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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Offline Maximizing Minimally Invasive Proper Orthogonal Decomposition for Reduced-Order Modeling of S n Radiation Transport

Deterministic solutions to the Sn radiation transport equation can be computationally expensive to calculate. Reduced-order modeling enables efficient approximation of the full-order model (FOM) solution. We propose a novel method for constructing reduced-order models (ROMs) of the S n radiation transport equation, offline maximizing minimally invasive (OMMI) proper orthogonal decomposition (POD). POD uses the method of snapshots to create a reduced-order basis for constructing an ROM. Minimally invasive POD leverages the sweep infrastructure existing in deterministic transport codes to create a POD-based ROM, even when infeasible by traditional methods. Offline maximizing minimally invasive proper orthogonal decomposition (OMMI-POD) extends minimally invasive POD by performing sweeps offline, therefore maximizing the potential speedup. OMMI-POD does so by creating a library of reduced systems from a training set. This library of reduced systems is then interpolated to provide a rapid approximate solution of the S n radiation transport equation. The model is evaluated on a set of test problems, achieving a low error with a 466 times speedup over the FOM. Also presented is a study of the effect of sampling method on the performance of OMMI-POD, specifically comparing naive uniform sampling to the more accurate and computationally expensive greedy sampling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Many-Body Basis Set Amelioration Method for Incremental Full Configuration Interaction

Incremental full configuration interaction (iFCI) is a polynomial-cost electronic structure method that systematically approaches the FCI limit by employing the method of increments to solve the Schrödinger equation through a many-body expansion. This article introduces the many-body basis set amelioration (MBBSA) method, which is designed to allow iFCI to be applicable to larger atomic orbital basis sets. MBBSA uses a series of inexpensive iFCI calculations to approximate the correlation energy that would be found using a more expensive, highly accurate iFCI calculation. Here, when compared to standard iFCI computations on smaller molecules in triple-zeta and larger basis sets, MBBSA provides approximations to the total and relative energies within chemical accuracy. MBBSA exhibits a reduced cost of between 60-92% when compared to standard iFCI calculations, with larger systems experiencing the largest benefit. Tests of MBBSA on two reactions that involve highly correlated systems, the automerization of cyclobutadiene and a Criegee intermediate reaction, show that MBBSA has practical utility for studying realistic chemistries.

Basis sets↗
DOE OSTI2015

The Initial State of a Primordial Anisotropic Stage of Inflation

We investigate the possibility that the inflationary period in the early universe was preceded by a primordial stage of strong anisotropy. In particular we focus on the simplest model of this kind, where the spacetime is described by a non-singular Kasner solution that quickly evolves into an isotropic de Sitter space, the so-called Kasner-de Sitter solution. The initial Big Bang singularity is replaced, in this case, by a horizon. We show that the extension of this metric to the region behind the horizon contains a timelike singularity which will be visible by cosmological observers. This makes it impossible to have a reliable prediction of the quantum state of the cosmological perturbations in the region of interest. In this paper we consider the possibility that this Kasner-de Sitter universe is obtained as a result of a quantum tunneling process effectively substituting the region behind the horizon by an anisotropic parent vacuum state, namely a 1+1 dimensional spacetime compactified over an internal flat torus, T{sub 2}, which we take it to be of the form de Sitter{sub 2}×T{sub 2} or Minkowski{sub 2}×T{sub 2}. As a first approximation to understand the effects of this anisotropic initial state, we compute the power spectrum of a massless scalar field in these backgrounds. In both cases, the spectrum converges at small scales to the isotropic scale invariant form and only present important deviations from it at the largest possible scales. We find that the decompactification scenario from M{sub 2}×T{sub 2} leads to a suppressed and slightly anisotropic power spectrum at large scales which could be related to some of the anomalies present in the current CMB data. On the other hand, the spectrum of the universe with a dS{sub 2}×T{sub 2} parent vacuum presents an enhancement in power at large scales not consistent with observations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

An adaptive Gaussian process-based method for efficient Bayesian experimental design in groundwater contaminant source identification problems: ADAPTIVE GAUSSIAN PROCESS-BASED INVERSION

Surrogate models are commonly used in Bayesian approaches such as Markov Chain Monte Carlo (MCMC) to avoid repetitive CPU-demanding model evaluations. However, the approximation error of a surrogate may lead to biased estimations of the posterior distribution. This bias can be corrected by constructing a very accurate surrogate or implementing MCMC in a two-stage manner. Since the two-stage MCMC requires extra original model evaluations, the computational cost is still high. If the information of measurement is incorporated, a locally accurate approximation of the original model can be adaptively constructed with low computational cost. Based on this idea, we propose a Gaussian process (GP) surrogate-based Bayesian experimental design and parameter estimation approach for groundwater contaminant source identification problems. A major advantage of the GP surrogate is that it provides a convenient estimation of the approximation error, which can be incorporated in the Bayesian formula to avoid over-confident estimation of the posterior distribution. The proposed approach is tested with a numerical case study. Without sacrificing the estimation accuracy, the new approach achieves about 200 times of speed-up compared to our previous work using two-stage MCMC.

Zhang, Jiangjiang↗
DOE OSTI2014

Sphere-plate Casimir interaction in (D + 1)-dimensional spacetime

In this paper, we derive the formula for the Casimir interaction energy between a sphere and a plate in (D + 1)-dimensional Minkowski spacetime. It is assumed that the scalar field satisfies the Dirichlet or Neumann boundary conditions on the sphere and the plate. As in the D = 3 case, the formula is of TGTG type. One of our main contributions is deriving the translation matrices which express the change of bases between plane waves and spherical waves for general D. Using orthogonality of Gegenbauer polynomials, it turns out that the final TGTG formula for the Casimir interaction energy can be simplified to one that is similar to the D = 3 case. To illustrate the application of the formula, both large separation and small separation asymptotic behaviors of the Casimir interaction energy are computed. The large separation leading term is proportional to L{sup −D+1} if the sphere is imposed with Dirichlet boundary condition, and to L{sup −D−1} if the sphere is imposed with Neumann boundary condition, where L is distance from the center of the sphere to the plane. For the small separation asymptotic behavior, it is shown that the leading term is equal to the one obtained using proximity force approximation. The next-to-leading order term is also computed using perturbation method. It is shown that when the space dimension D is larger than 5, the next-to-leading order has sign opposite to the leading order term. Moreover, the ratio of the next-to-leading order term to the leading order term is linear in D, indicating a larger correction at higher dimensions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Analytic derivative couplings and first-principles exciton/phonon coupling constants for an ab initio Frenkel-Davydov exciton model: Theory, implementation, and application to compute triplet exciton mobility parameters for crystalline tetracene

Recently, we introduced an ab initio version of the Frenkel-Davydov exciton model for computing excited-state properties of molecular crystals and aggregates. Within this model, supersystem excited states are approximated as linear combinations of excitations localized on molecular sites, and the electronic Hamiltonian is constructed and diagonalized in a direct-product basis of non-orthogonal configuration state functions computed for isolated fragments. In this work, we derive and implement analytic derivative couplings for this model, including nuclear derivatives of the natural transition orbital and symmetric orthogonalization transformations that are part of the approximation. Nuclear derivatives of the exciton Hamiltonian’s matrix elements, required in order to compute the nonadiabatic couplings, are equivalent to the “Holstein” and “Peierls” exciton/phonon couplings that are widely discussed in the context of model Hamiltonians for energy and charge transport in organic photovoltaics. As an example, we compute the couplings that modulate triplet exciton transport in crystalline tetracene, which is relevant in the context of carrier diffusion following singlet exciton fission.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Stimulus Sensitivity of a Spiking Neural Network Model

Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawkes processes, which have been used to model spiking neural networks. Using mean-field approximation, the response of the network to a stimulus is computed and we provide a notion of stimulus sensitivity. It appears that the maximal sensitivity is achieved in the sub-critical regime, yet almost critical for a range of biologically relevant parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation

Deep learning has exhibited remarkable results across diverse areas. To understand its success, substantial research has been directed towards its theoretical foundations. Nev- ertheless, the majority of these studies examine how well deep neural networks can model functions with uniform regularities. In this paper, we explore a different angle: how deep neural networks can adapt to varying degrees of smoothness in functions and nonuni- form data distributions across different locations and scales. More precisely, we focus on a broad class of functions defined by nonlinear tree-based approximation methods. This class encompasses a range of function types, such as functions with uniform regularities and discontinuous functions. We develop nonparametric approximation and estimation theories for this class using deep ReLU networks. Our results show that deep neural networks are adaptive to the nonuniform smoothness of functions and nonuniform data distributions at different locations and scales. We apply our results to several function classes, and derive the corresponding approximation and generalization errors. The validity of our results is demonstrated through numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Impact of the differential fluence distribution of brachytherapy sources on the spectroscopic dose-rate constant

Purpose: To investigate why dose-rate constants for {sup 125}I and {sup 103}Pd seeds computed using the spectroscopic technique, Λ{sub spec}, differ from those computed with standard Monte Carlo (MC) techniques. A potential cause of these discrepancies is the spectroscopic technique’s use of approximations of the true fluence distribution leaving the source, φ{sub full}. In particular, the fluence distribution used in the spectroscopic technique, φ{sub spec}, approximates the spatial, angular, and energy distributions of φ{sub full}. This work quantified the extent to which each of these approximations affects the accuracy of Λ{sub spec}. Additionally, this study investigated how the simplified water-only model used in the spectroscopic technique impacts the accuracy of Λ{sub spec}. Methods: Dose-rate constants as described in the AAPM TG-43U1 report, Λ{sub full}, were computed with MC simulations using the full source geometry for each of 14 different {sup 125}I and 6 different {sup 103}Pd source models. In addition, the spectrum emitted along the perpendicular bisector of each source was simulated in vacuum using the full source model and used to compute Λ{sub spec}. Λ{sub spec} was compared to Λ{sub full} to verify the discrepancy reported by Rodriguez and Rogers. Using MC simulations, a phase space of the fluence leaving the encapsulation of each full source model was created. The spatial and angular distributions of φ{sub full} were extracted from the phase spaces and were qualitatively compared to those used by φ{sub spec}. Additionally, each phase space was modified to reflect one of the approximated distributions (spatial, angular, or energy) used by φ{sub spec}. The dose-rate constant resulting from using approximated distribution i, Λ{sub approx,i}, was computed using the modified phase space and compared to Λ{sub full}. For each source, this process was repeated for each approximation in order to determine which approximations used in the spectroscopic technique affect the accuracy of Λ{sub spec}. Results: For all sources studied, the angular and spatial distributions of φ{sub full} were more complex than the distributions used in φ{sub spec}. Differences between Λ{sub spec} and Λ{sub full} ranged from −0.6% to +6.4%, confirming the discrepancies found by Rodriguez and Rogers. The largest contribution to the discrepancy was the assumption of isotropic emission in φ{sub spec}, which caused differences in Λ of up to +5.3% relative to Λ{sub full}. Use of the approximated spatial and energy distributions caused smaller average discrepancies in Λ of −0.4% and +0.1%, respectively. The water-only model introduced an average discrepancy in Λ of −0.4%. Conclusions: The approximations used in φ{sub spec} caused discrepancies between Λ{sub approx,i} and Λ{sub full} of up to 7.8%. With the exception of the energy distribution, the approximations used in φ{sub spec} contributed to this discrepancy for all source models studied. To improve the accuracy of Λ{sub spec}, the spatial and angular distributions of φ{sub full} could be measured, with the measurements replacing the approximated distributions. The methodology used in this work could be used to determine the resolution that such measurements would require by computing the dose-rate constants from phase spaces modified to reflect φ{sub full} binned at different spatial and angular resolutions.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2013

Imaging high stage river-water intrusion into a contaminated aquifer along a major river corridor using 2D time-lapse surface electrical resistivity tomography

The Hanford 300 Area is located adjacent to the Columbia River in south-central Washington State, USA, and was a former site for nuclear fuel processing operations. Waste disposal practices resulted in persistent unsaturated zone and groundwater contamination, the primary contaminant of concern being uranium. Uranium behavior at the site is intimately linked with river stage driven groundwater-river water exchange such that understanding the nature of river water intrusion into the 300 Area is critical for predicting uranium desorption and transport. In this paper we use time-lapse electrical resistivity tomography (ERT) to image the inland intrusion of river during high stage conditions. We demonstrate a modified time-lapse inversion approach, whereby the transient water table elevation is explicitly modeled by removing regularization constraints across the water table boundary. This implementation was critical for producing meaningful imaging results. We inverted approximately 1200 data sets (400 per line over 3 lines) using high performance computing resources to produce a time-lapse sequence of changes in bulk conductivity caused by river water intrusion during the 2011 spring runoff cycle over approximately 125 days. The resulting time series for each mesh element was then analyzed using common time series analysis to reveal the timing and location of river water intrusion beneath each line. The results reveal non-uniform flows characterized by preferred flow zones where river water enters and exits quickly with stage increase and decrease, and low permeability zones with broader bulk conductivity ‘break through’ curves and longer river water residence times. The time-lapse ERT inversion approach removes the deleterious effects of changing water table elevation and enables remote and spatial continuous groundwater-river water exchange monitoring using surface based ERT arrays under conditions where groundwater and river water conductivity are in contrast.

300 Area↗
DOE OSTI2014

H I-to-H{sub 2} transitions and H I column densities in galaxy star-forming regions

We present new analytic theory and radiative transfer computations for the atomic-to-molecular (H I-to-H{sub 2}) transitions and the buildup of atomic hydrogen (H I) gas columns in optically thick interstellar clouds irradiated by far-UV (FUV) photodissociating radiation fields. We derive analytic expressions for the total H I column densities for (one-dimensional (1D)) planar slabs, for beamed or isotropic radiation fields, from the weak- to strong-field limits, for gradual or sharp atomic-to-molecular transitions, and for arbitrary metallicity. Our expressions may be used to evaluate the H I column densities as functions of the radiation field intensity and the H{sub 2}-dust-limited dissociation flux, the hydrogen gas density, and the metallicity-dependent H{sub 2} formation rate coefficient and FUV dust grain absorption cross section. We make the distinction between 'H I-dust' and 'H{sub 2}-dust' opacity, and we present computations for the 'universal H{sub 2}-dust-limited effective dissociation bandwidth'. We validate our analytic formulae with Meudon PDR code computations for the H I-to-H{sub 2} density profiles and total H I column densities. We show that our general 1D formulae predict H I columns and H{sub 2} mass fractions that are essentially identical to those found in more complicated (and approximate) spherical (shell-core) models. We apply our theory to compute H{sub 2} mass fractions and star-formation thresholds for individual clouds in self-regulated galaxy disks, for a wide range of metallicities. Our formulae for the H I columns and H{sub 2} mass fractions may be incorporated into hydrodynamics simulations for galaxy evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A Butterfly-Accelerated Volume Integral Equation Solver for Broad Permittivity and Large-Scale Electromagnetic Analysis

In this work, a butterfly-accelerated volume integral equation (VIE) solver is proposed for fast and accurate electromagnetic (EM) analysis of scattering from heterogeneous objects. The proposed solver leverages the hierarchical off-diagonal butterfly (HOD-BF) scheme to construct the system matrix and obtain its approximate inverse, used as a preconditioner. Complexity analysis and numerical experiments validate the O(N log 2 N) construction cost of the HOD-BF-compressed system matrix and O(N log 1.5 N) inversion cost for the preconditioner, where N is the number of unknowns in the high-frequency EM scattering problem. For many practical scenarios, the proposed VIE solver requires less memory and computational time to construct the system matrix and obtain its approximate inverse compared to a H matrix-accelerated VIE solver. The accuracy and efficiency of the proposed solver have been demonstrated via its application to the EM analysis of large-scale canonical and real-world structures comprising of broad permittivity values and involving millions of unknowns.

42 ENGINEERING↗
DOE OSTI2014

Parareal in time 3D numerical solver for the LWR Benchmark neutron diffusion transient model

In this paper we present a time-parallel algorithm for the 3D neutrons calculation of a transient model in a nuclear reactor core. The neutrons calculation consists in numerically solving the time dependent diffusion approximation equation, which is a simplified transport equation. The numerical resolution is done with finite elements method based on a tetrahedral meshing of the computational domain, representing the reactor core, and time discretization is achieved using a θ-scheme. The transient model presents moving control rods during the time of the reaction. Therefore, cross-sections (piecewise constants) are taken into account by interpolations with respect to the velocity of the control rods. The parallelism across the time is achieved by an adequate use of the parareal in time algorithm to the handled problem. This parallel method is a predictor corrector scheme that iteratively combines the use of two kinds of numerical propagators, one coarse and one fine. Our method is made efficient by means of a coarse solver defined with large time step and fixed position control rods model, while the fine propagator is assumed to be a high order numerical approximation of the full model. The parallel implementation of our method provides a good scalability of the algorithm. Numerical results show the efficiency of the parareal method on large light water reactor transient model corresponding to the Langenbuch–Maurer–Werner benchmark.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Hi-COLA: fast, approximate simulations of structure formation in Horndeski gravity

We introduce Hi-COLA, a code designed to run fast, approximate N-body simulations of non-linear structure formation in reduced Horndeski gravity. Given an input Lagrangian, Hi-COLA dynamically constructs the appropriate field equations and consistently solves for the cosmological background, linear growth, and screened fifth force of that theory. Hence Hi-COLA is a general, adaptable, and useful tool that allows the mildly non-linear regime of many Horndeski theories to be investigated for the first time, at low computational cost. In this work, we first describe the screening approximations and simulation setup of Hi-COLA for theories with Vainshtein screening. We validate the code against traditional N-body simulations for cubic Galileon gravity, finding 2.5% agreement up to k max = 1.2 h/Mpc. To demonstrate the flexibility of Hi-COLA, we additionally run the first simulations of an extended shift-symmetric gravity theory. We use the consistency and modularity of Hi-COLA to dissect how the modified background, linear growth, and screened fifth force all contribute to departures from ΛCDM in the non-linear matter power spectrum. Hi-COLA can be found at https://github.com/Hi-COLACode/Hi-COLA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Improving the five-point bootstrap

We present a new algorithm for the numerical evaluation of five-point conformal blocks in d-dimensions, greatly improving the efficiency of their computation. To do this we use an appropriate ansatz for the blocks as a series expansion in radial coordinates, derive a set of recursion relations for the unknown coefficients in the ansatz, and evaluate the series using a Padé approximant to accelerate its convergence. We then study the 〈σσϵσσ〉 correlator in the 3d critical Ising model by truncating the operator product expansion (OPE) and only including operators with conformal dimension below a cutoff ∆ ⩽ ∆cutoff. We approximate the contributions of the operators above the cutoff by the corresponding contributions in a suitable disconnected five-point correlator. Using this approach, we compute a number of OPE coefficients with greater accuracy than previous methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Scalable Algorithms for Inverse Problems With High-Dimensional Parameter Spaces

Inverse problems, which involve inferring unknown parameters from observed data, present significant computational challenges, especially in large-scale settings with high-dimensional unknown parameters and nonlinear relationships between the unknowns and observations. Bayesian inference provides an approach for addressing these problems, often relying on sequential sampling methods like Markov chain Monte Carlo (MCMC) to approximate the posterior distribution of the parameters. However, MCMC methods become computationally demanding as the dimensionality of the problem increases, particularly in large-scale systems where likelihood evaluations rely on solving partial differential equations (PDEs) on large spatial domains with finely resolved meshes. To overcome these limitations, recent advancements have focused on designing scalable computa tional techniques – for both PDE simulations and sampling strategies – to make Bayesian methods feasible for high-dimensional problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Propagation of radio frequency waves through turbulent plasmas

The practical and economic viability of tokamak fusion reactors depends, in a significant way, on the efficiency of radio frequency (RF) waves to deliver energy and momentum to the plasma in the core of the reactor. The RF electromagnetic waves, excited by antenna structures placed near the wall of a tokamak, have to propagate through the turbulent edge plasma along their path to the core of the fusion device. In present day experiments, the radial width of the edge region and scrape-off layer is of the order of a few centimeters. In ITER, and in future fusion reactors, this width will be of the order of tens of centimeters. Any effects on RF waves due to plasma turbulence have to be properly understood in order to optimize the delivery of RF energy and momentum into the core. This paper is on a multi-pronged, theoretical and computational, approach that is being pursued to quantify the effect of edge plasma turbulence on the propagation of RF waves. The theoretical and analytical models are based on solutions of the Faraday-Ampere equation in a magnetized plasma and on the Kirchhoff tangent plane approximation. An effective medium approach has been developed so as to approximate the permittivity of a turbulent plasma by analytical expressions. The computations are being carried out with a newly developed code ScaRF that is based on the finite difference finite domain technique for solving Maxwell's equations. The plasma permittivity can be assigned as desired. The code is being used to validate the analytical and theoretical models and to evaluate their limitations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗