Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “distributed inference”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Switchback Boundary Dissipation and Relative Age

We examine Parker Solar Probe (PSP) magnetic field and plasma observations during its first encounter with the Sun in early 2018 November. During this perihelion time, impulsive reversals in the magnetic field, called "switchbacks," were found in the data set characterized by a quick rotation in B along with a simultaneous increase in solar wind flow. In this work, we examine the structure and morphology of 920 switchback boundaries as PSP enters and exits the structures, specifically looking for evidence of boundary degradation, dissipation, and associated ultralow frequency (ULF) magnetic wave activity. We find that boundaries with the most abrupt, step-function-like change in Br and Vr also show little evidence of dissipation and ULF wave activity. In contrast, there is a set of boundaries that appears highly degraded with ULF magnetic activity in the vicinity of the boundary. We thus infer that the steep, step-like boundaries with little ULF activity are relatively young in comparison to the degraded boundaries. The distribution in relative ages suggests that the switchback boundary formation process is dynamic and evolving, even occurring near the PSP observation point inside of 40 Rs.

W. M. Farrell↗
DOE OSTI2026

Simultaneous global and local clustering in multiplex networks with covariate information

Understanding both global and layer-specific group structures is useful for uncovering complex patterns in networks with multiple interaction types. In this work, we introduce a new model, the hierarchical multiplex stochastic blockmodel, which simultaneously detects communities within individual layers of a multiplex network while inferring a global node clustering across the layers. A stochastic blockmodel is assumed in each layer, with probabilities of layer-level group memberships determined by a node’s global group assignment. Our model uses a Bayesian framework, employing a probit stick-breaking process to construct node-specific mixing proportions over a set of shared Griffiths–Engen–McCloseky distributions. These proportions determine layer-level community assignment, allowing for an unknown and varying number of groups across layers, while incorporating nodal covariate information to inform the global clustering. We propose a scalable variational inference procedure with parallelisable updates for application to large networks. Extensive simulation studies demonstrate our model’s ability to accurately recover both global and layer-level clusters in complicated settings, and applications to real data showcase the model’s effectiveness in uncovering interesting latent network structure.

community detection↗
DOE OSTI2021

Contaminant Source Identification from Finite Sensor Data: Perron–Frobenius Operator and Bayesian Inference

Sensors in the built environment ensure safety and comfort by tracking contaminants in the occupied space. In the event of contaminant release, it is important to use the limited sensor data to rapidly and accurately identify the release location of the contaminant. Identification of the release location will enable subsequent remediation as well as evacuation decision-making. In previous work, we used an operator theoretic approach—based on the Perron–Frobenius (PF) operator—to estimate the contaminant concentration distribution in the domain given a finite amount of streaming sensor data. In the current work, the approach is extended to identify the most probable contaminant release location. The release location identification is framed as a Bayesian inference problem. The Bayesian inference approach requires considering multiple release location scenarios, which is done efficiently using the discrete PF operator. The discrete PF operator provides a fast, effective and accurate model for contaminant transport modeling. The utility of our PF-based Bayesian inference methodology is illustrated using single-point release scenarios in both two and three-dimensional cases. The method provides a fast, accurate, and efficient framework for real-time identification of contaminant source location.

42 ENGINEERING↗
DOE OSTI2024

Multiscale Flow for robust and optimal cosmological analysis

We propose Multiscale Flow, a generative Normalizing Flow that creates samples and models the field-level likelihood of two-dimensional cosmological data such as weak lensing. Multiscale Flow uses hierarchical decomposition of cosmological fields via a wavelet basis and then models different wavelet components separately as Normalizing Flows. The log-likelihood of the original cosmological field can be recovered by summing over the log-likelihood of each wavelet term. This decomposition allows us to separate the information from different scales and identify distribution shifts in the data such as unknown scale-dependent systematics. The resulting likelihood analysis can not only identify these types of systematics, but can also be made optimal, in the sense that the Multiscale Flow can learn the full likelihood at the field without any dimensionality reduction. We apply Multiscale Flow to weak lensing mock datasets for cosmological inference and show that it significantly outperforms traditional summary statistics such as power spectrum and peak counts, as well as machine learning–based summary statistics such as scattering transform and convolutional neural networks. We further show that Multiscale Flow is able to identify distribution shifts not in the training data such as baryonic effects. Finally, we demonstrate that Multiscale Flow can be used to generate realistic samples of weak lensing data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A small core in Vesta inferred from Dawn’s observations

Vesta’s large-scale interior structure had previously been constrained primarily using the gravity and shape data from the Dawn mission. However, these data alone still allow a wide range of possibilities for the differentiation state of the body. The moment of inertia is arguably the most diagnostic parameter related to the radial density distribution of a planetary body, making it crucial for assessing the body’s state of internal differentiation. Determining the moment of inertia requires additional measurements of the amplitudes of small rotational motions, such as precession and nutation. Here we report an updated estimate of the moment of inertia of Vesta inferred from Dawn’s Doppler tracking via the Deep Space Network and onboard imaging data. The recovered value for Vesta’s normalized polar moment of inertia is $\overline{C}$/MR 2 = 0.4208 ± 0.0047 (where M is the mass of Vesta and R is the reference radius), which is only 6.6% lower than the homogeneous value of 0.4505. This value, combined with the gravity field and global shape, suggests that Vesta’s interior has limited density stratification beneath its howardite–eucrite–diogenite-dominated crust. We propose two possible origin scenarios that are consistent with the observed constraints. In the first scenario, Vesta’s interior did not undergo full differentiation due to late accretion. In the second scenario, Vesta originated as an impact remnant of a larger differentiated body re-accreted with non-chondritic bulk composition produced from a catastrophic impact. Vesta did not experience complete differentiation in either scenario, suggesting that its current state reflects a complex interplay between its accretion timing, thermal evolution, redistribution of 26 Al bearing melt and/or impact processes.

CNEOS 2014-01-08 bolide↗
NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 1

Contents include the following: Observations with Near Infrared Spectrometer for Hayabusa Mission in the Cruising Phase. First Results of Quadrantid Meteor Spectrum. Compositional Investigation of Binary Near-Earth Asteroid 66063 (1998 RO1): A Potentially Undifferentiated Assemblage. Impact-induced Hydrothermal Activity on Early Mars. HRTEM and EFTEM Studies of Phyllosilicate-Organic Matter Associations in Matrix and Dark Inclusions in the EET92042 CR2 Carbonaceous Chondrite. Volumetric Analysis of Martian Rampart Craters. High Pressure Melting of H-Chondrite: A Match for the Martian Basalt Source Mantle. MERView: A New Computer Program for Easy Display of MER-acquired M ssbauer Data. Distribution, Exchange, and Topographic Control of Subsurface Ice on Mars. Shock-induced Damage Beneath Normal and Oblique Impact Craters. Amphitrites Patera Studied from the Mars Express HRSC Data. Oxygen Isotope Microanalysis of Enveloping Compound Chondrules in CV3 and LL3 Chondrites. Gamma-Ray Irradiation in the Early Solar System and the Conundrum of the Lu-176 Decay Constant. Magnesium Isotope Mapping of Silica-rich Grains Having. Extreme Oxygen Isotope Anomalies Extreme Oxygen Isotopic Anomalies from Irradiation in the Early Solar System, Re-Examining the Role of Chondrules in Producing the Elemental Fractionations in Chondrites. Meteorite Data on the Solar Modulation of Galactic Cosmic Rays and an Inference on the Solar Activity Influence on Climate of the Earth. Volatiles Enrichments and Composition of Jupiter. Thinking Like a Wildcatter Prospecting for Methane in Arabia Terra, Mars. Size Distribution of Genesis Solar Wind Array Collector Fragments. Initial Subdivision of Genesis Early Science Polished Aluminum Collector. Presolar Graphite and Its Noble Gases. Young Pb-Isotopic Ages of Chondrules in CB Carbonaceous Chondrites. Fe Isotopic Composition of Martian Meteorites. Petrology and Geochemistry of Nakhlite MIL 03346: A New Martian Meteorite from Antarctica.

Source record↗
DOE OSTI2023

Deducing subnanometer cluster size and shape distributions of heterogeneous supported catalysts

Abstract Infrared (IR) spectra of adsorbate vibrational modes are sensitive to adsorbate/metal interactions, accurate, and easily obtainable in-situ or operando. While they are the gold standards for characterizing single-crystals and large nanoparticles, analogous spectra for highly dispersed heterogeneous catalysts consisting of single-atoms and ultra-small clusters are lacking. Here, we combine data-based approaches with physics-driven surrogate models to generate synthetic IR spectra from first-principles. We bypass the vast combinatorial space of clusters by determining viable, low-energy structures using machine-learned Hamiltonians, genetic algorithm optimization, and grand canonical Monte Carlo calculations. We obtain first-principles vibrations on this tractable ensemble and generate single-cluster primary spectra analogous to pure component gas-phase IR spectra. With such spectra as standards, we predict cluster size distributions from computational and experimental data, demonstrated in the case of CO adsorption on Pd/CeO 2 (111) catalysts, and quantify uncertainty using Bayesian Inference. We discuss extensions for characterizing complex materials towards closing the materials gap.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1978

Round jet in a cross flow - Influence of injection angle on vortex properties

A model is developed to infer the properties of a pair of diffuse contrarotating vortices for perpendicular jet injection into the cross flow. Attention is given to pressure distribution on the surface where the jet exhausts, especially in terms of V/STOL applications. A V/STOL wind tunnel experiment is described, whereby a round jet of air (10.16 cm dia) was discharged through a horizontal flat plate into the cross flow of the wind tunnel test section at angles of 45, 60, 75, and 90 deg. Results indicate that the effective vortex strength for both velocity ratios is highest near the jet orifice, and decreases as the vortices are swept downstream, at which point the effective vortex spacing increases. In addition, the core radius of the vortex exhibits properties similar to those of the effective vortex spacing

Krausche, D.↗
NASA NTRS1992

The natural thermoluminescence of meteorites. IV - Ordinary chondrites at the Lewis Cliff ice field

Results of natural thermoluminescence (TL) measurements of 302 meteorites from the vicinity of the Lewis Cliff in the Beardmore region of Antarctica are presented in order to identify fragments of a single fall and to elucidate ice sheet movements and the mechanisms by which meteorite concentration occurs at this site. From the distribution of meteorites on the ice, the shape of the fields of 'paired' meteorites, and trends in the natural TL data, it is inferred that there is a western component to the movement of the ice at this location, as well as the previously supposed movement to the north. The western vector explains the concentration of meteorites along the western edge of the ice tongue. These new natural TL data identify several recent falls and several meteorites which probably had unusually small perihelia immediately prior to capture by the earth.

Benoit, Paul H.↗
NASA NTRS1994

Cometary dust: A thermal criterion to identify cometary samples among the collected interplanetary dust

The relative proportions of the cometary and the asteroidal contributions to the interplanetary dust have not yet been definitively established. These proportions may vary with time as a result of major catastrophic disruptions in the main belt or the appearance of fresh, active comets. Dermott et al. and Reach suggest the debris from catastrophic collisions in the main belt can account for most of the zodiacal cloud particles. Earth collection of these asteroidal particles is strongly favored by near-Earth gravitational enhancement. However, comets are observed to produce interplanetary dust particles (IDP's), and the identification of cometary IDP's would allow inferences of the compositions, mineralogies, and physical properties of the comets. The peak temperatures reached by IDP's on atmospheric entry indicate the distribution of IDP velocities. Each IDP contains many internal thermometers: minerals that transform above certain temperatures, volatile elements that are lost sequentially with increasing temperatures, solar flare tracks that anneal at different temperatures in different minerals, and solar-implanted noble gases that outgas progressively with temperature. Thus, limits on the peak temperature reached by each IDP on Earth atmospheric entry can be set. Other aspects of this investigation are covered.

Flynn, George J.↗
NASA NTRS1995

Average motion, structure and orientation of the distant magnetotail determined from remote sensing of the edge of the plasma sheet boundary layer with E greater than 35 keV ions

We study gradients of the energetic ion intesity observed at the edge of the plasma sheet boundary layer (PSBL) by the energetic ion anisotropy spectrometer (EPAS) on International Sun Earth Explorer 3 (ISEE 3). In particular, we have determined the velocity of the boundary relative to the spacecraft in the direction perpendicular to the tail axis and the angle which the boundary normal makes to the spacecraft spin axis for 1160 PSBL encounters at X(sub GSM) greater than -240 R(sub E). By asuming that, on average, the edge of the PSBL is parallel to the cross-tail current sheet, we are then able to determine a number of properties of the structure, orientation and motion of the deep geomagnetic tail. We conclude the following: (1) Most crossings of the edge of the PSBL are caused by transverse motuion of the entire tail induced by solar wind direction variations, although some are caused by reconfiguration of the tail due to geomagnetic activity. (2) The typical velocity of the PSBL (and hence of the tail) in the direction perpendicular to the tail axis is 50-85 km/s. (3) The average twist of the tail is near zero, with the edge of the PSBL (and by inference the cross-tail current sheet) lying parallel to the ecliptic plane (however, large twists are found in individual events and the distribution of twists is broad, with one standard deviation of approximately 50 deg. (4) The width of the distribution decreases with downtail distance. (5) The variation of the distributions with cross-tail position reveals that this decreas in width is most likely due to the edge of the PSBL being concave, or significantly flared at the tail flanks, in the near-Earth region. (6) During days on which the Interplanetary Magnetic Field (IMF) has 'away' sector structure, the north lobe of the trail is twisted on average towards dawn by 7.0 +/-2.4 deg. (7) During days on which the IMF has 'toward' sector structure, the north lobe is tilted towards duskby 3.8 +/- 2.3. (8) A subset of events for which IMP 8 solar wind data are available show that, for southward IMF BH(sub z) the tail has a mean twist of -12.3 +/- 5.0 deg for IMF B(sub Y) greater than 0 and 5.5 +/- 3.8 deg for IMF B(sub Y) less than 0 (positive twist angles correspond to a tilt of the northern lobe towards dusk). (9) For northward IMF B(sub z) the tail has a twist of -23.9 +/- 5.0 deg for IMF B(sub Y) greater than 0 and 13.4 +/- 6.0 deg for IMF B(sub y) less than 0. Hence the tail appears more twisted on average for the IMF B(sub Z) northward case. (10) The distribution of tail twist is wider for lower levels of geomagnetic activity, indicating that the tail is able to twist more at lower levels of activity. (11) The data set reveals no evident effect of the earth's dipole wobble; tail orientation appears to be controlled by the solar wind and IMF, such that the GSE coordinate system may be appropriate for the study of field and plasma structures in the distant tail region.

Owen, C. J.↗
NASA NTRS2012

Flux Estimates of Ions from the Lunar Exosphere

We compare estimates for the ion fluxes of twelve expected constituents of the lunar exosphere with estimates for the ion fluxes ejected from the lunar surface by solar wind ions and electrons. Our estimates demonstrate that measurements of lunar ions will help constrain the abundances of many undetected species in the lunar exosphere, particularly AI and Si, because the expected ion flux levels from the exosphere exceed those from the surface. To correctly infer the relative abundances of exospheric ions and neutrals from Kaguya Ion Mass Analyzer (IMA) measurements, we must take into account the velocity distributions of local ions. The predicted spectrum underestimates the measured levels of 0+ relative to other lunar ion species, a result that may suggest contributions by molecular ions to the measured 0+ rates.

Sarantos, M.↗
NASA NTRS2011

A Sensitivity Study on the Effects of Particle Chemistry, Asphericity and Size on the Mass Extinction Efficiency of Mineral Dust in the Earth's Atmosphere: From the Near to Thermal IR

To determine a plausible range of mass extinction efficiencies (MEE) of terrestrial atmospheric dust from the near to thermal IR, sensitivity analyses are performed over an extended range of dust microphysical and chemistry perturbations. The IR values are subsequently compared to those in the near-IR, to evaluate spectral relationships in their optical properties. Synthesized size distributions consistent with measurements, model particle size, while composition is defined by the refractive indices of minerals routinely observed in dust, including the widely used OPAC/Hess parameterization. Single-scattering properties of representative dust particle shapes are calculated using the T-matrix, Discrete Dipole Approximation and Lorenz-Mie light-scattering codes. For the parameterizations examined, MEE ranges from nearly zero to 1.2 square meters per gram, with the higher values associated with non-spheres composed of quartz and gypsum. At near-IR wavelengths, MEE for non-spheres generally exceeds those for spheres, while in the thermal IR, shape-induced changes in MEE strongly depend on volume median diameter (VMD) and wavelength, particularly for MEE evaluated at the mineral resonant frequencies. MEE spectral distributions appear to follow particle geometry and are evidence for shape dependency in the optical properties. It is also shown that non-spheres best reproduce the positions of prominent absorption peaks found in silicates. Generally, angular particles exhibit wider and more symmetric MEE spectral distribution patterns from 8-10 micrometers than those with smooth surfaces, likely due to their edge-effects. Lastly, MEE ratios allow for inferring dust optical properties across the visible-IR spectrum. We conclude the MEE of dust aerosol are significant for the parameter space investigated, and are a key component for remote sensing applications and the study of direct aerosol radiative effects.

Hansell, R. A., Jr.↗
NASA NTRS1997

The Galim LL/EH Polymict Breccia: Evidence for Impact-Induced Exchange Between Reduced and Oxidized Meteoritic Material

Galim is a polymict breccia consisting of a heavily shocked (shock stage S6) LL6 chondrite, Galim (a), and an impact-melted EH chondrite, Galim (b). Relict chondrules in Galim (b) served as nucleation sites for euhedral enstatite grains crystallizing from the impact melt. Many of the reduced phases typical of EH chondrites (e.g., Si-bearing metallic Fe-Ni; Ti-bearing troilite) are absent. Galim (b) was probably shock-melted while in contact with a more oxidized source, namely, Galim (a); during this event, Si was oxidized from the metal and Ti was oxidized from troilite. Galim (a) contains shock veins and recrystallized, unzoned olivine. The absence of evidence for reduction in Galim (a) may indicate that the amount of LL material greatly exceeded that of EH material; shock metamorphism may have taken place on the LL parent body. Shock-induced redox reactions such as those inferred for the Galim breccia appear to be restricted mainly to asteroids because the low-end tail of their relative-velocity distribution permits mixing of intact disparate materials (including accretion of projectiles of different oxidation states), whereas the peak of the distribution leads to high equilibration shock pressures (allowing impact-induced exchange between previously accreted, disequilibrated materials). Galim probably formed by a two-stage process: (I) accretion to the LL parent body of an intact EH projectile at low relative velocities, and (2) shock metamorphism of the assemblage by the subsequent impact of another projectile at significantly higher relative velocities.

Rubin, Alan E.↗
DOE OSTI2020

Exploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data

The physics of ferroelectric domain walls is explored using the Bayesian inference analysis of atomically resolved STEM data. We demonstrate that domain wall profile shapes are ultimately sensitive to the nature of the order parameter in the material, including the functional form of Ginzburg-Landau-Devonshire expansion, and numerical value of the corresponding parameters. The preexisting materials knowledge naturally folds in the Bayesian framework in the form of prior distributions, with the different order parameters forming competing (or hierarchical) models. Here, we explore the physics of the ferroelectric domain walls in BiFeO 3 using this method, and derive the posterior estimates of relevant parameters. More generally, this inference approach both allows learning materials physics from experimental data with associated uncertainty quantification, and establishing guidelines for instrumental development answering questions on what resolution and information limits are necessary for reliable observation of specific physical mechanisms of interest.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

pop-cosmos : redshifts and physical properties of KiDS-1000 galaxies

ABSTRACT Principled Bayesian inference of galaxy properties has not previously been performed for wide-area weak-lensing surveys with millions of sources. We address this gap by applying the pop-cosmos generative model to perform spectral energy distribution (SED) fitting for 4 million KiDS (Kilo-Degree Survey)-1000 galaxies. Calibrated on deep COSMOS2020 photometric data, pop-cosmos specifies a physically motivated prior over the galaxy population up to $z \simeq 6$ in stellar population synthesis (SPS) parameter space. Using the Speculator SPS emulator with GPU (graphics processing unit)-accelerated Markov Chain Monte Carlo sampling, we perform full posterior inference at 8.2 GPU seconds per galaxy, obtaining joint constraints on galaxy redshifts and physical properties. We validate photometric redshifts against $\sim \!185\,\!000$ KiDS galaxies cross-matched to Dark Energy Spectroscopic Instrument Data Release 1 spectroscopic samples, achieving low bias ($2\times 10^{-3}$), scatter ($\sigma _{\mathrm{MAD}}=0.03$), and outlier fraction (3.2 per cent) for the Bright Galaxy Survey, with comparable performance (bias $3\times 10^{-2}$, $\sigma _{\mathrm{MAD}}=0.05$, 1.0 per cent outliers) for luminous red galaxies (LRGs). Within the LRG sample, we identify massive, dusty, star-forming contaminants at $z \simeq 0.4$ satisfying standard colour selections for quenched populations. We infer trends in stellar mass, star formation, metallicity, and dust across five tomographic redshift bins consistent with established scaling relations. Using specific star formation rate constraints, we identify $\sim$7 per cent of KiDS-1000 galaxies as quenched, versus 37 per cent implied by conservative colour cuts. This enables the construction of weak-lensing samples defined by physical properties while mitigating intrinsic alignment systematics and preserving statistical power. Our analysis validates pop-cosmos out of sample, establishing it as a scalable approach for galaxy evolution and cosmological analyses with photometric surveys.

Halder, Anik [Institute of Astronomy and Kavli Ins↗
DOE OSTI2025

Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. Furthermore, to facilitate Bayesian inference with intractable likelihoods, we propose to utilize optimization iterates for maximum a posteriori estimation to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. We demonstrate the effectiveness of our Bayesian optimization algorithms in nonconvex benchmark objective functions, in a machine learning hyperparameter tuning problem, and in a black-box engineering design problem. The effectiveness of our posterior approximation approach is demonstrated in two Bayesian inference problems for parameters of dynamical systems.

Bayesian inference↗
NASA NTRS2021

Salvaging Data Records with Missing Data: Data Imputation using the Multivariate t Distribution

When doing multivariate data analysis, one commonobstacle is the presence of incomplete observations, i.e., observationsfor which one or more key fields are blank. Missing datais often countered by deleting entire observations that containmissing data. The negative effects of deleting entire observationsare multiple: deleting observations reduces sample size andcan also result in biased inferences even if data is missing atrandom. In addition, knowledge contained within incompleteobservations is knowledge lost when they are deleted– and theeffort spent collecting that knowledge is effort wasted. Data imputationmethods, or methods of statistically “filling-in” missingdata, can help combat small sample sizes by using the existinginformation in partially complete observations with the end goalof producing less biased and higher confidence inferences. Whena sample from a multivariate normal population is only partiallycomplete, and the missing data meets appropriate assumptions(missing at random), robust data imputation of the missing datacan be implemented with monotone data augmentation (MDA)using the multivariate t distribution.Missing data imputation is applied to data from the NASA InstrumentCost Model (NICM) using the MDA algorithm underthe assumption of having a multivariate t distribution with fixeddegrees of freedom. A sensitivity analysis to the degrees offreedom parameter is presented to demonstrate robustness ofthe multivariate t distribution when dealing with small samplesas compared to the multivariate normal distribution.

DiNicola, Michael↗