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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Stellar Wakes from Dark Matter Subhalos

Here we propose a novel method utilizing stellar kinematic data to detect low-mass substructure in the Milky Way’s dark matter halo. By probing characteristic wakes that a passing dark matter subhalo leaves in the phase-space distribution of ambient halo stars, we estimate sensitivities down to subhalo masses of ∼10 7 M ⊙ or below. The detection of such subhalos would have implications for dark matter and cosmological models that predict modifications to the halo-mass function at low halo masses. We develop an analytic formalism for describing the perturbed stellar phase-space distributions, and we demonstrate through idealized simulations the ability to detect subhalos using the phase-space model and a likelihood framework. Our method complements existing methods for low-mass subhalo searches, such as searches for gaps in stellar streams, in that we can localize the positions and velocities of the subhalos today.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

DC Arc Incident Energy in Photovoltaic Systems: Methods for Evaluation

Renewable energy systems continue to be one of the fastest growing segments of the energy industry. This article focuses on the understanding of how photovoltaic (PV) technology behaves under dc arc conditions. Emphasis is placed on the electrical safety aspect of dc arc-flash incident energy (IE) evaluation. Because of the fast proliferation of PV systems and lack of formal equivalent calculation guidelines, such as IEEE 1584 for ac systems, it has been necessary to rely on different equations and models presented by various researchers over the last few years. This article discusses the behavior of PV systems under arc conditions and presents the results of the available methods to estimate the dc arc-flash IE. It provides a comparative analysis of a proposed arc-flash IE calculation method against different laboratory tests, including those performed for this article at the National Renewable Energy Laboratory (NREL). Detailed explanations are provided regarding the effect of the PV module current-voltage (I-V) and power-voltage (P-V) curves under arcing conditions. Examples of the application of the proposed calculation method to the test measurements are included.

arc discharges↗
DOE OSTI2022

Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations

Optimal experimental design (OED) is the general formalism of sensor placement and decisions on the data collection strategy for engineered or natural experiments. This problem is prevalent in many critical fields such as battery design, numerical weather prediction, geosciences, environmental and urban studies. State-of-the-art computational methods for experimental design do not accommodate correlation structure in observational errors produced by many expensive-to-operate devices such as X-ray machines, radars, and satellites. Discarding evident data correlations leads to biased results, higher expenses, and waste of valuable resources. We present a general formulation of the OED formalism for model-constrained large-scale Bayesian linear inverse problems, where measurement errors are generally correlated. The proposed approach utilizes the Hadamard product of matrices to formulate the weighted-likelihood, and is valid for both finite as well as infinite-dimensional Bayesian inverse problems. Extensive numerical experiments are carried out for empirical verification of the proposed approach using an advection-diffusion model, where the objective is to optimally place a small set of sensors, under a limited budget, to predict the concentration of a contaminant in a closed and bounded domain.

Correlated observations↗
DOE OSTI2021

Explicit physics-informed neural networks for nonlinear closure: The case of transport in tissues

In upscaling methods, closures for nonlinear problems present a well-known challenge. While a number of theoretical methods have been proposed for handling such closures, nonlinearities still remain a significant obstacle for many problems. In this work, we use a combination of formal upscaling and data-driven machine learning for explicitly closing a nonlinear transport and reaction process in multiscale tissues. The classical effectiveness factor model is used to formulate the macroscale reaction kinetics. We train a multilayer perceptron network using training data generated by direct numerical simulations over microscale examples. Once trained, the network is used in an algorithm for numerically solving the upscaled (coarse-grained) differential equation describing mass transport and reaction in two example tissues. The network is described as being explicit in the sense that the network is trained using macroscale concentrations and gradients of concentration as components of the feature space rather than incorporating them as part of a constraint in the optimization process. Network training and solutions to the macroscale transport equations were computed for two different tissues. The two tissue types (brain and liver) exhibit markedly different geometrical complexity and spatial scale (cell size and sample size). The upscaled solutions for the average concentration are compared with numerical solutions derived from the microscale concentration fields by a posteriori averaging. There are three outcomes of this work of particular note. 1) Our overall approach results in an upscaled nonlinear PDE. The PDE is closed using a neural network, and our approach results in the definition of the classical effectiveness factor for effecting closure. 2) We identify particular source terms for the closure problem that are important for representing the structure of the closure. These source terms involve macroscale concentrations and their gradients. We adopt these source terms to use as explicit features in the learning algorithm. We find the trained networks that include the macroscale source terms generate models that are able to predict the correction factor with increased fidelity over those that do not. 3) We find that the trained network exhibits good generalizability, and it is able to predict the effectiveness factor with high fidelity for realistically-structured tissues despite the significantly different scale and geometrical complexity of the two example tissue types. This latter result emphasizes our purposeful connection between conventional averaging methods with the use of machine learning for closure; this contrasts with some machine learning methods for upscaling where the exact form of the macroscale equation remains unknown.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

TU-F-BRE-03: Application of a Novel Mass-Density Compensation Optimization Method to Improve the Response of a Liquid-Filled Ionization Chamber in Nonstandard Fields

Purpose: To improve the response of the microLion detector (PTW 31018) in small field conditions by optimizing the density of the detector's non-sensitive components using a novel method based on the detector's dose response function. Methods: The central values h(0,0) of the perturbation functions for the microLion detector and a volume of water equivalent to its sensitive volume were calculated using the Monte Carlo user code egs-chamber by scoring the dose absorbed by a 6 MV photon pencil beam incident on their centroids. Values of h(0,0) were plotted as a function of the density of the microLion's graphite electrode with the detector placed in the axial orientation. The optimized density was found by finding the minimal value of h(0,0). Results: A density of 1.37 g/cm3 was found to minimize the perturbation function of the microLion detector. The modified microLion's response was then evaluated in small square fields with sides in the range of 5 – 40 mm and found to be consistent with highly watere-quivalent detectors such as a scintillating detector (Exradin W1) and a generic alanine detector in both axial and radial orientations. Conclusion: This work illustrates a novel method which can used to optimize the design of radiation detectors in small fields. This method should also work with other optimization parameters (e.g. thickness of electrode). Density-compensated detectors have the potential to eliminate the need to evaluate nonstandard field correction factors as described by the IAEA-AAPM formalism (Alfonso et al.) and simplify future dosimetry protocols for SRS/SBRT modalities. Finally, we also expect an improvement in the response of density-compensated detectors for composite IMRT fields.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Revisiting the assignment of atomic charges in metal oxides based on core-level x-ray photoelectron spectra: The case of Ti in SrTiO3(001)

We demonstrate that assigning formal charges to transition metal (TM) cations based on core-level (CL) x-ray photoemission binding energies in oxides leads to physically inconsistent pictures of electronic structure. O 2p–TM 3d hybridization is well known to result in significant covalency in TM–O bonds, thereby reducing TM cation charges from their fully ionic values. However, the ionic bonding model remains the working paradigm for assigning TM CL features, and the resulting cation charges are often taken to be representative of the material under study. Here, we show that a more physically meaningful way to assign charges is to extract information about charge distributions utilizing Dirac–Hartree–Fock theory to calculate CL spectra from first principles and then use the resulting wave functions to determine charges based on orbital occupancies. TM cation charges can also be determined using density functional theory and Bader population analysis. We illustrate these two methods using the Ti 2p spectrum for SrTiO3(001) and show that the agreement between them is excellent. Significantly, the resulting Ti charge is considerably lower than the formal charge. The high degree of similarity between the Ti 2p spectrum for SrTiO3 and those for the rutile and anatase polymorphs of TiO2 suggests that the charge densities surrounding Ti in the latter materials are similar to that in SrTiO3. Taking a broader perspective, oxides containing other first-row transition metals also exhibit covalent character, leading to TM cation charges lower than the analogous fully ionic values in these materials as well.

Chambers, Scott A. (ORCID:000000025415043X)↗
DOE OSTI2015

Förster resonance energy transfer, absorption and emission spectra in multichromophoric systems. III. Exact stochastic path integral evaluation

A numerically exact path integral treatment of the absorption and emission spectra of open quantum systems is presented that requires only the straightforward solution of a stochastic differential equation. The approach converges rapidly enabling the calculation of spectra of large excitonic systems across the complete range of system parameters and for arbitrary bath spectral densities. With the numerically exact absorption and emission operators, one can also immediately compute energy transfer rates using the multi-chromophoric Förster resonant energy transfer formalism. Benchmark calculations on the emission spectra of two level systems are presented demonstrating the efficacy of the stochastic approach. This is followed by calculations of the energy transfer rates between two weakly coupled dimer systems as a function of temperature and system-bath coupling strength. It is shown that the recently developed hybrid cumulant expansion (see Paper II) is the only perturbative method capable of generating uniformly reliable energy transfer rates and emission spectra across a broad range of system parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Regioselective Arene C−H Alkylation Enabled by Organic Photoredox Catalysis

Abstract Expanding the toolbox of C−H functionalization reactions applicable to the late‐stage modification of complex molecules is of interest in medicinal chemistry, wherein the preparation of structural variants of known pharmacophores is a key strategy for drug development. One manifold for the functionalization of aromatic molecules utilizes diazo compounds and a transition‐metal catalyst to generate a metallocarbene species, which is capable of direct insertion into an aromatic C−H bond. However, these high‐energy intermediates can often require directing groups or a large excess of substrate to achieve efficient and selective reactivity. Herein, we report that arene cation radicals generated by organic photoredox catalysis engage in formal C−H functionalization reactions with diazoacetate derivatives, furnishing sp 2 –sp 3 coupled products with moderate‐to‐good regioselectivity. In contrast to previous methods utilizing metallocarbene intermediates, this transformation does not proceed via a carbene intermediate, nor does it require the presence of a transition‐metal catalyst.

Holmberg‐Douglas, Natalie↗
DOE OSTI2020

Regioselective Arene C−H Alkylation Enabled by Organic Photoredox Catalysis

Abstract Expanding the toolbox of C−H functionalization reactions applicable to the late‐stage modification of complex molecules is of interest in medicinal chemistry, wherein the preparation of structural variants of known pharmacophores is a key strategy for drug development. One manifold for the functionalization of aromatic molecules utilizes diazo compounds and a transition‐metal catalyst to generate a metallocarbene species, which is capable of direct insertion into an aromatic C−H bond. However, these high‐energy intermediates can often require directing groups or a large excess of substrate to achieve efficient and selective reactivity. Herein, we report that arene cation radicals generated by organic photoredox catalysis engage in formal C−H functionalization reactions with diazoacetate derivatives, furnishing sp 2 –sp 3 coupled products with moderate‐to‐good regioselectivity. In contrast to previous methods utilizing metallocarbene intermediates, this transformation does not proceed via a carbene intermediate, nor does it require the presence of a transition‐metal catalyst.

Holmberg‐Douglas, Natalie↗
DOE OSTI2018

Validation of Statistical Uncertainties in Subcritical Benchmark Measurements: Part I - Theory and Simulations

Subcritical neutron noise measurements are often used to determine multiplication of a system with Special Nuclear Material. This work presents an uncertainty approach which incorporates the singles and doubles counting rates determined by the Hage-Cifarelli formalism. This is a moments-based approach which utilizes time correlations between prompt neutrons in order to assess the system multiplication. After the method is described, a validation is presented which utilizes simulated data generated using a 0-D point-kinetics Monte Carlo code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Structural search for stable Mg–Ca alloys accelerated with a neural network interatomic model

Here, we have combined a neural network formalism with metaheuristic structural global search algorithms to systematically screen the Mg–Ca binary system for new (meta)stable alloys. The combination of these methods allows for an efficient exploration of the potential energy surface beyond the possibility of the traditional searches based on ab initio energy evaluations. The identified pool of low-enthalpy structures was complemented with special quasirandom structures (SQS) at different stoichiometries. In addition to the only Mg–Ca phase known to form under standard synthesis conditions, C14-Mg 2 Ca, the search has uncovered several candidate materials that could be synthesized under elevated temperatures or pressures. We demonstrate that the vibrational entropy lowers the relative free energy of several phases with magnesium kagome layers: C15 and C36 Laves structures at the 2:1 composition and an orthorhombic oS36 structure at the 7:2 composition. The estimated phase transition temperatures close to the melting point leave open the possibility of synthesizing the predicted materials at high temperatures. At high pressures up to 10 GPa, two new phases at the 1:1 and 3:1 Mg:Ca stoichiometries become thermodynamically stable and should form in multi-anvil experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

How to calculate linear absorption spectra with lifetime broadening using fewest switches surface hopping trajectories: A simple generalization of ground-state Kubo theory

In this paper, we develop a surface hopping approach for calculating linear absorption spectra using ensembles of classical trajectories propagated on both the ground and excited potential energy surfaces. We demonstrate that our method allows the dipole-dipole correlation function to be determined exactly for the model problem of two shifted, uncoupled harmonic potentials with the same harmonic frequency. For systems where nonadiabatic dynamics and electronic relaxation are present, preliminary results show that our method produces spectra in better agreement with the results of exact quantum dynamics calculations than spectra obtained using the standard ground-state Kubo formalism. As such, our proposed surface hopping approach should find immediate use for modeling condensed phase spectra, especially for expensive calculations using ab initio potential energy surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Algebraic solutions of shape-invariant position-dependent effective mass systems

Keeping in view the ordering ambiguity that arises due to the presence of position-dependent effective mass in the kinetic energy term of the Hamiltonian, a general scheme for obtaining algebraic solutions of quantum mechanical systems with position-dependent effective mass is discussed. We quantize the Hamiltonian of the pertaining system by using symmetric ordering of the operators concerning momentum and the spatially varying mass, initially proposed by von Roos and Lévy-Leblond. The algebraic method, used to obtain the solutions, is based on the concepts of supersymmetric quantum mechanics and shape invariance. In order to exemplify the general formalism a class of non-linear oscillators has been considered. This class includes the particular example of a one-dimensional oscillator with different position-dependent effective mass profiles. Explicit expressions for the eigenenergies and eigenfunctions in terms of generalized Hermite polynomials are presented. Moreover, properties of these modified Hermite polynomials, like existence of generating function and recurrence relations among the polynomials have also been studied. Furthermore, it has been shown that in the harmonic limit, all the results for the linear harmonic oscillator are recovered.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Electricity consumption patterns within cities: application of a data-driven settlement characterization method

Urban areas presently consume around 75% of global primary energy supply, which is expected to significantly increase in the future due to urban growth. Having sustainable, universal energy access is a pressing challenge for most parts of the globe. Understanding urban energy consumption patterns may help to address the challenges to urban sustainability and energy security. However, urban energy analyses are severely limited by the lack of urban energy data. Such datasets are virtually non-existent for the developing countries. As per current projections, most of the new urban growth is bound to occur in these data-starved regions. Hence, there is an urgent need of research methods for monitoring and quantifying urban energy utilization patterns. Here, we apply a data-driven approach to characterize urban settlements based on their formality, which is then used to assess intra-urban urban energy consumption in Johannesburg, South Africa; Sana’a, Yemen; and Ndola, Zambia. Electricity is the fastest growing energy fuel. By analyzing the relationship between the settlement types and the corresponding nighttime light emission, a proxy of electricity consumption, we assess the differential electricity consumption patterns. Our study presents a simple and scalable solution to fill the present data void to understand intra-city electricity consumption patterns.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Quantifying Energetics of Topological Frustration in Carbon Nanostructures

We develop a graph theoretical formalism to account for the fact that sp2 carbon can become spin ordered or generate free radicals for purely topological reasons. The graph theory method is combined with open-density-functional theory calculations to establish the existence of a universal energy of frustration term that is shown to greatly improve the description of carbon nanostructure energetics using classical force-fields. The methodology is illustrated for a number of systems and, owing to the small computational overhead associated, is shown to be easily integratable into any modeling approach based on an adjacency matrix.

Bullard, Zachary↗
DOE OSTI2021

Facile ab initio approach for self-localized polarons from canonical transformations

Electronic states in a crystal can localize due to strong electron-phonon (e-ph) interactions, forming so-called small polarons. Methods to predict the formation and energetics of small polarons are either computationally costly or not geared toward quantitative predictions. Here we show a formalism based on canonical transformations to compute the polaron formation energy and wave function using ab initio e-ph interactions. Comparison of the calculated polaron and band-edge energies allows us to determine whether charge carriers in a material favor a localized small polaron over a delocalized Bloch state. Due to its low computational cost, our approach enables efficient studies of the formation and energetics of small polarons, as we demonstrate by investigating electron and hole polaron formation in alkali halides and metal oxides and peroxides. We outline refinements of our scheme and extensions to compute transport in the polaron hopping regime.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Anomaly Detection in Gamma Spectra Using Hopfield Neural Network with B-SAT and Grover’s Algorithm on a Quantum Computing Simulator

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. In principle, gamma radiation sources can be detected and identified by their unique spectral lines. However, detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. In recent prior work, we have developed a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm to detect a weak signal anomaly hidden among the highly fluctuating background spectra. The objective of this work is to explore quantum computing methods to increase the speed of HNN. The approach is based on the Grover’s search algorithm in conjunction with a 3-SAT problem formalism. The Grover’s algorithm is implemented on a quantum computing simulator using Qiskit software. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign, where the anomaly is a subset of measurements containing a 137 Cs source. Results indicate that using Grover’s algorithm on a quantum simulator reduces runtime of HNN by two orders of magnitude.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Assessment of Methods to Control Invasive Reed Canarygrass (Phalaris arundinacea) in Tidal Freshwater Wetlands

Controlling non-native invasive species is a significant challenge facing natural area managers in North America and around the world. Reed canarygrass (Phalaris arundinacea), is invasive in temperate freshwater wetlands throughout the United States and Canada. While methods for the prevention or elimination of reed canarygrass are generally well established, methods suitable for the unique conditions in tidal wetlands remain poorly understood. Namely, prolonged inundation of tidal wetlands for control purposes may only be accomplished with a concomitant loss of habitat connectivity and other functions. Restoration practitioners aiming to design self-sustaining wetlands in the lower Columbia River and estuary, on the northwestern Pacific Coast, have found that reed canarygrass is widespread and quick to establish throughout the 176-river-kilometer tidal freshwater floodplain. Here we report the results of a comprehensive effort to develop the knowledge base for control in tidal wetlands, through systematic review of the scientific literature, interviews with experienced practitioners, and field observations at nine Pacific Northwest sites. The review framework incorporated practical considerations and key environmental conditions: elevation related to hydrologic regime, salinity, shade, and nutrient availability. The results support implementation of multiple methods for a minimum of five years, on the largest possible area, ideally the watershed scale. Applicable methods include control in advance of restoration, topographic modification such as scrape-downs and mounds; establishing strong native competitors; and periodic, targeted control. Formal field experiments are needed to evaluate factors that influence control. Developing science-based, effective, practicable approaches to control reed canarygrass should improve restoration outcomes in natural areas.

intertidal, invasive, Phalaris arundinacea, reed c↗