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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Mechanism-based constitutive modeling of ZEK100 magnesium alloy with crystal plasticity and in-situ HEXRD experiment

The constitutive behavior of a hexagonal close-packed (HCP) polycrystalline ZEK100 magnesium alloy was investigated here using combined high energy X-ray diffraction (HEXRD) from a synchrotron source and crystal plasticity modeling approach. The in-situ tensile test data coupled with the HEXRD enabled the tracking of the lattice strain evolution during deformation. The microscopic behavior represented by lattice strain and the macroscopic behavior represented by stress-strain curves were then used together as objective function to estimate the critical resolved shear stress (CRSS) and hardening parameters of available slip and deformation twin systems in the ZEK100 alloy. An enhanced predominant twinning reorientation (ePTR) scheme was proposed in the current work, and the ePTR parameters were determined for the first time by the use of basal plane peak intensity along loading direction measured from HEXRD. Two crystal plasticity models, the computationally efficient elastic-plastic self-consistent (EPSC) and crystal plasticity finite element (CPFE) models, were developed incorporating the deformation twinning for the HCP-structured metals. The determined constitutive parameters were further validated by comparing the predicted deformation texture with the measured one. The work provides a useful and computationally-efficient modeling scheme to understand the slip/twin induced deformation behaviors of the ZEK100 alloy in micro- and macro-scales.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Experimental and Computational Evaluation of Lipidomic In-Source Fragmentation as a Result of Postionization with Matrix-Assisted Laser Desorption/Ionization

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide spatially resolved molecular information about a sample. Recently, a postionization approach (MALDI-2) has been commercially integrated with MALDI-MSI, allowing for bettered sensitivity and consequent improved spatial resolution. While advantages of MALDI-2 have previously been established, we demonstrate here statistically increased in-source fragmentation (ISF) results from postionization with a commercial instrument. Via lipid standard analyses, known MALDI ISF pathways (e.g., loss of trimethylamine) were statistically increased in MALDI-2 compared to MALDI-1 (65–172% increase in fragmentation). Gas phase molecular modeling with density functional theory estimated that the most-weighted virtual orbitals to excite within lipids involve ester and phosphate bonds. Protonated lipid excitation energies are furthermore red-shifted compared to those of other adduct types [e.g., 254 nm for protonated PC(16:0/18:1)] and approach the MALDI-2 laser energy (266 nm). Analysis of rat brain homogenate detected statistically more positive-ion mode peaks with MALDI-2 (1090) than that with MALDI-1 (719), where Kernel density estimations showed that the majority of this enhancement occurs with low m/z ions (i.e., m/z 75–500). Taken together with the lipid standard data, these observations may indicate ISF due to postionization. Finally, while artifact contributions from matrix blanks were also noted, both experimental and computational data sets suggest that the overall extent of ISF is statistically increased in MALDI-2 compared to MALDI-1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Spatiotemporal and Statistical Mapping of Transition Metal Equilibria in Alkaline Media

Transition metal dissolution and redeposition (D/R) kinetics in alkaline media play a critical role in various chemical and electrochemical processes. Competitive reaction kinetics between different transition metals can modulate individual metal behavior in these processes. To date, these phenomena have remained largely unmeasured, and even when captured, they are difficult to statistically characterize due to their dynamic nature, simultaneous occurrence, and spatially heterogeneous nature. Here, in this study, we develop a statistical analysis framework based on in situ and operando X-ray fluorescence microscopy (XFM) to investigate the relative D/R kinetics of multiple transition metals in alkaline media. By employing statistical analysis, we quantify the spatial distribution of D/R species and assess the rate at which the system reaches equilibrium under varying reaction conditions. We show that pH does not simply change the rate of dissolution and redeposition, but reorganizes the cross-element kinetic correlations among Ni, Fe, and Mn and accelerates the spatial equilibration of D/R events, as quantified through correlation analysis, reaction-rate estimation, probability function distributions, and texture-based monitoring statistics. Additionally, we demonstrate how modifying the solvent environment can influence D/R kinetics, providing a pathway for tuning materials synthesis and process optimization. Our study offers valuable insights into the complex interplay between different transition metals and provides a reliable statistical framework for spatial analysis of diverse imaging data sets, enabling deeper extraction of latent information across multiple modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Importance sampling large deviations in nonequilibrium steady states. I

Large deviation functions hold information on the stability and response of systems driven into nonequilibrium steady states and in such a way are similar to free energies for systems at equilibrium. As with equilibrium free energies, evaluating large deviation functions numerically for all but the simplest systems is difficult because by construction they depend on exponentially rare events. In this first paper of a series, we assess different trajectory-based sampling methods capable of computing large deviation functions of time integrated observables within nonequilibrium steady states. We highlight some convergence criteria and best practices using a number of different models, including a biased Brownian walker, a driven lattice gas, and a model of self-assembly. We show how two popular methods for sampling trajectory ensembles, transition path sampling and diffusion Monte Carlo, suffer from exponentially diverging correlations in trajectory space as a function of the bias parameter when estimating large deviation functions. Improving the efficiencies of these algorithms requires introducing guiding functions for the trajectories.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

DESI mock challenge: constructing DESI galaxy catalogues based on FastPM simulations

Together with larger spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI), the precision of large-scale structure studies and thus the constraints on the cosmological parameters are rapidly improving. Therefore, one must build realistic simulations and robust covariance matrices. We build galaxy catalogues by applying a halo occupation distribution (HOD) model upon the FastPM simulations, such that the resulting galaxy clustering reproduces high-resolution N-body simulations. While the resolution and halo finder are different from the reference simulations, we reproduce the reference galaxy two-point clustering measurements – monopole and quadrupole – to a precision required by the DESI Year 1 emission line galaxy sample down to non-linear scales, i.e. $k\lt 0.5\, h\, \mathrm{Mpc}^{-1}$ or $s\gt 10\, \mathrm{Mpc}\, h^{-1}$. Furthermore, we compute covariance matrices based on the resulting FastPM galaxy clustering – monopole and quadrupole. We study for the first time the effect of fitting on Fourier conjugate (e.g. power spectrum) on the covariance matrix of the Fourier counterpart (e.g. correlation function). We estimate the uncertainties of the two parameters of a simple clustering model and observe a maximum variation of 20 per cent for the different covariance matrices. Nevertheless, for most studied scales the scatter is between 2 and 10 per cent. Consequently, using the current pipeline we can precisely reproduce the clustering of N-body simulations and the resulting covariance matrices provide robust uncertainty estimations against HOD fitting scenarios. We expect our methodology will be useful for the coming DESI data analyses and their extension for other studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Load Profile Inpainting for Missing Load Data Restoration and Baseline Estimation

This paper introduces a Generative Adversarial Nets (GAN) based, Load Profile Inpainting Network (Load-PIN) for restoring missing load data segments and estimating the baseline for a demand response event. The inputs are time series load data before and after the inpainting period together with explanatory variables (e.g., weather data). Here, we propose a Generator structure consisting of a coarse network and a fine-tuning network. The coarse network provides an initial estimation of the data segment in the inpainting period. The fine-tuning network consists of self-attention blocks and gated convolution layers for adjusting the initial estimations. Loss functions are specially designed for the fine-tuning and the discriminator networks to enhance both the point-to-point accuracy and realisticness of the results. We test the Load-PIN on three real-world data sets for two applications: patching missing data and deriving baselines of conservation voltage reduction (CVR) events. We benchmark the performance of Load-PIN with five existing deep-learning methods. Our simulation results show that, compared with the state-of-the-art methods, Load-PIN can handle varying-length missing data events and achieve 15-30% accuracy improvement.

14 SOLAR ENERGY↗
DOE OSTI2021

Distributed electric field sensing using fibre optics in borehole environments

In the past decade, rapid advances in distributed optical fibre sensing technologies have made it possible to record various geophysical data (e.g. strain, temperature and pressure) continuously in both time and space along the fibre, providing an unprecedented quantity and spatial density of data compared to traditional geophysical measurements as well as reducing data acquisition cost. To date, no distributed fibre-based electromagnetic field sensing system has been implemented although electromagnetic sensing could have a broad range of applications to geophysical imaging and monitoring in borehole environments. The goal of this paper is to provide a theoretical feasibility study regarding the design and use of an electromagnetic sensing optical fibre for geophysical applications. First, we present the sensitivity analysis of a ‘hypothetical’ optical fibre coated with polyvinylidene fluoride, a polymer that provides relatively high piezoelectric properties, yet unlike ceramics, is flexible. Next, using a two-dimensional electromagnetic modelling algorithm, we simulate the earth electric-field-to-fibre-strain transfer function and estimate the theoretical sensitivity of the optical fibre to electric fields. Given the state-of-the-art distributed acoustic sensing strain sensitivities in the picometres strain range, our numerical modelling analysis suggests that a perfectly coupled polyvinylidene fluoride–coated optical fibre can measure electric field values in the mV/m to V/m amplitude range. We then apply a cylindrically symmetric modelling algorithm to simulate numerical models demonstrating the applicability of such a fibre in an oilfield environment. Scenarios investigated employ an electric field source and suggest that the measurements can be used to distinguish the oil versus water ratio with a fibre mounted inside a producing steel cased oil well as well as distinguishing between brine and hydrocarbon filled reservoir zones with a fibre located outside of the casing.

58 GEOSCIENCES↗
DOE OSTI2026

1999 Puget Sound Household Travel Survey

The 1999 Puget Sound Household Travel Survey was conducted between July and November. NuStats Research and Consulting conducted the survey on behalf of the Puget Sound Regional Council. The purpose of the study was to provide data to continue developing and refining the Regional Travel Demand Forecasting Model, as well as to provide a better understanding of travel behavior in the Puget Sound region. The study area consists of King, Kitsap, Pierce, and Snohomish counties. The resultant dataset will be used to fulfill the model's functions of estimating trip generation and distribution, mode choice, and assignments. The study had household members 16 years old or older keep track of travel for a 48-hour period. A total of 9,028 households were recruited to participate in the study. Of these, 6,000 households (66.5%) completed travel diaries, and the information was retrieved from all household members regardless of age. An “attitude” survey about transportation and land use issues was also mailed to household members 16 years old or older.

1Hz data↗
DOE OSTI2026

1998/99 Thurston County Household Travel Study

The survey was conducted under the auspices of the Thurston Regional Planning Council, and it was funded through a state grant awarded to Intercity Transit of Olympia, Washington. Data collection was from September 1998 through March 1999. The purpose of the study was to provide data for the continuing development and refinement of the Regional Travel Demand Forecasting Model, as well as to provide a better understanding of travel behavior in the southern Puget Sound region of Washington. The resultant data set will be used to fulfill the model's functions of estimating trip generation and distribution, mode choice, and assignments. Participating households were assigned specific “travel days” to record their travel over a 48-hour period. A total of 2,465 households were recruited to participate in the study. Of these, 1,537 households completed travel diaries, and the information was retrieved from 3,653 household members regardless of age. Households member made 25,278 total trips during their 48-hour diary period.

1Hz data↗
DOE OSTI2023

SHASTA-HELP

This tool contains functionality for estimating the storage potential of pure and blended natural gas-hydrogen mixtures in various subsurface formations and is intended to be used for pre-characterization or site screening purposes. Detailed storage analysis should be conducted by full reservoir simulation models.

Hydrogen↗
DOE OSTI2017

Validation of PV-RPM Code in the System Advisor Model.

This paper describes efforts made by Sandia National Laboratories (SNL) and the National Renewable Energy Laboratory (NREL) to validate the SNL developed PV Reliability Performance Model (PV - RPM) algorithm as implemented in the NREL System Advisor Model (SAM). The PV - RPM model is a library of functions that estimates component failure and repair in a photovoltaic system over a desired simulation period. The failure and repair distributions in this paper are probabilistic representations of component failure and repair based on data collected by SNL for a PV power plant operating in Arizona. The validation effort focuses on whether the failure and repair dist ributions used in the SAM implementation result in estimated failures that match the expected failures developed in the proof - of - concept implementation. Results indicate that the SAM implementation of PV - RPM provides the same results as the proof - of - concep t implementation, indicating the algorithms were reproduced successfully.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA

Performing stochastic inversion on a computationally expensive forward simulation model with a high-dimensional uncertain parameter space (e.g. a spatial random field) is computationally prohibitive even with gradient information provided. Moreover, the ‘nonlinear’ mapping from parameters to observables generally gives rise to non-Gaussian posteriors even with Gaussian priors, thus hampering the use of efficient inversion algorithms designed for models with Gaussian assumptions. In this work, we propose a novel Bayesian stochastic inversion methodology, characterized by a tight coupling between a gradient-based Langevin Markov Chain Monte Carlo (LMCMC) method and a kernel principal component analysis (KPCA). This approach addresses the ‘curse-of-dimensionality’ via KPCA to identify a low-dimensional feature space within the high-dimensional and nonlinearly correlated spatial random field. Moreover, non-Gaussian full posterior probability distribution functions are estimated via an efficient LMCMC method on both the projected low-dimensional feature space and the recovered high-dimensional parameter space. We demonstrate this computational framework by integrating and adapting recent developments such as data-driven statistics-on-manifolds constructions and reduction-through-projection techniques to solve inverse problems in linear elasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Determination of Stress-Free Lattice Spacing (D₀) for Residual Stress Relaxation Measurement in Ni-based Superalloys by Neutron Diffraction

The residual stress and its relaxation in critical engineering components are key to structural materials reliability. The determination of residual stress in bulk engineering structures like Ni-based superalloys can be conducted by measuring the lattice strain with penetrating neutron diffraction. The state-of-the-art engineering diffraction beamline VULCAN at the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS) provides the critical capability to evaluate the residual strain/stress relaxation in engineering component thanks to the high flux and event data features. By the means of residual stress/strain calculation, it is critical to accurately determine the stress-free lattice spacing d₀, which can be altered by the change of chemistry, unrelieved stress, and measurement scheme. Here we reported d₀ determination for determining residual stress relaxation and distribution in Alloy 718 superalloys after different quenching treatments. Selection of locations for d₀ measurement was discussed by considering the neutron path, attenuation and sample alignment. A dynamic d₀ that resulted from atom diffusion and chemistry change was estimated as function of time for the in-situ relaxation characterization. It demonstrated how the dynamic d₀ values may influence on the strain calculation in different thermally treated samples. The results highlight the importance of dynamic d₀ for in-situ relaxation involving chemical changes and provide guidance to the dynamic d₀ measurement and simulation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tau-Jet Matching and Tag-and-Probe Tau Tagging Efficiencies for HH→bbτ+τ− Searches Using Run 3 CMS Scouting Data

We are studying tau-jet matching efficiency and tau tagging efficiency for the search for Higgs boson pair production in the HH→bbτ+τ− decay channel using Run 3 CMS scouting data. Collision events in the CMS detector produce many particle candidates, so jets are clustered using the anti-kT algorithm to identify possible tau signatures. In Monte Carlo simulation, tau-jet matching efficiency can be measured by comparing generated taus to reconstructed jets. In actual collision data, however, generated taus are not available, so we use a tag-and-probe method with Z→τ+τ− candidate events. In this method, one tau candidate is used as the tag and the other as the probe. The invariant mass of the tau-pair candidates is plotted and fitted with signal and background functions to estimate the number of real tau events and determine the tagging efficiency. By comparing efficiencies in data and Monte Carlo simulation, this work helps evaluate the performance of scouting-based tau reconstruction and tau tagging for future HH→bbτ+τ− searches.

Bellot, Annella [North Central Coll.; Fermilab]↗
DOE OSTI2026

Tau-Jet Matching and Tag-and-Probe Tau Tagging Efficiencies for HH→bbτ+τ− Searches Using Run 3 CMS Scouting Data

We are studying tau-jet matching efficiency and tau tagging efficiency for the search for Higgs boson pair production in the HH→bbτ+τ− decay channel using Run 3 CMS scouting data. Collision events in the CMS detector produce many particle candidates, so jets are clustered using the anti-kT algorithm to identify possible tau signatures. In Monte Carlo simulation, tau-jet matching efficiency can be measured by comparing generated taus to reconstructed jets. In actual collision data, however, generated taus are not available, so we use a tag-and-probe method with Z→τ+τ− candidate events. In this method, one tau candidate is used as the tag and the other as the probe. The invariant mass of the tau-pair candidates is plotted and fitted with signal and background functions to estimate the number of real tau events and determine the tagging efficiency. By comparing efficiencies in data and Monte Carlo simulation, this work helps evaluate the performance of scouting-based tau reconstruction and tau tagging for future HH→bbτ+τ− searches.

Bellot, Annella [North Central Coll.; Fermilab]↗
DOE OSTI2017

Structure in the 3D Galaxy Distribution. III. Fourier Transforming the Universe: Phase and Power Spectra

We demonstrate the effectiveness of a relatively straightforward analysis of the complex 3D Fourier transform of galaxy coordinates derived from redshift surveys. Numerical demonstrations of this approach are carried out on a volume-limited sample of the Sloan Digital Sky Survey redshift survey. The direct unbinned transform yields a complex 3D data cube quite similar to that from the Fast Fourier Transform of finely binned galaxy positions. In both cases, deconvolution of the sampling window function yields estimates of the true transform. Simple power spectrum estimates from these transforms are roughly consistent with those using more elaborate methods. The complex Fourier transform characterizes spatial distributional properties beyond the power spectrum in a manner different from (and we argue is more easily interpreted than) the conventional multipoint hierarchy. We identify some threads of modern large-scale inference methodology that will presumably yield detections in new wider and deeper surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

The Clustering of High-redshift (2.9 ≤ $z$ ≤ 5.1) Quasars in SDSS Stripe 82

We present a measurement of the two-point autocorrelation function of photometrically selected high-$z$ quasars over ~100 deg 2 on the Sloan Digital Sky Survey Stripe 82 field. Selection is performed using three machine-learning algorithms in a six-dimensional optical/mid-infrared color space. Optical data from the Sloan Digital Sky Survey are combined with overlapping deep mid-infrared data from the $Spitzer$ IRAC Equatorial Survey and the $Spitzer$-HETDEX Exploratory Large-Area survey. Our selection algorithms are trained on the colors of known high-$z$ quasars. The selected quasar sample consists of 1378 objects and contains both spectroscopically confirmed quasars and photometrically selected quasar candidates. These objects span a redshift range of 2.9 ≤ $z$ ≤ 5.1 and are generally fainter than $i$ = 20.2, a regime that has lacked sufficient number density to perform autocorrelation function measurements of photometrically classified quasars. We compute the angular correlation function of these data, marginally detecting quasar clustering. We fit a single power law with an index of $δ$ = 1.39 ± 0.618 and amplitude of $θ_0$ = 0$^{\prime}_{.}$71 ± 0$^{\prime}_{.}$546 . A dark matter model is fit to the angular correlation function to estimate the linear bias. At the average redshift of our survey ($\langle z\rangle =3.38$), the bias is $b$ = 6.78 ± 1.79. Using this bias, we calculate a characteristic dark matter halo mass of 1.70–9.83$\times {10}^{12}{h}^{-1}\,{M}_{\odot }$. Our bias estimate suggests that quasar feedback intermittently shuts down the accretion of gas onto the central supermassive black hole at early times. If confirmed, these results hint at a level of luminosity dependence in the clustering of quasars at high-$z$.

79 ASTRONOMY AND ASTROPHYSICS↗