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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Supercharging simulation-based inference for Bayesian optimal experimental design

Abstract Bayesian optimal experimental design (BOED) seeks to maximize the expected information gain (EIG) of experiments. This requires a likelihood estimate, which in many settings is intractable. Simulation-based inference (SBI) provides powerful tools for this regime. However, existing work explicitly connecting SBI and BOED is restricted to a single contrastive EIG bound. We show that the EIG admits multiple formulations which can directly leverage modern SBI density estimators, encompassing neural posterior, likelihood, and ratio estimation. Building on this perspective, we define a novel EIG estimator using neural likelihood estimation. Further, we identify optimization as a key bottleneck of gradient based EIG maximization and show that a simple multi-start parallel gradient ascent procedure can substantially improve reliability and performance. With these innovations, our SBI-based BOED methods are able to match or outperform by up to 22% existing state-of-the-art approaches across standard BOED benchmarks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

UF6 Density and Mass Flow Measurements for Enrichment Plants using Acoustic Techniques

A key enabling capability for enrichment plant safeguards being considered by the International Atomic Energy Agency (IAEA) is high-accuracy, noninvasive, unattended measurement of UF6 gas density and mass flow rate. Acoustic techniques are currently used to noninvasively monitor gas flow in industrial applications; however, the operating pressures at gaseous centrifuge enrichment plants (GCEPs) are roughly two orders magnitude below the capabilities of commercial instrumentation. Pacific Northwest National Laboratory is refining acoustic techniques for estimating density and mass flow rate of UF6 gas in scenarios typical of GCEPs, with the goal of achieving 1% measurement accuracy. Proof-of-concept laboratory measurements using a surrogate gas for UF6 have demonstrated signatures sensitive to gas density at low operating pressures such as 10–50 Torr, which were observed over the background acoustic interference. Current efforts involve developing a test bed for conducting acoustic measurements on flowing SF6 gas at representative flow rates and pressures to ascertain the viability of conducting gas flow measurements under these conditions. Density and flow measurements will be conducted to support the evaluation. If successful, the approach could enable an unattended, noninvasive approach to measure mass flow in unit header pipes of GCEPs.

Good, Morris S.↗
DOE OSTI2018

Acoustic Techniques for UF6 Density and Mass Flow Measurements

A key enabling capability for enrichment plant safeguards is high-accuracy, non-invasive, unattended measurement of UF6 gas density and mass flow rate. Acoustic techniques are currently used to non-invasively monitor gas flow in industrial applications; however, the operating pressures at gaseous centrifuge enrichment plants (GCEPs) are roughly two orders magnitude below the capabilities of commercial instrumentation. Pacific Northwest National Laboratory is refining acoustic techniques for estimating density and mass flow rate of UF6 gas in scenarios typical of gaseous centrifuge enrichment plants, with the goal of achieving 1% measurement uncertainty. Proof-of-concept laboratory measurements of UF6 have demonstrated signature sensitivity to gas density at pressures equivalent to 10-50 Torr of UF6, typical pressures for GCEP unit header pipes. This sensitivity was clearly observable above background acoustic interference. Current efforts involve developing a test bed for conducting acoustic measurements on flowing surrogate gas, air and SF6, at representative flow rates and pressures to ascertain the viability of conducting gas flow measurements under these conditions. Density and flow measurements will be conducted to support the evaluation. If successful, the approach could enable an unattended, non-invasive approach to measure UF6 density and mass flow in unit header pipes of GCEPs.

International safeguards instrumentation, acoustic↗
DOE OSTI2014

The radius distribution of planets around cool stars

We calculate an empirical, non-parametric estimate of the shape of the period-marginalized radius distribution of planets with periods less than 150 days using the small yet well-characterized sample of cool (T{sub eff} < 4000 K) dwarf stars in the Kepler catalog. In particular, we present and validate a new procedure, based on weighted kernel density estimation, to reconstruct the shape of the planet radius function down to radii smaller than the completeness limit of the survey at the longest periods. Under the assumption that the period distribution of planets does not change dramatically with planet radius, we show that the occurrence of planets around these stars continues to increase to below 1 R{sub ⊕}, and that there is no strong evidence for a turnover in the planet radius function. In fact, we demonstrate using many iterations of simulated data that a spurious turnover may be inferred from data even when the true distribution continues to rise toward smaller radii. Finally, the sharp rise in the radius distribution below ∼3 R{sub ⊕} implies that a large number of planets await discovery around cool dwarfs as the sensitivities of ground-based transit surveys increase.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

Study of the post-flare loops on 29 July 1973. IV - Revision of T and n sub e values and comparison with the flare of 21 May 1980

Revised temperature and density estimates are provided in a synthesis of previous studies of the two-ribbon solar flare of July 29, 1973 and results are compared with observations of a similar event by the Solar Maximum Mission on May 21, 1980. Photographs taken through X ray filters permitted determination of the spatial distribution of temperature and density in the loop system and variations over time. The entire growth process of the flare is detailed, including the magnetic field configurations and the enlargement of the Halpha flare ribbon separation distance. The temperature is revised to 8.8 million K during maximum soft X ray emission and 6.8 million K at the appearance of the last Halpha loops. The 1973 flare is noted to have occurred in an old, decaying spotless region, producing higher loops at lower density than the 1980 flare, which displayed ribbons imbedded in a sunspot group.

Svestka, Z.↗
DOE OSTI2026

A Bayesian inferencing framework for ultrasound wave speed measurements in metal additive manufacturing

Process-related changes during metal additive manufacturing introduce microstructural variability in the material properties of printed parts, directly affecting component reliability. Accurate estimation of these property variations with part performance are essential for quality assurance. Ultrasound testing offers a non-destructive means to estimate mechanical properties and detect defects; however, conventional analysis methods often neglect the influence of microstructural variability, limiting their effectiveness. Here, this research presents a Bayesian inference technique for quantifying wave speed uncertainty from ultrasound measurements of metal additive manufactured parts. By integrating prior ultrasound data with a Bayesian model, the proposed approach generates posterior density estimates of wave speed that systematically account for manufacturing-induced variability and uncertainty. The novelty of this research lies in applying a Bayesian framework to analyze experimental ultrasound measurements within the context of metal additive manufacturing variability. The method enhances the accuracy of wave speed estimation by 64%, defect position by 50% and increases confidence associated with wave speed variance by 30% across different porosity levels, thereby providing a robust foundation for improved decision-making and increased reliability in additively manufactured components.

Additive manufacturing↗
DOE OSTI2011

A robust and efficient approach to detect 3D rectal tubes from CT colonography

Purpose: The rectal tube (RT) is a common source of false positives (FPs) in computer-aided detection (CAD) systems for CT colonography. A robust and efficient detection of RT can improve CAD performance by eliminating such ''obvious'' FPs and increase radiologists' confidence in CAD. Methods: In this paper, we present a novel and robust bottom-up approach to detect the RT. Probabilistic models, trained using kernel density estimation on simple low-level features, are employed to rank and select the most likely RT tube candidate on each axial slice. Then, a shape model, robustly estimated using random sample consensus (RANSAC), infers the global RT path from the selected local detections. Subimages around the RT path are projected into a subspace formed from training subimages of the RT. A quadratic discriminant analysis (QDA) provides a classification of a subimage as RT or non-RT based on the projection. Finally, a bottom-top clustering method is proposed to merge the classification predictions together to locate the tip position of the RT. Results: Our method is validated using a diverse database, including data from five hospitals. On a testing data with 21 patients (42 volumes), 99.5% of annotated RT paths have been successfully detected. Evaluated with CAD, 98.4% of FPs caused by the RT have been detected and removed without any loss of sensitivity. Conclusions: The proposed method demonstrates a high detection rate of the RT path, and when tested in a CAD system, reduces FPs caused by the RT without the loss of sensitivity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Dynamic Performance Enhancement for Nonlinear Stochastic Systems Using RBF Driven Nonlinear Compensation with Extended Kalman Filter

In this paper, a novel hybrid control method is proposed to enhance the control performance of the PI based control system for a class of nonlinear and non-Gaussian stochastic dynamic processes with unmeasurable states. Firstly, to enhance the tracking performance of the PI controller where the PI parameters are fixed in many actual control systems, the compensative signal is formed using the extended Kalman filter(EKF) based state estimator and driven by the radial basis function (RBF) neural network based compensator. In addition, the weights of RBF is trained to minimize the entropy criterion of tracking error as the process is subjected to non-Gaussian disturbances. Meanwhile, since the precise statistical property of noises is hard to obtain for many industrial processes, the kernel density estimation (KDE) technique is employed in this paper to estimate the entropy. The convergence of RBF network is discussed and the stability of the resulted closed-loop hybrid control system is analyzed in mean square sense. Finally, a numerical example and a practical system testing are given to illustrate the effectiveness of the proposed control method.

stochastic systems, PI Controller, Entropy, Extend↗
DOE OSTI2021

Non-Gaussian estimates of tensions in cosmological parameters

We discuss how to efficiently and reliably estimate the level of agreement and disagreement on parameter determinations from different experiments, fully taking into account non-Gaussianities in the parameter posteriors. We develop two families of scalable algorithms that allow us to perform this type of calculations in increasing number of dimensions and for different levels of tensions. One family of algorithms rely on kernel density estimates of posterior distributions while the other relies on machine learning modeling of the posterior distribution with normalizing flows. We showcase their effectiveness and accuracy with a set of benchmark examples and find both methods agree with each other and the true tension within 0.5σ in difficult cases and generally to 0.2σ or better. This allows us to study the level of internal agreement between different measurements of the clustering of cosmological structures from the Dark Energy Survey and their agreement with measurements of the Cosmic Microwave Background from the Planck satellite.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

NONPARAMETRIC EMPIRICAL BAYES ESTIMATION THROUGH DECONVOLUTION IN PROBABILISTIC RISK ANALYSIS

The advent of Markov Chain Monte Carlo (MCMC) simulations and availability of open source software made full hierarchical Bayesian analysis tractable and a popular choice in parameter estimation for Probabilistic Risk Assessment (PRA). However, despite its theoretical attractiveness, the hierarchical Bayesian analysis is not without its problems. Two of the most prominent practical difficulties in applying hierarchical Bayes analysis in practice to analyze source-to-source variability, for example, is its sensitivity to the selection of the first-stage prior and dependence of the rate of convergence on the selection of the first-stage prior. The first-stage prior in hierarchical Bayesian analysis is usually assumed having a parametric form, often conjugate to the likelihood function (aleatory model). To facilitate convergence for hierarchical Bayes models, the first-stage prior is frequently set through empirical Bayes estimate, which can use available historical data to find the parameters of the first-stage prior. The paper discusses a new nonparametric empirical Bayes estimation and compare it to several well-known parametric estimates such as method of moments and maximum likelihood. The new nonparametric technique exploits the prior predictive distribution as integral equation and proceeds to solve it with respect to prior assuming the sampling data distribution and aleatory model are available. The discussion covers topics such as selection of aleatory model for future data, selection of regularization parameter, and density estimation for historical data. For comparison, the paper is using contrived as well as real-world data from utilities. Utilities data represent failure data with Poisson distribution used for aleatory model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Impact of Cosmic Filaments on Galaxy Morphological Evolution and Predictions of Early Cosmic Web Structure for Roman

We leverage the IllustrisTNG cosmological simulations to test how the large-scale cosmic web shapes galaxy morphology and to forecast the early cosmic web structure that the Nancy Grace Roman Space Telescope will reveal. In the hydrodynamic TNG50 and N-body TNG50-Dark runs, we reconstruct the cosmic web at redshifts z = 0, 0.5, 1, 2, 3, and 4 with the Monte Carlo Physarum Machine density estimator and the DisPerSE structure identification framework. We confirm that dark matter halos start out predominantly prolate (elongated), and their shapes are aligned with their nearest filaments; prolate galaxies retain strong shape alignment with their outer halos to later times. At z ≥ 1, the fraction of prolate (spheroidal) halos increases (decreases) toward lower stellar mass, higher redshift, and lower filament density. At z < 1, more spheroidal (oblate) stellar structures preferentially reside in higher-density (lower-density) filaments. We also find that higher-density filaments favor extended rotationally supported disks, whereas lower-density filaments more often host smaller dispersion-supported systems. Then, generating mock galaxy samples from TNG100 and TNG50, we predict the early cosmic web accessible to Roman. We find that the spectroscopic emission-line depth planned for the High-Latitude Wide-Area Survey (HLWAS) yields a highly incomplete galaxy sample that does not accurately trace the z = 1 cosmic web. A survey ≥2.5× deeper over a few square degrees would enable a proper reconstruction and reveal qualitatively correct filament–galaxy morphology relationships. Nevertheless, the planned HLWAS Deep field should still identify most galaxy overdensities; targeted deeper spectroscopy of these regions would efficiently and adequately map the early filamentary structure.

Hasan, Farhanul [Space Telescope Science Institute↗
DOE OSTI2017

Monte Carlo Perturbation Theory Estimates of Sensitivities to System Dimensions

Here, Monte Carlo methods are developed using adjoint-based perturbation theory and the differential operator method to compute the sensitivities of the k-eigenvalue, linear functions of the flux (reaction rates), and bilinear functions of the forward and adjoint flux (kinetics parameters) to system dimensions for uniform expansions or contractions. The calculation of sensitivities to system dimensions requires computing scattering and fission sources at material interfaces using collisions occurring at the interface—which is a set of events with infinitesimal probability. Kernel density estimators are used to estimate the source at interfaces using collisions occurring near the interface. The methods for computing sensitivities of linear and bilinear ratios are derived using the differential operator method and adjoint-based perturbation theory and are shown to be equivalent to methods previously developed using a collision history–based approach. The methods for determining sensitivities to system dimensions are tested on a series of fast, intermediate, and thermal critical benchmarks as well as a pressurized water reactor benchmark problem with iterated fission probability used for adjoint-weighting. The estimators are shown to agree within 5% and 3σ of reference solutions obtained using direct perturbations with central differences for the majority of test problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

TH-AB-202-04: Auto-Adaptive Margin Generation for MLC-Tracked Radiotherapy

Purpose: To develop an auto-adaptive margin generator for MLC tracking. The generator is able to estimate errors arising in image guided radiotherapy, particularly on an MR-Linac, which depend on the latencies of machine and image processing, as well as on patient motion characteristics. From the estimated error distribution, a segment margin is generated, able to compensate errors up to a user-defined confidence. Method: In every tracking control cycle (TCC, 40ms), the desired aperture D(t) is compared to the actual aperture A(t), a delayed and imperfect representation of D(t). Thus an error e(t)=A(T)-D(T) is measured every TCC. Applying kernel-density-estimation (KDE), the cumulative distribution (CDF) of e(t) is estimated. With CDF-confidence limits, upper and lower error limits are extracted for motion axes along and perpendicular leaf-travel direction and applied as margins. To test the dosimetric impact, two representative motion traces were extracted from fast liver-MRI (10Hz). The traces were applied onto a 4D-motion platform and continuously tracked by an Elekta Agility 160 MLC using an artificially imposed tracking delay. Gafchromic film was used to detect dose exposition for static, tracked, and error-compensated tracking cases. The margin generator was parameterized to cover 90% of all tracking errors. Dosimetric impact was rated by calculating the ratio between underexposed points (>5% underdosage) to the total number of points inside FWHM of static exposure. Results: Without imposing adaptive margins, tracking experiments showed a ratio of underexposed points of 17.5% and 14.3% for two motion cases with imaging delays of 200ms and 300ms, respectively. Activating the margin generated yielded total suppression (<1%) of underdosed points. Conclusion: We showed that auto-adaptive error compensation using machine error statistics is possible for MLC tracking. The error compensation margins are calculated on-line, without the need of assuming motion or machine models. Further strategies to reduce consequential overdosages are currently under investigation. This work was funded by the SoRTS consortium, which includes the industry partners Elekta, Philips and Technolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Electrostatic sensors for SPIDER experiment: Design, manufacture of prototypes, and first tests

A system of electrostatic sensors has been designed for the SPIDER (Source for the production of Ions of Deuterium Extracted from RF plasma) experiment, prototype RF source of the ITER NBI (neutral beam injection). A prototype of the sensor system was manufactured and tested at the BATMAN (BAvarian Test MAchine for Negative ions) facility, where the plasma environment is similar to that of SPIDER. Different aspects concerning the mechanical manufacturing and the signal conditioning are presented, among them the RF compensation adopted to reduce the RF effects which could lead to overestimated values of the electron temperature. The first commissioning tests provided ion saturation current values in the range assumed for the design, so the deduced plasma density estimate is consistent with the expected values.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2013

Mars-GRAM 2010: Additions and Resulting Improvements

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM has been utilized during previous aerobraking operations in the atmosphere of Mars. Mars-GRAM has also been used in the prediction and validation of Mars Pathfinder hypersonic aerodynamics, the aerothermodynamic and entry dynamics studies for Mars Polar Lander, the landing site selection process for the Mars Science Laboratory (MSL), the Mars Aerocapture System Study (MASS) as well as the Aerocapture Technology Assessment Group (TAG). Most recently, Mars-GRAM 2010 was used to develop the onboard atmospheric density estimator that is part of the Autonomous Aerobraking Development Plan. The most recent release of Mars-GRAM 2010 contains several changes including an update to Fortran 90/95 and the addition of adjustment factors. Following the completion of a comparison analysis between Mars-GRAM, Thermal Emission Spectrometer (TES), as well as Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) aerobraking density data, adjustment factors were added to Mars-GRAM 2010 that alter the input data from National Aeronautics and Space Administration (NASA) Ames Mars General Circulation Model (MGCM) and the University of Michigan Mars Thermospheric General Circulation Model (MTGCM) for the mapping year 0 user-controlled dust case. The addition of adjustment factors resolved the issue of previous versions of Mars-GRAM being less than realistic when used for sensitivity studies for mapping year 0 and large optical depth values, such as tau equal to 3. Mars-GRAM was evaluated at locations and times of TES limb observations and adjustment factors were determined. For altitudes above 80 km and below 135 km, Mars-GRAM (MTGCM) densities were compared to aerobraking densities measured by Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) to determine the adjustment factors. The adjustment factors generated by this process had to satisfy the gas law as well as the hydrostatic relation and are expressed as a function of height (z), Latitude (Lat) and areocentric solar longitude (Ls). The greatest adjustments are made at large optical depths such as tau greater than 1. The addition of the adjustment factors has led to better correspondence to TES Limb data from 0-60 km altitude as well as better agreement with MGS, ODY and MRO data at approximately 90-130 km altitude. Improved Mars-GRAM atmospheric simulations for various locations, times and dust conditions on Mars will be presented at the workshop session. The latest results validating Mars-GRAM 2010 versus Mars Climate Sounder data will also be presented. Mars-GRAM 2010 updates have resulted in improved atmospheric simulations which will be very important when beginning systems design, performance analysis, and operations planning for future aerocapture, aerobraking or landed missions to Mars.

Justh, Hilary L.↗
NASA NTRS1983

Inverting a dispersive scene's side-scanned image

Consideration is given to the problem of using a remotely sensed, side-scanned image of a time-variant scene, which changes according to a dispersion relation, to estimate the structure at a given moment. Additive thermal noise is neglected in the models considered in the formal treatment. It is shown that the dispersion relation is normalized by the scanning velocity, as is the group scanning velocity component. An inversion operation is defined for noise-free images generated by SAR. The method is extended to the inversion of noisy imagery, and a formulation is defined for spectral density estimation. Finally, the methods for a radar system are used for the case of sonar.

Harger, R. O.↗
DOE OSTI2016

Low-temperature, high-density plasmas in long micro-tubes

A low-temperature He microplasma plume generated in a micro quartz tube with the inner diameter decreasing from 245 μm to 6 μm is reported. The microplasma plume has a length of around 1.5 cm and reaches the position where the tube diameter is 10 μm. Though the inner diameter of the tube is in sub-millimeter, the cross section of the tube is not fully filled with the plasma only until the tube inner diameter is down to 30 μm. The electron density estimated from H{sub α} stark broadening increases as the inner diameter of the tube decreases. The ignition voltage increases from 11 kV to 40 kV as the diameter of the inner quartz tube decreases from 245 μm to 10 μm. Further analysis shows that, in order to ignite a non-equilibrium plasma plume in 1 μm diameter tube, the applied voltage of about 65 kV is needed and the plasma density could be as high as ∼10{sup 18 }cm{sup −3}.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Geostatistical Mapping of Salinity Conditioned on Borehole Logs, Montebello Oil Field, California

We present a geostatistics-based stochastic salinity estimation framework for the Montebello Oil Field that capitalizes on available total dissolved solids (TDS) data from groundwater samples as well as electrical resistivity (ER) data from borehole logging. Data from TDS samples (n = 4924) was coded into an indicator framework based on falling below four selected thresholds (500, 1000, 3000, and 10,000 mg/L). Collocated TDS-ER data from the surrounding groundwater basin were then employed to produce a kernel density estimator to establish conditional probabilities for ER data (n = 8 boreholes) falling below the selected TDS thresholds within the Montebello Oil Field area. Directional variograms were estimated from these indicator coded data, and 500 TDS realizations from conditional indicator simulation were generated for the subsurface region above the Montebello Oil Field reservoir. Simulations were summarized as 3D maps of median TDS, most likely salinity class, and probability for exceeding each of the specified TDS thresholds. Results suggested TDS was below 500 mg/L in most of the study area, with a trend toward higher values (500 to 1000 mg/L) to the southwest; consistent with the average regional groundwater flow direction. Discrete localized zones of TDS greater than 1000 mg/L were observed, with one of these zones in the greater than 10,000 mg/L range; however, these areas were not prevalent. The probabilistic approach used here is adaptable and is readily modified to include additional data and types and can be employed in time-lapse salinity modeling through Bayesian updating.

54 ENVIRONMENTAL SCIENCES↗