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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 OSTI2025

Analysis and optimization of seismic monitoring networks with Bayesian optimal experimental design

SUMMARY Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations or experiments which can optimally reduce uncertainty and hence increase the performance of a monitoring network. Information theory guides OED by formulating the choice of experiment or sensor placement as an optimization problem that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge and models of expected observation data. Therefore, within the context of seismo-acoustic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize a sensor network’s ability to locate seismic events from arrival time data of detected seismic phases at the regional-scale. This framework requires five elements: (i) A likelihood function that describes the distribution of detection and traveltime data from the sensor network, (ii) A prior distribution that describes a priori belief about seismic events, (iii) A Bayesian solver that uses a prior and likelihood to identify the posterior distribution of seismic events given the data, (iv) An algorithm to compute EIG about seismic events over a data set of hypothetical prior events, (v) An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we explore many relevant questions to monitoring such as: how to trade off sensor fidelity and earth model uncertainty; how sensor types, number and locations influence uncertainty; and how prior models and constraints influence sensor placement.

58 GEOSCIENCES↗
DOE OSTI2023

Suppressed superexchange interactions in the cuprates by bond-stretching oxygen phonons

We study a multiorbital Hubbard–Su-Schrieffer-Heeger model for the one-dimensional (1D) corner-shared cuprates in the adiabatic and nonadiabatic limits using exact diagonalization and determinant quantum Monte Carlo. At half filling and in the adiabatic limit, lattice dimerization can be achieved only over a narrow range of couplings slightly below a critical coupling g c . Beyond this value, the sign of the effective hopping changes, and the lattice becomes unstable. Strong lattice fluctuations replace the dimerization state in the nonadiabatic case. We also examine the model's temperature-dependent uniform and dynamical magnetic susceptibilities and compare them to the results of an effective spin-1/2 Heisenberg model. In doing so, we demonstrate that lattice fluctuations induced by the e-ph interaction suppress the effective superexchange interaction when g < g c . Furthermore, our results elucidate the effect of bond-stretching phonons in the parent cuprate compounds in general and are particularly relevant to 1D cuprates, where strong e-ph interactions have recently been inferred.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Hemiptera phylogenomic resources: Tree‐based orthology prediction and conserved exon identification

Abstract High‐throughput sequencing of transcriptomes and targeted genomic regions are advancing our knowledge of The Tree of Life. Building phylogenies with regions of the genome requires 1‐to‐1 orthologue resources of genes and noncoding loci. One organismal group that has received little attention in this area is the Hemiptera, the fifth largest insect order represented by ~103,590 named species. Here, we present a set of 3,872 Hemiptera 1‐to‐1 orthogroups based on tree‐based orthology inference of eight Hemiptera species with publicly available genome sequences. We also estimate a set of 406 orthologous exons with similar mRNA splice sites that can be used for Sanger sequencing and develop enrichment probes for targeted genome sequencing for phylogenomic inference. We show this novel set of orthologues is informative at the protein, coding sequence and exon molecular levels and provides robust branch support in both gene tree–species tree methods and concatenated sequence phylogenies. In addition, we demonstrate the utility of these loci to resolve relationships in whiteflies, Bemisia tabaci , a large species complex with few phylogenomic resources. Last, we compare our Hemiptera phylogeny with previously published phylogenies and other orthologue databases, while providing suggestions on further improvement to this phylogenomic resource.

Owen, Christopher L.↗
DOE OSTI2025

Fast and Scalable FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices with Application to Linear Inverse Problems Governed by Autonomous Dynamical Systems

In this work, we present an efficient and scalable algorithm for performing matrix-vector multiplications (matvecs) for block Toeplitz matrices. Such matrices, which are shift-invariant with respect to their blocks, arise in the context of solving inverse problems governed by autonomous systems, and time-invariant systems in particular. In this article, we consider inverse problems that infer unknown parameters from observational data of a linear time-invariant dynamical system given in the form of partial differential equations (PDEs). Matrix-free Newton-conjugate-gradient methods are often the gold standard for solving these inverse problems, but they require numerous actions of the Hessian on a vector. Matrix-free adjoint-based Hessian matvecs require solution of a pair of linearized forward/adjoint PDE solves per Hessian action, which may be prohibitive for large-scale inverse problems. Time invariance of the forward PDE problem leads to a block Toeplitz structure of the discretized parameter-to-observable (p2o) map defining the mapping from inputs (parameters) to outputs (observables) of the PDEs. This block Toeplitz structure enables us to exploit two key properties: (1) compact storage of the p2o map and its adjoint, and (2) efficient fast Fourier transform–based Hessian matvecs. The proposed algorithm is mapped onto large multi-GPU clusters and achieves more than 80% of peak bandwidth on NVIDIA A100 GPUs. Excellent weak scaling is shown for up to 48 A100 GPUs. For the targeted problems, the implementation executes Hessian matvecs within fractions of a second, which is orders of magnitude faster than can be achieved by conventional matrix-free Hessian matvecs via forward/adjoint PDE solves.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. Furthermore, the combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

General Bayesian Inference over the Stiefel Manifold via the Givens Transform

We introduce here an approach based on the Givens representation for posterior inference in statistical models with orthogonal matrix parameters, such as factor models and probabilistic principal component analysis (PPCA). We show how the Givens representation can be used to develop practical methods for transforming densities over the Stiefel manifold into densities over subsets of Euclidean space. We demonstrate how to deal with issues arising from the topology of the Stiefel manifold and how to inexpensively compute the change-of-measure terms. We introduce an auxiliary parameter approach that limits the impact of topological issues. We provide both analysis of our methods and numerical examples demonstrating the effectiveness of the approach. We also discuss how our Givens representation can be used to define general classes of distributions over the space of orthogonal matrices. We then give demonstrations on several examples showing how the Givens approach performs in practice in comparison with other methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Comprehensive Material Characterization and Simultaneous Model Calibration for Improved Computational Simulation Credibility

Computational simulation is increasingly relied upon for high-consequence engineering decisions, and a foundational element to solid mechanics simulations is a credible material model. Our ultimate vision is to interlace material characterization and model calibration in a real-time feedback loop, where the current model calibration results will drive the experiment to load regimes that add the most useful information to reduce parameter uncertainty. The current work investigated one key step to this Interlaced Characterization and Calibration (ICC) paradigm, using a finite load-path tree to incorporate history/path dependency of nonlinear material models into a network of surrogate models that replace computationally-expensive finite-element analyses. Our reference simulation was an elastoplastic material point subject to biaxial deformation with a Hill anisotropic yield criterion. Training data was generated using either a space-filling or adaptive sampling method, and surrogates were built using either Gaussian process or polynomial chaos expansion methods. Surrogate error was evaluated to be on the order of 10 ⁻5 and 10 ⁻3 percent for the space-filling and adaptive sampling training data, respectively. Direct Bayesian inference was performed with the surrogate network and with the reference material point simulator, and results agreed to within 3 significant figures for the mean parameter values, with a reduction in computational cost over 5 orders of magnitude. These results bought down risk regarding the surrogate network and facilitated a successful FY22-24 full LDRD proposal to research and develop the complete ICC paradigm.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Challenges Ahead for Multimessenger Analyses of Gravitational Waves and Kilonova: A Case Study on GW190425

In recent years, there have been significant advances in multimessenger astronomy due to the discovery of the first, and so far only confirmed, gravitational wave event with a simultaneous electromagnetic (EM) counterpart, as well as improvements in numerical simulations, gravitational wave (GW) detectors, and transient astronomy. This has led to the exciting possibility of performing joint analyses of the GW and EM data, providing additional constraints on fundamental properties of the binary progenitor and merger remnant. Here, in this work, we present a new Bayesian framework that allows inference of these properties, while taking into account the systematic modeling uncertainties that arise when mapping from GW binary progenitor properties to photometric light curves. We extend the relative binning method presented in Zackay et al. to include extrinsic GW parameters for fast analysis of the GW signal. The focus of our EM framework is on light curves arising from r-process nucleosynthesis in the ejected material during and after merger, the so-called kilonova, and particularly on black hole–neutron star systems. As a case study, we examine the recent detection of GW190425, where the primary object is consistent with being either a black hole or a neutron star. We show quantitatively how improved mapping between binary progenitor and outflow properties, and/or an increase in EM data quantity and quality are required in order to break degeneracies in the fundamental source parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

The ball bearing as a rheological test device

An angular-contact ball bearing provides an easily obtainable, precise mechanical system for rheological tests on thin films under high pressure. The test conditions are by definition similar to those found in practice. Accessible independent variables include size, pressure, bulk temperature, roughness, adsorbed surfactant, fluid type, fluid quantity, fluid supply rate, film thickness, entrainment velocity, transit time, and combined strain. Easily measured or inferred variables include slip, changes in film thickness with time (transients), strain rate, lubricant elastic modulus (thin film, high pressure), tractive force, lubricant chemical degradation rate, and lubricant degradation product. Methods for setting and obtaining these quantities in a bearing are discussed, together with experimental limitations on them.

Kingsbury, E.↗
NASA NTRS1985

Measuring Clouds With Microwaves and Infrared

Combination of microwave and infrared measurements from satellites yields data from which thicknesses and temperature of clouds inferred. Microwave radiation measured by satellite used to determine thickness of cloud and difference between cloud-top temperature and mean temperature of interior. Technique extends capability of previously established method in which infrared radiation returned to satellite by cloud used to determine temperature and altitude of cloud top and fractional area of Earth covered by cloud.

Pandey, P. C.↗
NASA NTRS1991

A machine independent expert system for diagnosing environmentally induced spacecraft anomalies

A new rule-based, machine independent analytical tool for diagnosing spacecraft anomalies, the EnviroNET expert system, was developed. Expert systems provide an effective method for storing knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms which allow approximate reasoning and inference, and the ability to attack problems not rigidly defines. The EviroNET expert system knowledge base currently contains over two hundred rules, and links to databases which include past environmental data, satellite data, and previous known anomalies. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose.

Rolincik, Mark J.↗
NASA NTRS1992

An expert system for diagnosing environmentally induced spacecraft anomalies

A new rule-based, machine independent analytical tool was designed for diagnosing spacecraft anomalies using an expert system. Expert systems provide an effective method for saving knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms, which allow approximate reasoning and inference and the ability to attack problems not rigidly defined. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The modularity of the expert system allows for easy updates and modifications. It not only provides scientists with needed risk analysis and confidence not found in algorithmic programs, but is also an effective learning tool, and the window implementation makes it very easy to use. The system currently runs on a Micro VAX II at Goddard Space Flight Center (GSFC). The inference engine used is NASA's C Language Integrated Production System (CLIPS).

Rolincik, Mark↗
NASA NTRS1993

Inferring heuristic classification hierarchies from natural language input

A methodology for inferring hierarchies representing heuristic knowledge about the check out, control, and monitoring sub-system (CCMS) of the space shuttle launch processing system from natural language input is explained. Our method identifies failures explicitly and implicitly described in natural language by domain experts and uses those descriptions to recommend classifications for inclusion in the experts' heuristic hierarchies.

Hull, Richard↗
NASA NTRS1997

Parameterizing Grid-Averaged Longwave Fluxes for Inhomogeneous Marine Boundary Layer Clouds

This paper examines the relative impacts on grid-averaged longwave flux transmittance (emittance) for Marine Boundary Layer (MBL) cloud fields arising from horizontal variability of optical depth tau and cloud sides, First, using fields of Landsat-inferred tau and a Monte Carlo photon transport algorithm, it is demonstrated that mean all-sky transmittances for 3D variable MBL clouds can be computed accurately by the conventional method of linearly weighting clear and cloudy transmittances by their respective sky fractions. Then, the approximations of decoupling cloud and radiative properties and assuming independent columns are shown to be adequate for computation of mean flux transmittance. Since real clouds have nonzero geometric thicknesses, cloud fractions A'(sub c) presented to isotropic beams usually exceed the more familiar vertically projected cloud fractions A(sub c). It is shown, however, that when A(sub c)less than or equal to 0.9, biases for all-sky transmittance stemming from use of A(sub c) as opposed to A'(sub c) are roughly 2-5 times smaller than, and opposite in sign to, biases due to neglect of horizontal variability of tau. By neglecting variable tau, all-sky transmittances are underestimated often by more than 0.1 for A(sub c) near 0.75 and this translates into relative errors that can exceed 40% (corresponding errors for all-sky emittance are about 20% for most values of A(sub c). Thus, priority should be given to development of General Circulation Model (GCM) parameterizations that account for the effects of horizontal variations in unresolved tau, effects of cloud sides are of secondary importance. On this note, an efficient stochastic model for computing grid-averaged cloudy-sky flux transmittances is furnished that assumes that distributions of tau, for regions comparable in size to GCM grid cells, can be described adequately by gamma distribution functions. While the plane-parallel, homogeneous model underestimates cloud transmittance by about an order of magnitude when 3D variable cloud transmittances are less than or equal to 0.2 and by approx. 20% to 100% otherwise, the stochastic model reduces these biases often by more than 80%.

Barker, Howard W.↗
NASA NTRS1999

A Precise Calibration Technique for Measuring High Gas Temperatures

A technique was developed for direct measurement of gas temperatures in the range of 2050 K - 2700 K with improved accuracy and reproducibility. The technique utilized the low-emittance of certain fibrous Materials, and the uncertainty of the technique was limited by the uncertainty in the melting points of the materials, i.e., +/- 15 K. The materials were pure, thin, metal-oxide fibers whose diameters varied from 60 mm to 400 mm in the experiments. The sharp increase in the emittance of the fibers upon melting was utilized as indication of reaching a known gas temperature. The accuracy of the technique was confirmed by both calculated low emittance values of transparent fibers, of order 0.01, up to a few degrees below their melting point and by the fiber-diameter independence of the results. This melting-point temperature was approached by increments not larger than 4 K, which was accomplished by controlled increases of reactant flow rates in hydrogen-air and/or hydrogen- oxygen flames. As examples of the applications of the technique, the gas-temperature measurements were used (a) for assessing the uncertainty in infering gas temperatures from thermocouple measurements, and (b) for calibrating an IR camera to measure gas temperatures. The technique offers an excellent calibration reference for other gas-temperature measurement methods to improve their accuracy and reliably extending their temperature range of applicability.

Gokoglu, Suleyman A.↗
NASA NTRS2000

A Precise Calibration Technique for Measuring High Gas Temperatures

A technique was developed for direct measurement of gas temperatures in the range of 2050 K 2700 K with improved accuracy and reproducibility. The technique utilized the low-emittance of certain fibrous materials, and the uncertainty of the technique was United by the uncertainty in the melting points of the materials, i.e., +/-15 K. The materials were pure, thin, metal-oxide fibers whose diameters varied from 60 microns to 400 microns in the experiments. The sharp increase in the emittance of the fibers upon melting was utilized as indication of reaching a known gas temperature. The accuracy of the technique was confirmed by both calculated low emittance values of transparent fibers, of order 0.01, up to a few degrees below their melting point and by the fiber-diameter independence of the results. This melting-point temperature was approached by increments not larger than 4 K, which was accomplished by controlled increases of reactant flow rates in hydrogen-air and/or hydrogen-oxygen flames. As examples of the applications of the technique, the gas-temperature measurements were used: (a) for assessing the uncertainty in inferring gas temperatures from thermocouple measurements, and (b) for calibrating an IR camera to measure gas temperatures. The technique offers an excellent calibration reference for other gas-temperature measurement methods to improve their accuracy and reliably extending their temperature range of applicability.

Gokoglu, Suleyman A.↗
NASA NTRS2001

Seismic Study of the Dynamics of the Solar Subsurface from SoHO Observations

In collaboration with Dr. Baudin, we have developed and refined the new observational methodology for local helioseismology known as time-distance analysis. Global helioseismology study the solar oscillations as a superposition of resonant modes, whose properties (mode frequencies) reflect the global structure of the sun (sound speed stratification, rotation rate, etc). In contrast, local helioseismology look at the solar oscillations as wave packets whose propagation will be affected by perturbations of the media sampled. These local perturbations (sound speed or velocity flows) will modify the propagation time, that in turn can be used as a diagnostic tool for a given region. From a data reduction perspective, the processing of solar dopplergrams that result in time-distance maps, i.e. propagation times as a function of distance between bounces at the surface, is radically different from the methodology used for global mode analysis. We have, in a first step, further develop the programs needed to carry out such analysis. We have then applied them to NMI data set, and explore the trade-off between various averaging and filtering approaches - steps required to improve the signal-to-noise ratio of correlation maps - and the resulting stability and precision of the fitted propagation times. While excessive averaging (whether over space, propagation distance, or time) will reduce the diagnostic potential of the method, insufficient averaging lead to unstable fits, or uncertainties so large as to hide the information we seek. In a second phase, we have developed the analysis methodology required to infer local properties from perturbation in time propagation. Namely, we have developed time-distance inversion techniques, with an emphasis on inferences of velocity flows from time anomalies. Note also that during the period covered by this grant, all the investigators on this proposal (i.e., Drs. Baudin, Eff-Darwich, Korzennik, and Noyes) took part in the organization of the SOHO 6 /GONG 99 Workshop: Structure and Dynamics of the Interior of the Sun and Sunlike Stars, held on June 1-4 1999 at the Boston Park Plaza Hotel in Boston, Massachusetts, USA. it was very well attended by more than 160 participants from 26 countries from all over the world. The proceedings were published in two volumes as ESA SP-418, with Sessions I-III in Volume 1, and Sessions IV-VI in Volume 2 (1,000 pages in total). The complete contents are also included in digital form on a CD-ROM included with Volume 1. This CD-ROM also contains additional multi-media material that complements some of the contributions.

Korzennik, Sylvain G.↗
NASA NTRS2010

Predicting the Size and Timing of Sunspot Maximum for Cycle 24

For cycle 24, the minimum value of the 12-month moving average (12-mma) of the AA-geomagnetic index in the vicinity of sunspot minimum (AAm) appears to have occurred in September 2009, measuring about 8.4 nT and following sunspot minimum by 9 months. This is the lowest value of AAm ever recorded, falling below that of 8.9 nT, previously attributed to cycle 14, which also is the smallest maximum amplitude (RM) cycle of the modern era (RM = 64.2). Based on the method of Ohl (the preferential association between RM and AAm for an ongoing cycle), one expects cycle 24 to have RM = 55+/-17 (the +/-1 - sigma prediction interval). Instead, using a variation of Ohl's method, one based on using 2-cycle moving averages (2-cma), one expects cycle 23's 2-cma of RM to be about 115.5+/-8.7 (the +/-1 - sigma prediction interval), inferring an RM of about 62+/-35 for cycle 24. Hence, it seems clear that cycle 24 will be smaller in size than was seen in cycle 23 (RM = 120.8) and, likely, will be comparable in size to that of cycle 14. From the Waldmeier effect (the preferential association between the ascent duration (ASC) and RM for an ongoing cycle), one expects cycle 24 to be a slow-rising cycle (ASC > or equal to 48 months), having RM occurrence after December 2012, unless it turns out to be a statistical outlier.

Wilson, Robert M.↗