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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Constraints on Cosmological Parameters from the 500 deg$^2$ SPTpol Lensing Power Spectrum

We present cosmological constraints based on the cosmic microwave background (CMB) lensing potential power spectrum measurement from the recent 500 deg$^2$ SPTpol survey, the most precise CMB lensing measurement from the ground to date. We fit a flat $\Lambda$CDM model to the reconstructed lensing power spectrum alone and in addition with other data sets: baryon acoustic oscillations (BAO) as well as primary CMB spectra from Planck and SPTpol. The cosmological constraints based on SPTpol and Planck lensing band powers are in good agreement when analysed alone and in combination with Planck full-sky primary CMB data. Within the $\Lambda$CDM model, CMB lensing data are primarily sensitive to the amount of large-scale structure as parametrized by $\sigma_8\Omega_m^{0.25}$. With weak priors on the baryon density and other parameters, the SPTpol CMB lensing data alone provide a 4% constraint on $\sigma_8\Omega_m^{0.25} = 0.0593 \pm 0.025$. Jointly fitting with BAO data, we find $\sigma_8=0.779 \pm 0.023$, $\Omega_m = 0.368^{+0.032}_{-0.037}$, and $H_0 = 72.0^{+2.1}_{-2.5}\,\text{km}\,\text{s}^{-1}\,\text{Mpc}^{-1} $, up to $2\,\sigma$ away from the central values preferred by Planck lensing + BAO. However, we recover good agreement between SPTpol and Planck when restricting the analysis to similar scales. We also consider single-parameter extensions to the flat $\Lambda$CDM model. In combination with Planck primary CMB measurements and BAO, the SPTpol lensing spectrum constrains the spatial curvature to be $\Omega_K = -0.0007 \pm 0.0025$ and the sum of the neutrino masses to be $\sum m_{\nu} < 0.23$ eV at 95% C.L., both in good agreement with the full-sky Planck lensing results. With the differences in the $S/N$ of the lensing modes (abridged)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Understanding the impact of nuclear-data covariances on various integral responses using adjustment

The EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) project created a library of sensitivities for nine different integral responses with respect to nuclear data. These integral responses were obtained from measurements at LLNL (Lawrence Livermore National Laboratory) pulsed spheres, critical and sub-critical assemblies. At the same time, covariances for ENDF/B-VIII.0 were processed at LANL (Los Alamos National Laboratory). The combination of these data allow us to study the impact of nuclear-data covariances on various integral responses, either by forward-propagating covariances via sensitivities, or by using nuclear data, integral responses, and sensitivities for adjustment. Here, we will present: the impact of 1 H, 9 Be, 12 C, 27 Al, 56 Fe, 235,238 U, and 239,240 Pu ENDF/B-VIII.0 covariances on simulated bounds of the following integral responses: LLNL pulsed-spheres neutron-leakage spectra, the effective neutron multiplication factor, reaction rates, and reactivity coefficients of ICSBEP critical assemblies. Also, adjustment results with the same nuclear-data covariances and responses will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2002

Sensitivity of Lower Stratospheric Assimilated Ozone on Error Covariance Modeling and Data Selection

Assimilated ozone is produced at the NASA/Goddard Data Assimilation Office by blending ozone retrieved from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument and the Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) measurements into an off-line transport model. The current system tends to overestimate the amount of lower stratospheric ozone. This is a region where ozone plays a key role in the forcing of climate. A biased ozone field in this region will adversely impact calculations of the stratosphere-troposphere exchange and, when used as a first guess in retrievals, the values determined from satellite observations. Since these are all important applications of assimilated ozone products, effort is being directed towards reducing this bias. The SBUV ozone data have a coarse vertical resolution with increased uncertainty below the ozone maximum, and TOMS provides only total ozone columns. Thus, the assimilated ozone in the lower stratosphere, and its vertical distribution in particular, are only weakly constrained by the incoming SBUV and TOMS data. Consequently, the assimilated ozone distribution should be sensitive to changes in inputs to the statistical analysis scheme. Accordingly, the sensitivity of the assimilated lower stratospheric ozone fields to changes in the TOMS error-covariance modeling and the SBUV data selection has been investigated. The use of a spatially correlated TOMS error covariance model led to improvements in the product. However, withholding the SBUV/2 data for the layer between 63 and 126 hPa typically degraded the product, a result which vindicates the use of this layer ozone product, despite its known errors. These efforts to improve the lower stratospheric distribution will be extended to include a more advanced forecast error covariance model, and by assimilating ozone products from new instruments on Envisat and EOS Aura.

Stajner, Ivanka↗
DOE OSTI2024

A First Search for Argon-Bound Neutron-Antineutron Oscillation using the MicroBooNE LArTPC

The use of Liquid Argon Time Projection Chambers (LArTPCs) as a detector technology in neutrino experiments has grown considerably over the past two decades. The excellent spatial and calorimetric resolution offered by LArTPCs enable precise neutrino oscillation measurements as well as beyond-Standard Model searches. One such search, which is the focus of this note, is the search for nucleus-bound neutron-antineutron (n ₋ n̄) oscillation. The n ₋ n̄ oscillation process is a baryon number violating process that produces a unique, star-like topology as a result of multiple final state pions. This unique signature is a key feature that may be used to search for this signal process. This note describes a machine learning-based analysis of MicroBooNE data, making use of a sparse convolutional neural network to search for n ₋ n̄ oscillation-like signals in MicroBooNE. While the future DUNE LArTPC can search for this signature with high sensitivity, existing MicroBooNE data can be used to demonstrate and validate methodologies that can be used as part of the DUNE search. This document presents the first-ever search for n ₋ n̄ oscillation in a LArTPC, using MicroBooNE off-beam data (data collected when the neutrino beam was not running).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A first search for argon-bound neutron-antineutron oscillation using the MicroBooNE LArTPC

The use of Liquid Argon Time Projection Chambers (LArTPCs) as a detector technology in neutrino experiments has grown considerably over the past two decades. The excellent spatial and calorimetric resolution offered by LArTPCs enable precise neutrino oscillation measurements as well as beyond-Standard Model searches. One such search, which is the focus of this note, is the search for nucleus-bound neutron-antineutron (n – n̄) oscillation. The n – n̄ oscillation process is a baryon number violating process that produces a unique, star-like topology as a result of multiple final state pions. This unique signature is a key feature that may be used to search for this signal process. This note describes a machine learning-based analysis of MicroBooNE data, making use of a sparse convolutional neural network to search for n – n̄ oscillation-like signals in MicroBooNE. While the future DUNE LArTPC can search for this signature with high sensitivity, existing MicroBooNE data can be used to demonstrate and validate methodologies that can be used as part of the DUNE search. This document presents the first-ever search for n – n̄ oscillation in a LArTPC, using MicroBooNE off-beam data (data collected when the neutrino beam was not running).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1992

Sensitivity of wildlife habitat models to uncertainties in GIS data

Decision makers need to know the reliability of output products from GIS analysis. For many GIS applications, it is not possible to compare these products to an independent measure of 'truth'. Sensitivity analysis offers an alternative means of estimating reliability. In this paper, we present a CIS-based statistical procedure for estimating the sensitivity of wildlife habitat models to uncertainties in input data and model assumptions. The approach is demonstrated in an analysis of habitat associations derived from a GIS database for the endangered California condor. Alternative data sets were generated to compare results over a reasonable range of assumptions about several sources of uncertainty. Sensitivity analysis indicated that condor habitat associations are relatively robust, and the results have increased our confidence in our initial findings. Uncertainties and methods described in the paper have general relevance for many GIS applications.

Stoms, David M.↗
NASA NTRS1994

Direct Monitoring of Trace Atmospheric Species via Ion Trap Mass Spectrometry

There is an ever-increasing emphasis on the part of government agencies, academia, and industry on enhancing our understanding of atmospheric processes and assessing the impact of human activities on these processes. While issues such as the ozone hole and rising levels of greenhouse gases have received major attention. relatively little is known about the types, concentrations, sources, and sinks of hydrocarbons in the troposphere and stratosphere. Such information would be of tremendous utility in assessing the roles of various anthropogenic and biogenic processes on global carbon cycles. An ion trap mass spectrometer has been developed for monitoring trace levels of hydrocarbons in the atmosphere on NASA's DC-8 "flying laboratory". This aircraft is used to provide measurements in support of a number of "Mission to Planet Earth" activities and tropospheric chemistry experiments. In past missions, specific compounds have been monitored via highly specialized instrumentation, fast GO, or collection of whole air samples for subsequent ground-based analysis. The ion trap has several features. including small size. excellent sensitivity, and broad applicability, which make it highly atttrat:ive for atmospheric monitoring. The design of this instrument, its air sampling interface. and the various complications associated with aircraft-deployment will be described. Data showing the sensitivity of the instrument for detecting hydrocarbons at mixing ratios below one part-per-billion, and the use of MS/MS for direct, on-line, real-time monitoring will be presented.

Palmer, P. T.↗
NASA NTRS1980

NASA/FAA flight-test investigation of helicopter microwave landing system approaches

The helicopter Microwave Landing System flight-test investigations, conducted by a joint NASA/FAA effort in order to gather statistical data for establishing terminal instrument procedures criteria, and to provide a performance data base for developing advanced MLS guidance concepts, are presented. The specific flight-test objectives were to: (1) develop acceptable angle-only MLS approach profiles; (2) determine tracking errors; (3) determine altitude loss during missed approach; (4) evaluate guidance display sensitivities; and (5) evaluate pilot acceptability. Fourteen pilots flew 140 manual (without stability augmentation) dual-pilot simulated instrument approaches in a UH-1H helicopter. The flight profiles flown included 3-, 6-, and 9-degree glideslope, centerline approaches to decision heights of 50, 100, and 150 ft, respectively. The angular guidance display sensitivities and the data acquisition system are also described. Eight major conclusions are made, and include the following: (1) the use of pitch attitude to control airspeed and collective to control glideslope was the preferred pilot technique for the steep glideslope approaches, and (2) angular guidance deviation indicator sensitivity requirements for helicopter MLS approaches to STOLports and heliports have been found to be significantly different from standard ILS sensitivities.

Peach, I. L., Jr.↗
NASA NTRSDate not supplied

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗
DOE OSTI2025

Weakly supervised anomaly detection for resonant new physics in the dijet final state using proton-proton collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

An anomaly detection search for narrow-width resonances beyond the Standard Model that decay into a pair of jets is presented. The search is based on 139 fb −1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded during 2015–2018 with the ATLAS detector at the Large Hadron Collider. The analysis is optimized without a particular signal model and aims to be sensitive to a broad range of new physics. It uses two different machine learning strategies to estimate the background in different signal regions. In each region, a weakly supervised classifier is trained to distinguish this background model from data. The analysis focuses on events with high transverse momentum jets reconstructed as large-radius jets. The mass and substructure of these jets are used as inputs to the classifiers. After a classifier-based selection, the distribution of the invariant mass of the two jets is used to search for potential local excesses. The model-independent results of both the anomaly detection methods show no signs of significant local excesses. In addition to model-independent results, a representative set of signal models is injected into the data, and the sensitivity of the methods to these scenarios is reported.

Aad, G. [Aix-Marseille Université] (ORCID:00000002↗
NASA NTRS2005

The Next Generation of Planetary Atmospheric Probes

Entry probes provide useful insights into the structures of planetary atmospheres, but give only one-dimensional pictures of complex four-dimensional systems that vary on all temporal and spatial scales. This makes the interpretation of the results quite challenging, especially as regards atmospheric dynamics. Here is a planetary meteorologist's vision of what the next generation of atmospheric entry probe missions should be: Dedicated sounding instruments get most of the required data from orbit. Relatively simple and inexpensive entry probes are released from the orbiter, with low entry velocities, to establish ground truth, to clarify the vertical structure, and for adaptive observations to enhance the dataset in preparation for sensitive operations. The data are assimilated onboard in real time. The products, being immediately available, are of immense benefit for scientific and operational purposes (aerobraking, aerocapture, accurate payload delivery via glider, ballooning missions, weather forecasts, etc.).

Houben, Howard↗
DOE OSTI2024

Exploring the Links between Structural Distortions, Orbital Ordering, and Multipolar Magnetic Ordering in Double Perovskites Containing Re(VI) and Os(VII)

A combination of high-resolution powder diffraction techniques and solid-state NMR has been employed to explore the links between crystal structure, orbital ordering, and magnetism in three isostructural double perovskites containing transition metal ions with a 5d 1 configuration. In Ba 2 ZnReO 6 , both neutron and synchrotron X-ray powder diffraction data reveal a cubic-to-tetragonal transition at 23 K that breaks the degeneracy of the t 2g orbitals and leads to a pattern of orbital ordering that stabilizes magnetic ordering when the sample is cooled below 16 K. Similar behavior is observed in Ba 2 MgReO 6 , with an orbital ordering temperature of 33 K and a magnetic ordering temperature of 18 K. Prior theoretical works suggest that the pattern of orbital order seen in the P42/mnm space group is needed to stabilize the heavily canted antiferromagnetism of these compounds. Unfortunately, powder diffraction data is not sensitive enough to differentiate between the I4/mmm and P42/mnm structural models, as the distortions are too subtle to be unambiguously identified from either neutron or synchrotron X-ray powder diffraction methods. In contrast, both diffraction and 7 Li NMR data indicate that Ba 2 LiOsO 6 retains the cubic structure down to 1.7 K. The antiferromagnetic ground state and lack of any sign of orbital ordering in Ba 2 LiOsO 6 provide compelling evidence that the electronically driven tetragonal distortion seen in Ba2ZnReO6, and Ba2MgReO6 is intimately linked to the magnetic ordering seen in those compounds. The absence of magnetic reflections in high intensity neutron powder diffraction data collected on Ba 2 MgReO 6 strongly suggests ordering of multipolar moments on Re(VI), likely ferro-octupolar ordering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

Multibaseline TanDEM-X Mangrove Height Estimation: The Selection of the Vertical Wavenumber

We generated a large-scale mangrove forest height map using multiple TanDEM-X (TDX) interferometric synthetic aperture radar (InSAR) acquisitions with various spatial baselines in order to improve the height estimation accuracy across a wide range of forest heights. The forest height inversion using InSAR data is strongly dependent upon the vertical wavenumber (i.e., perpendicular baseline). First, we investigated the role of the vertical wavenumber in forest height inversion from InSAR data using the sensitivity of the interferometric (volume) coherence to forest height. We used corrected but lower resolution and accuracy Shuttle Radar Topography Mission (SRTM) mangrove height maps as a priori information over Akanda and Pongara National Parks in Gabon to estimate lower and upper boundaries of the vertical wavenumber over test sites from the measured coherence-to-height sensitivity. Only TDX acquisitions within the boundaries of the vertical wavenumber were selected and combined for multibaseline mangrove height inversion. Mangrove forest height was obtained with multibaseline TDX acquisitions and was validated against the reference height derived from field measurement data providing improvements in multibaseline inversion over existing height estimates (i.e., SRTM height) and single-baseline inversions (multibaseline inversion: r(exp 2) = 0.98, root mean square error (RMSE) of 2.73 m; SRTM height: r(exp 2) = 0.86, RMSE = 7.21 m; single-baseline inversions: r(exp 2) = 0.08-0.97, RMSE = 3.86-11.10 m). As a result, to accurately estimate forest heights over a wide range (3-60 m), multibaseline InSAR acquisitions (at least three different baselines) are needed to exclude biases associated with the vertical wavenumber in forest height inversion.

vertical wavenumber.↗
NASA NTRSDate not supplied

Enabling Model Organism and Commercial Astronaut Data Access Through the NASA Open Science Data Repository

NASA’s Open Science Data Repository (OSDR) brings together omics data from NASA’s GeneLab project and non-omics data, including physiological, phenotypic, imaging, and behavioral data from NASA’s Ames Life Sciences Data Archive (ALSDA) collected from decades of space biology research, providing open and FAIR (findable, accessible, interoperable, and reusable) access of these precious data to scientists world-wide. This rich source of meticulously curated metadata and data from spaceflight and analog studies has been mined by the scientific community resulting in dozens of high impact scientific publications that reveals a complex network of molecular and physiological effects of spaceflight across living systems, from microbes to plants, to mammals. Understanding how these effects translate to the human condition is critical as we move deeper into the era of commercial space travel. However, the integration of data, specifically omics data, from astronauts is particularly challenging due to their sensitive nature. OSDR has risen to this challenge by developing a mechanism to control access to identifiable levels of omics data, such as raw sequence data, while enabling public access to processed, unidentifiable, data and associated metadata that will allow the scientific community to interrogate human astronaut data alongside data from model organisms to begin answering these critical questions. The 2021 SpaceX Inspiration4 (I4) mission collected a comprehensive atlas of biological measurements from four civilian astronauts, providing a wealth of data to characterize the effects of spaceflight on the human body. These data include both non-omics and omics assays such as direct RNA sequencing (RNA-seq), single nuclei ATAC-seq and RNA-seq, metagenomics, proteomics, and comprehensive metabolic and cytokine panels, all of which have been integrated into the OSDR system across no less than 9 studies. Each study has been carefully curated using community-backed OSDR standards for sample and assay level metadata ensuring these data are findable and accessible. In addition to hosting both raw and processed data from the principal investigator team for each assay type, the GeneLab team plans to re-process the I4 omics data using GeneLab’s standard processing pipelines. The GeneLab processed data outputs will allow for comparisons across studies on OSDR and enable visualization of these data through the OSDR data visualization platform thereby enabling data reusability and interoperability. Here we describe the robust privacy and security protocols implemented by OSDR to safeguard sensitive health data from astronauts while facilitating metadata and processed data sharing for research purposes. We further provide a road map for navigating the vast amount of data provided for each I4 study on the OSDR, including experimental design, associated experiments, payloads, and missions, data generation and analysis protocols, and associated scientific articles. Additionally, we illustrate how to interrogate the standardized metadata provided in the sample and assay tables as well as various means to download and access the data including programmatically through the GeneLab Open API (GLOpenAPI). The open access of datasets in NASA’s OSDR provides a unique opportunity for the scientific community, as well as citizen scientists and students, to continue using OSDR resources to further unlock profound insights into the consequences of space travel on the human body. Through implementation of security measures to protect sensitive human data, the OSDR seeks to strengthen the science exchange between the Biological and Physical Sciences Program and the Human Research Program, per recommendation 4-1 of the 2023-2032 Decadal Survey, and encourage further sharing and dissemination of astronaut data to provide the scientific community with the resources needed to lay the groundwork for developing targeted mitigation strategies to help withstand the rigors of long-duration spaceflight.

Amanda Marie Saravia-butler↗
DOE OSTI2024

Data-Driven Surrogate Modeling with Microstructure-Sensitivity of Viscoplastic Creep in Grade 91 Steel

Abstract To support the development of advanced steel alloys tailored to withstand extreme conditions, it is imperative to account for the mechanical performance of components, while considering the influence of local microstructure on the macroscopic response. To this end, this study focuses on the development of microstructure-sensitive constitutive models for the mechanical response of Grade 91 steel exposed to extreme thermo-mechanical environments. Polynomial chaos expansion (PCE) surrogates are used to emulate high-fidelity polycrystal simulations of the viscoplastic response of Grade 91 steel as a function of the microstructure fingerprint (e.g., dislocations and precipitates). To cover a wide temperature–stress domain, two separate PCE surrogates—one that captures softening and the other that captures hardening behavior—are combined using another (sparse) Gaussian process regression model. The resulting constitutive creep surrogate model is integrated within the MOOSE finite element framework to simulate the intricate effects of microstructure, in particular MX-phase precipitates, on a component with a graded microstructure. Surrogate sensitivity analysis is applied to quantify the relevant impact of spatially varying microstructure on the creep response in a test-case involving a Grade 91 alloy with a prototypical weld.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Differentially Private Synthesis and Sharing of Network Data Via Bayesian Exponential Random Graph Models

Abstract Network data often contain sensitive relational information. One approach to protecting sensitive information while offering flexibility for network analysis is to share synthesized networks based on the information in originally observed networks. We employ differential privacy (DP) and exponential random graph models (ERGMs) and propose the DP-ERGM method to synthesize network data. We apply DP-ERGM to two real-world networks. We then compare the utility of synthesized networks generated by DP-ERGM, the DyadWise Randomized Response (DWRR) approach, and the Synthesis through Conditional distribution of Edge given nodal Attribute (SCEA) approach. In general, the results suggest that DP-ERGM preserves the original information significantly better than two other approaches in network structural statistics and inference for ERGMs and latent space models. Furthermore, DP-ERGM satisfies node DP through modeling the global network structure with ERGM, a stronger notion of privacy than the edge DP under which DWRR and SCEA operate.

graph synthesis↗