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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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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Scalable statistical inference of photometric redshift via data subsampling

Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for bigger problems. But full probabilistic statistical models often outperform other models in quantifying uncertainties associated with model predictions. We develop a data-driven statistical modeling framework that combines the uncertainties from an ensemble of statistical models learned on smaller subsets of data carefully chosen to account for imbalances in the input space. We demonstrate this method on a photometric redshift estimation problem in cosmology, which seeks to infer a distribution of the redshift—the stretching effect in observing the light of far-away galaxies—given multivariate color information observed for an object in the sky. Our proposed method performs balanced partitioning, graph-based data subsampling across the partitions, and training of an ensemble of Gaussian process models.

data subsampling↗
NASA NTRS1994

An optimization-based approach for integrated controls-structures design of flexible spacecraft

The control of flexible spacecraft is a difficult problem because of large number of elastic modes; low value, closely-spaced frequencies; very small damping; and uncertainties in math models. The traditional design approach is to design the structure first and then to design the control system. This view-graph presentation develops a methodology for spacecraft design which addresses control/structure interaction issues, produces technology for simultaneous control/structure design, and translates into algorithms and computational tools for practical integrated computer-aided design.

Maghami, P. G.↗
NASA NTRS1947

Scale effect and optimum relations for sea surface planning

From the general dimensional and mechanical similarity theory it follows that a condition of steady motion of a given shape\bottom with constant speed on the surface of water is determined by four nondimensional parameters. By considering the various systems of independent parameters which are applied in theory and practice and special tests, there is determined their mutual relations and their suitability as planning characteristics. In studying the scale effect on the basis of the Prnndtl formula for the friction coefficient for a turbulent condition the order of magnitude is given of the error in applying the model data to full scale in the case of a single-step bottom For a bottom of complicated shape it is shown how from the test data of the hydrodynamic characteristics for one speed with various loads, or one load with various speeds, there may be obtained by simple computation with good approximation the hydrodynamic characteristics for a different speed or for a different load. (These considerations may be of use in solving certain problems on the stability of planning.) This permits extrapolating the curve of resistance against speed for large speeds inaccessible in the tank tests or for other loads which were not tested. The data obtained by computation are in good agreement with the test results. Problems regarding the optimum trim angle or the optimum width in the case of planning of a flat plate are considered from the point of view of the minimum resistance for a given load on the water and planning speeds. Formulas and graphs are given for the optimum value of the planning coefficient and the corresponding values of the trim angle and width of the flat plate.

Sedov, L.↗
DOE OSTI2025

CONCURRENT, CONDENSED STEIN VARIATIONAL GRADIENT DESCENT FOR UNCERTAINTY QUANTIFICATION OF NEURAL NETWORKS

In this work, we propose a Stein variational gradient descent (SVGD) method to concurrently sparsify, train, and provide uncertainty quantification (UQ) of a complexly parameterized model, such as a neural network (NN). It employs a graph reconciliation and condensation process to reduce complexity and increase similarity in the Stein ensemble of parameterizations. Therefore, the proposed concurrent, condensed SVGD (ccSVGD) method can provide UQ on parameters, not just outputs. Furthermore, the parameter reduction speeds up the convergence of the Stein gradient descent as it reduces the combinatorial complexity by aligning and differentiating the sensitivity to parameters. These properties are demonstrated with an illustrative example and an application to a mechanical response representation problem in solid mechanics.

42 ENGINEERING↗
DOE OSTI2026

Navigating Large Chemical Spaces Using Graph Theory and Integer Programming

Navigating and analyzing large chemical spaces are necessary to accelerate the design and discovery of new molecules and chemical processes. In this work, we introduce a computational framework that integrates graph theory and integer programming to enable the efficient navigation of large chemical spaces. Our framework represents the chemical space as a graph, wherein nodes represent molecules and edges represent the degree of similarity or connectivity based on domain-specific information. Using the graph representation, we identify representative molecules by computing the so-called minimum dominating set (MDS), which in our context is the minimum set of molecules that is connected to all other molecules. We present a suite of solution strategies for the MDS problem including heuristic and rigorous integer programming (IP) approaches. We show that these approaches allow us to capture physicochemical properties and domain-specific logic and constraints, facilitating the identification of molecules with the target properties. We demonstrate the effectiveness of the proposed approach by navigating the chemical space of per- and polyfluoroalkyl substances (PFAS); this comprises approximately 15,000 molecular structures. We compare our framework against traditional dimensionality reduction and clustering methods such as t-SNE and K-means clustering.

Chemical structure↗
DOE OSTI2022

Quantum Local Search with the Quantum Alternating Operator Ansatz

We present a new hybrid, local search algorithm for quantum approximate optimization of constrained combinatorial optimization problems. We focus on the Maximum Independent Set problem and demonstrate the ability of quantum local search to solve large problem instances on quantum devices with few qubits. This hybrid algorithm iteratively finds independent sets over carefully constructed neighborhoods and combines these solutions to obtain a global solution. We study the performance of this algorithm on 3-regular, Community, and Erdős-Rényi graphs with up to 100 nodes.

Tomesh, Teague↗
NASA NTRS1993

A Report on Stochastic Fairness Queueing (SFQ) Experiments

SRI International (SRI) has developed an improved queueing algorithm, known as Stochastic Fairness Queueing (SFQ), for best-effort traffic (i.e., traffic that does not require any guaranteed service). SFQ is a probablistic variant of strict fair queueing where instead of a single queue being allocated per flow, a fixed number of queues are used and a hash function maps the IP source and destination to a particular queue. A seed to the hash function is also perturbed occasionally to help distribute the flows amongst different queues when more than one flow maps to the same queue during the lifetime of the flow. SFQ provides 'fair' access by trying to ensure that each flow from source to destination host obtains equal access to the available bandwidth. This report covers a series of experiments performed on DARTnet evaluating the behavior and performance of SFQ against a FIFO queueing discipline. These experiments were designed to show SFQ's advantages and performance, and include tests demonstrating: Fair utilization of available resources; Starvation prevention; Graceful degradation under overload conditions; and Resource usage. In general, the experiments do show that SFQ is better than FIFO queueing at allocating bandwidth equally among a set of flows. SFQ also prevents a stream from dominating the available bandwidth, which seems to be a tendency with FIFO queueing (i.e., if a flow demands more than its share of the available bandwidth, with FIFO queueing that stream receives a disproportionate amount when compared to flows demanding less than their share). Furthermore, SFQ seems to reward 'nice' users of the network by providing a lower variance in delay and more throughput when their resource demand is less than their available share. Both SFQ and FIFO queueing seem to degrade fairly well as the network becomes saturated and to recover well as the network becomes less congested. Not unexpectedly, FIFO queueing is a little more efficient than SFQ-the delays are less and the throughput slightly higher because SFQ requires more processing. However, the performance difference between the two queueing disciplines is relatively small. However, the experiments do point out some interesting behavior. FIFO queueing can behave better than SFQ with seed perturbation. We recommend further evaluation of the hash function and the seed perturbation technique. There are probably weaknesses in their current selection that cause this unexpected behavior. SFQ also seems to possess good scaling properties. To verify this, more experiments with a larger number of streams from more hosts need to be executed and examined, including the staggered introduction of streams. Staggering the streams may prove important, because graphs in the degradation experiment revealed some unexpected increases and decreases in throughput, which should be examined. This may again be due to the interaction of the hash function with the seed perturbation but it may also be related to some other unknown problem.

Denny, Barbara A.↗
NASA NTRS1997

Two Improved Algorithms for Envelope and Wavefront Reduction

Two algorithms for reordering sparse, symmetric matrices or undirected graphs to reduce envelope and wavefront are considered. The first is a combinatorial algorithm introduced by Sloan and further developed by Duff, Reid, and Scott; we describe enhancements to the Sloan algorithm that improve its quality and reduce its run time. Our test problems fall into two classes with differing asymptotic behavior of their envelope parameters as a function of the weights in the Sloan algorithm. We describe an efficient 0(nlogn + m) time implementation of the Sloan algorithm, where n is the number of rows (vertices), and m is the number of nonzeros (edges). On a collection of test problems, the improved Sloan algorithm required, on the average, only twice the time required by the simpler Reverse Cuthill-Mckee algorithm while improving the mean square wavefront by a factor of three. The second algorithm is a hybrid that combines a spectral algorithm for envelope and wavefront reduction with a refinement step that uses a modified Sloan algorithm. The hybrid algorithm reduces the envelope size and mean square wavefront obtained from the Sloan algorithm at the cost of greater running times. We illustrate how these reductions translate into tangible benefits for frontal Cholesky factorization and incomplete factorization preconditioning.

Kumfert, Gary↗
NASA NTRS2008

The Cosmic Ray Electron Excess

This slide presentation reviews the possible sources for the apparent excess of Cosmic Ray Electrons. The presentation reviews the Advanced Thin Ionization Calorimeter (ATIC) instrument, the various parts, how cosmic ray electrons are measured, and shows graphs that review the results of the ATIC instrument measurement. A review of Cosmic Ray Electrons models is explored, along with the source candidates. Scenarios for the excess are reviewed: Supernova remnants (SNR) Pulsar Wind nebulae, or Microquasars. Each of these has some problem that mitigates the argument. The last possibility discussed is Dark Matter. The Anti-Matter Exploration and Light-nuclei Astrophysics (PAMELA) mission is to search for evidence of annihilations of dark matter particles, to search for anti-nuclei, to test cosmic-ray propagation models, and to measure electron and positron spectra. There are slides explaining the results of Pamela and how to compare these with those of the ATIC experiment. Dark matter annihilation is then reviewed, which represent two types of dark matter: Neutralinos, and kaluza-Kline (KK) particles, which are next explained. The future astrophysical measurements, those from GLAST LAT, the Alpha Magnetic Spectrometer (AMS), and HEPCAT are reviewed, in light of assisting in finding an explanation for the observed excess. Also the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) could help by revealing if there are extra dimensions.

Chang, J.↗
NASA NTRS1987

Recent progress in the development and understanding of SUPG methods with special reference to the compressible Euler and Navier-Stokes equations

The current status of streamline-upwind/Petrov-Galerkin (SUPG) methods for the analysis of flow problems is surveyed in an analytical review. Problem areas addressed include classical Galerkin, upwind, artificial-diffusion, SUPG, discontinuous Galerkin, space-time FEM, and discontinuity-capturing approaches to the scalar advection-diffusion equation; incompressible flows; advective-diffusive systems; and the compressible Euler and Navier-Stokes equations. Graphs and diagrams are provided, and the good stability properties of state-of-the-art SUPG methods are pointed out.

Hughes, Thomas J. R.↗
NASA NTRS1990

A nonrecursive order N preconditioned conjugate gradient: Range space formulation of MDOF dynamics

While excellent progress has been made in deriving algorithms that are efficient for certain combinations of system topologies and concurrent multiprocessing hardware, several issues must be resolved to incorporate transient simulation in the control design process for large space structures. Specifically, strategies must be developed that are applicable to systems with numerous degrees of freedom. In addition, the algorithms must have a growth potential in that they must also be amenable to implementation on forthcoming parallel system architectures. For mechanical system simulation, this fact implies that algorithms are required that induce parallelism on a fine scale, suitable for the emerging class of highly parallel processors; and transient simulation methods must be automatically load balancing for a wider collection of system topologies and hardware configurations. These problems are addressed by employing a combination range space/preconditioned conjugate gradient formulation of multi-degree-of-freedom dynamics. The method described has several advantages. In a sequential computing environment, the method has the features that: by employing regular ordering of the system connectivity graph, an extremely efficient preconditioner can be derived from the 'range space metric', as opposed to the system coefficient matrix; because of the effectiveness of the preconditioner, preliminary studies indicate that the method can achieve performance rates that depend linearly upon the number of substructures, hence the title 'Order N'; and the method is non-assembling. Furthermore, the approach is promising as a potential parallel processing algorithm in that the method exhibits a fine parallel granularity suitable for a wide collection of combinations of physical system topologies/computer architectures; and the method is easily load balanced among processors, and does not rely upon system topology to induce parallelism.

Kurdila, Andrew J.↗
NASA NTRS2005

APGEN Version 5.0

Activity Plan Generator (APGEN), now at version 5.0, is a computer program that assists in generating an integrated plan of activities for a spacecraft mission that does not oversubscribe spacecraft and ground resources. APGEN generates an interactive display, through which the user can easily create or modify the plan. The display summarizes the plan by means of a time line, whereon each activity is represented by a bar stretched between its beginning and ending times. Activities can be added, deleted, and modified via simple mouse and keyboard actions. The use of resources can be viewed on resource graphs. Resource and activity constraints can be checked. Types of activities, resources, and constraints are defined by simple text files, which the user can modify. In one of two modes of operation, APGEN acts as a planning expert assistant, displaying the plan and identifying problems in the plan. The user is in charge of creating and modifying the plan. In the other mode, APGEN automatically creates a plan that does not oversubscribe resources. The user can then manually modify the plan. APGEN is designed to interact with other software that generates sequences of timed commands for implementing details of planned activities.

Maldague, Pierre↗
DOE OSTI2025

Bounce-averaged theory in arbitrary multi-well plasmas: solution domains and the graph structure of their connections

Bounce-averaged theories provide a framework for simulating relatively slow processes, such as collisional transport and quasilinear diffusion, by averaging these processes over the fast periodic motions of a particle on a closed orbit. This procedure dramatically increases the characteristic time scale and reduces the dimensionality of the modelled system. The natural coordinates for such calculations are the constants of motion (COM) of the fast particle motion, which by definition do not change during an orbit. However, for sufficiently complicated fields – particularly in the presence of local maxima of the electric potential and magnetic field – the COM are not sufficient to specify the particle trajectory. In such cases, multiple domains in COM space must be used to solve the problem, with boundary conditions enforced between the domains to ensure continuity and particle conservation. Previously, these domains have been imposed by hand, or by recognising local maxima in the fields, limiting the flexibility of bounce-averaged simulations. Here, we present a general set of conditions for identifying consistent domains and the boundary condition connections between the domains, allowing the application of bounce-averaged theories in arbitrarily complicated and dynamically evolving electromagnetic field geometries. We also show how the connections between the domains can be represented by a directed graph, which can help to succinctly represent the trajectory bifurcation structure.

fusion plasma↗
DOE OSTI2023

Benchmarking the PCMCI Causal Discovery Algorithm for Spatiotemporal Systems

Causal discovery algorithms construct hypothesized causal graphs that depict causal dependencies among variables in observational data. While powerful, the accuracy of these algorithms is highly sensitive to the underlying dynamics of the system in ways that have not been fully characterized in the literature. In this report, we benchmark the PCMCI causal discovery algorithm in its application to gridded spatiotemporal systems. Effectively computing grid-level causal graphs on large grids will enable analysis of the causal impacts of transient and mobile spatial phenomena in large systems, such as the Earth’s climate. We evaluate the performance of PCMCI with a set of structural causal models, using simulated spatial vector autoregressive processes in one- and two-dimensions. We develop computational and analytical tools for characterizing these processes and their associated causal graphs. Our findings suggest that direct application of PCMCI is not suitable for the analysis of dynamical spatiotemporal gridded systems, such as climatological data, without significant preprocessing and downscaling of the data. PCMCI requires unrealistic sample sizes to achieve acceptable performance on even modestly sized problems and suffers from a notable curse of dimensionality. This work suggests that, even under generous structural assumptions, significant additional algorithmic improvements are needed before causal discovery algorithms can be reliably applied to grid-level outputs of earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

FINETUNA: fine-tuning accelerated molecular simulations

Abstract Progress towards the energy breakthroughs needed to combat climate change can be significantly accelerated through the efficient simulation of atomistic systems. However, simulation techniques based on first principles, such as density functional theory (DFT), are limited in their practical use due to their high computational expense. Machine learning approaches have the potential to approximate DFT in a computationally efficient manner, which could dramatically increase the impact of computational simulations on real-world problems. However, they are limited by their accuracy and the cost of generating labeled data. Here, we present an online active learning framework for accelerating the simulation of atomic systems efficiently and accurately by incorporating prior physical information learned by large-scale pre-trained graph neural network models from the Open Catalyst Project. Accelerating these simulations enables useful data to be generated more cheaply, allowing better models to be trained and more atomistic systems to be screened. We also present a method of comparing local optimization techniques on the basis of both their speed and accuracy. Experiments on 30 benchmark adsorbate-catalyst systems show that our method of transfer learning to incorporate prior information from pre-trained models accelerates simulations by reducing the number of DFT calculations by 91%, while meeting an accuracy threshold of 0.02 eV 93% of the time. Finally, we demonstrate a technique for leveraging the interactive functionality built in to Vienna ab initio Simulation Package (VASP) to efficiently compute single point calculations within our online active learning framework without the significant startup costs. This allows VASP to work in tandem with our framework while requiring 75% fewer self-consistent cycles than conventional single point calculations. The online active learning implementation, and examples using the VASP interactive code, are available in the open source FINETUNA package on Github.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Optimal trajectories for an aerospace plane. Part 2: Data, tables, and graphs

Data, tables, and graphs relative to the optimal trajectories for an aerospace plane are presented. A single-stage-to-orbit (SSTO) configuration is considered, and the transition from low supersonic speeds to orbital speeds is studied for a single aerodynamic model (GHAME) and three engine models. Four optimization problems are solved using the sequential gradient-restoration algorithm for optimal control problems: (1) minimization of the weight of fuel consumed; (2) minimization of the peak dynamic pressure; (3) minimization of the peak heating rate; and (4) minimization of the peak tangential acceleration. The above optimization studies are carried out for different combinations of constraints, specifically: initial path inclination that is either free or given; dynamic pressure that is either free or bounded; and tangential acceleration that is either free or bounded.

Miele, Angelo↗
NASA NTRS1991

Stellar turbulent convection - A new model and applications

Improvements of the mixing-length theory (MLT) of turbulent convection in stellar atmospheres are developed theoretically. It is pointed out that inaccuracies are introduced into MLT by the approximating assumptions of a single large eddy (rather than many eddies of different sizes) and of incompressibility. In the proposed new model, the full spectrum of turbulent eddies is determined using more recent turbulence models (e.g., the eddy-damped quasi-normal Markovian model of Orszag, 1977), and a new formula for the convective flux is obtained which gives values up to 10 times greater than those of the MLT at high convective efficiencies. The problem of compressibility is addressed by adding one of two new expressions (one with no free parameters) for the mixing length. Numerical results from simulations of a solar-type star and a 0.8-solar-mass globular-cluster star are presented in tables and graphs and discussed in detail; the agreement with observations is found to be better than with the MLT.

Canuto, V. M.↗
NASA NTRS1981

Some statistical problems inherent in measuring precipitation

A formula permitting calculation of the mean-square error of the mean value of a random variable due to periodic sampling is derived and applied to estimating the sampling error for satellite observation of the mean rainfall during the GARP Atlantic Tropical Experiment (GATE). The effects of both spatial resolution and frequency of observation on the sampling error are summarized in graphs. It is found that four observations per day are sufficient to determine the monthly mean rainfall over an area of 2.5 deg square (280km x 280km) to within a standard deviation of 5 percent of its mean value; two samples per day would yield an error with a standard deviation slightly less than 10 percent of the mean. A satellite instrument with less frequent sampling may produce significantly greater error in the estimate of monthly mean rainfall.

Flueck, J. A.↗