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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

High-Fidelity Calibration and Characterization of Hyperspectral Computed Tomography System

This document archives the results developed by the Lab Directed Research and Development (LDRD) project sponsored by Sandia National Laboratories (SNL). In this work, a numerical study was performed to show the feasibility of approximating the non-linear operator of SNL's unique high-energy hyperspectral computed tomography system as a sequence of linear operators. The four main results gained from this work include the development of a simulation test-bed using a particle-transport Monte Carlo approach; the demonstration to assemble a linear operator of almost-arbitrary resolution for a given narrow energy window, developing a compression approach to dramatically reduce the size of the linear operator via a spline approach, and the demonstration of using the linear operator to perform processing of x-ray data; in this case, the development of an iterative reconstruction method. This numerical study has indicated that if these results can be replicated on the SNL system, the improved performance could be revolutionary as the method to approximate the nonlinear operator for a hyperspectral CT system is not feasible to perform on a traditional CT system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies

There exist several different reliability-and approximation-based methods to determine the contribution of solar resources toward resource adequacy. However, most of these approaches require knowing in advance the installed capacities of both conventional and solar generators. This is a complication since generator capacities are actually decision variables in capacity planning studies. In this paper, we study the effect of time resolution and solar PV penetration using a planning model that accounts for the full distribution of generator outages and solar resource variability. We also describe a modification of a standard deterministic planning model that enforces a resource adequacy target through a reserve margin constraint. Our numerical experiments show that at least 50 days worth of data are necessary to approximate the results of the full-resolution model with a maximum error of 2.5% on costs and capacity. We also show that the amount of displaced capacity of conventional generation decreases rapidly as the penetration of solar PV increases. We find that using an exogenously defined and constant capacity value based on time-series data can yield relatively accurate results for small penetration levels. For higher penetration levels, the modified deterministic planning model better captures avoided costs and the decreasing value of solar PV.

14 SOLAR ENERGY↗
DOE OSTI2024

Validation of a Tapered Impact Damper for Traffic Signal Structure Vibrations Using the Method of Harmonic Balance

Significant vibration amplitudes and cycles can be produced when traffic signal structures with low inherent damping are excited near one of their natural frequencies. For the mitigation of wind-induced vibrations, dynamic vibration absorbers coupled to the structure are often used. Here, this research investigates the performance of a tapered impact damper, consisting of a hanging spring-mass oscillator inside a housing capable of reducing vibration amplitude over a broader frequency range than the conventional tuned mass damper. A nonlinear, two degree-of-freedom model is developed with coordinates representing the traffic structure and the tapered impact damper. This research focuses on the application of the harmonic balance method to approximate the periodic solutions of the nonlinear equations to compute the nonlinear dynamics of the damped traffic signal structure. After designing and manufacturing a tapered impact damper, the traffic signal structure is tested with and without the damper using free vibration snapback tests. The experimental frequency and damping backbone curves are used to validate the analytical model, and the effectiveness of the damper is discussed.

42 ENGINEERING↗
DOE OSTI2021

Tick bite frequency, prevention practices and Lyme disease diagnoses among U.S. Hispanic survey respondents

Abstract Tick bite prevention practices, knowledge of Lyme disease (LD) symptoms and transmission, and patterns of LD diagnoses among Hispanic persons have been reported but not comprehensively evaluated. In 2014, CDC examined questions from a prospective nationwide survey of U.S. Hispanic adults conducted via the Offerwise QueOpinas panel regarding ticks and LD. From October to November, a total of 2,649 surveys were released and 1,006 completed surveys returned. Overall, 44% of respondents reported routinely practising at least one form of personal protection against tick bites, and wearing repellent was the most commonly reported method (29%). Approximately 6% of respondents reported a tick bite for either themselves or someone in their household during the previous 12 months. An individual or household diagnosis of LD in the previous year was reported by 2% of respondents, with the highest proportion of diagnoses reported by respondents from high LD incidence states. The annual incidence of healthcare provider‐diagnosed LD in the survey population was higher than national surveillance estimates for reported LD among U.S. Hispanic persons during 2000–2013. As annual incidence of LD continues to increase, it is important to ensure equitable access to information about LD, including disease transmission, manifestations, and prevention recommendations. Results from this survey can help inform public health outreach focused on effective tick bite prevention methods and early recognition of LD.

Beck, Alyssa↗
DOE OSTI2019

Piezoelectric Properties of 2D Nanoallotropes of Boron Nitride

Abstract—: The independent components of the tensor of piezoelectric moduli are calculated for various 2D nanoallotropes of boron nitride. The principle of the proposed approximation calculation method consists in the fact that the effective dipole moment of the unit cell of the 2D structure normalized to the unit area is expressed through the tensor of elastic rigidities and relative cell deformations. It is shown that, in addition to well-known graphite-like boron nitride h-BN, its other hexagonal and tetragonal nanoallotropes possessing higher piezoelectric properties in comparison to h-BN can be of practical interest as well.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Molecular dynamics simulations of reflection and sputtering behavior of boron under deuterium ion irradiation

Boronization is a commonly used method of wall conditioning in fusion reactors. The application of boron films to the plasma-facing materials results in enhanced plasma performance due to the reduction of intrinsic impurities. This is primarily driven by a reduction in oxygen content that is chemically trapped in the boron film. The reactive nature of these boron films also raises questions concerning interactions with hydrogen isotopes. In this work, boron-deuterium interactions were studied using molecular dynamics (MD). Reactive force field potentials were used to model the chemical interactions between B and D. An amorphous boron substrate was irradiated by D atoms at varying incident energies, 10 eV < E i < 150 eV and angles, 0° < α < 85°. The reflection probability was calculated and compared to results from the commonly-used binary collision approximation (BCA) method. This comparison found that the BCA underestimated the reflection probability at E i < 35 eV and α > 45 ∘ . The source of this discrepancy was found to be the surface binding energy model. The BCA calculation with an isotropic surface binding energy model was more closely aligned to the MD result. This, in combination with a correction function based on the MD results allows for corrections to the reflection probability of deuterium impinging on boron surfaces. The sputtering of the substrate material was also studied. While this study did not contain sufficient events to quantitatively describe the sputtering behavior, some qualitative results emerged: namely, chemical sputtering of B and D-containing molecules (BD, BD 2 , BD 3 ) at low ( < 20 eV) incident deuterium energies. This result suggests that chemical sputtering could be a significant factor in limiting boron coating lifetime when exposed to lower ion energies, such as those in detached plasmas. The results show that chemical interactions should be taken into account when modeling the interactions between D ions and B surfaces.

Boron↗
DOE OSTI2019

Density estimation techniques for multiscale coupling of kinetic models of the plasma material interface

In this work we analyze two classes of Density-Estimation techniques which can be used to consistently couple different kinetic models of the plasma-material interface, intended as the region of plasma immediately interacting with the first surface layers of a material wall. In particular, we handle the general problem of interfacing a continuum multi-species Vlasov-Poisson-BGK plasma model to discrete surface erosion models. The continuum model solves for the energy-angle distributions of the particles striking the surface, which are then driving the surface response. A modification to the classical Binary-Collision Approximation (BCA) method is here utilized as a prototype discrete model of the surface, to provide boundary conditions and impurity distributions representative of the material behavior during plasma irradiation. The numerical tests revealed the superior convergence properties of Gaussian Mixture Models over Kernel Density Estimation methods, with Gaussian Mixtures and Epanechnikov-KDEs both being up to two orders of magnitude faster than Gaussian-KDEs. The methodology here presented allows a self-consistent treatment of the plasma-material interface in magnetic fusion devices, including both the near-surface plasma (plasma sheath and presheath) in magnetized conditions, and surface effects such as sputtering, back-scattering, and ion implantation. The same coupling techniques can also be utilized for other discrete material models such as Molecular Dynamics.

42 ENGINEERING↗
DOE OSTI2025

Kolmogorov-Arnold wavefunctions

Here, this work investigates Kolmogorov-Arnold network-based (KAN) wave-function Ansätz as viable representations for quantum Monte Carlo simulations. Through systematic analysis of one-dimensional model systems, we evaluate their computational efficiency and representational power against established methods. Our numerical experiments suggest some efficient training methods and we explore how the computational cost scales with desired precision, particle number, and system parameters. Roughly speaking, KANs seem to be 10 times cheaper computationally than other neural-network-based Ansätz . We also introduce a novel approach for handling strong short-range potentials—a persistent challenge for many numerical techniques—which generalizes efficiently to higher-dimensional, physically relevant systems with short-ranged strong potentials common in atomic and nuclear physics.

1-dimensional systems↗
DOE OSTI2016

Fully coupled hydro-mechanical numerical manifold modeling of porous rock with dominant fractures

Coupled hydro-mechanical (HM) processes are significant in geological engineering such as oil and gas extraction, geothermal energy, nuclear waste disposal and for the safety assessment of dam foundations and rock slopes, where the geological media usually consist of fractured rock masses. We developed a model for the analysis of coupled hydro-mechanical processes in porous rock containing dominant fractures, by using the numerical manifold method (NMM). In the current model, the fractures are regarded as different material domains from surrounding rock, i.e., finite-thickness fracture zones as porous media. Compared with the rock matrix, these fractured porous media are characterized with nonlinear behavior of hydraulic and mechanical properties, involving not only direct (poroelastic) coupling but also indirect (property change) coupling. By combining the potential energy associated with mechanical responses, fluid flow and solid–fluid interactions, a new formulation for direct HM coupling in porous media is established. For indirect coupling associated with fracture opening/closure, we developed a new approach implicitly considering the nonlinear properties by directly assembling the corresponding strain energy. Compared with traditional methods with approximation of the nonlinear constitutive equations, this new formulation achieves a more accurate representation of the nonlinear behavior. We implemented the new model for coupled HM analysis in NMM, which has fixed mathematical grid and accurate integration, and developed a new computer code. We tested the code for direct coupling on two classical poroelastic problems with coarse mesh and compared the results with the analytical solutions, achieving excellent agreement, respectively. We tested for indirect coupling on models with a single dominant fracture and obtained reasonable results. The current poroelastic NNM model with a continuous finite-thickness fracture zone will be further developed considering thin fractures in a discontinuous approach for a comprehensive model for HM analysis in fractured porous rock masses.

58 GEOSCIENCES↗
DOE OSTI2022

Mana and thermalization: Probing the feasibility of near-Clifford Hamiltonian simulation

Quantum hydrodynamics is the emergent classical dynamics governing transport of conserved quantities in generic strongly interacting quantum systems. Here, recent matrix product operator methods [1,2] have made simulations of quantum hydrodynamics in 1+1D tractable, but they do not naturally generalize to 2+1D or higher, and they offer limited guidance as to the difficulty of simulations on quantum computers. Near-Clifford simulation algorithms are not limited to one dimension, and future error-corrected quantum computers will likely be bottlenecked by non-Clifford operations. We therefore investigate the non-Clifford resource requirements for simulation of quantum hydrodynamics using mana, a resource theory of non-Clifford operations. For infinite-temperature starting states, we find that the mana of subsystems quickly approaches zero, while for starting states with energy above some threshold the mana approaches a nonzero value. Surprisingly, in each case the finite-time mana is governed by the subsystem entropy, not the thermal state mana; we argue that this is because mana is a sensitive diagnostic of finite-time deviations from canonical typicality.

1-dimensional spin chains↗
DOE OSTI2019

Isoscalar and isovector giant resonances in 92,94,96,98,100 $\mathrm{Mo}$ and 90,92,94 $\mathrm{Zr}$

The response functions, S(E), and centroid energies, E CEN , of the isoscalar and isovector giant resonances of multipolarity L = 0 - 3 in 92,94,96,98,100 Mo and 90,92,94 Zr have been calculated employing the spherical Hartree-Fock (HF) based random phase approximation (RPA) method, using the Skyrme-type effective nucleon-nucleon interaction. In particular, we investigate the recent experimental results of the uncharacteristic behavior of E CEN for the isoscalar giant resonances, by extending our HF-based RPA calculations with only the KDE0v1 interaction to 32 additional Skyrme interactions. The main result of our investigation is that we find significant disagreements between the theoretical and the experimental values of E CEN for isoscalar giant monopole and dipole resonance of some nuclei. For the isoscalar giant octupole resonance we find the theoretical values of the E CEN to be well above the experimental results. We also study the sensitivity of E CEN to nuclear matter (NM) properties, including the effective mass, the incompressibility coefficient and the symmetry energy at saturation density, by determining the Pearson linear correlation coefficient between the calculated values of E CEN and the various nuclear matter properties of each Skyrme parametrization. So, for the isovector giant dipole resonance we find good agreement between the experimental and theoretical values of E CEN for Skyrme interactions with values of the enhancement coefficient of the energy weighted sum rule, κ, in the range between 0.25 – 0.70

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition

Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.

Hanson, Joshua↗
DOE OSTI2019

Multidimensional sum-up rounding for integer programming in optimal experimental design

Here we present a numerical method for approximating the solution of convex integer programs stemming from optimal experimental design. The statistical setup consists of a Bayesian framework for linear inverse problems for which the direct relationship is described by a discretized integral equation. Specifically, we aim to find the optimal sensor placement from a set of candidate locations where data are collected with measurement error. The convex objective function is a measure of the uncertainty, described here by the trace or log-determinant of the posterior covariance matrix, for the discretized linear inverse problem solution. The resulting convex integer program is relaxed, producing a lower bound. An upper bound is obtained by extending the sum-up rounding approach to multiple dimensions. For this extension, we analyze its accuracy as a function of the discretization mesh size for a rectangular domain. We show asymptotic optimality of the integer solution defining the upper bound for different experimental design criteria (A- and D-optimal), by proving the convergence to zero of the gap between the upper and lower bounds as the mesh size goes to zero. The technique is illustrated on a two-dimensional gravity surveying problem for both A-optimal and D-optimal sensor placement where our designs yield better results compared with a thresholding rounding approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Maximum Kolmogorov-Sinai Entropy Versus Minimum Mixing Time in Markov Chains

We establish a link between the maximization of Kolmogorov Sinai entropy (KSE) and the minimization of the mixing time for general Markov chains. Since the maximisation of KSE is analytical and easier to compute in general than mixing time, this link provides a new faster method to approximate the minimum mixing time dynamics. It could be interesting in computer sciences and statistical physics, for computations that use random walks on graphs that can be represented as Markov chains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Analysis of the Stress State of Hollow Cylinders with Concave Corrugated Cross Sections

In the three-dimensional statement, by the method of approximation of functions by discrete Fourier series, we perform the analysis of the dependence of the stress state of a hollow cylinder whose cross section has the form of joined concave semicorrugations subjected to the action of internal pressure under certain conditions imposed on the end faces on the thicknesses and curvatures of the cross sections of the cylinders caused by the changes in the number of semicorrugations. The results of the solution of the problem are presented in the form of the plots of distributions of the fields of displacements and stresses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Influence of the Variations of Orthotropy Parameters on the Stress State of Hollow Cylinders with Concave Corrugated Cross Sections

In the three-dimensional statement, by the method of approximation of functions by discrete Fourier series, we analyze the influence of orthotropy parameters on the stress state of hollow cylinders with cross sections in the form of connected concave semicorrugations subjected to the action of internal pressure under certain conditions on the ends. The results of investigations of the stress state are presented in the form of plots and a table.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Karhunen–Loève deep learning method for surrogate modeling and approximate Bayesian parameter estimation

We evaluate the performance of the Karhunen-Loève Deep Neural Network (KL-DNN) framework for surrogate modeling and approximate Bayesian parameter estimation in partial differential equation models. In the surrogate model, the Karhunen-Loève (KL) expansions are used for the dimensionality reduction of the number of unknown parameters and variables, and a deep neural network is employed to relate the reduced space of parameters to that of the state variables. The KL-DNN surrogate model is used to formulate a maximum-a-posteriori-like least-squares problem, which is randomized to draw samples of the posterior distribution of the parameters. We test the proposed framework for a hypothetical unconfined aquifer via comparison with the forward MODFLOW and inverse PEST++ iterative ensemble smoother (IES) solutions as well as the state-of-the-art Fourier neural operator (FNO) and deep operator networks (DeepONets) operator learning surrogate models. Our results show that the KL-DNN surrogate model outperforms FNO and DeepONet for forward predictions. For solving inverse problems, the randomized algorithm provides the same or more accurate Bayesian predictions of the parameters than IES as evidenced by the higher log-predictive probability of both the estimated parameter field and the forecast hydraulic head. The posterior mean obtained from the randomized algorithm is closer to the reference parameter field than that obtained with FNO as the maximum a posteriori estimate.

Approximate Bayesian inference↗