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At least 271 records · Page 15

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DOE OSTI2024

Distributed strain sensing using Bi-metallic coated fiber optic sensors embedded in stainless steel

Silica fiber optic sensors are resistant to corrosive environments and high temperatures, making them attractive candidates for harsh conditions found in nuclear and aerospace industries. Moreover, fibers can be deployed remotely for continuous measuring of spatially distributed temperatures and strains. Here, this study investigated embedding a Ni/Cu bi-metallic coated fiber in a stainless-steel 316 (SS316) matrix using laser powder bed fusion towards functionalizing metal components for site-specific health monitoring. The embedded fiber was continuously interrogated during controlled heating to 1000°C. The measured fiber strains were similar to the expected differential thermal strains between the fiber and the SS316 matrix, until divergent behavior was observed at temperatures >500°C. No debonding at the matrix–coating–fiber interfaces was observed during microscopy, but significant interactions between the coatings and matrix resulted in diffusion-driven chemistry variations and Kirkendall void formation. Applying the strain-lag theory revealed plastic behavior in the Ni coating at temperatures >500°C, limiting the strain transfer to the fiber at higher temperatures. It was estimated that the elastic modulus in the Ni coating had decreased from ~200 GPa at room temperature to below 40 GPa, starting at 600°C. The low elastic modulus above 600°C is within the margin of what the tangent modulus would be in the case of bilinear isotropic hardening. Regardless of the divergent strain transfer at higher temperatures, the fiber was exposed to the equivalent of 1.9 % engineering strain at 1000°C, but measured only a 0.7 % engineering strain due to the poor strain transfer. Although compensating for the plastic behavior of Ni proved challenging, the bonding of a brittle silica fiber to a metal matrix surviving to 1000°C invites potential iterations on coating material for future application. For example, the embedded fiber is sufficient for acoustic energy transfer, realizing high temperature distributed acoustic sensing.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A comparison study on trading behavior and profit distribution in local energy transaction games

With the increasing integration of distributed energy resources, localized peer-to-peer energy transactions are receiving more attention since they could absorb more distributed renewables locally and stabilize the power grid. To better study the trading behavior and provide guidance for a viable local market design, different game-theoretical frameworks including cooperative and non-cooperative games are established and compared here. For the cooperative grand coalition, the maximum social welfare is guaranteed, the Shapley value and bargaining based approaches are implemented for further profit redistribution. It is shown that the asymmetrical bargaining power can be critical in the final payment clearing and it is equivalent to the Shapley value allocation if prosumers bargain based on their marginal contributions. Non-cooperative trading is formulated by using a Stackelberg bilevel model in which the upper level has the privilege in internal price setting. However, system optimum is not obtained due to competition, and the selfish leader could take away 89% of the collective benefit by price-gap based arbitraging. Aiming for a long-lasting trading market, a virtual benevolent leader and a uniform price structure in which purchase price equals selling price are tested. Experimental results indicate that maximum social welfare and a fairer profit allocation can be achieved with a uniform price structure, regardless of the selfish or benevolent attitude.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Cosmology with persistent homology: a Fisher forecast

Abstract Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool to the dark matter halo catalogs from theQuijotesimulations, and build a summary statistic for comparison with the joint power spectrum and bispectrum statistic regarding their information content on cosmological parameters and primordial non-Gaussianity. Through a Fisher analysis, we find that constraints from persistent homology are tighter for 8 out of the 10 parameters by margins of 13–50%. The complementarity of the two statistics breaks parameter degeneracies, allowing for a further gain in constraining power when combined. We run a series of consistency checks to consolidate our results, and conclude that our findings motivate incorporating persistent homology into inference pipelines for cosmological survey data.

Astronomy & Astrophysics↗

DOE OSTI2025

The DESI-Lensing Mock Challenge: large-scale cosmological analysis of 3x2-pt statistics

The current generation of large galaxy surveys will test the cosmological model by combining multiple types of observational probes. Realising the statistical promise of these new datasets requires rigorous attention to all aspects of analysis including cosmological measurements, modelling, covariance and parameter likelihood. In this paper we present the results of an end-to-end simulation study designed to test the analysis pipeline for the combination of the Dark Energy Spectroscopic Instrument (DESI) Year 1 galaxy redshift dataset and separate weak gravitational lensing information from the Kilo-Degree Survey, Dark Energy Survey and Hyper-Suprime-Cam Survey. Our analysis employs the 3x2-pt correlation functions including cosmic shear and galaxy-galaxy lensing, together with the projected correlation function of the spectroscopic DESI lenses. We build realistic simulations of these datasets including galaxy halo occupation distributions, photometric redshift errors, weights, multiplicative shear calibration biases and magnification. We calculate the analytical covariance of these correlation functions including the Gaussian, noise and super-sample contributions, and show that our covariance determination agrees with estimates based on the ensemble of simulations. We use a Bayesian inference platform to demonstrate that we can recover the fiducial cosmological parameters of the simulation within the statistical error margin of the experiment, investigating the sensitivity to scale cuts. This study is the first in a sequence of papers in which we present and validate the large-scale 3x2-pt cosmological analysis of DESI-Y1.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Renormalon cancellation and linear power correction to threshold-like asymptotics of space-like parton correlators

Abstract In this paper, we show that the common hard kernel of double-log-type or threshold-type factorization for certain space-like parton correlators that arise in the context of lattice parton distributions, theheavy-light Sudakov hard kernel, has linear infrared (IR) renormalon. We explicitly demonstrate how this IR renormalon correlates with ultraviolet (UV) renormalons of next-to-leading power operators in two explicit examples: threshold asymptotics of space-like quark-bilinear coefficient functions and transverse momentum dependent (TMD) factorization of quasi wave function amplitude. Theoretically, the pattern of renormalon cancellation complies with general expectations to marginal asymptotics in the UV limit. Practically, this linear renormalon explains the slow convergence of imaginary parts observed in lattice extraction of the Collins-Soper kernel and signals the relevance of next-to-leading power contributions. Fully factorized, fully controlled threshold asymptotic expansion for space-like quark-bilinear coefficient functions in coordinate and moment space has also been proposed.

Physics↗

DOE OSTI2025

Conjugate Heat Transfer Modeling of Salt-Filled Fuel Pins for Stable Salt Reactor Safety Analysis

The Stable Salt Reactor (SSR) combines the proven structural design of light water reactor fuel assemblies with the inherent safety and fuel-cycle advantages of molten salt technology. In its fast reactor configuration, the SSR utilizes recycled nuclear waste as fuel, sealed within narrow salt-filled fuel pins and cooled by a surrounding liquid salt coolant. Reliable transfer of heat from the molten fuel salt through the cladding to the external coolant is essential for both reactor safety and performance. This work investigates conjugate heat transfer (CHT) in the SSR’s salt-filled fuel pins using NekRS, a high-fidelity spectral element computational fluid dynamics (CFD) solver. The analyses capture internal natural convection within the molten fuel salt and external forced convection in the coolant, under steady-state and transient operating conditions. Parametric studies evaluate how variations in reactor power and coolant flow rate influence heat transfer distributions and system response. The high-fidelity CFD results are time-averaged and post-processed for direct comparison with moderate-fidelity Reynolds-averaged Navier–Stokes (RANS) models, and for the development of reduced-order models within the SAM system code. These validated models support fast-running safety analyses of normal and off-normal transients, improving predictive capability for key safety margins. By integrating advanced CFD with system-level safety tools, this study strengthens the modeling framework for SSR design, reduces uncertainty in molten salt CHT simulations, and accelerates the engineering and licensing of next-generation nuclear reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Metrics and Analytical Frameworks for Valuing Energy Efficiency and Distributed Energy Resources in the Built Environment: Preprint

This paper summarizes efforts to develop new—and enhance existing—analytical frameworks and metrics to quantify the value that grid-interactive efficient homes with solar (GEB-solar homes) can provide. Industry is working to characterize and understand these capabilities and benefits, but existing analytical frameworks for evaluating energy efficiency (EE) are often siloed from those that evaluate distributed energy resources (DERs). Five metrics were adapted from an extensive literature review and applied to case studies of a modeled home in Riverside, California: ramp up/down, cover factor demand/supply, and curtailable load. Eight different technology scenarios were analyzed using a more tightly connected suite of building-to-grid models (BEopt, REopt, ReEDS, and PLEXOS). Additionally, an initial version of the Cambium tool was developed, characterizing the marginal prices and emissions from NREL’s 2018 Standard Scenarios. These grid costs were extended to a time-varying proxy retail rate and applied as part of a new grid alignment metric. In the results, a more integrated combination of GEB-solar technologies led to a higher cover factor demand—the percentage of gross home load covered by on-site solar—however, a benchmark was required to determine what range of cover factor was “best” for given grid conditions. To that end, a grid alignment cost metric was applied to the case study scenarios. The average cost to serve the net load of the home decreased from a median of ~$0.24/kWh to ~$0.10/kWh when the most integrated technology scenario was optimized towards the grid pricing proxy versus the time-of-use (TOU) rate.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2026

Constrained variational optimization of counting-time allocation in sequential scattering measurements: Application to Bonse–Hart USANS

Sequential scattering measurements are often performed under a fixed experimental-time budget, even though the expected count rate varies strongly across the measured coordinate. When the dwell time at each measurement position can be controlled independently, this variation creates a general resource-allocation problem: how should the available time be distributed to minimize the uncertainty of the reconstructed profile? We formulate this problem as a constrained variational optimization for measurements governed by Poisson counting statistics. When each measurement is treated independently, minimizing the averaged squared relative uncertainty yields an inverse-square-root intensity allocation. The formulation is then generalized to include correlations between neighboring measurements and an instrumental resolution operator, leading to an allocation criterion that equalizes the marginal reduction in posterior uncertainty per unit measurement time. Bonse–Hart ultra-small-angle neutron scattering (USANS), in which reciprocal space is sampled sequentially through analyzer-angle stepping, provides an experimentally grounded application. Computational benchmarking shows that the optimized allocation outperforms uniform-time and constant-relative-error strategies, while application to an experimentally measured graphite USANS profile from the Spallation Neutron Source, using Poisson resampling under alternative schedules, demonstrates how counting time should be redistributed toward weak-intensity regions under an identical total duration. The resulting framework applies to sequential scattering and related scanning measurements whenever local dwell times are adjustable and directly determine the measurement uncertainties, and when the relevant correlation and instrumental-response models are available.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗

DOE OSTI2023

The Spatial Clustering of ROSAT All-Sky Survey Active Galactic Nuclei. V. The Evolution of Broad-line AGN Clustering Properties in the Last 6 Gyr

This is the fifth paper in a series of investigations of the clustering properties of luminous, broad-emission-line active galactic nuclei (AGNs) identified in the ROSAT All-Sky Survey (RASS) and Sloan Digital Sky Survey (SDSS). In this work we measure the cross-correlation function (CCF) between RASS/SDSS Data Release 14 AGNs with the SDSS CMASS galaxy sample at 0.44 < z < 0.64. We apply halo occupation distribution (HOD) modeling to the CCF along with the autocorrelation function of the CMASS galaxies. We find that X-ray-selected and optically selected AGNs at 0.44 < z < 0.64 reside in statistically identical halos with a typical dark matter halo (DMH) mass of $M$$^{typ,AGN}_{DMH}$ ~ 10 12.7 h –1 M ⊙ . The acceptable HOD parameter space for these two broad-line AGN samples have only statistically marginal differences caused by small deviations of the CCFs in the one-halo-dominated regime on small scales. In contrast to optically selected AGNs, the X-ray AGN sample may contain a larger population of satellites at MDMH ~ 1013h–1M⊙. We compare our measurements in this work with our earlier studies at lower independent redshift ranges, spanning a lookback time of 6 Gyr. The comparison over this wider redshift range of 0.07 < z < 0.64 reveals (i) no significant difference between the typical DMH masses of X-ray-selected and optically selected AGNs, (ii) weak positive clustering dependencies of $M$$^{typ,AGN}_{DMH}$ with L X and M BH , (iii) no significant dependence of $M$$^{typ,AGN}_{DMH}$ on Eddington ratio, and (iv) the same DMH masses host more-massive accreting black holes at high redshift than at low redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Innovative Thermal Strategies: Electrification's Best Friend

Because transportation and heat are the most significant contributors to greenhouse gas (GHG) emissions in the northern U.S., electrification of transport and heat are prominent elements of many decarbonization plans, such as that of New York State (NYS). A key challenge is then to decarbonize the electric supply and distribution system ("the grid") that supplies electricity, a process colloquially known as "greening the grid", so that the saved direct carbon emissions are not offset by additional indirect emissions from electrical generation on the grid. Applying this "simple" decarbonization plan to locations with high winter heating loads and modest renewable resources is challenging. Understanding the impact of thermal system design to grid demands in these locations and the related marginal power source for electrification options is critical to allocating proper resources to solve decarbonization challenges and quantifying the resultant carbon emissions impact.

battery storage↗

DOE OSTI2024

Fish Friendly Water Rules' Impact On the Power Grid with High VRE Levels

Columbia River basin multipurpose reservoirs are operated for hydropower production and many other purposes considering the aquatic habitat of the river basin. Specifically, the river basin fish population is a vital element for the tribal community of the river basin. When conventional thermal power plants are retired, hydropower flexibility balances the wind and solar variability of the power grid and provides grid services to maximize the high renewable power absorption. On the other hand, over-reliance on hydropower could harm the river basin fish habitat. For example, water release pulses during peak electricity demand hours and shorter-term water release variation could harm the fish population. Power grid planners, environmentalists, Columbia Basin tribes, hydro regulators, and water resource planners work together to understand the impacts of Columbia River basin operation in a fish-friendly way in the current power grid and power grid with higher renewable power share. We examine different levels of renewable share in the Western Interconnection to understand the multiple weather years and future climate projection and operating scenario impact on the power grid and water system. We measure power grid impacts for various water resources planning scenarios in terms of total system operating cost, system reliability indicators, changes in wind and solar generation and curtailments, local marginal prices, and revenue for hydropower producers. The study results inform reservoir operating rules decisions from hydropower power producers, system operators, other water users, tribes, environmentalists, and other stakeholders.

environmental↗

DOE OSTI2022

Extraction of the higher-twist parton distribution $e(x)$ from CLAS data

We present the first point-by-point extraction of a twist-3 PDF. The scalar PDF, e(x), is accessed through the analysis of the data for the sin φR-moment of the beam-spin asymmetry for dihadron production in semi-inclusive DIS off proton target at CLAS and CLAS12. The dihadron formalism allows for use of collinear framework, hence calling for a minimal set of approximations and hypotheses. The extracted PDF e(x) carries insights into the physics of the largely-unexplored quark-gluon correlations, and its first Mellin moment is related to the marginally known scalar charge of the nucleon. We show that the proton flavor combination of the scalar PDF is nonzero at more than 74% probability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Interpretable Data-Driven Probabilistic Power System Load Margin Assessment with Uncertain Renewable Energy and Loads

The increasing uncertainties caused by the high-penetration of stochastic renewable generation resources poses a significant threat to the power system voltage stability. To address this issue, this paper proposes a probabilistic deep kernel learning enabled surrogate model to extract the hidden relationship between uncertain sources, i.e., wind power and loads, and load margin for probabilistic load margin assessment (PLMA). Unlike other deep learning approaches, a kernel SHAP provides the sensitivity analysis as well as interpretability of the inputs to outputs influences. This allows identifying the critical factors that affect load margin so that corrective control can be initiated for stability enhancement. Numerical results carried out on the IEEE 118-bus power system demonstrate the accuracy and efficiency of the proposed data-driven PLMA scheme.

deep kernel learning↗

DOE OSTI2020

On the quantification and efficient propagation of imprecise probabilities with copula dependence

This paper addresses the problem of quantification and propagation of uncertainties associated with dependence modeling when data for characterizing probability models are limited. Practically, the system inputs are often assumed to be mutually independent or correlated by a multivariate Gaussian distribution. However, this subjective assumption may introduce bias in the response estimate if the real dependence structure deviates from this assumption. In this work, we overcome this limitation by introducing a flexible copula dependence model to capture complex dependencies. Here, a hierarchical Bayesian multimodel approach is proposed to quantify uncertainty in dependence model-form and model parameters that result from small data sets. This approach begins by identifying, through Bayesian multimodel inference, a set of candidate marginal models and their corresponding model probabilities, and then estimating the uncertainty in the copula-based dependence structure, which is conditional on the marginals and their parameters. The overall uncertainties integrating marginals and copulas are probabilistically represented by an ensemble of multivariate candidate densities. A novel importance sampling reweighting approach is proposed to efficiently propagate the overall uncertainties through a computational model. Through an example studying the influence of constituent properties on the out-of-plane properties of transversely isotropic E-glass fiber composites, we show that the composite property with copula-based dependence model converges to the true estimate as data set size increases, while an independence or arbitrary Gaussian correlation assumption leads to a biased estimate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Methane Hydrate Formation and Evolution During Sedimentation

We explored methane hydrate formation with sedimentation with a newly developed one-dimensional, multiphase flow, multicomponent transport numerical model. Our model couples methane hydrate formation from in situ microbial methane generation within the hydrate stability zone (HSZ), methane recycling, and microbial methane generation below the base of the hydrate stability zone (BHSZ). Both recycled methane and deeply generated methane are transported into the HSZ by buoyancy-driven free gas flow. Free gas flows through the HSZ by both the processes of capillary-dependent pore fillings and by salt exclusion during hydrate formation, with the former being the dominant mechanism. We quantitively illustrated the formation of enriched hydrate in muddy sediments above, and interconnected free gas below, the BHSZ, which are common features along the world's continental margin. In addition, we showed two ways to form concentrated methane hydrate above the BHSZ. The first mechanism is local free gas flow during methane recycling. This happens at sites with sufficient methane generation above the BHSZ. The second mechanism is deep microbial methane generation which is transported into the HSZ by free gas flow. This mechanism plays a more important role at sites with high sedimentation rates. This study provides new insights into methane hydrate formation and distribution below the seafloor. It is important for understanding the carbon cycle and carbon storage below the seafloor and for resource evaluation and exploitation.

58 GEOSCIENCES↗

DOE OSTI2023

Tonian Carbonates Record Phosphate-Rich Shallow Seas

The early-middle Neoproterozoic is thought to have witnessed significant perturbations to marine P cycling, in turn facilitating the rise of eukaryote-dominated primary production. However, with few robust constraints on aqueous P concentrations, current understanding of Neoproterozoic P cycling is generally model-dependent. To provide new geochemical constraints, we combined microanalytical data sets with solid-state Nuclear Magnetic Resonance, synchrotron-based X-ray Absorption Near Edge Structure spectroscopy, and micro-X-ray Fluorescence imaging to characterize the speciation and distribution of P in Tonian shallow-water carbonate rocks. These data reflect shallow water phosphate concentrations 10–100× higher than modern systems, supporting the hypothesis that tectonically-driven influxes in P periodically initiated kinetically-controlled CaCO 3 deposition, in turn destabilizing marine carbonate chemistry, climate, and nutrient inventories. Alongside these observations, a new compilation and statistical analysis of mudstone geochemistry data indicates that, in parallel, C org and P burial increased across later Tonian continental margins until becoming decoupled at the close of the Tonian, implicating widespread N-limitation triggered by increasing atmospheric O 2 .

58 GEOSCIENCES↗

DOE OSTI2021

Adaptive Critical Balance and Firehose Instability in an Expanding, Turbulent, Collisionless Plasma

Abstract Using a hybrid-kinetic particle-in-cell simulation, we study the evolution of an expanding, collisionless, magnetized plasma in which strong Alfvénic turbulence is persistently driven. Temperature anisotropy generated adiabatically by the plasma expansion (and consequent decrease in the mean magnetic-field strength) gradually reduces the effective elasticity of the field lines, causing reductions in the linear frequency and residual energy of the Alfvénic fluctuations. In response, these fluctuations modify their interactions and spatial anisotropy to maintain a scale-by-scale “critical balance” between their characteristic linear and nonlinear frequencies. Eventually the plasma becomes unstable to kinetic firehose instabilities, which excite rapidly growing magnetic fluctuations at ion-Larmor scales. The consequent pitch-angle scattering of particles maintains the temperature anisotropy near marginal stability, even as the turbulent plasma continues to expand. The resulting evolution of parallel and perpendicular temperatures does not satisfy double-adiabatic conservation laws, but is described accurately by a simple model that includes anomalous scattering. Our results have implications for understanding the complex interplay between macro- and microscale physics in various hot, dilute, astrophysical plasmas, and offer predictions concerning power spectra, residual energy, ion-Larmor-scale spectral breaks, and non-Maxwellian features in ion distribution functions that may be tested by measurements taken in high-beta regions of the solar wind.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Parallel algorithms for finding connected components using linear algebra

Finding connected components is one of the most widely used operations on a graph. Optimal serial algorithms for the problem have been known for half a century, and many competing parallel algorithms have been proposed over the last several decades under various different models of parallel computation. This paper presents a class of parallel connected-component algorithms designed using linear-algebraic primitives. These algorithms are based on a PRAM algorithm by Shiloach and Vishkin and can be designed using standard GraphBLAS operations. Here, we demonstrate two algorithms of this class, one named LACC for Linear Algebraic Connected Components, and the other named FastSV which can be regarded as LACC’s simplification. With the support of the highly-scalable Combinatorial BLAS library, LACC and FastSV outperform the previous state-of-the-art algorithm by a factor of up to 12x for small to medium scale graphs. For large graphs with more than 50B edges, LACC and FastSV scale to 4K nodes (262K cores) of a Cray XC40 supercomputer and outperform previous algorithms by a significant margin. This remarkable performance is accomplished by (1) exploiting sparsity that was not present in the original PRAM algorithm formulation, (2) using high-performance primitives of Combinatorial BLAS, and (3) identifying hot spots and optimizing them away by exploiting algorithmic insights.

97 MATHEMATICS AND COMPUTING↗