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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Development of an Exactly Solvable Model of Resonance Tunneling of Electromagnetic Waves through Gradient Barriers in a Nonuniform Magnetoactive Plasma

An exactly solvable one-dimensional model describing resonance tunneling (reflectionless transmission) of a transverse electromagnetic wave through wide layers of magnetoactive plasma is developed on the basis of the Helmholtz equation. The plasma layers include a set of spatially localized density structures the amplitudes and thicknesses of which are such that approximate methods are inapplicable for their analysis. The profiles of the plasma density structures strongly depend on the choice of the free parameters of the problem that determine the amplitudes of plasma density modulation, characteristic scale lengths of the density structures, their number, and the total thickness of the nonuniform plasma layer. The plasma layers can also include a set of random inhomogeneities. The propagation of electromagnetic waves through such complicated plasma inhomogeneities is analyzed numerically within the proposed exactly solvable model. According to calculations, there are a wide set of inhomogeneous structures for which an electromagnetic wave incident from vacuum can propagate through the plasma layer without reflection, i.e., the complete tunneling of thick plasma barriers takes place. The model also allows one to exactly solve a one-dimensional problem on the nonlinear transillumination of a nonuniform plasma layer in the presence of cubic nonlinearity. It is important that, due to nonlinearity, the thicknesses of the evanescent plasma regions can decrease substantially and, at a sufficiently strong nonlinearity, such regions will disappear completely. The problem of resonance tunneling of electromagnetic radiation through gradient wave barriers is of interest for various applications, such as efficient heating of dense plasma by electromagnetic radiation and transmission of electromagnetic signals from a source located in the near-Earth plasma or deep in the plasma of an astrophysical object through the surrounding evanescent regions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Dispersive approaches for three-particle final state interaction

In this work, we presented different representations of Khuri-Treiman equation, the advantage and disadvantage of each representations are discussed. With a scattering amplitude toy model, we also studied the sensitivity of solution of KT equation to left-hand cut of toy model and to the different approximate methods. At last, we give a brief discussion of Watson's theorem when three particles in final states are involved.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Mapping of the transient electric field causing spark suppression in Micromegas of the ATLAS New Small Wheels

Resistive strips Micromegas are employed in the ATLAS New Small Wheel project. They have already been installed and operate in the experimental cavern of the ATLAS experiment at CERN. This work attempts to describe the mechanism of the surface electric charge spread on a resistive strip of the Micromegas detector and the created transient electric field leading to the suppression of the spark rate in the amplification region. The electric field spatial mapping is calculated versus time by using the accurate 3-layer geometry as a function of the resistive layer thickness around its value used in Micromegas detectors. We also used the approximated method based on 2-layer geometry to investigate its discrepancy from the accurate one.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Quantum Computing and Second Quantization

Quantum computers are by their nature many particle quantum systems. Both the many-particle arrangement and being quantum are necessary for the existence of the entangled states, which are responsible for the parallelism of the quantum computers. Second quantization is a very important approximate method of describing such systems. This lecture will present the general idea of the second quantization, and discuss shortly some of the most important formulations of second quantization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

pyDecay: A CRAM-Based Isotope Decay Solver

This module (pyDecay) implements a Chebyshev Rational Approximation Method (CRAM) for solving isotope decay equations, based on the work of M. Pusa. It provides a numerically stable and efficient method for evaluating the matrix exponential involved in nuclear decay calculations. This implementation of CRAM relies on the incomplete partial factorization (IPF) algorithm published by Pusa [3], with corrections noted by Romano et al.

Skutnik, SteveEugene [Oak Ridge National Laborator↗
DOE OSTI2018

Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives precisely the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Sensitivity, Recalculated

Prior to this study, the sensitivity in nEXO was calculated using an approximate method that does not provide 90% coverage. I find it useful to understand the confidence level of a limit by focusing on the confidence level as a property of the method used to find the limit.A particular method (algorithm,formula) is applied to an experiment to produce a limit. That experiment was conducted in a particular universe with certain values of the physical parameters. We’d like a method than produces a correct limit for 90% of the experiments that could run. We also want that to be true for every universe—that is, regardless of the physical parameter value, the method should still produce a correct limit 90% of the time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Gauging Variational Inference

Computing partition function is the most important statistical inference task arising in applications of Graphical Models (GM). Since it is computationally intractable, approximate methods have been used to resolve the issue in practice, where meanfield (MF) and belief propagation (BP) are arguably the most popular and successful approaches of a variational type. In this paper, we propose two new variational schemes, coined Gauged-MF (G-MF) and Gauged-BP (G-BP), improving MF and BP, respectively. Both provide lower bounds for the partition function by utilizing the so-called gauge transformation which modifies factors of GM while keeping the partition function invariant. Moreover, we prove that both G-MF and G-BP are exact for GMs with a single loop of a special structure, even though the bare MF and BP perform badly in this case. Our extensive experiments, on complete GMs of relatively small size and on large GM (up-to 300 variables) confirm that the newly proposed algorithms outperform and generalize MF and BP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Initial Testing of the Microscopic Depletion Implementation in the MAMMOTH Reactor Physics Application

Present and new nuclear fuels that will be tested at the Transient Reactor Test (TREAT) facility will be analyzed with the MAMMOTH reactor physics application, currently under development, at Idaho National Laboratory. MAMMOTH natively couples the BISON, RELAP-7, and Rattlesnake applications within the MOOSE framework. This system allows the irradiation of fuel from beginning of life in a nuclear reactor until it is placed in TREAT for fuel testing within the same analysis mesh and, thus, retaining a very high level of resolution and fidelity. The calculation of the isotopic distribution in fuel requires the solution to the decay and transmutation equations coupled to the neutron transport equation. The Chebyshev Rational Approximation Method (CRAM) is the current state-of-the-art in the field, as was chosen to be the solver for the decay and transmutation equations. This report shows that the implementation of the CRAM solver within MAMMOTH is correct with various analytic benchmarks for decay and transmutation of nuclides. The results indicate that the solutions with CRAM order 16 achieve the level of precision of the benchmark. The CRAM solutions show little sensitivity to the time step size and consistently produce a high level of accuracy for isotopic decay for time steps of 1x10^11 years. Comparisons to DRAGON5 with 297 isotopes yield comparable results, but some differences need to be further analyzed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Solar-Centered Grid Project Final Technical Report

This final technical Report for the Solar-Centered Grid project examines interactions of barriers to high levels of solar penetration at the Balancing Authority level and explores approaches to solutions to several such barriers. Results of a study to pool ACE variability and responsibility among disparate neighboring BAs are presented, as well as a methodology and results of a study for predicting ACE and frequency deviations in the sub-10-minute timeframe to serve as the underpinning for operational tools for managing fast solar ramps at the BA level. An example of approximate methods for cost-benefit analysis for probabilistic control center tools is presented, followed by a draft guide of best practices for such analysis.

14 SOLAR ENERGY↗
DOE OSTI2021

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multi-Objective Adaptive Mesh Refinement Using Reinforcement Learning

Finite element methods approximate the solution to a partial differential equation (PDE) on a mesh consisting of many elements. In general, using more, smaller elements results in a lower error in the approximation. However, it is often possible to lower the error substantially by only refining, or decreasing the size of, the few elements in the mesh that have the highest error. Adaptive mesh refinement (AMR) is a process that selectively refines regions of a mesh with high error to achieve a desired accuracy in as few degrees of freedom (DOFs) as possible. AMR is favorable compared to uniform refinement, which refines all elements of the mesh equally, because it can often achieve the same accuracy without wasting extra computation time on refinement of elements that already have low error. However, it is difficult to know which elements to refine. In this report we explore ways to choose which elements to refine such that we minimize both the resulting error and the cumulative DOFs used in computation. In particular, we introduce a Pareto-front learning algorithm that trains a policy to give the optimal refinement actions to minimize the cumulative DOFs used to achieve a given target error. Such a policy is useful because it can be deployed on many different problem types where different accuracy levels are desired. Furthermore, training a single policy for a range of target errors allows us to use transfer learning to reduce the required training time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Characterizing the Uncertainty of Measurement of Traceable Isotope Ratios with Bayesian Statistical Techniques

Analytical techniques such as multicollector—inductively coupled plasma—mass spectrometry (MC-ICP-MS) are routinely employed at SRNL, other National Laboratories, and in academia to determine the precise isotopic composition of diverse natural and anthropogenic samples (e.g., rocks and nuclear materials). Quantifying and reporting uncertainty in such analyses, while regularly performed, have a rigorous statistical foundation. The Guide to the Expression of Uncertainty in Measurement 4 (GUM) outlines conventional techniques used to assess such uncertainty. As the accessibility and speed of statistical computing increase, there is a need to modernize conventional techniques. For example, Supplement 1 to the 3rd to the GUM suggests the use of approximation methods as an updated approach to the GUM.

McLarty, Ellis C.↗
DOE OSTI2024

Discovery of 15 A-F Main Sequence Pulsating Star Candidates

Delta Scuti stars, spanning spectral types A to F with masses between 1.5 and 2.5 solar masses, exhibit a complex mix of radial and non-radial pressure modes. This study focuses on 15 Delta Scuti, Gamma Doradus, and Hybrid candidate stars using TESS satellite photometry data with a time series of exposures ranging from 20 to 600 seconds across different sky regions. Employing the prewhitening technique via fast Fourier transforms, significant frequencies are extracted from light curves. Three approximation methods are used to estimate critical stellar parameters such as density, radius, and mass. This research also verifies the variability of these stars, which are currently not classified as variable in databases like SIMBAD.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Computational Algorithms for Unit Commitment with AC Power Flows (Final Report)

Security-constrained unit commitment (SCUC) is a key component in power system operations. When AC power flow constraints are considered in the SCUC model (AC-SCUC), the problem becomes extremely difficult due to its discrete and non-convex nature, as described in “Grid Optimization Competition Challenge 3 Problem Formulation (GOCC)”. There are four main challenges: (i) Discrete decisions regarding unit online/offline status and start-up/shut-down procedures for every single unit. The number of discrete decision variables increases considerably when a system integrates multiple generators; (ii) Configuration-based combined-cycle formulations, and multi-commodity models that include ramping products, spin/non-spin products, and regulation up/down products. The combined-cycle units introduce additional discrete decision variables and auxiliary service products further complicate the model by connecting multi-commodity products’ continuous and discrete variables; (iii) SCUC models with AC power flow constraints are far more complex due to massive bilinear terms in the large-scale nonlinear power balance equations. The nonlinear power balance equations are further complicated by the discrete step control variables of shunts; (iv) N − 1 contingency analysis. The size of the model increases linearly with the number of contingencies considered, greatly increasing the size of the optimization model. Accordingly, there is an emergent need to develop a robust algorithm capable of deriving a high-quality solution in a short time and passing through contingency tests simultaneously. In this project, we explore innovative techniques to address this challenging problem by integrating advanced polyhedral theory, approximation methods, relaxation strategies, decomposition techniques, and parallel computing. Each technique approaches the problem from a different perspective, leveraging its specific strengths to tackle distinct challenges. Each individual method has demonstrated its effectiveness in the PI’s previous research. Their integration is expected to significantly reduce the computational time required to solve the proposed complex problem. Successful completion of this project has the potential to transform the industry by enhancing optimization solvers capable of handling large-scale day-ahead energy market clearing models within strict time constraints, while incorporating AC power flow constraints. This advancement will lead to reduced overall generation costs and, consequently, increased social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

On the Estimation of Circumbinary Orbital Properties

We describe a fast, approximate method to characterize the orbits of satellites around a central binary in numerical simulations. A goal is to distinguish the free eccentricity—the random motion of a satellite relative to a dynamically cool orbit—from oscillatory modes driven by the central binary’s time-varying gravitational potential. We assess the performance of the method using the Kepler-16, Kepler-47, and Pluto–Charon systems. We then apply the method to a simulation of orbital damping in a circumbinary environment, resolving relative speeds between small bodies that are slow enough to promote mergers and growth. These results illustrate how dynamical cooling can set the stage for the formation of Tatooine-like planets around stellar binaries and the small moons around the Pluto–Charon binary planet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Analysis of the Intrinsic Mid-infrared L band to Visible–Near-infrared Flux Ratios in Spectral Synthesis Models of Composite Stellar Populations

We analyze the intrinsic flux ratios of various visible–near-infrared filters with respect to 3.5 μm for simple and composite stellar populations (CSPs), and their dependence on age, metallicity, and star formation history (SFH). UV/optical light from stars is reddened and attenuated by dust, where different sightlines across a galaxy suffer varying amounts of extinction. Tamura et al. (2009) developed an approximate method to correct for dust extinction on a pixel-by-pixel basis, dubbed the “β{sub V}” method, by comparing the observed flux ratio to an empirical estimate of the intrinsic ratio of visible and ∼3.5 μm data. Through extensive modeling, we aim to validate the “β{sub V}” method for various filters spanning the visible through near-infrared wavelength range, for a wide variety of simple and CSPs. Combining Starburst99 and BC03 models, we built spectral energy distributions (SEDs) of simple (SSP) and composite (CSP) stellar populations for various realistic SFHs, while taking metallicity evolution into account. We convolve various 0.44–1.65 μm filter throughput curves with each model SED to obtain intrinsic flux ratios β{sub λ,0}. When unconstrained in redshift, the total allowed range of β{sub V,0} is 0.6–4.7, or almost a factor of eight. At known redshifts, and in particular at low redshifts (z ≲ 0.01), β{sub V,0} is predicted to span a narrow range of 0.6–1.9, especially for early-type galaxies (0.6–0.7), and is consistent with observed β{sub V} values. The β{sub λ} method can therefore serve as a first-order dust-correction method for large galaxy surveys that combine JWST (rest-frame 3.5 μm) and HST (rest-frame visible–near-IR) data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Nonthermal Ionization of Kilonova Ejecta: Observable Impacts

The characteristic rapid rise and decline at optical wavelengths of a kilonova is the product of the low ejecta mass (≲0.05 M ⊙ ) and high ejecta velocity (≳0.1c). We show that, even at very early times (≲2 days), regions of ejecta fall below critical density and temperature thresholds at which nonlocal thermodynamic equilibrium (NLTE) effects become important. Here, we present an approximate method for calculating the ionization state of the ejecta that accounts for the NLTE impact of high-energy electrons produced in the beta decay of freshly synthesized r-process elements. We find that incorporating ionization from high-energy electrons produces an “inverted” and “blended” ionization structure, where the most highly ionized species are located in the fastest moving homologous ejecta, and multiple ionization states coexist. In radiation transport calculations, the higher degree of ionization reduces line blanketing in optical bands, leading to improved agreement with the light-curve properties of AT 2017gfo, such as the duration, decay rates, brightness, and colors. Our quasi-NLTE implementation helps to alleviate tensions in kilonova modeling: for high-velocity (∼0.3 c) ejecta components, our models require less mass for a given peak brightness in optical bands, by as much as a factor of 3; our models can explain the presence of observed features associated to Sr II, W III, Se III, and Te III under conditions where LTE models would predict only neutral species; and we naturally predict the coexistence of species like Sr II and Ce III without the need for fine-tuning of the ejecta properties.

High energy astrophysics↗