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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Distribution of genetic variation underlying adult migration timing in steelhead of the Columbia River basin

Abstract Fish migrations are energetically costly, especially when moving between freshwater and saltwater, but are a viable strategy for Pacific salmon and trout ( Oncorhynchus spp.) due to the advantageous resources available at various life stages. Anadromous steelhead ( O. mykiss ) migrate vast distances and exhibit variation for adult migration phenotypes that have a genetic basis at candidate genes known as greb1L and rock1 . We examined the distribution of genetic variation at 13 candidate markers spanning greb1L , intergenic, and rock1 regions versus 226 neutral markers for 113 populations ( n = 9,471) of steelhead from inland and coastal lineages in the Columbia River. Patterns of population structure with neutral markers reflected genetic similarity by geographic region as demonstrated in previous studies, but candidate markers clustered populations by genetic variation associated with adult migration timing. Mature alleles for late migration had the highest frequency overall in steelhead populations throughout the Columbia River, with only 9 of 113 populations that had a higher frequency of premature alleles for early migration. While a single haplotype block was evident for the coastal lineage, we identified multiple haplotype blocks for the inland lineage. The inland lineage had one haplotype block that corresponded to candidate markers within the greb1L gene and immediately upstream in the intergenic region, and the second block only contained candidate markers from the intergenic region. Haplotype frequencies had similar patterns of geographic distribution as single markers, but there were distinct differences in frequency between the two haplotype blocks for the inland lineage. This may represent multiple recombination events that differed between lineages where phenotypic differences exist between freshwater entry versus arrival timing as indicated by Micheletti et al. (2018a). Redundancy analyses were used to model environmental effects on allelic frequencies of candidate markers, and significant variables were migration distance, temperature, isothermality, and annual precipitation. This study improves our understanding of the spatial distribution of genetic variation underlying adult migration timing in steelhead as well as associated environmental factors and has direct conservation and management implications.

Collins, Erin E.↗
DOE OSTI2024

e RPCA : Robust Principal Component Analysis for Exponential Family Distributions

Abstract Robust principal component analysis (RPCA) is a widely used method for recovering low‐rank structure from data matrices corrupted by significant and sparse outliers. These corruptions may arise from occlusions, malicious tampering, or other causes for anomalies, and the joint identification of such corruptions with low‐rank background is critical for process monitoring and diagnosis. However, existing RPCA methods and their extensions largely do not account for the underlying probabilistic distribution for the data matrices, which in many applications are known and can be highly non‐Gaussian. We thus propose a new method called RPCA for exponential family distributions (), which can perform the desired decomposition into low‐rank and sparse matrices when such a distribution falls within the exponential family. We present a novel alternating direction method of multiplier optimization algorithm for efficient decomposition, under either its natural or canonical parametrization. The effectiveness of is then demonstrated in two applications: the first for steel sheet defect detection and the second for crime activity monitoring in the Atlanta metropolitan area.

Zheng, Xiaojun↗
DOE OSTI2020

Numerical investigation of micro-galvanic corrosion in Mg alloys: Role of the cathodic intermetallic phase size and spatial distributions

Magnesium alloys are of increasing interest in structural applications due to their low-density, moderate specific strength and stiffness, recyclability, and high damping among other properties. However, the wide-scale applicability of magnesium alloys in structural applications has been limited due to many factors including its poor corrosion resistance. In this work, a numerical investigation to simulate the micro-galvanic corrosion behavior was performed to examine the influence of size and distribution of cathodic intermetallic phase (ß-Mg17Al12) in a Mg matrix. The ratio of cathodic to anodic surface area was kept constant in each simulation condition to understand the effect of size and spacing distributions. In general, fragmentation of a larger intermetallic particle into smaller ones was found to enhance the localized current density. However, the uniform distribution of this small intermetallic phase throughout the matrix was found to reduce the overall dissolution current density and hence, pitting corrosion severity.

Beura, Vikrant↗
DOE OSTI2020

Distributions in CFT. Part I. Cross-ratio space

We show that the four-point functions in conformal field theory are defined as distributions on the boundary of the region of convergence of the conformal block expansion. The conformal block expansion converges in the sense of distributions on this boundary, i.e. it can be integrated term by term against appropriate test functions. This can be interpreted as a giving a new class of functionals that satisfy the swapping property when applied to the crossing equation, and we comment on the relation of our construction to other types of functionals. Our language is useful in all considerations involving the boundary of the region of convergence, e.g. for deriving the dispersion relations. We establish our results by elementary methods, relying only on crossing symmetry and the standard convergence properties of the conformal block expansion. This is the first in a series of papers on distributional properties of correlation functions in conformal field theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Jet fragmentation transverse momentum distributions in pp and p-Pb collisions at $ \sqrt{s}$, $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV

Jet fragmentation transverse momentum ( j T ) distributions are measured in proton-proton (pp) and proton-lead (p-Pb) collisions at s NN = 5 . 02 TeV with the ALICE experiment at the LHC. Jets are reconstructed with the ALICE tracking detectors and electromagnetic calorimeter using the anti- k T algorithm with resolution parameter R = 0 . 4 in the pseudorapidity range |η| < 0 . 25. The j T values are calculated for charged particles inside a fixed cone with a radius R = 0 . 4 around the reconstructed jet axis. The measured j T distributions are compared with a variety of parton-shower models. Herwig and P ythia 8 based models describe the data well for the higher j T region, while they underestimate the lower j T region. The j T distributions are further characterised by fitting them with a function composed of an inverse gamma function for higher j T values (called the “wide component”), related to the perturbative component of the fragmentation process, and with a Gaussian for lower j T values (called the “narrow component”), predominantly connected to the hadronisation process. The width of the Gaussian has only a weak dependence on jet transverse momentum, while that of the inverse gamma function increases with increasing jet transverse momentum. For the narrow component, the measured trends are successfully described by all models except for Herwig. For the wide component, Herwig and PYTHIA 8 based models slightly underestimate the data for the higher jet transverse momentum region. These measurements set constraints on models of jet fragmentation and hadronisation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Adversarial classification via distributional robustness with Wasserstein ambiguity

Abstract We study a model for adversarial classification based on distributionally robust chance constraints. We show that under Wasserstein ambiguity, the model aims to minimize the conditional value-at-risk of the distance to misclassification, and we explore links to adversarial classification models proposed earlier and to maximum-margin classifiers. We also provide a reformulation of the distributionally robust model for linear classification, and show it is equivalent to minimizing a regularized ramp loss objective. Numerical experiments show that, despite the nonconvexity of this formulation, standard descent methods appear to converge to the global minimizer for this problem. Inspired by this observation, we show that, for a certain class of distributions, the only stationary point of the regularized ramp loss minimization problem is the global minimizer.

Ho-Nguyen, Nam (ORCID:0000000344647730)↗
DOE OSTI2022

Mascon distribution techniques for asteroids and comets

The mass-concentration model is an approach that has been used to model the gravitational fields of irregularly shaped bodies such as asteroids and comets. By this approach, the body is treated as a collection of point masses. The method is conceptually simple, easy to program, valid down to the surface, and capable of modeling arbitrary density heterogeneities. How the mass concentrations are distributed as well as how mass is assigned to these concentrations is, however, nontrivial. These aspects significantly affect the accuracy and efficiency of the gravitational model. In this paper, we frame the distribution process in terms of numerical integration applied to finite volume meshes. We describe a new method using unstructured, curvilinear, finite volume meshes to significantly improve the accuracy of the mass-concentration model. We then compare the accuracy and efficiency of several variations of our distribution technique to those from literature using Asteroid Eros and Bennu as example bodies. Our results show that the mascon model can be as accurate as the analytic polyhedral model at the surface using an equivalent number of computational elements—i.e., mascon to surface facets. We report the improvement in the model’s performance can be mainly attributed to the volume mesh topology while mesh curving can provide modest case-dependent improvements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Measurement of distribution coefficients on TODGA resin and development of a group separation for mixed activation and fission product samples

Batch equilibrium experiments were performed to determine the distribution coefficients for Sc, Ir, and Ta on N,N,N’,N’tetraoctyl-1,5-diglycolamide (TODGA) resin in various acid matrices. Distribution coefficients were determined in hydrochloric acid (Sc, Ir), nitric acid (Sc, Ta), and a mixture of nitric acid and 0.2M hydrofluoric acid (Sc, Ir, Ta). The distribution coefficients determined through these experiments were then utilized to create a group separation method for activation products, fission products, and environmental constituents.

Louie, Christina A.↗
DOE OSTI2023

Pseudo-rapidity distributions of charged particles in asymmetric collisions using Tsallis thermodynamics

Abstract The pseudo-rapidity distributions of the charged particles produced in the asymmetric collision systems p+Al, p+Au and$$^3$$ 3 He+Au at$$\sqrt{s_\text {NN}} = 200$$ s NN = 200 GeV are evaluated in the framework of a fireball model with Tsallis thermodynamics. The fireball model assumes that the experimentally measured particles are produced by fireballs following the Tsallis distribution and it can effectively describe the experimental data. Our results as well as previous results for d+Au collisions at$$\sqrt{s_\text {NN}} = 200$$ s NN = 200 GeV and p+Pb collisions at$$\sqrt{s_\text {NN}} = 5.02$$ s NN = 5.02 TeV validate that the fireball model based on Tsallis thermodynamics can provide a universal framework for pseudo-rapidity distribution of the charged particles produced in asymmetric collision systems. We predict the centrality dependence of the total charged particle multiplicity in the p+Al, p+Au and$$^3$$ 3 He+Au collisions. Additionally, the dependences of the fireball model parameters ($$y_{0a}$$ y 0 a ,$$y_{0A}$$ y 0 A ,$$\sigma _{a}$$ σ a and$$\sigma _{A}$$ σ A ) on the centrality and system size are studied.

Nuclear Science & Technology↗
DOE OSTI2025

On the distribution of stacking faults at dissociated medium-angle grain boundaries: Crystallographic geometry and metastability

Grain boundaries in FCC metals with low stacking-fault energy can form in dissociated configurations of stacking faults. Perhaps the most studied example is 9R stacking at boundaries near Σ3{112}, where the distribution of stacking faults is related to the emission of Shockley partial dislocations. Here, we combine atomic-resolution electron microscopy, atomistic simulations, and dislocation theory to demonstrate that boundaries vicinal to Σ33a support the stabilization of dissociated 9R stacking within a narrow range of inclinations. This boundary is interesting since its misorientation (20.05°) lies in the medium-angle regime, just past the upper misorientation limit for low-angle boundaries, motivating questions for how best to describe it in terms of dislocations. Our HAADF-STEM observations of thin film bicrystals, supported by atomistic modeling, reveal that this inclination dependence arises from specific geometric constraints on the arrangement of Shockley partial dislocations at the interface. Quantification of stacking-fault distributions across multiple boundaries indicates that the density and spacing of faults closely follow the ideal 9R motif, with subtle variations reflecting the complex energy landscape of these boundaries. Through energetic analysis, we establish the presence of competing metastable states enabled by variations in stacking sequences, emphasizing the significant role of crystallographic geometry. We generalize our analysis as a function of misorientation, showing how 9R at the Σ33a boundary is related to previous observations and calculations of HCP at a 29.7° boundary. This study provides a crystallographically grounded framework connecting dislocation structures, stacking-fault distributions, and metastability at grain boundaries in FCC metals.

Atomistic modeling↗
DOE OSTI2022

Impact of model predictive control-enabled home energy management on large-scale distribution systems with photovoltaics

Residential customers use more than one-quarter of the electricity in the world. Optimally managing home energy consumption is an effective way of easing the operational challenges facing the electric grid with increasing solar photovoltaics (PV). This paper studies the impact of the future proliferation of home energy management systems (HEMS) in the presence of PV on large-scale distribution systems. First, we present a stochastic HEMS model that minimizes residential customers' thermal discomfort and energy costs under uncertainty. The HEMS model schedules the optimal operations of residential appliances in the presence of PV within a mixed-integer linear programming-based model predictive control framework that links the proposed HEMS to a quasi-steady-state time-series simulation tool. Additionally, extensive simulations are conducted for a stand-alone residential home using two tariff structures and for 1977 homes on an 8,500-node distribution feeder. Simulation results quantify the impact of the future proliferation of HEMS on the large-scale distribution system with PV.

14 SOLAR ENERGY↗
DOE OSTI2023

Cost analysis of distributed storage in AC and DC microgrids

Building and microgrid designs with highly-distributed electrical storage have potential advantages over today's conventional topologies with centralized storage. Herein this paper studies the capital cost benefits of several residential behind-the-meter distributed-storage topologies, including AC and DC versions of systems with load-packaged batteries and resilient sub-networks. The study begins by defining the block configuration of each topology. This work then develops a model for the cost of the power electronics necessary to interface with the storage elements. Finally, the analysis develops a model for the total cost of each storage topology, incorporating the installation and soft costs. The results suggest that while the cost of power electronics is lower in centralized topologies, the total cost is lower for distributed storage due to the avoided costs of installation and permitting. This paper also explores the benefits of load-packaged batteries for savings in electrical infrastructure.

25 ENERGY STORAGE↗
DOE OSTI2025

Viewing is understanding: Graphite microstructure effects on infiltrated molten salt distribution revealed by 3D neutron tomography

Molten salt infiltration in the pore network of nuclear graphite may cause unwanted changes to graphite's local structure and mechanical and thermal properties. A detailed and comprehensive understanding of molten salt intrusion (distribution across sample cross section and penetration depth) is needed to assess its effects. Here, in this work, we report on an improved methodology for the use of neutron imaging (computed tomography) to evaluate salt penetration and distribution of a wide range of graphite grades with diverse microstructures. Neutron tomography data were acquired on the same graphite sample before and after salt intrusion; the 3D reconstructed volumes were digitally co-registered and subtracted. The difference in neutron attenuation coefficient represents direct visualization of FLiNaK (LiF–NaF–KF) salt distribution in the salt-impregnated graphite samples. This improved methodology was applied to investigate the effect of exposure times (12 h and 336 h) and of graphite microstructure when exposed to FLiNaK at 750 °C and 3 bar (gauge) pressure, starting from flowing argon at near atmospheric pressure. The results show that medium-grained and fine-grained graphites evolve to equilibrium at significantly different rates: fast salt uptake in medium-grained graphites produces salt deposits throughout the volume of graphite specimens, whereas salt infiltration in fine-grained graphites is much slower and limited to exposed surfaces.

FLiNaK infiltration↗
DOE OSTI2025

Chemistry imaging and distribution analysis of rare earth elements in coal using LIBS and LA-ICP-MS instruments

Currently, demand for rare earth elements (REEs) increased significantly. Coal is actively evaluated as potential economic sources for extraction of REEs. Here, in this work, laser-induced breakdown spectroscopy (LIBS) was evaluated for rapid estimation of REEs content and their distribution in the natural coal samples. The results were compared with similar laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) measurements. Thirteen coal samples (nine standard samples and five natural samples) were used in this study. Powder samples were pressed into pellets while coal chunks were directly ablated for data recording. Pellets of the powder standard samples were used to optimize the data acquisition system and then data recorded with this optimized system was used to identify the proper data acquisition and analysis models. After establishing the proper data acquisition system and analysis model using the standard samples, natural coal samples in powder form and their chunks were utilized to record LIBS and LA-ICP-MS spectra. Multivariate calibration models were developed using four of the natural samples, which were evaluated by predicting the REE content in the fifth sample. Principal component analysis was performed on the LIBS data obtained from the natural samples and it classified all the samples with high accuracy. Two-dimensional (2D) elemental mapping on coal chunk samples was also performed using both LIBS and LA-ICP-MS to study the distribution of REEs in the samples. The resulting elemental images and their correlations can be used to infer mineral distributions.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Stress due to electric charge density distribution in a dielectric slab

The spatial distribution of electric field due to an imposed electric charge density profile in an infinite slab of dielectric material is derived analytically by integrating Gauss’s law. Various charge density distributions are considered, including exponential and power-law forms. Here, the Maxwell stress tensor is used to compute a notional static stress in the material due to the charge density and its electric field. Characteristics of the electric field and stress distributions are computed for example cases in polyethylene, showing that field magnitudes exceeding the dielectric strength would be required in order to achieve a stress exceeding the ultimate tensile strength.

42 ENGINEERING↗
DOE OSTI2020

Citric acid-assisted accumulation of Ni and other metals by Odontarrhena muralis: Implications for phytoextraction and metal foliar distribution assessed by μ-SXRF

Odontarrhena muralis is one of the most promissing plant species for Ni phytomining, and soil amendments can further increase its Ni phytoextraction ability. Here we investigated whether Ni phytomining/phytoremediation using this Ni hyperaccumulator can benefit from applying citric acid to a serpentine soil that is naturally enriched in Ni (>1000 mg kg -1 ). Synchrotron micro X-ray fluorescence (μ-SXRF) was used to image Ni and other metal distributions in whole fresh leaves of O. muralis. Leaf Ni accumulation in plants grown on citric acid-amended soil increased up to 55% while Co, Cr, Fe, Mn, and Zn concentrations were 4-, 14-, 6-, 7- and 1.3-fold higher than the control treatment. O. muralis presented high bioconcentration factors (leaf to soil concentration ratio) to Ni and Zn whereas Cr was seemingly excluded from uptake. The μ-SXRF images showed a uniform distribution of Ni, preferential localization of Co in the leaf tip, and clear concentration of Mn in the base of trichomes. The citric acid treatments strongly increased the Co fluoerescence intensity in the leaf tip and altered the spatial distribution of Mn across the leaf, but there was no difference in Ni fluorescence counts between the trichome-base region and the bulk leaf. Our data from a serpentine soil suggests that citrate treatment enhances Ni uptake, but Co is excreted from leaves even in low leaf concentrations, which can make Co phytoming using O. muralis unfeasible in natural serpentine soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Model to inform the expansion of hydrogen distribution infrastructure

A growing hydrogen economy requires new hydrogen distribution infrastructure to link geographically distributed hubs of supply and demand. The Hydrogen Optimization with Deployment of Infrastructure (HOwDI) Model helps meet this requirement. The model is a spatially resolved optimization framework that determines location-specific hydrogen production and distribution infrastructure to cost-optimally meet a specified location-based demand. While these results are useful in understanding hydrogen infrastructure development, there is uncertainty in some costs that the model uses for inputs. Thus, the project team took the modeling effort a step further and developed a Monte Carlo methodology to help manage uncertainties. Seven scenarios were run using existing infrastructure and new demand in Texas exploring different policy and tax approaches. The inclusion of tax credits increased the percentage of runs that could deliver hydrogen at <$\$4$ /kg from 31% to 77% and decreased the average dispensed cost from $\$4.35$ /kg to $\$3.55$ /kg. However, even with tax credits there are still some runs where unabated SMR is deployed to meet new demand as the low-carbon production options are not competitive. Every scenario, except for the zero-carbon scenario (without tax credits), resulted in at least 20% of the runs meeting the $\$4$ /kg dispensed fuel cost target. This indicates that multiple pathways exist to deliver $\$4$ /kg hydrogen.

08 HYDROGEN↗
DOE OSTI2022

A second-order distributed memory parallel fast sweeping method for the Eikonal equation

The Eikonal equation is used to calculate wave propagation and distance fields, and due to its complexity requires numerical treatment for its solution. In this work, we present a second-order distributed memory parallel fast sweeping method. The second-order solution switches on a two-point stencil when two upwind points are available, and reverts to first-order otherwise. In all examples, the second-order method improves the solution over the first-order, allowing for significant savings in memory while achieving the same accuracy. Parallelization over distributed memory saw good weak scaling with optimal convergence. The computational time for second-order was approximately 2.5 times slower than first-order, where the largest amount of mesh points ran on 144 cores (512 GB) was ≈20 billion. The savings in memory from the second-order method combined with the distributed memory algorithm result in the ability to solve problems much larger than are possible with the serial first-order method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗