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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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NASA NTRS1994

Software for Data Analysis with Graphical Models

Probabilistic graphical models are being used widely in artificial intelligence and statistics, for instance, in diagnosis and expert systems, as a framework for representing and reasoning with probabilities and independencies. They come with corresponding algorithms for performing statistical inference. This offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper illustrates the framework with an example and then presents some basic techniques for the task: problem decomposition and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

Buntine, Wray L.↗
DOE OSTI2022

An adaptive stochastic sequential quadratic programming with differentiable exact augmented lagrangians

In this study, we consider solving nonlinear optimization problems with a stochastic objective and deterministic equality constraints. We assume for the objective that its evaluation, gradient, and Hessian are inaccessible, while one can compute their stochastic estimates by, for example, subsampling. We propose a stochastic algorithm based on sequential quadratic programming (SQP) that uses a differentiable exact augmented Lagrangian as the merit function. To motivate our algorithm design, we first revisit and simplify an old SQP method Lucidi developed for solving deterministic problems, which serves as the skeleton of our stochastic algorithm. Based on the simplified deterministic algorithm, we then propose a non-adaptive SQP for dealing with stochastic objective, where the gradient and Hessian are replaced by stochastic estimates but the stepsizes are deterministic and prespecified. Finally, we incorporate a recent stochastic line search procedure Paquette and Scheinberg into the non-adaptive stochastic SQP to adaptively select the random stepsizes, which leads to an adaptive stochastic SQP. The global "almost sure" convergence for both non-adaptive and adaptive SQP methods is established. Numerical experiments on nonlinear problems in CUTEst test set demonstrate the superiority of the adaptive algorithm.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Progress Towards a Common CERES Cloud Mask Algorithm for MODIS and VIIRS: Evaluation using CALIOP Data

For over two decades The Clouds and the Earth’s Radiant Energy System (CERES) project has endeavored to produce a long-term global climate data record for detecting changes in the Earth’s radiation budget and to improve understanding of how clouds contribute to those changes. CERES incorporates cloud information derived from passive narrowband satellite imaging radiometers, and over the course of the project different instruments have contributed to this effort, namely the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS).Cloud properties have been derived from MODIS on the Aqua satellite for CERES since 2002,and VIIRS on the NOAA-20 satellite launched in 2017 will continue the cloud record once Aqua-MODIS reaches the end of its operational lifetime. However, MODIS and VIIRS have different spectral capabilities and characteristics which complicates our ability to seamlessly transition the record from MODIS to VIIRS. This study evaluates some of the recent algorithm modifications incorporated by the CERES Cloud Working Group towards developing a unified cloud mask algorithm for MODIS and VIIRS that utilizes a set of spectral bands common to both instruments. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products are used to evaluate MODIS and VIIRS regional cloud fraction estimates and identify areas where improvements can be made. The cloud mask algorithm relies on computed estimates of cloud-free top-of-atmosphere radiances to differentiate cloudy and cloud-free imager pixels. The unified cloud mask algorithm currently under development uses a reduced number of spectral bands common to both MODIS and VIIRS and so relies on the accuracy of these simulated cloud-free radiances more heavily than predecessor algorithms, i.e., the CERES Edition 4 cloud mask, which use as much spectral information as available on each imager with less consideration for cross-platform consistency. Our validation strategy using CALIOP data is also described. The CALIOP observations are critical for assessing cloud detection accuracies and for independently confirming cloud-free conditions which enables a more robust evaluation of the simulated cloud-free radiances for biases due to factors such as view angle and the spectral dependence of water vapor absorption. These effects are known to differ for the two satellite instruments. Comparisons of MODIS and VIIRS cloud fractions are presented in context with estimates from CALIOP and from the CERES Edition 4 cloud mask algorithm to gauge current progress in developing accurate and consistent MODIS and VIIRS cloud properties for CERES.

CERES↗
DOE OSTI2012

Event-Based Parareal: A data-flow based implementation of parareal

Parareal is an iterative algorithm that, in effect, achieves temporal decomposition for a time-dependent system of differential or partial differential equations. A solution is obtained in a shorter wall-clock time, but at the expense of increased compute cycles. The algorithm combines a fine solver that solves the system to acceptable accuracy with an approximate coarse solver. The critical task for the successful implementation of parareal on any system is the development of a coarse solver that leads to convergence in a small number of iterations compared to the number of time slices in the full time interval, and is, at the same time, much faster than the fine solver. Fast coarse solvers may not lead to sufficiently rapid convergence, and slow coarse solvers may not lead to significant gains even if the number of iterations to convergence is satisfactory. We find that the difficulty of meeting these conflicting demands can be substantially eased by using a data-driven, event-based implementation of parareal instead of the conventional algorithm where solver tasks are executed sequentially. For given convergence properties, the event-based approach relaxes the speed requirements on the coarse solver by a factor of , where is the number of iterations required for a converged solution. This may, for many problems, lead to an efficient parareal implementation that would otherwise not be possible or would require substantial coarse solver development.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

An advanced algorithm for construction of Integral Transport Matrix Method operators using accumulation of single cell coupling factors

The Integral Transport Matrix Method (ITMM) has been shown to be an effective method for solving the neutron transport equation in large domains on massively parallel architectures. In the limit of very large number of processors, the speed of the algorithm, and its suitability for unstructured meshes, i.e. other than an ordered Cartesian grid, is limited by the construction of four matrix operators required for obtaining the solution in each sub-domain. The existing algorithm used for construction of these matrix operators, termed the differential mesh sweep, is computationally expensive and was developed for a structured grid. This work proposes the use of a new algorithm for construction of these operators based on the construction of a single, fundamental matrix representing the transport of a particle along every possible path throughout the sub-domain mesh. Each of the operators is constructed by multiplying an element of this fundamental matrix by two factors dependent only upon the operator being constructed and on properties of the emitting and incident cells. The ITMM matrix operator construction time for the new algorithm is demonstrated to be shorter than the existing algorithm in all tested cases with both isotropic and anisotropic scattering considered. While also being a more efficient algorithm on a structured Cartesian grid, the new algorithm is promising in its geometric robustness and potential for being applied to an unstructured mesh, with the ultimate goal of application to an unstructured tetrahedral mesh on a massively parallel architecture. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Rythmos: Solution and Analysis Package for Differential-Algebraic and Ordinary-Differential Equations

Time integration is a central component for most transient simulations. It coordinates many of the major parts of a simulation together, e.g., a residual calculation with a transient solver, solution with the output, various operator-split physics, and forward and adjoint solutions for inversion. Even though there is this variety in these transient simulations, there is still a common set of algorithms and procedures to progress transient solutions for ordinary-differential equations (ODEs) and differential-alegbraic equations (DAEs). Rythmos is a collection of these algorithms that can be used for the solution of transient simulations. It provides common time-integration methods, such as Backward and Forward Euler, Explicit and Implicit Runge-Kutta, and Backward-Difference Formulas. It can also provide sensitivities, and adjoint components for transient simulations. Rythmos is a package within Trilinos, and requires some other packages (e.g., Teuchos and Thrya) to provide basic time-integration capabilities. It also can be coupled with several other Trilinos packages to provide additional capabilities (e.g., AztecOO and Belos for linear solutions, and NOX for non-linear solutions). The documentation is broken down into three parts: Theory Manual, User's Manual, and Developer's Guide. The Theory Manual contains the basic theory of the time integrators, the nomenclature and mathematical structure utilized within Rythmos, and verification results demonstrating that the designed order of accuracy is achieved. The User's Manual provides information on how to use the Rythmos, description of input parameters through Teuchos Parameter Lists, and description of convergence test examples. The Developer's Guide is a high-level discussion of the design and structure of Rythmos to provide information to developers for the continued development of capabilities. Details of individual components can be found in the Doxygen webpages.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Data Analysis with Graphical Models: Software Tools

Probabilistic graphical models (directed and undirected Markov fields, and combined in chain graphs) are used widely in expert systems, image processing and other areas as a framework for representing and reasoning with probabilities. They come with corresponding algorithms for performing probabilistic inference. This paper discusses an extension to these models by Spiegelhalter and Gilks, plates, used to graphically model the notion of a sample. This offers a graphical specification language for representing data analysis problems. When combined with general methods for statistical inference, this also offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper outlines the framework and then presents some basic tools for the task: a graphical version of the Pitman-Koopman Theorem for the exponential family, problem decomposition, and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

Buntine, Wray L.↗
DOE OSTI2016

On the adaptivity and complexity embedded into differential evolution

This research deals with the comparison of the two modern approaches for evolutionary algorithms, which are the adaptivity and complex chaotic dynamics. This paper aims on the investigations on the chaos-driven Differential Evolution (DE) concept. This paper is aimed at the embedding of discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE and comparing the influence to the performance with the state of the art adaptive representative jDE. This research is focused mainly on the possible disadvantages and advantages of both compared approaches. Repeated simulations for Lozi map driving chaotic systems were performed on the simple benchmark functions set, which are more close to the real optimization problems. Obtained results are compared with the canonical not-chaotic and not adaptive DE. Results show that with used simple test functions, the performance of ChaosDE is better in the most cases than jDE and Canonical DE, furthermore due to the unique sequencing in CPRNG given by the hidden chaotic dynamics, thus better and faster selection of unique individuals from population, ChaosDE is faster.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Supercontinuum Fourier transform spectrometry with balanced detection on a single photodiode

We demonstrate a method of combining a supercontinuum light source with a commercial Fourier transform spectrometer, using a novel approach to dual-beam balanced detection, implemented with phase-sensitive detection on a single light detector. A 40 dB reduction in the relative intensity noise is achieved for broadband light, analogous to conventional balanced detection methods using two matched photodetectors. Unlike conventional balanced detection, however, this method exploits the time structure of the broadband source to interleave signal and reference pulse trains in the time domain, recording the broadband differential signal at the fundamental pulse repetition frequency of the supercontinuum. The method is capable of real-time correction for instability in the supercontinuum spectral structure over a broad range of wavelengths and is compatible with commercially designed spectrometers. A proof-of-principle experimental setup is demonstrated for weak absorption in the 1500-1600 nm region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

A new Green's function Monte Carlo algorithm for the solution of the two-dimensional nonlinear Poisson–Boltzmann equation: Application to the modeling of the communication breakdown problem in space vehicles during re-entry

The objective of this paper is the exposition of a recently-developed, novel Green's function Monte Carlo (GFMC) algorithm for the solution of nonlinear partial differential equations and its application to the modeling of the plasma sheath region around a cylindrical conducting object, carrying a potential and moving at low speeds through an otherwise neutral medium. The plasma sheath is modeled in equilibrium through the GFMC solution of the nonlinear Poisson–Boltzmann (NPB) equation. The traditional Monte Carlo based approaches for the solution of nonlinear equations are iterative in nature, involving branching stochastic processes which are used to calculate linear functionals of the solution of nonlinear integral equations. Over the last several years, one of the authors of this paper, K. Chatterjee has been developing a philosophically-different approach, where the linearization of the equation of interest is not required and hence there is no need for iteration and the simulation of branching processes. Instead, an approximate expression for the Green's function is obtained using perturbation theory, which is used to formulate the random walk equations within the problem sub-domains where the random walker makes its walks. However, as a trade-off, the dimensions of these sub-domains have to be restricted by the limitations imposed by perturbation theory. The greatest advantage of this approach is the ease and simplicity of parallelization stemming from the lack of the need for iteration, as a result of which the parallelization procedure is identical to the parallelization procedure for the GFMC solution of a linear problem. The application area of interest is in the modeling of the communication breakdown problem during a space vehicle's re-entry into the atmosphere. However, additional application areas are being explored in the modeling of electromagnetic propagation through the atmosphere/ionosphere in UHF/GPS applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

On spectral methods for solving variable-order fractional integro-differential equations

This paper applies the shifted Jacobi–Gauss collocation (SJ–G-C) method for solving variable-order fractional integro-differential equations (VO-FIDE) with initial conditions. The Riemann–Liouville fractional derivative, D{sup ν(x)}, and integral, I{sup ν(x)}, of variable order are combined, and the SJ–G-C applied to produce a system of algebraic equations. Numerical experiments demonstrate the applicability and reliability of the algorithm when compared with current methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

OmniFed: A Modular Framework for Configurable Federated Learning from Edge to HPC

Federated Learning (FL) is critical for edge and High Performance Computing (HPC) where data is not centralized and privacy is crucial. We present OmniFed, a modular framework designed around decoupling and clear separation of concerns for configuration, orchestration, communication, and training logic. Its architecture supports configuration-driven prototyping and code-level override-what-you-need customization. We also support different topologies, mixed communication protocols within a single deployment, and popular training algorithms. It also offers optional privacy mechanisms including Differential Privacy (DP), Homomorphic Encryption (HE), and Secure Aggregation (SA), as well as compression strategies. These capabilities are exposed through well-defined extension points, allowing users to customize topology and orchestration, learning logic, and privacy/compression plugins, all while preserving the integrity of the core system. We evaluate multiple models and algorithms to measure various performance metrics. By unifying topology configuration, mixed-protocol communication, and pluggable modules in one stack, OmniFed streamlines FL deployment across heterogeneous environments. Github repository is available at https://github.com/at-aaims/OmniFed.

Tyagi, Sahil [ORNL] (ORCID:0009000783144745)↗
DOE OSTI2022

Optimal band selection for target detection with a LWIR multispectral imager

Multispectral imaging can offer many benefits in cost, complexity, resolution, size, weight, and power, relative to hyperspectral imaging. When designing a multispectral system, spectral bandpasses can be selected using optimization algorithms configured to maximally separate target detection scores between target and background regions. A hyperspectral image (HSI) can serve as the source of data from which band groupings can be tested for optimality. The output of an adaptive cosine estimator target detection algorithm is used in an objective function. Three optimization algorithms are compared: particle swarm, dual annealing, and differential evolution. A global optimum is also found using a brute force approach on the Livermore Computing Syrah supercomputer. Three materials are investigated: calcite, gypsum, and limestone. This is done for 3-, 4-, and 5-band systems. The data originate from a longwave infrared HSI of a material display board. The optimization algorithms were run 30 times for every scenario. Performance statistics (maximum, minimum, mean, standard deviation, and median) based on the separation values are given. Additional characterization was performed using receiver operator characteristic (ROC) curves and the area under the ROC curve. While good performance was obtained for the three optimization algorithms, the dual annealing algorithm produced the highest and most consistent detection separation scores on average.

47 OTHER INSTRUMENTATION↗
NASA NTRS1991

An all digital implementation of a modified Hamming net for video compression with prediction and quantization circuits

The hardware and algorithms used to vector quantize (VQ) predicted pixel intensity differences for real-time video compression are described. The hardware is designed for rapid vector quantization performance, which entails the development of application-specific associative memory circuits. A modified DPCM algorithm is originally examined to determine how neural circuitry could enhance its operation. It was determined that quantization and encoding could be improved by consolidating these two functions into one, and by increasing the amount of information (i.e. number of pixels) quantized at a time. The result is a predictive scheme that vector quantizes differential values. Some of the disadvantages of VQ algorithms are solved using associative memories. The video compression algorithm and the associative memory design are described.

Kaul, Richard↗
NASA NTRS2001

Retrieval of Polar Stratospheric Cloud Microphysical Properties from Lidar Measurements: Dependence on Particle Shape Assumptions

A retrieval algorithm has been developed for the microphysical analysis of polar stratospheric cloud (PSC) optical data obtained using lidar instrumentation. The parameterization scheme of the PSC microphysical properties allows for coexistence of up to three different particle types with size-dependent shapes. The finite difference time domain (FDTD) method has been used to calculate optical properties of particles with maximum dimensions equal to or less than 2 mu m and with shapes that can be considered more representative of PSCs on the scale of individual crystals than the commonly assumed spheroids. Specifically. these are irregular and hexagonal crystals. Selection of the optical parameters that are input to the inversion algorithm is based on a potential data set such as that gathered by two of the lidars on board the NASA DC-8 during the Stratospheric Aerosol and Gas Experiment 0 p (SAGE) Ozone Loss Validation experiment (SOLVE) campaign in winter 1999/2000: the Airborne Raman Ozone and Temperature Lidar (AROTEL) and the NASA Langley Differential Absorption Lidar (DIAL). The 0 microphysical retrieval algorithm has been applied to study how particle shape assumptions affect the inversion of lidar data measured in leewave PSCs. The model simulations show that under the assumption of spheroidal particle shapes, PSC surface and volume density are systematically smaller than the FDTD-based values by, respectively, approximately 10-30% and approximately 5-23%.

Reichardt, J.↗
DOE OSTI2014

A Spitzer five-band analysis of the Jupiter-sized planet TrES-1

With an equilibrium temperature of 1200 K, TrES-1 is one of the coolest hot Jupiters observed by Spitzer. It was also the first planet discovered by any transit survey and one of the first exoplanets from which thermal emission was directly observed. We analyzed all Spitzer eclipse and transit data for TrES-1 and obtained its eclipse depths and brightness temperatures in the 3.6 μm (0.083% ± 0.024%, 1270 ± 110 K), 4.5 μm (0.094% ± 0.024%, 1126 ± 90 K), 5.8 μm (0.162% ± 0.042%, 1205 ± 130 K), 8.0 μm (0.213% ± 0.042%, 1190 ± 130 K), and 16 μm (0.33% ± 0.12%, 1270 ± 310 K) bands. The eclipse depths can be explained, within 1σ errors, by a standard atmospheric model with solar abundance composition in chemical equilibrium, with or without a thermal inversion. The combined analysis of the transit, eclipse, and radial-velocity ephemerides gives an eccentricity of e=0.033{sub −0.031}{sup +0.015}, consistent with a circular orbit. Since TrES-1's eclipses have low signal-to-noise ratios, we implemented optimal photometry and differential-evolution Markov Chain Monte Carlo (MCMC) algorithms in our Photometry for Orbits, Eclipses, and Transits pipeline. Benefits include higher photometric precision and ∼10 times faster MCMC convergence, with better exploration of the phase space and no manual parameter tuning.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Relocating microseismicity from downhole monitoring of the Decatur CCS site using a modified double-difference algorithm

SUMMARY The injection of CO2 at the Decatur carbon capture and storage site has generated significant microseismic activity, which occurs in distinct spatial clusters up to approximately 2.2 km from the primary injection well. Accurate and precise event locations are vital for the characterization of the microseismicity to help understand the reservoir response to the CO2 injection, whilst enabling the identification of minor faults and fractures below the resolution of conventional active seismic imaging. However, microseismic monitoring of fluid injection sites, such as Decatur, is often performed using a network of borehole sensors often from a single well. While these downhole sensors have excellent detection capabilities, their poor azimuthal coverage limits the ability to precisely determine event locations. We have developed a modified double-difference relocation algorithm suitable for both 1-D and 3-D velocity models, and which incorporates differential back azimuth observations to allow the benefits of the original double-difference algorithm to be applicable to a downhole microseismic monitoring setting. Applying the modified double-difference algorithm to the microseismicity at Decatur, we have successfully relocated 4293 events. The relocation included over 59 million observations for 757 285 event pairs, split across seven geographic regions. Despite the majority of observations being recorded in only two boreholes, with an almost identical azimuthal coverage, the results have shown to be reliable with significantly reduced residuals and low uncertainties associated with the final locations. We have analysed the residuals in terms of their association with each geographic region, data type, station and individual events, to fully appreciate their influence in the inversion and the fit of the data to the final set of event locations. For each region, the relocated seismicity has become less diffuse with improved clustering, and with newly visible linear features often orientated in a NE–SW direction. These results show the potential improvements that can be made to microseismic event locations recorded by a borehole network with a limited and variable azimuthal distribution.

58 GEOSCIENCES↗