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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

The effects of the geosynchronous energetic particle radiation environment on spacecraft charging phenomena

The energetic electron environment at the geosynchronous orbit is responsible for a variety of adverse charging effects on spacecraft components. The most serious of these is the degradation and failure of a complementary-metal-oxide-semiconductor (CMOS) electronic components as a result of internal charge-buildup induced by the energetic electrons. Efforts to accurately determine the expected lifetime of these components in this orbit are hampered by the lack of detailed knowledge of the electron spectrum and intensity, particularly of the more penetrating energies greater than 1.5 MeV. This problem is illustrated through the calculation of the dose received by a CMOS device from the energetic electrons and associated bremsstrahlung as a function of aluminum shielding thickness using the NASA AE-6 and the Aerospace measured electron environments. Two computational codes which were found to be in good agreement were used to perform the calculations. For a given shielding thickness the dose received with the two radiation environments differ by as much as a factor of seven with a corresponding variation in lifetime of the CMOS.

Reagan, J. B.↗
NASA NTRS2004

Rapid Chemometric Filtering of Spectral Data

A method of rapid, programmable filtering of spectral transmittance, reflectance, or fluorescence data to measure the concentrations of chemical species has been proposed. By programmable is meant that a variety of spectral analyses can readily be performed and modified in software, firmware, and/or electronic hardware, without need to change optical filters or other optical hardware of the associated spectrometers. The method is intended to enable real-time identification of single or multiple target chemical species in applications that involve high-throughput screening of multiple samples. Examples of such applications include (but are not limited to) combinatorial chemistry, flow cytometry, bead assays, testing drugs, remote sensing, and identification of targets. The basic concept of the proposed method is to perform real-time crosscorrelations of a measured spectrum with one or more analytical function(s) of wavelength that could be, for example, the known spectra of target species. Assuming that measured spectral intensities are proportional to concentrations of target species plus background spectral intensities, then after subtraction of background levels, it should be possible to determine target species concentrations from cross-correlation values. Of course, the problem of determining the concentrations is more complex when spectra of different species overlap, but the problem can be solved by use of multiple analytical functions in combination with computational techniques that have been developed previously for analyses of this type. The method is applicable to the design and operation of a spectrometer in which spectrally dispersed light is measured by means of an active-pixel sensor (APS) array. The row or column dimension of such an array is generally chosen to be aligned along the spectral-dispersion dimension, so that each pixel intercepts light in a narrow spectral band centered on a wavelength that is a known function of the pixel position. The proposed method admits of two hardware implementations for computing cross-correlations in real time.

Beaman, Gregory↗
DOE OSTI2024

Transformational Regional-Scale Earthquake Simulations with the DOE EarthQuake SIMulation Exascale Framework

Earthquakes present worldwide risk to economic and human safety. The 2023 earthquakes in Turkiye provided a reminder of the potential for catastrophic consequences with 50,700 deaths and 15.7 million people affected. The ability to predict ground motions and infrastructure damage for earthquakes continues to be a challenging problem for scientists and engineers. Until now, estimates of ground motions have been performed empirically by looking at sparse data from past earthquakes. This approach can provide statistical information on intensity amplitudes but cannot inform site-specific ground motions essential to developing the most effective resilience. Interest has grown in large-scale computational models to simulate earthquakes at regional scale. The U.S. Department of Energy EarthQuake SIMulation (EQSIM) framework was developed for regional-scale earthquake simulations at unprecedented fidelity, taking advantage of emerging GPU-accelerated systems. This article describes the EQSIM workflow and demonstrates regional-scale simulations with the new computational capability available to scientists in their quest to mitigate future disasters.

58 GEOSCIENCES↗
DOE OSTI2017

Accelerated solution of discrete ordinates approximation to the Boltzmann transport equation via model reduction

Radiation heat transfer is an important phenomenon in many physical systems of practical interest. When participating media is important, the radiative transfer equation (RTE) must be solved for the radiative intensity as a function of location, time, direction, and wavelength. In many heat-transfer applications, a quasi-steady assumption is valid, thereby removing time dependence. The dependence on wavelength is often treated through a weighted sum of gray gases (WSGG) approach. The discrete ordinates method (DOM) is one of the most common methods for approximating the angular (i.e., directional) dependence. The DOM exactly solves for the radiative intensity for a finite number of discrete ordinate directions and computes approximations to integrals over the angular space using a quadrature rule; the chosen ordinate directions correspond to the nodes of this quadrature rule. This paper applies a projection-based model-reduction approach to make high-order quadrature computationally feasible for the DOM for purely absorbing applications. First, the proposed approach constructs a reduced basis from (high-fidelity) solutions of the radiative intensity computed at a relatively small number of ordinate directions. Then, the method computes inexpensive approximations of the radiative intensity at the (remaining) quadrature points of a high-order quadrature using a reduced-order model constructed from the reduced basis. Finally, this results in a much more accurate solution than might have been achieved using only the ordinate directions used to compute the reduced basis. One- and three-dimensional test problems highlight the efficiency of the proposed method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Parallel methodology to capture cyclic variability in motored engines

Numerical prediction of of cycle-to-cycle variability (CCV) in SI engines is extremely challenging for two key reasons: (i) high-fidelity methods such as large eddy simulation (LES) are require to accurately capture the in-cylinder turbulent flowfield, and (ii) CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. In this study, a new methodology is proposed to dissociate this long time-scale problem into several shorter time-scale problems, which can considerably reduce the computational time without sacrificing the fidelity of the simulations. The strategy is to perform multiple single-cycle simulations in parallel by effectively perturbing the simulation parameters such as the initial and boundary conditions. It is shown that by perturbing the initial velocity field effectively based on the intensity of the in-cylinder turbulence, the mean and variance of the in-cylinder flowfield is captured reasonably well. Adding perturbations in the initial pressure field and the boundary pressure improves the predictions. It is shown that this new approach is able to give accurate predictions of the flowfield statistics in less than one-tenth of time required for the conventional approach of simulating consecutive engine cycles.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2012

Nonlinear Estimation Approach to Real-Time Georegistration from Aerial Images

When taking aerial images, it is important to know locations of specific points of interest in an Earth-centered coordinate system (latitude, longitude, height). The correspondence between a pixel location in the image and its Earth coordinate is known as georegistration. There are two main technical challenges arising in the intended application. The first is that no known features are assumed to be available in any of the images. The second is that the intended applications are real time. Here, images are taken at regular intervals (i.e. once per second), and it is desired to make decisions in real time based on the geolocation of specific objects seen in the images as they arrive. This is in sharp contrast to most current methods for geolocation that operate "after-the-fact" by processing, on the ground, a database of stored images using computationally intensive methods. The solution is a nonlinear estimation algorithm that combines processed realtime camera images with vehicle position and attitude information ob tained from an onboard GPS receiver. This approach provides accurate georegistration estimates (latitude, longitude, height) of arbitrary features and/or points of interest seen in the camera images. This solves the georegistration problem at the modest cost of augmenting the camera information with a GPS receiver carried onboard the vehicle.

Bayard, David S.↗
DOE OSTI2022

Tensor networks for High Energy Physics: contribution to Snowmass 2021

Tensor network methods are becoming increasingly important for high-energy physics, condensed matter physics and quantum information science (QIS). We discuss the impact of tensor network methods on lattice field theory, quantum gravity and QIS in the context of High Energy Physics (HEP). These tools will target calculations for strongly interacting systems that are made difficult by sign problems when conventional Monte Carlo and other importance sampling methods are used. Further development of methods and software will be needed to make a significant impact in HEP. We discuss the roadmap to perform quantum chromodynamics (QCD) related calculations in the coming years. The research is labor intensive and requires state of the art computational science and computer science input for its development and validation. We briefly discuss the overlap with other science domains and industry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Invertible neural networks for real-time control of extrusion additive manufacturing

Material extrusion additive manufacturing (AM) has enabled an elegant fabrication pathway for a vast material library. Nonetheless, each material requires optimization of printing parameters generally determined through significant trial-and-error testing. To eliminate arduous, iteration-based optimization approaches, many researchers have used machine learning (ML) algorithms which provide opportunities for automated process optimization. Here, in this work, we demonstrate the use of an ML-driven approach for real-time material extrusion print-parameter optimization through in-situ monitoring of printed line geometry. To do this, we use deep invertible neural networks (INNs) which can solve both forward and inverse, or optimization, problems using a single network. By combining in-situ computer vision and deep INNs, the printing parameters can be autonomously optimized to print a target line width in 1.2 s. Furthermore, defects that occur during printing can be rapidly identified and corrected autonomously. The methods developed and presented in this work eliminate user-intensive, time-consuming, and iterative parameter discovery approaches that currently limit accelerated implementation of extrusion-based AM processes. Furthermore, the presented approach can be generalized to provide real-time monitoring and optimization pathways for increasingly complex AM environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Parallel String Graph Construction and Transitive Reduction for De Novo Genome Assembly

One of the most computationally intensive tasks in computational biology is de novo genome assembly, the decoding of the sequence of an unknown genome from redundant and erroneous short sequences. A common assembly paradigm identifies overlapping sequences, simplifies their layout, and creates consensus. Despite many algorithms developed in the literature, the efficient assembly of large genomes is still an open problem. In this work, we introduce new distributed-memory parallel algorithms for overlap detection and layout simplification steps of de novo genome assembly, and implement them in the diBELLA 2D pipeline. Our distributed memory algorithms for both overlap detection and layout simplification are based on linear-algebra operations over semirings using 2D distributed sparse matrices. Our layout step consists of performing a transitive reduction from the overlap graph to a string graph. We provide a detailed communication analysis of the main stages of our new algorithms. diBELLA 2D achieves near linear scaling with over 80% parallel efficiency for the human genome, reducing the runtime for overlap detection by 1.2-1.3× for the human genome and 1.5-1.9× for C.elegans compared to the state-of-the-art. Our transitive reduction algorithm outperforms an existing distributed-memory implementation by 10.5-13.3× for the human genome and 18-29× for the C. elegans. Our work paves the way for efficient de novo assembly of large genomes using long reads in distributed memory.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1983

Human capabilities: Long residence - An uncharted field

In the context of the planned NASA space station, it is anticipated that a number of problems will be posed by permanent residence in space. Not only will the intensive training which has characterized earlier manned programs diminish under the pressure of increased launch rates, but the new and larger crews will socially, educationally, psychologically and physiologically constitute a far more heterogeneous group than those of the past. In addition, advanced computer technology will result in a degree of reliance on onboard data processing which will alter the relations of ground and space operators, requiring careful integration of people and technologies. Attention is given to questions of food, robotics, extravehicular activity, hygiene and environmental noise.

Chambers, A.↗
NASA NTRS1995

Interaction of an interplanetary shock with the heliospheric plasma sheet

Interplanetary shocks often propagate along the heliospheric plasma sheet (HPS) where the interplanetary magnetic field (IMF) changes its polarity. This problem is investigated by the time-dependent 2.5-D MHD numerical model in the meridional plane. An example of computation is shown in the figure using density (log) contours and IMF vectors. Values of plasma parameters along the HPS fluctuate in time due to the Kelvin-Helmholtz instability. The HPS with its decreased intensity of the IMF as well as with its increased mass density causes a dimple in the shock structure (relatively weak for the forward shock, significant for the reverse shock, and very large for the contact discontinuity). Beyond the forward shock, the HPS is slightly compressed due to the post-shock increase of the azimuthal IMF component. Then follows expansion of the HPS surrounded by the highly-deformed contact discontinuity. A significant draping of IMF lines occurs around this structure that increases the meridional component of the IMF. This can cause a favorable condition for initiation of a geomagnetic storm.

Odstrcil, D.↗
NASA NTRS2006

Beam Heating of Samples: Modeling and Verification

Energy absorbed from the X-ray beam by the sample requires cooling by forced convection (i.e. cryostream) to minimize temperature increase and the damage caused to the sample by the X-ray heating. In this presentation we will first review the current theoretical models and recent studies in the literature, which predict the sample temperature rise for a given set of beam parameters. It should be noted that a common weakness of these previous studies is that none of them provide actual experimental confirmation. This situation is now remedied in our investigation where the problem of x-ray sample heating is taken up once more. We have theoretically investigated, and at the same time, in addition to the numerical computations, performed experiments to validate the predictions. We have modeled, analyzed and experimentally tested the temperature rise of a 1 mm diameter glass sphere (sample surrogate) exposed to an intense synchrotron X-ray beam, while it is being cooled in a uniform flow of nitrogen gas. The heat transfer, including external convection and internal heat conduction was theoretically modeled using CFD to predict the temperature variation in the sphere during cooling and while it was subjected to an undulator (ID sector 19) X-ray beam at the APS. The surface temperature of the sphere during the X-ray beam heating was measured using the infrared camera measurement technique described in a previous talk. The temperatures from the numerical predictions and experimental measurements are compared and discussed. Additional results are reported for the two different sphere sizes and for two different supporting pin orientations.

Kazmierczak, Michael↗
DOE OSTI2015

Monte Carlo based investigation of Berry phase for depth resolved characterization of biomedical scattering samples

The propagation of light in turbid media is an active area of research with relevance to numerous investigational fields, e.g., biomedical diagnostics and therapeutics. The statistical random-walk nature of photon propagation through turbid media is ideal for computational based modeling and simulation. Ready access to super computing resources provide a means for attaining brute force solutions to stochastic light-matter interactions entailing scattering by facilitating timely propagation of sufficient (>10million) photons while tracking characteristic parameters based on the incorporated physics of the problem. One such model that works well for isotropic but fails for anisotropic scatter, which is the case for many biomedical sample scattering problems, is the diffusion approximation. In this report, we address this by utilizing Berry phase (BP) evolution as a means for capturing anisotropic scattering characteristics of samples in the preceding depth where the diffusion approximation fails. We extend the polarization sensitive Monte Carlo method of Ramella-Roman, et al.,1 to include the computationally intensive tracking of photon trajectory in addition to polarization state at every scattering event. To speed-up the computations, which entail the appropriate rotations of reference frames, the code was parallelized using OpenMP. The results presented reveal that BP is strongly correlated to the photon penetration depth, thus potentiating the possibility of polarimetric depth resolved characterization of highly scattering samples, e.g., biological tissues.

back scattered Mueller matrix↗
DOE OSTI2014

Anomaly Detection in Dynamic Networks

Anomaly detection in dynamic communication networks has many important security applications. These networks can be extremely large and so detecting any changes in their structure can be computationally challenging; hence, computationally fast, parallelisable methods for monitoring the network are paramount. For this reason the methods presented here use independent node and edge based models to detect locally anomalous substructures within communication networks. As a first stage, the aim is to detect changes in the data streams arising from node or edge communications. Throughout the thesis simple, conjugate Bayesian models for counting processes are used to model these data streams. A second stage of analysis can then be performed on a much reduced subset of the network comprising nodes and edges which have been identified as potentially anomalous in the first stage. The first method assumes communications in a network arise from an inhomogeneous Poisson process with piecewise constant intensity. Anomaly detection is then treated as a changepoint problem on the intensities. The changepoint model is extended to incorporate seasonal behavior inherent in communication networks. This seasonal behavior is also viewed as a changepoint problem acting on a piecewise constant Poisson process. In a static time frame, inference is made on this extended model via a Gibbs sampling strategy. In a sequential time frame, where the data arrive as a stream, a novel, fast Sequential Monte Carlo (SMC) algorithm is introduced to sample from the sequence of posterior distributions of the change points over time. A second method is considered for monitoring communications in a large scale computer network. The usage patterns in these types of networks are very bursty in nature and don’t fit a Poisson process model. For tractable inference, discrete time models are considered, where the data are aggregated into discrete time periods and probability models are fitted to the communication counts. In a sequential analysis, anomalous behavior is then identified from outlying behavior with respect to the fitted predictive probability models. Seasonality is again incorporated into the model and is treated as a changepoint model on the transition probabilities of a discrete time Markov process. Second stage analytics are then developed which combine anomalous edges to identify anomalous substructures in the network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Development of the finite slab geometry in the NORA code

In this work we develop the complete linearization formalism for the radiation transfer equation in slab geometry. This development was motivated by an observed convergence instability arising from the NORA code’s inner boundary while modeling a suite of simple test problems in slab geometry presented at the Line Transfer Workshop held in LLNL in May of 2019. The convergence issue was seen to emerge early on in Newton-Raphson iterations. These test problems required parameters in the former NORA inner boundary to achieve the asymptotic limit of zero incoming intensity. In this work we derive the limiting case directly to gain insight into the former algorithm’s pathology.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Catching the whispers from Uranus

Sophisticated telecommunications techniques are described that were used to acquire images of Uranus, its 14 moons and ten narrow rings darker than coal. The images, equal in quality to those transmitted from Saturn several years earlier despite the signal being weaker by 6 dB due to the increased distance, were received from Voyager 2 during its January 24, 1986 flyby of Uranus. Solutions to the problem of the weakening signal were found in modifications to Voyager's image processing system and NASA's ground tracking network. In April 1985, Voyager's prime flight data computer was reconfigured to accept only nonimaging science data, and its backup, only imaging data; the latter was reprogrammed to determine only arithmetic differences between adjacent pixel intensities rather than absolute intensities. By image compression, equivalent imaging information could be sent at lower bit rates. Instead of Golay coding, Reed-Solomon onboard encoding was used. These techniques gained the equivalent of 4-dB in imaging yield. Additional improvements were gained by using earth station antennas in pairs (the Parkes radio telescope and the Canberra ground station antenna). Moves under way to prepare for the Voyager encounter with Neptune in 1989 are described (using additional antennas and arrays, scaling up the Deep Space Network antennas from 64 m to 70 m, etc.) to assure almost Saturn-equivalent pictures despite a further 3.5-dB drop in signal strength.

Bartok, C. D.↗
DOE OSTI2011

Open Problems in Network-aware Data Management in Exa-scale Computing and Terabit Networking Era

Accessing and managing large amounts of data is a great challenge in collaborative computing environments where resources and users are geographically distributed. Recent advances in network technology led to next-generation high-performance networks, allowing high-bandwidth connectivity. Efficient use of the network infrastructure is necessary in order to address the increasing data and compute requirements of large-scale applications. We discuss several open problems, evaluate emerging trends, and articulate our perspectives in network-aware data management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The Science DMZ: A Network Design Pattern for Data-Intensive Science

The ever-increasing scale of scientific data has become a significant challenge for researchers that rely on networks to interact with remote computing systems and transfer results to collaborators worldwide. Despite the availability of high-capacity connections, scientists struggle with inadequate cyberinfrastructure that cripples data transfer performance, and impedes scientific progress. The Science DMZ paradigm comprises a proven set of network design patterns that collectively address these problems for scientists. We explain the Science DMZ model, including network architecture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercomputing centers and research laboratories, highlighting the effectiveness of the Science DMZ model in diverse operational settings. In all, the Science DMZ model is a solid platform that supports any science workflow, and flexibly accommodates emerging network technologies. As a result, the Science DMZ vastly improves collaboration, accelerating scientific discovery.

Dart, Eli↗