SEARCH · Search NASA

Results for “inference methods”

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,423 records · Page 79

All sources NASA NTRS DOE OSTI

DOE OSTI2025

A convergence metric for counting statistics in time-resolved small angle neutron scattering

Here, this work introduces a model-independent, dimensionless metric for predicting optimal measurement duration in time-resolved small-angle neutron scattering using early-time data. Built on a Gaussian process regression framework, the method reconstructs scattering profiles with quantified uncertainty, even from sparse or noisy measurements. Demonstrated on the EQ-SANS instrument at the Spallation Neutron Source, the approach generalizes to general SANS instruments with a two-dimensional detector. A key result is the discovery of a dimensionless convergence metric revealing a universal power-law scaling in profile evolution across soft matter systems. When time is normalized by a system-specific characteristic time t*, the variation in inferred profiles collapses onto a single curve with an exponent between −2 and −1. This trend emerges within the first ten time steps, enabling early prediction of measurement sufficiency. The method supports real-time experimental optimization and is especially valuable for maximizing efficiency in low-flux environments such as compact accelerator-based neutron sources.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗

NASA NTRS2011

Comparison of Resource Requirements for a Wind Tunnel Test Designed with Conventional vs. Modern Design of Experiments Methods

The factors that determine data volume requirements in a typical wind tunnel test are identified. It is suggested that productivity in wind tunnel testing can be enhanced by managing the inference error risk associated with evaluating residuals in a response surface modeling experiment. The relationship between minimum data volume requirements and the factors upon which they depend is described and certain simplifications to this relationship are realized when specific model adequacy criteria are adopted. The question of response model residual evaluation is treated and certain practical aspects of response surface modeling are considered, including inference subspace truncation. A wind tunnel test plan developed by using the Modern Design of Experiments illustrates the advantages of an early estimate of data volume requirements. Comparisons are made with a representative One Factor At a Time (OFAT) wind tunnel test matrix developed to evaluate a surface to air missile.

DeLoach, Richard↗

DOE OSTI2024

Implementing Superresolution of Nonstationary Tides with Wavelets: An Introduction to CWT_Multi

Abstract Tides are often nonstationary due to nonastronomical influences. Investigating variable tidal properties implies a trade-off between separating adjacent frequencies (using long analysis windows) and resolving their time variations (short analysis windows). Previous continuous wavelet transform (CWT) tidal methods resolved tidal species. Here, we present CWT_Multi, a MATLAB code that 1) uses CWT linearity (via the “response coefficient method”) to implement superresolution, i.e., resolving tidal constituents beyond the Rayleigh criterion; 2) provides a Munk–Hasselmann constituent selection criterion appropriate for superresolution; and 3) introduces an objective, time-variable form of inference (“dynamic inference”) based on time-varying data properties. CWT_Multi resolves tidal species on time scales of days, and multiple constituents per species with fortnightly filters. It outputs astronomical phase lags and admittances, analyzes multiple records, and provides power spectra of the signal(s), residual(s), and reconstruction(s); confidence limits; and signal-to-noise ratios. Artificial data and water levels from the Lower Columbia River Estuary (LCRE) and San Francisco Bay Delta (SFBD) are used to test CWT_Multi and compare it to harmonic analysis programs NS_Tide and UTide. CWT_Multi provides superior reconstruction, detiding, dynamic analysis utility, and time resolution of constituents (but with broader confidence limits). Dynamic inference resolves closely spaced constituents (like K 1 , S 1 , and P 1 ) on fortnightly time scales, quantifying impacts of diel power peaking (with a 24-h period, like S 1 ) on water levels in the LCRE. CWT_Multi also helps quantify the impacts of high flows and a salt barrier closing on tidal properties in the SFBD. On the other hand, CWT_Multi does not excel at prediction, and results depend on analysis details, as for any method applied to nonstationary data. Significance Statement Ocean tides, especially in coastal and estuarine systems, are often nonstationary, in the sense that the mean and standard deviation of tidal properties vary over time, usually in response to some nontidal process. We introduce here a MATLAB code, CWT_Multi, that uses wavelet transforms to resolve both tidal species and constituents on time scales from a few days to months. Our code accommodates multiple scalar time series and has typical tidal analysis features like constituent selection and inference, plus two forms of uncertainty analyses. It is flexible, allowing the user to adapt analysis properties to diverse datasets. CWT_Multi is applicable to many problems involving time-variable tides, including sea level rise, compound flooding, sediment transport, and wetland habitat analyses. Application to vector data is a straightforward extension, but further development of our uncertainty analysis is merited. Because nonstationary tidal analysis is rapidly advancing, we also define the features of a “well-formed” analysis code.

Lobo, Matthew↗

DOE OSTI2021

Quantitative assessment of Distributed Acoustic Sensing at the Source Physics Experiment, Phase II

In this report, we assess the data recorded by a Distributed Acoustic Sensing (DAS) cable deployed during the Source Physics Experiment, Phase II (DAG) in comparison with the data recorded by nearby 4.5-Hz geophones. DAS is a novel recording method with unprecedented spatial resolution, but there are significant concerns around the data fidelity as the technology is ramped up to more common usage. Here we run a series of tests to quantify the similarity between DAS data and more conventional data and investigate cases where the higher spatial resolution of the DAS can provide new insights into the wavefield. These tests include 1D modeling with seismic refraction and bootstrap uncertainties, assessing the amplitude spectra with distance from the source, measuring the frequency dependent inter-station coherency, estimating time-dependent phase velocity with beamforming and semblance, and measuring the cross-correlation between the geophone and the particle velocity inferred from the DAS. In most cases, we find high similarity between the two datasets, but the higher spatial resolution of the DAS provides increased details and methods of estimating uncertainty.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Quantitative assessment of Distributed Acoustic Sensing at the Source Physics Experiment (Phase II)

58 GEOSCIENCES↗

NASA NTRS1986

Measuring interstellar dust grains from the haloes of binary X-ray sources

A method for determining the location, size distribution, and composition of interstellar dust grains from the haloes of binary X-ray sources is described. The method is based on the time dependence of the halo X-ray emission during an eclipse of the point source. The distance of the dust cloud is inferred directly from observations of the growth of the dark circle around the eclipsed point source. Grain size distribution in the interstellar dust clouds is derived from the halo brightness profile at a given photon energy. The composition of the grains is obtained by observing the spectral features in the total optical depth due to X-ray scattering near the photoionization thresholds of the elements in the grains. The haloes become dim just below the ionization threshold, and sharply increase in function brightness as the photon energy increases beyond the absorption edge of the relevant atom. The method makes it possible to observe and analyze the halo emission during eclipse even without imaging the source. It is suggested that haloes probably account for the soft X-rays observed during eclipses and dips observed in sources including 4U1915-05 and X1755-338.

Xu, Y.↗

NASA NTRS2003

Furrow Topography and the Elastic Thickness of Ganymede's Dark Terrain Lithosphere

The effective elastic thickness of Ganymede's lithosphere tell of the satellite's thermal evolution through time. Generally it has been inferred that dark terrain, which is less tectonically deformed than grooved terrain, represents regions of cooler and thicker lithosphere [1]. The ancient dark terrain is cut by furrows, tectonic troughs about 5 to 20 km in width, which may have formed in response to large ancient impacts [1, 2]. We have applied the methods of [3] to estimate effective elastic thickness based on topographic profiles across tectonic furrows, extracted from a stereo-derived digital elevation model (DEM) of dark terrain in Galileo Regio [4]. Asymmetry in furrow topography and inferred flexure suggests asymmetric furrow fault geometry. We find effective elastic thicknesses ~0.4 km, similar to analyzed areas alongside bright grooved terrain. Data and Analysis: A broken-plate elastic model.

Pappalardo, Robert T.↗

NASA NTRS2017

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 (FFT) 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 multi-point hierarchy. We identify some threads of modern large scale inference methodology that will presumably yield detections in new wider and deeper surveys.

Galactic clusters↗

DOE OSTI2022

SDSS-IV MaNGA: the chemical co-evolution of gas and stars in spiral galaxies

ABSTRACT We investigate archaeologically how the metallicity in both stellar and gaseous components of spiral galaxies of differing masses evolve with time, using data from the SDSS-IV MaNGA survey. For the stellar component, we can measure this evolution directly by decomposing the galaxy absorption-line spectra into populations of different ages and determining their metallicities. For the gaseous component, we can only measure the present-day metallicity directly from emission lines. However, there is a well-established relationship between gas metallicity, stellar mass, and star formation rate which does not evolve significantly with redshift; since the latter two quantities can be determined directly for any epoch from the decomposition of the absorption-line spectra, we can use this relationship to infer the variation in gas metallicity over cosmic time. Comparison of present-day values derived in this way with those obtained directly from the emission lines confirms the validity of the method. Application of this approach to a sample of 1619 spiral galaxies reveals how the metallicity of these systems has changed over the last 10 billion yr since cosmic noon. For lower-mass galaxies, both stellar and gaseous metallicity increase together, as one might expect in well-mixed fairly isolated systems. In higher-mass systems, the average stellar metallicity has not increased in step with the inferred gas metallicity, and actually decreases with time. Such disjoint behaviour is what one might expect if these more massive systems have accreted significant amounts of largely pristine gas over their lifetimes, and this material has not been well mixed into the galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

A novel application of cosmic rays for spent nuclear fuel monitoring - 15738

Monitoring nuclear waste and controlling spent nuclear fuel at its source is one of the main strategies to minimize the risks of nuclear proliferation and reduce potential homeland threats. Storage of high level waste from a fission reactor typically involves placing spent fuel in sealed dry casks. After the spent nuclear fuel has been placed inside the dry cask, the cask is welded, not allowing for visual inspection. Conventional methods for examining the interior of materials e.g., X-rays, are limited by the fact that they cannot penetrate very dense well-shielded objects. Instead, cosmic ray muons have the potential to allow for assessment of spent nuclear fuel stored within sealed dense dry casks. Objectives: 1.Exploit the ability of cosmic ray muons to penetrate high density materials allowing the distribution of materials within the object to be inferred from the muon tracks. 2. Develop a monitoring system that tracks the path of cosmic ray muons, including their deflection and attenuation, to identify the contents of a closed dry cask. Methods: - Monte-Carlo simulations using Geant4; - Bayesian decision theory for signal classification; - Wavelet analysis for noise cancellation; - Chaotic Neural Networks for signal encryption. Results: 1. Preliminary statistical analysis proved that the method is feasible and has the ability to identify the presence of spent nuclear fuel in a dry cask. 2. Using monoenergetic muons, a dry cask with one fuel assembly missing can be correctly identified with error rate <1%. Broader merit: Once completed, the proposed project for cosmic ray muon transport will enable a new and potentially transformative approach towards efficient, inexpensive and remote cosmic ray muon applications in archaeology, medicine and safeguarding of nuclear materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

The clustering of DESI-like luminous red galaxies using photometric redshifts

ABSTRACT We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging data set, and use the halo occupation distribution (HOD) framework to fit the clustering signal. The photometric LRG sample in this study contains 2.7 million objects over the redshift range of 0.4 < z < 0.9 over 5655 deg2. We have developed new photometric redshift (photo-z) estimates using the Legacy Survey DECam and WISE photometry, with σNMAD = 0.02 precision for LRGs. We compute the projected correlation function using new methods that maximize signal-to-noise ratio while incorporating redshift uncertainties. We present a novel algorithm for dividing irregular survey geometries into equal-area patches for jackknife resampling. For a five-parameter HOD model fit using the MultiDark halo catalogue, we find that there is little evolution in HOD parameters except at the highest redshifts. The inferred large-scale structure bias is largely consistent with constant clustering amplitude over time. In an appendix, we explore limitations of Markov chain Monte Carlo fitting using stochastic likelihood estimates resulting from applying HOD methods to N-body catalogues, and present a new technique for finding best-fitting parameters in this situation. Accompanying this paper, we have released the Photometric Redshifts for the Legacy Surveys catalogue of photo-z’s obtained by applying the methods used in this work to the full Legacy Survey Data Release 8 data set. This catalogue provides accurate photometric redshifts for objects with z < 21 over more than 16 000 deg2 of sky.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters

High-precision calorimeter simulation at current and future colliders imposes rapidly growing computational demands, motivating the development of machine-learning surrogates for traditional Monte Carlo tools such as Geant4. Flow matching and diffusion-based generative models have become leading approaches for high-dimensional fast simulation because of their sample quality, but typically require ${\cal O}(100)$ function evaluations at inference and often rely on auxiliary networks to constrain global observables, compromising streamlined end-to-end generation. We introduce a unified framework that improves the balance between speed, shower quality, and physics fidelity. The method combines: (i) an average velocity field integrator that enables sampling in one or a few evaluations; (ii) a learned generative prior in shower space, constructed from data rather than random noise; and (iii) physics-guided loss terms that impose inductive biases on key observables during training. These elements are training time regularizers, preserving end-to-end inference with no additional cost. With only one or a few evaluation steps, the model achieves shower quality competitive with state-of-the-art flow and diffusion approaches, tested on several public high granularity calorimeter datasets. The results demonstrate inter-layer shower structure consistent with the underlying physics, providing a strong candidate for future fast simulation workflows.

Jiang, Cheng [Edinburgh U.]↗

DOE OSTI2018

Unsupervised learning about 4D features of microparticle motion

Material clusters of different sizes are known to exist in high-temperature plasmas due to plasma-wall interactions. The facts that these clusters, ranging from sub-microns to above mm in size, can move from one location to another quickly and that there are a lot of them make high-speed imaging and tracking one of the best, effective, and sometimes only diagnostic. An unsupervised machine learning technique based on deconvolutional neural networks is developed to analyze two-camera videos of high-temperature microparticles generated from exploding wires. The neural network utilizes a locally competitive algorithm to infer representations and optimize a dictionary composed of kernels, or basis vectors, for image analysis. Our primary goal is to use this method for feature recognition and prediction of the time-dependent three-dimensional (or “4D”) microparticle motion. Features equivalent to local velocity vectors have been identified as the dictionary kernels or “building blocks” of the scene. The dictionary elements from the left and right camera views are found to be strongly correlated and satisfy the projection geometrical constraints. The results show that unsupervised machine learning techniques are promising approaches to process large sets of images for high-temperature plasmas and other scientific experiments. In conclusion, machine learning techniques can be useful to handle the large amount of data and therefore aid the understanding of plasma-wall interaction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Review and meta-analysis of electron temperatures from high-intensity laser–solid interactions

The accelerated electron spectrum from high-intensity laser–solid interaction is often conveniently described using a Boltzmann distribution, whose temperature is known within the field as the hot-electron temperature. The importance of the electron temperature is highlighted by the sheer number of experimental and simulation studies on the subject over the past three decades. Recently, multi-kJ, multi-ps pulses have yielded electron spectra with temperatures far beyond the expected ponderomotive result. Expressions that predict the electron temperature considering laser parameters beyond intensity and wavelength have been developed, albeit using small datasets. In this review, we present what is, to the best of our knowledge, the largest dataset of electron temperatures gathered from experimental measurements and particle-in-cell simulations. This dataset allows us to compare existing analytical and empirical hot-electron temperature scaling models over a wide parameter range. We also develop new scaling models that incorporate the laser pulse duration of the laser and the plasma scale length. Three models that include pulse-duration and scale length dependence are especially successful at predicting both simulated and experimental data. The dataset will soon be made publicly available to encourage further investigation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Deceptive Infusion of Data: A Novel Data Masking Paradigm for High-Valued Systems

This work addresses how analysts of a high-valued system (e.g., nuclear reactor, aircraft turbine designs) can extract findable, accessible, interoperable, and reusable scientific data for public dissemination to artificial intelligence and machine-learning (AI/ML) researchers in a manner that cannot be reverse-engineered, potentially compromising sensitive or proprietary information. State-of-the-art methods address this problem through data masking techniques, which allow access to a subset of the information while obfuscating private and potentially identifying information (e.g., personally identifying medical data). These methods are unsuitable for industrial engineering processes, where AI/ML tools need explicit access to all the data available to draw the best inference about the system to help optimize its performance and identify its vulnerabilities, etc. Our novel deceptive infusion of data paradigm provides a solution to this conundrum by developing a mathematical approach capable of concealing the identity of the system while providing full access to all the features employed by AI/ML tools to ensure their optimal performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2013

STEPS TOWARD UNVEILING THE TRUE POPULATION OF ACTIVE GALACTIC NUCLEI: PHOTOMETRIC CHARACTERIZATION OF ACTIVE GALACTIC NUCLEI IN COSMOS

Using a physically motivated, model-based active galactic nucleus (AGN) characterization technique, we fit a large sample of X-ray-selected AGNs with known spectroscopic redshifts from the Cosmic Evolution Survey field. We identify accretion disks in the spectral energy distributions of broad- and narrow-line AGNs, and infer the presence or absence of host galaxy light in the SEDs. Based on infrared and UV excess AGN selection techniques, our method involves fitting a given SED with a model consisting of three components: infrared power-law emission, optical-UV accretion disk emission, and host galaxy emission. Each component can be varied in relative contribution, and a reduced chi-square minimization routine is used to determine the optimum parameters for each object. Using this technique, both broad- and narrow-line AGNs fall within well-defined and plausible bounds on the physical parameters of the model, allowing trends with luminosity and redshift to be determined. In particular, based on our sample of spectroscopically confirmed AGNs, we find that approximately 95% of the broad-line AGNs and 50% of the narrow-line AGNs in our sample show evidence of an accretion disk, with maximum disk temperatures ranging from 1 to 10 eV. Because this fitting technique relies only on photometry, we hope to apply it in future work to the characterization and eventually the selection of fainter AGNs than are accessible in wide-field spectroscopic surveys, and thus probe a population of less luminous and/or higher redshift objects without prior redshift or X-ray data. With the abundant availability of photometric data from large surveys, the ultimate goal is to use this technique to create large samples that will complement and complete AGN catalogs selected by X-ray emission alone.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

The PSZ-MCMF catalogue of Planck clusters over the DES region

ABSTRACT We present the first systematic follow-up of Planck Sunyaev–Zeldovich effect (SZE) selected candidates down to signal-to-noise (S/N) of 3 over the 5000 deg2 covered by the Dark Energy Survey. Using the MCMF cluster confirmation algorithm, we identify optical counterparts, determine photometric redshifts, and richnesses and assign a parameter, fcont, that reflects the probability that each SZE-optical pairing represents a random superposition of physically unassociated systems rather than a real cluster. The new PSZ-MCMF cluster catalogue consists of 853 MCMF confirmed clusters and has a purity of 90 per cent. We present the properties of subsamples of the PSZ-MCMF catalogue that have purities ranging from 90 per cent to 97.5 per cent, depending on the adopted fcont threshold. Halo mass estimates M500, redshifts, richnesses, and optical centres are presented for all PSZ-MCMF clusters. The PSZ-MCMF catalogue adds 589 previously unknown Planck identified clusters over the DES footprint and provides redshifts for an additional 50 previously published Planck-selected clusters with S/N>4.5. Using the subsample with spectroscopic redshifts, we demonstrate excellent cluster photo-z performance with an RMS scatter in Δz/(1 + z) of 0.47 per cent. Our MCMF based analysis allows us to infer the contamination fraction of the initial S/N>3 Planck-selected candidate list, which is ∼50 per cent. We present a method of estimating the completeness of the PSZ-MCMF cluster sample. In comparison to the previously published Planck cluster catalogues, this new S/N>3 MCMF confirmed cluster catalogue populates the lower mass regime at all redshifts and includes clusters up to z∼1.3.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

An Adaptive Bayesian Parameter Estimation of a Synchronous Generator Under Gross Errors

Polynomial-chaos-expansion-based surrogate models have recently been advocated in the literature for power system dynamic parameter estimation. Regarding the estimation of the uncertain generator parameters, a Bayesian inference framework has been proposed based on a polynomial-based reduced-order representation of the synchronous machines using assumed parameter values. Then, the non-Gaussian posterior probability distribution functions (pdfs) of these parameters are recovered through the stochastic sampling approach efficiently. However, facing very large parameter errors, the reliability of the surrogate model decreases, yielding biased estimation results. To overcome this problem, here we develop hierarchical Bayesian inference framework that processes the measurements provided by phasor measurement units, while making use of multifidelity surrogates together with the importance sampling method. The latter allows us to estimate in an efficient manner the posterior pdfs of the uncertain parameters through the normalized weights of the prior samples. To improve the accuracy of the posterior pdfs, an adaptive procedure is further adopted in the importance sampling for the gradual evolution of its proposal functions. The new proposals assist in fine-tuning the sample space and thereby help to construct surrogates with higher fidelity. Through an iterative process, this approach is able to estimate accurately and efficiently non-Gaussian posterior pdfs of the uncertain generator parameters subject to gross errors.

42 ENGINEERING↗