficient animation-design pipeline with predictive coarse-resolution previews providing rapid design iterations for a final, to-be-generated, high-resolution animation. In contrast, previously, to design such scenes with comparable dynamics would require prohibitively slow design iterations via repeated direct simulations on high-resolution meshes. We evaluate and demonstrate Progressive Dynamics's features over a wide range of challenging stress-tests, benchmarks, and animation design tasks. Here Progressive Dynamics efficiently computes consistent previews at costs comparable to coarsest-level direct simulations. Its matching progressive refinements across levels then generate rich, high-resolution animations with high-speed dynamics, impacts, and the complex detailing of the dynamic wrinkling, folding, and sliding of frictionally contacting thin shells and fabrics.

Computer Science↗
DOE OSTI2022

ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. We describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.

3D printing↗
DOE OSTI2025

Generalizable, fast, and accurate DeepQSPR with fastprop

Abstract Quantitative Structure–Property Relationship studies (QSPR), often referred to interchangeably as QSAR, seek to establish a mapping between molecular structure and an arbitrary target property. Historically this was done on a target-by-target basis with new descriptors being devised to specifically map to a given target. Today software packages exist that calculate thousands of these descriptors, enabling general modeling typically with classical and machine learning methods. Also present today are learned representation methods in which deep learning models generate a target-specific representation during training. The former requires less training data and offers improved speed and interpretability while the latter offers excellent generality, while the intersection of the two remains under-explored. This paper introduces , a software package and general Deep-QSPR framework that combines a cogent set of molecular descriptors with deep learning to achieve state-of-the-art performance on datasets ranging from tens to tens of thousands of molecules. provides both a user-friendly Command Line Interface and highly interoperable set of Python modules for the training and deployment of feedforward neural networks for property prediction. This approach yields improvements in speed and interpretability over existing methods while statistically equaling or exceeding their performance across most of the tested benchmarks. is designed with Research Software Engineering best practices and is free and open source, hosted at github.com/jacksonburns/fastprop.

Burns, Jackson W. (ORCID:0000000206579426)↗
DOE OSTI2017

Characterization of local hydride re-orientation in high burn-up PWR fuel rods induced by high pressure at high temperatures

Hydride re-orientation in high burn-up PWR fuel rods was induced by high pressure at high temperatures. The high-burnup specimens were sectioned from PWR rods taken from a 15×15 assembly of the H.B. Robinson (HBR) Unit 2 reactor. Out-of cell benchmark tests performed on unirradiated hydrided Zircaloy-4 specimens were conducted to determine the appropriate temperature, pressure, cooling rate, and number of cooling cycles for the reorientation of the irradiated in-cell specimens. The in-cell hydride reorientation tests were performed using high-burnup fuel specimens under a hoop stress ≈145 MPa at 400°C. The specimens were heated to the target temperature of 400°C, held for 3 hours, cooled at 1°C/min to 170°C,and then heated at 1°C/min to the target temperature again for five cycles. Post test metallographic examinations showed that a significant amount of radial hydrides were induced in the HBR fuel rods. The length of radial hydride was up to 60 μm. For unirradiated materials, the ductility of the radial hydride treated specimens is significantly reduced as compared to the as-hydrided specimens having the same hydrogen concentration (≈300 wppm in this work). The mechanical testing on irradiated fueled samples with hydride reorientation experiments have been performed, and will be reported separately in the near future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗