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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Microscopic predictions for the production of neutron-rich nuclei in the reaction Yb 176 + Yb 176

Background: Production of neutron-rich nuclei is of vital importance to both understanding nuclear structure far from stability and to informing astrophysical models of the rapid neutron capture process (r-process). Multinucleon transfer (MNT) in heavy-ion collisions offers a possibility to produce neutron-rich nuclei far from stability. Purpose: The 176 Yb + 176 Yb reaction has been suggested as a potential candidate to explore the neutron-rich region surrounding the principal fragments. The current study has been conducted with the goal of providing guidance for future experiments wishing to study this (or similar) system. Methods: Time-dependent Hartree-Fock (TDHF) and its time-dependent random-phase approximation (TDRPA) extension are used to examine both scattering and MNT characteristics in 176 Yb + 176 Yb. TDRPA calculations are performed to compute fluctuations and correlations of the neutron and proton numbers, allowing for estimates of primary fragment production probabilities. Results: Both scattering results from TDHF and transfer results from the TDRPA are presented for different energies, orvientations, and impact parameters. In addition to fragment composition, scattering angles and total kinetic energies, as well as correlations between these observables are presented. Conclusions: 176 Yb + 176 Yb appears to be an interesting probe for the midmass neutron-rich region of the chart of nuclides. Lastly, the predictions of both TDHF and TDRPA are speculative, and will benefit from future experimental results to test the validity of this approach to studying MNT in heavy, symmetric collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Effects of quasiparticle-vibration coupling on Gamow-Teller strength and 𝛽 decay with the Skyrme proton-neutron finite-amplitude method

We adapt the proton-neutron finite-amplitude method, which in its original form is an efficient implementation of the Skyrme quasiparticle random phase approximation, to include the coupling of quasiparticles to like-particle phonons. The approach allows us to add beyond-quasiparticle random-phase approximation correlations to computations of Gamow-Teller strength and 𝛽-decay rates in deformed nuclei for the first time. We test the approach in several deformed isotopes for which measured strength distributions are available. Furthermore, the additional correlations dramatically improve agreement with the data, and will lead to improved global 𝛽-decay rates.

Beta decay↗
DOE OSTI2016

Statistical Hauser-Feshbach theory with width-fluctuation correction including direct reaction channels for neutron-induced reactions at low energies

Here, a model to calculate particle-induced reaction cross sections with statistical Hauser-Feshbach theory including direct reactions is given. The energy average of the scattering matrix from the coupled-channels optical model is diagonalized by the transformation proposed by Engelbrecht and Weidenmüller [C. A. Engelbrecht and H. A. Weidenmüller, Phys. Rev. C 8, 859 (1973)]. The ensemble average of S -matrix elements in the diagonalized channel space is approximated by a model of Moldauer [P. A. Moldauer, Phys. Rev. C 12, 744 (1975)] using the newly parametrized channel degree-of-freedom ν a to better describe the Gaussian orthogonal ensemble (GOE) reference calculations. The Moldauer approximation is confirmed by a Monte Carlo study using a randomly generated S matrix, as well as the GOE threefold integration formula. Lastly, the method proposed is applied to the 238U(n,n') cross-section calculation in the fast-energy range, showing an enhancement in the inelastic scattering cross sections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Scattering of Magnons at Graphene Quantum-Hall-Magnet Junctions

Motivated by recent nonlocal transport studies of quantum-Hall-magnet (QHM) states formed in monolayer graphene’s N = 0 Landau level, here we study the scattering of QHM magnons by gate-controlled junctions between states with different integer filling factors ν . For the ν = 1 | – 1 | 1 geometry we find that magnons are weakly scattered by electric potential variation in the junction region, and that the scattering is chiral when the junction lacks a mirror symmetry. For the ν = 1 | 0 | 1 geometry, we find that kinematic constraints completely block magnon transmission if the incident angle exceeds a critical value. Our results explain the suppressed nonlocal–voltage signals observed in the ν = 1 | 0 | 1 case. We use our theory to propose that valley waves generated at ν = – 1 | 1 junctions and magnons can be used in combination to probe the spin or valley flavor structure of QHM states at integer and fractional filling factors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Real-Time Optimal Power Flow

Future power networks are expected to incorporate a large number of distributed energy resources, which introduce randomness and fluctuations as well as fast control capabilities. But traditional optimal power flow methods are only appropriate for applications that operate on a slow timescale. In this paper, we build on recent work to develop a real-time algorithm for AC optimal power flow, based on quasi-Newton methods. The algorithm uses second-order information to provide suboptimal solutions on a fast timescale, and can be shown to track the optimal power flow solution when the estimated second-order information is sufficiently accurate. We also give a specific implementation based on L-BFGS-B method, and show by simulation that the proposed algorithm has good performance and is computationally efficient.

Tang, Yujie↗
DOE OSTI2024

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-J-65: Motion Difference Between the Pancreas and Nearby Veins for Pancreas Motion Monitoring Using Ultrasound During Radiation Therapy

Purpose: As it is generally difficult to outline the pancreas on an ultrasound b-mode image, visualized structures such as the portal or the splenic veins are assumed to have the same motion as the pancreas. These structures can be used as a surrogate for monitoring pancreas motion during radiation therapy (RT) delivery using ultrasound. To verify this assumption, we studied the motion difference between the head of the pancreas, the portal vein, the tail of the pancreas, and splenic vein. Methods: 4DCT data acquired during RT simulation were analyzed for a total of 5 randomly selected patients with pancreatic cancer. The data was sorted into 10 respiratory phases from 0% to 90% (0%: end of the inspiration, 50%: end of expiration) . The head of the pancreas (HP), tail of the pancreas (TP), portal vein (PV), and splenic vein (SV) were contoured on all 10 phases. The volume change and motion were measured in the left-right (LR), anterior-superior (AP), and superior-inferior (SI) directions. Results: The volume change for all patients/phases were: 1.2 ± 3% for HP, 0.78 ± 1.6% for PV, 2.5 ± 2.9% for TP, and 0.53 ± 2.1% for SV. Motion for each structure was estimated from the centroid displacements due to the uniformity of the structures and the small volume change. The measured motion between HP and PV was: LR: 0.1 ± 0.17 mm, AP: 0.04 ± 0.1 mm, SI: 0.17 ± 0.16 mm and between TP and the PV was: LR: 0.05 ± 0.3 mm, AP: 0.1 ± 0.4 mm, SI: 0.01 ± 0.022 mm. Conclusion: There are small motion differences between the portal vein and the head of the pancreas, and the splenic vein and the tail of the pancreas. This suggests the feasibility of utilizing these features for monitoring the pancreas motion during radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Multiple trapping on a comb structure as a model of electron transport in disordered nanostructured semiconductors

A model of dispersive transport in disordered nanostructured semiconductors has been proposed taking into account the percolation structure of a sample and joint action of several mechanisms. Topological and energy disorders have been simultaneously taken into account within the multiple trapping model on a comb structure modeling the percolation character of trajectories. The joint action of several mechanisms has been described within random walks with a mixture of waiting time distributions. Integral transport equations with fractional derivatives have been obtained for an arbitrary density of localized states. The kinetics of the transient current has been calculated within the proposed new model in order to analyze time-of-flight experiments for nanostructured semiconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves

A thorough understanding of the neuroanatomy of peripheral nerves is required for a better insight into their function and the development of neuromodulation tools and strategies. In biophysical modeling, it is commonly assumed that the complex spatial arrangement of myelinated and unmyelinated axons in peripheral nerves is random, however, in reality the axonal organization is inhomogeneous and anisotropic. Present quantitative neuroanatomy methods analyze peripheral nerves in terms of the number of axons and the morphometric characteristics of the axons, such as area and diameter. In this study, we employed spatial statistics and point process models to describe the spatial arrangement of axons and Sinkhorn distances to compute the similarities between these arrangements (in terms of first- and second-order statistics) in various vagus and pelvic nerve cross-sections. We utilized high-resolution transmission electron microscopy (TEM) images that have been segmented using a custom-built high-throughput deep learning system based on a highly modified U-Net architecture. Our findings show a novel and innovative approach to quantifying similarities between spatial point patterns using metrics derived from the solution to the optimal transport problem. We also present a generalizable pipeline for quantitative analysis of peripheral nerve architecture. Our data demonstrate differences between male- and female-originating samples and similarities between the pelvic and abdominal vagus nerves.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Complex Disorder in Type-I Clathrates: Synthesis and Structural Characterization of A8GaxSn46−x (A = Rb, Cs; 6.9 < x < 7.5)

Exploratory studies in the systems Rb–Ga–Sn and Cs–Ga–Sn yielded the cubic type-I clathrates with refined compositions Rb8GaxSn46−x and Cs8GaxSn46−x (6.9 < x < 7.5). Nearly single-phase materials with good crystallinity were obtained from stoichiometric reactions of the elements. The structures were characterized by means of single-crystal X-ray diffraction methods. Both Rb8GaxSn46−x and Cs8GaxSn46−x represents cases, where a Group 13 element randomly substitutes a Group 14 element in the structure. The extent of Ga/Sn mixing is apparently governed by the drive of the system to achieve an optimal valence electron count, and hence, Rb8GaxSn46−x and Cs8GaxSn46−x (x ≈ 8) can be regarded as Zintl phases. This notion is supported by structure refinements on a multitude of single-crystal X-ray diffraction data, which also confirm that both types of cages in the cubic type-I structure are fully occupied by Rb and Cs atoms. The open-framework, comprised of 46 nodes per formula unit, adapts to the incorporation of nearly eight Ga atoms within the matrix of Sn, whereby small, short-range distortions result. The exact nature of these effects is still unclear, as so far, the structural variations could only be modeled as both positional and occupational disorder at one of three framework sites. Since vacancies in the structures of the binary type-I clathrates A8Sn46−x☐x (A = Rb, Cs; ☐ = missing Sn atom) are also known to cause local distortions, the latter were also synthesized with the same protocols used for the synthesis of A8GaxSn46−x and structurally re-analyzed. The results from the latter studies confirm that homogeneity issues abound, and that the final structures/compositions are an intricate function of the experimental conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Implementation of Dynamic Extensible Adaptive Locally Exchangeable Measures (IDEALEM) v 0.1

Handling large streaming data is essential for various applications such as network traffic analysis, social networks, energy cost trends, and environment modeling. However, it is in general intractable to store, compute, search, and retrieve large streaming data. This software addresses a fundamental issue, which is to reduce the size of large streaming data and still obtain accurate statistical analysis. As an example, when a high-speed network such as 100 Gbps network is monitored, the collected measurement data rapidly grows so that polynomial time algorithms (e.g., Gaussian processes) become intractable. One possible solution to reduce the storage of vast amounts of measured data is to store a random sample, such as one out of 1000 network packets. However, such static sampling methods (linear sampling) have drawbacks: (1) it is not scalable for high-rate streaming data, and (2) there is no guarantee of reflecting the underlying distribution. In this software, we implemented a dynamic sampling algorithm, based on the recent technology from the relational dynamic bayesian online locally exchangeable measures, that reduces the storage of data records in a large scale, and still provides accurate analysis of large streaming data. The software can be used for both online and offline data records.

Sim, Alex↗
DOE OSTI2020

3-D Radiological Data Acquisition, Visualization and Modeling - 20211

The U.S. Army Corps of Engineers (USACE) was tasked to investigate and remediate low activity radiological contamination from research and production of the nation's first nuclear weapons at the former DuPont Chambers Works Formerly Utilized Sites Remedial Action Program (FUSRAP) site (DuPont). The DuPont site had several buildings used for the Manhattan project that were demolished in the 1940's and 1950's apparently using heavy earthmoving equipment. Some of the contaminated rubble from the demolition appears to have been spread out by this equipment resulting in somewhat random scattering of radiologically contaminated soil and debris along with aqueous spills. Traditional investigative methods such as soil borings, test pits and 2-dimensional gamma walkovers were only partially successful in delineating the radiological contamination at the site. It was feared that even 'chasing' the contamination during remediation would miss contamination if the demolition resulted in discontinuous trails of radiologically contaminated soils. In evaluating the data generated over the interceding decades, the USACE determined that a better method to collect and process the remedial action radiological data was needed to enable the project team to optimize predictive planning and meet documentation expectations. The purpose of this paper is to provide an overview of the effort and progress to combine and organize radiological survey methods into a highly flexible sampling, modeling, and decision analysis approach that emphasizes the quality of decision-making during remediation. This innovative system blends multiple tools to develop a methodology that can extend MARRSIM [1] into the subsurface and provide tools that can be applied to other sites. (authors)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Guided basin-hopping search of small boron clusters with density functional theory

The search for the ground state structures of Boron clusters has been a difficult computational task due to the unique metalloid nature of Boron atom. Previous research works had overcome the problem in the search of the Boron ground-state structures by adding symmetry constraints prior to the process of locating the local minima in the potential energy surface (PES) of the Boron clusters. In this work, we shown that, with the deployment of a novel computational approach that incorporates density functional theory (DFT) into a guided global optimization search algorithm based on basin-hopping, it is possible to directly locate the local minima of small Boron clusters in the PES at the DFT level. The ground-state structures search algorithm as proposed in this work is initiated randomly and needs not a priori symmetry constraint artificially imposed throughout the search process. Small sized Boron clusters so obtained compare well to the results obtained by similar calculations in the literature. The electronic properties of each structures obtained are calculated within the DFT framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A Machine Learning Approach to Quantitative Analysis of Enamel Microstructure from Scanning Electron Microscopy Images

Dental enamel, the outermost tissue of mammalian teeth, must withstand a lifetime of wear and cyclic contact. To meet this demand, enamel possesses a combination of high hardness and resistance to fracture, properties that are typically mutually exclusive. The impressive damage tolerance has been attributed largely to decussation of the enamel rods, the principal unit of its microstructure. As such, enamel is inspiring the design of next‐generation structural materials. However, quantitative descriptions of the decussated enamel rod microstructure remain limited due to challenges encountered in applying computed tomography and in acquiring quality images appropriate for traditional digital processing methods. Here, a machine learning segmentation method is applied to images of the enamel obtained using scanning electron microscopy to support quantitative analysis of the microstructure. A pretrained convolutional neural network is used to expand the input training image dataset to allow the training of a random forest classifier, which ultimately segments the image with a very small training set ( n = 3 images). A validation of this segmentation method is presented, in addition to its application to calculate relevant microstructural parameters for images of tooth enamel from selected mammalian species. The methodology applied here is equally applicable to other hard tissues.

36 MATERIALS SCIENCE↗
DOE OSTI2016

The transport of suspended sediment in the wake of a marine hydrokinetic turbine: Simulations via a validated Discrete Random Walk (DRW) model

The interaction of sediment with Marine Hydrokinetic (MHK) Turbines is studied via turbulent flow simulation coupled with a model for particle dynamics. The Discrete Random Walk (DRW) model is commonly used for simulations of particle dispersion in environmental flows. A method to improve the accuracy of the DRW model in conjunction with RANS simulations of the flow around MHK turbines is presented. A key issues for the use of the DRW model in marine applications is identified, finding the right characteristic eddy lifetime scale, and a simple methodology based on G.I. Taylor's classical dispersion theory is develop to calibrate this physical model parameter. The model is validated against experiments in the literature and the physics of suspended sediment transport in the wake of an MHK turbine is studied with this improved method. The qualitative changes observed in the particle trajectories agree well with theoretical and empirical observations and the quantitive trends allow for comparison of multiple particle cases under different flow conditions, confirming that this implementation of CFD can become a powerful tool to select the most challenging cases, among the thousands of potential studies on the environmental effects of MHK energy, for further study with experiments and pilot projects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Learning planar Ising models

Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Synthetic High Impedance Fault Data through Deep Convolutional Generated Adversarial Network

High impedance faults (HIFs) have always been significant challenge in the power grids. Researchers have developed some advanced protective methods to detect the HIFs. To test and validate these methods, large amounts of HIF data are required. This paper presents a synthetic HIF data generating method using the deep convolutional generated adversarial network (DCGAN). The DCGAN includes a generator module to create synthetic HIF waveform from random noises; and a discriminator module to identify the flaws of those synthetic data, which ultimately help improve the quality of the synthetic data created by the generator. To test the fidelity of the generated synthetic HIF data, two different HIF-detection methods have been applied. Extensive simulation results have validated the effectiveness of using the DCGAN to create synthetic HIF data.

Yang, Kun↗
DOE OSTI2015

Radon detection in conical diffusion chambers: Monte Carlo calculations and experiment

The operation of radon detection diffusion chambers of truncated conical shape was studied using Monte Carlo calculations. The efficiency was studied for alpha particles generated randomly in the volume of the chamber, and progeny generated randomly on the interior surface, which reach track detectors placed in different positions within the chamber. Incidence angular distributions, incidence energy spectra and path length distributions are calculated. Cases studied include different positions of the detector within the chamber, varying atmospheric pressure, and introducing a cutoff incidence angle and energy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗