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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 451 records · Page 25

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NASA NTRS1993

Parallel execution of a three-dimensional, chemically reacting, Navier-Stokes code on distributed-memory machines

This paper describes the parallel version of the three-dimensional, chemically reacting, computational fluid dynamics (CFD) code, SPARK. This work was performed on the Intel iPSC/860-based parallel computers. The SPARK code utilizes relatively simple explicit numerical algorithms, but models complex chemical reactions. The code solves the equations over a regular structured mesh so a simple dam decomposition is used to assign work to the individual processors. The explicit nature of the algorithm, combined with the computational intensity of the chemistry calculations, results in a very low communication-to-computation ratio when compared to typical CFD codes. The efficiency of the parallel code is examined and shown to be about 65 percent when the problem size is scaled with the number of processors. Two low-angle wall-jet injection cases are solved to demonstrate the capability of the parallel code for solving large problems efficiently.

Otto, John C.↗

DOE OSTI2020

Requirements, Status, and Plans for Track Reconstruction at the sPHENIX Experiment

sPHENIX is a new experiment that is being constructed at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The primary physics goals of sPHENIX are to measure jets, their substructure, and the upsilon resonances in p+p, p+Au and Au+Au collisions. To realize these goals, a tracking system composed of a time projection chamber and several silicon detectors will be used to identify tracks that correspond to jets and upsilon decays. However, the sPHENIX experiment will collect approximately 200 PB of data utilizing a finite-sized computing center; thus, performing track reconstruction in a timely manner is a challenge due to the large occupancy of heavy-ion collisions. The sPHENIX experiment, its track reconstruction, and the need for implementing faster track-fitting algorithms, such as that provided by the A Common Tracking Software package, into the sPHENIX software stack are discussed.

Osborn, Joe↗

NASA NTRS2011

A Deterministic Electron, Photon, Proton and Heavy Ion Radiation Transport Suite for the Study of the Jovian System

A deterministic suite of radiation transport codes, developed at NASA Langley Research Center (LaRC), which describe the transport of electrons, photons, protons, and heavy ions in condensed media is used to simulate exposures from spectral distributions typical of electrons, protons and carbon-oxygen-sulfur (C-O-S) trapped heavy ions in the Jovian radiation environment. The particle transport suite consists of a coupled electron and photon deterministic transport algorithm (CEPTRN) and a coupled light particle and heavy ion deterministic transport algorithm (HZETRN). The primary purpose for the development of the transport suite is to provide a means for the spacecraft design community to rapidly perform numerous repetitive calculations essential for electron, proton and heavy ion radiation exposure assessments in complex space structures. In this paper, the radiation environment of the Galilean satellite Europa is used as a representative boundary condition to show the capabilities of the transport suite. While the transport suite can directly access the output electron spectra of the Jovian environment as generated by the Jet Propulsion Laboratory (JPL) Galileo Interim Radiation Electron (GIRE) model of 2003; for the sake of relevance to the upcoming Europa Jupiter System Mission (EJSM), the 105 days at Europa mission fluence energy spectra provided by JPL is used to produce the corresponding dose-depth curve in silicon behind an aluminum shield of 100 mils ( 0.7 g/sq cm). The transport suite can also accept ray-traced thickness files from a computer-aided design (CAD) package and calculate the total ionizing dose (TID) at a specific target point. In that regard, using a low-fidelity CAD model of the Galileo probe, the transport suite was verified by comparing with Monte Carlo (MC) simulations for orbits JOI--J35 of the Galileo extended mission (1996-2001). For the upcoming EJSM mission with a potential launch date of 2020, the transport suite is used to compute the traditional aluminum-silicon dose-depth calculation as a standard shield-target combination output, as well as the shielding response of high charge (Z) shields such as tantalum (Ta). Finally, a shield optimization algorithm is used to guide the instrument designer with the choice of graded-Z shield analysis.

Norman, Ryan B.↗

NASA NTRS1976

Automatic control of a robotic vehicle

Over the last several years Jet Propulsion Laboratory has been engaged in a project to develop some of the technology required to build a robotic vehicle for exploring planetary surfaces. An overview of hardware and software being developed for this project is given. Particular emphasis is placed on the description of the current design for the Vehicle System required for locomotion and the path planning algorithm.

Mcreynolds, S. R.↗

NASA NTRS1986

Goldstone field test activities: Sky survey

The goals are to conduct a research and development program aimed at determining the most effective way to do SETI within the constraints of current technology and estimated budgets. The general search strategy adopted is that which is recommended by the SETI Science Working Group. The strategy for an all sky survey for SETI was further developed over the last year. Scan patterns, scan rates, and signal detection algorithms were developed. Spectral power measurement instrumentation was tested at the Venus Station of the Goldstone Deep Space Communication Complex. A specially designed radio frequency interference (RFI) measurement system was built and installed at the Venus Station. A data base management system for storage and retrieval of the RFI data was partially implemented on a VAX 750 computer at the Jet Propulsion Laboratory.

Gulkis, S.↗

NASA NTRS1991

NASA/Ames Research Center's science and applications aircraft program

NASA-Ames Research Center operates a fleet of seven Science and Applications Aircraft, namely the C-141/Kuiper Airborne Observatory (KAO), DC-8, C-130, Lear Jet, and three ER-2s. These aircraft are used to satisfy two major objectives, each of equal importance. The first is to acquire remote and in-situ scientific data in astronomy, astrophysics, earth sciences, ocean processes, atmospheric physics, meteorology, materials processing and life sciences. The second major objective is to expedite the development of sensors and their attendant algorithms for ultimate use in space and to simulate from an aircraft, the data to be acquired from spaceborne sensors. NASA-Ames Science and Applications Aircraft are recognized as national and international facilities. They have performed and will continue to perform, operational missions from bases in the United States and worldwide. Historically, twice as many investigators have requested flight time than could be accommodated. This situation remains true today and is expected to increase in the years ahead. A major advantage of the existing fleet of aircraft is their ability to cover a large expanse of the earth's ecosystem from the surface to the lower stratosphere over large distances and time aloft. Their large payload capability allows a number of scientists to use multi-investigator sensor suites to permit simultaneous and complementary data gathering. In-flight changes to the sensors or data systems have greatly reduced the time required to optimize the development of new instruments. It is doubtful that spaceborne systems will ever totally replace the need for airborne science aircraft. The operations philosophy and capabilities exist at NASA-Ames Research Center.

Hall, G. Warren↗

DOE OSTI2021

Machine learning assisted modeling of mixing timescale for LES/PDF of high-Karlovitz turbulent premixed combustion

Accurate modeling of mixing in the transported probability density function (PDF) method remains a great challenge, especially for turbulent premixed combustion under extreme conditions such as high Karlovitz number Ka. Recently, a power-law based mixing timescale model was developed for the large-eddy simulations (LES)/PDF modeling of high-Ka number turbulent premixed flames. It is found in this work that the power-law mixing timescale model is highly sensitive to the model parameters. It is thus critically needed to develop accurate calibration of these model parameters. The empirical specification of the model parameters developed in Zhang et. al. is found to be inadequate for accurate modeling of the mixing timescale. Here, machine learning is introduced as an attractive alternative in this work for the specification of the model parameters. A high-Ka number DNS jet flame is used as the training and validation of the machine learning models. The choices of the input parameters are discussed and compared for the machine learning models. The effect of differential molecular diffusion on mixing is examined by including the effect of the Lewis number in the training of the machine learning models. The performance of different machine learning algorithms is compared for the specification of the mixing model parameters. Overall, excellent performance of the machine learning models is observed for assisting the mixing modeling. The feasibility, interpretability, applicability, generality, and portability of using machine learning are discussed in general to provide a perspective on applying data-driven machine learning for turbulent combustion modeling studies.

42 ENGINEERING↗

DOE OSTI2024

Experimental Examination of Additively Manufactured Patterns on Structural Nuclear Materials for Digital Image Correlation Strain Measurements

Abstract Background There are a limited number of commercially available sensors for monitoring the deformation of materials in-situ during harsh environment applications, such as those found in the nuclear and aerospace industries. Such sensing devices, including weldable strain gauges, extensometers, and linear variable differential transformers, can be destructive to material surfaces being investigated and typically require relatively large surface areas to attach (> 10 mm in length). Digital image correlation (DIC) is a viable, non-contact alternative to in-situ strain deformation. However, it often requires implementing artificial patterns using splattering techniques, which are difficult to reproduce. Objective Additive manufacturing capabilities offer consistent patterns using programmable fabrication methods. Methods In this work, a variety of small-scale periodic patterns with different geometries were printed directly on structural nuclear materials (i.e., stainless steel and aluminum tensile specimens) using an aerosol jet printer (AJP). Unlike other additive manufacturing techniques, AJP offers the advantage of materials selection. DIC was used to track and correlate strain to alternative measurement methods during cyclic loading, and tensile tests (up to 1100 µɛ) at room temperature. Results The results confirmed AJP has better control of pattern parameters for small fields of view and facilitate the ability of DIC algorithms to adequately process patterns with periodicity. More specifically, the printed 100 μm spaced dot and 150 μm spaced line patterns provided accurate measurements with a maximum error of less than 2% and 4% on aluminum samples when compared to an extensometer and commercially available strain gauges. Conclusion Our results highlight a new pattern fabrication technique that is form factor friendly for digital image correlation in nuclear applications.

Novich, K. A. (ORCID:0000000204466022)↗

NASA NTRS1983

Prediction of an axisymmetric combusting flow

A numerical model for turbulent, recirculating combusting flow is developed and applied to a research combustor. The model is based on the time-averaged Navier-Stokes equations with k-epsilon turbulence closure and the compositional fluctuations at each point are given probabilistically in terms of the mixture fraction. The probability density function is derived from transport equations for its first two moments along with an assumption regarding its shape. The resulting equations are solved using a standard line relaxation algorithm. It is found that the predictions of the model are in good agreement with data from an axisymmetric, bluff-body stabilized research combustor, while the major discrepancies are similar to those found in isothermal flow comparisons. The peculiar features of this flow which contribute to the errors are examined. The agreement between the theory and data deteriorates as the central jet velocity is increased which indicates an enhanced role for unsteady effects.

Correa, S. M.↗

NASA NTRS1992

CRRES microelectronic test chip orbital data. II

Data from a MOSFET matrix on two JPL (CIT Jet Propulsion Laboratory) CRRES (Combined Release and Radiation Effects Satellite) chips, each behind different amounts of shielding, are presented. Space damage factors are nearly identical to ground test values for pMOSFETs. The results from neighboring rows of MOSFETs show similar radiation degradation. The SRD (Space Radiation Dosimeter) is used to measure the total dose accumulated by the JPL chips. A parameter extraction algorithm that does not underestimate threshold voltage shifts is used. Temperature effects are removed from the MOSFET data.

Soli, G. A.↗

NASA NTRS2004

Concentration Measurements in Self-Excited Momentum Dominated Low-Density Gas Jets

Flow structure of self-excited, laminar, axisymmetric, momentum-dominated helium jets discharged vertically into ambient air was investigated using high-speed rainbow schlieren deflectometry technique. Measurements were obtained at temporal resolution of 1 ms and spatial resolution of 0.19 mm for two test cases with Richardson number of 0.034 and 0.018. Power spectra revealed that the oscillation frequency was independent of spatial coordinates, suggesting global oscillations in the flow. Abel inversion algorithm was used to reconstruct the concentration field of helium. Instantaneous concentration contours revealed changes in the flow field and evolution of vortical structures during an oscillation cycle. Temporal evolution plots of helium concentration at different axial locations provided detailed information about the instability in the flow field.

Yildirim, B. S.↗

DOE OSTI2024

A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks

Machine learning algorithms are heavily relied on to understand the vast amounts of data from high-energy particle collisions at the CERN Large Hadron Collider (LHC). The data from such collision events can naturally be represented with graph structures. Therefore, deep geometric methods, such as graph neural networks (GNNs), have been leveraged for various data analysis tasks in high-energy physics. One typical task is jet tagging, where jets are viewed as point clouds with distinct features and edge connections between their constituent particles. The increasing size and complexity of the LHC particle datasets, as well as the computational models used for their analysis, have greatly motivated the development of alternative fast and efficient computational paradigms such as quantum computation. In addition, to enhance the validity and robustness of deep networks, we can leverage the fundamental symmetries present in the data through the use of invariant inputs and equivariant layers. In this paper, we provide a fair and comprehensive comparison of classical graph neural networks (GNNs) and equivariant graph neural networks (EGNNs) and their quantum counterparts: quantum graph neural networks (QGNNs) and equivariant quantum graph neural networks (EQGNN). The four architectures were benchmarked on a binary classification task to classify the parton-level particle initiating the jet. Based on their area under the curve (AUC) scores, the quantum networks were found to outperform the classical networks. However, seeing the computational advantage of quantum networks in practice may have to wait for the further development of quantum technology and its associated application programming interfaces (APIs).

Forestano, Roy T. (ORCID:0000000203552076)↗

NASA NTRS1987

Implicit flux-corrected transport scheme for low-speed flow

A new high-order nonlinear Eulerian convection algorithm, the barely implicit correction (BIC)-FCT method, is presented. The BIC-FCT makes it possible to perform accurate, multidimensional, slow-flow calculations in which the fluid expansion is important. Owing to its low cost even in two dimensions, fairly detailed chemistry models and other physical processes can be included. Areas of BIC-FCT applicability include premixed flames, diffusion flames, and turbulent jet flames.

Patnaik, G.↗

NASA NTRS1994

Multi-dimensional combustor flowfield analyses in gas-gas rocket engine

The objectives of the present research are to improve design capabilities for low thrust rocket engines through understanding of the detailed mixing and combustions processes. Of particular interest is a small gaseous hydrogen-oxygen thruster which is considered as a coordinated part of an on-going experimental program at NASA LeRC. Detailed computational modeling requires the application of the full three-dimensional Navier Stokes equations, coupled with species diffusion equations. The numerical procedure is performed on both time-marching and time-accurate algorithms and using an LU approximate factorization in time, flux split upwinding differencing in space. The emphasis in this paper is focused on using numerical analysis to understand detailed combustor flowfields, including the shear layer dynamics created between fuel film cooling and the core gas in the vicinity on the nearby combustor wall; the integrity and effectiveness of the coolant film; three-dimensional fuel jets injection/mixing/combustion characteristics; and their impacts on global engine performance.

Tsuei, Hsin-Hua↗

DOE OSTI2022

Plasma image classification using cosine similarity constrained convolutional neural network

Plasma jets are widely investigated both in the laboratory and in nature. Astrophysical objects such as black holes, active galactic nuclei and young stellar objects commonly emit plasma jets in various forms. With the availability of data from plasma jet experiments resembling astrophysical plasma jets, classification of such data would potentially aid in not only investigating the underlying physics of the experiments but also the study of astrophysical jets. In this work we use deep learning to process all of the laboratory plasma images from the Caltech Spheromak Experiment spanning two decades. We found that cosine similarity can aid in feature selection, classify images through comparison of feature vector direction and be used as a loss function for the training of AlexNet for plasma image classification. We also develop a simple vector direction comparison algorithm for binary and multi-class classification. Using our algorithm we demonstrate 93 % accurate binary classification to distinguish unstable columns from stable columns and 92 % accurate five-way classification of a small, labelled data set which includes three classes corresponding to varying levels of kink instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1986

An optimization model for the US Air-Traffic System

A systematic approach for monitoring U.S. air traffic was developed in the context of system-wide planning and control. Towards this end, a network optimization model with nonlinear objectives was chosen as the central element in the planning/control system. The network representation was selected because: (1) it provides a comprehensive structure for depicting essential aspects of the air traffic system, (2) it can be solved efficiently for large scale problems, and (3) the design can be easily communicated to non-technical users through computer graphics. Briefly, the network planning models consider the flow of traffic through a graph as the basic structure. Nodes depict locations and time periods for either individual planes or for aggregated groups of airplanes. Arcs define variables as actual airplanes flying through space or as delays across time periods. As such, a special case of the network can be used to model the so called flow control problem. Due to the large number of interacting variables and the difficulty in subdividing the problem into relatively independent subproblems, an integrated model was designed which will depict the entire high level (above 29000 feet) jet route system for the 48 contiguous states in the U.S. As a first step in demonstrating the concept's feasibility a nonlinear risk/cost model was developed for the Indianapolis Airspace. The nonlinear network program --NLPNETG-- was employed in solving the resulting test cases. This optimization program uses the Truncated-Newton method (quadratic approximation) for determining the search direction at each iteration in the nonlinear algorithm. It was shown that aircraft could be re-routed in an optimal fashion whenever traffic congestion increased beyond an acceptable level, as measured by the nonlinear risk function.

Mulvey, J. M.↗

DOE OSTI2023

Arctic cyclones have become more intense and longer-lived over the past seven decades

Intense cyclones driving extreme Arctic weather and climate events have been more frequently observed during recent years, causing dramatic environmental and socioeconomic impacts. However, inconsistencies have emerged about long-term changes in Arctic cyclone activity. Here we analyze multiple reanalysis datasets covering a multidecadal period with improvements to the cyclone tracking algorithm and the integrated cyclone activity metric. The results indicate an intensification of Arctic cyclone activity over the last seven decades. There has been a long-term shift of the maximum cyclone counts from weaker to stronger cyclones and a pronounced lengthening of the duration of strong cyclones. Spatial analysis shows increased strong cyclone frequency over the Arctic, driven by enhanced lower troposphere baroclinicity, amplified winter jet stream waves over the subpolar North Atlantic, and a strengthened summer tropospheric vortex over the central Arctic. The stratospheric vortex has also intensified the tropospheric waves and vortex with distinct dynamics between winter and summer. Recently enhanced baroclinicity over large areas of the Arctic and midlatitudes suggests more complicated atmospheric dynamics than what is hypothesized with Arctic-amplification-induced decrease in meridional temperature gradients.

Atmospheric dynamics↗

NASA NTRS2006

Tracking the Martian CO2 Polar Ice Caps in Infrared Images

Researchers at NASA s Jet Propulsion Laboratory have developed a method for automatically tracking the polar caps on Mars as they advance and recede each year (see figure). The seasonal Mars polar caps are composed mainly of CO2 ice and are therefore cold enough to stand out clearly in infrared data collected by the Thermal Emission Imaging System (THEMIS) onboard the Mars Odyssey spacecraft. The Bimodal Image Temperature (BIT) histogram analysis algorithm analyzes raw, uncalibrated data to identify images that contain both "cold" ("polar cap") and "warm" ("not polar cap") pixels. The algorithm dynamically identifies the temperature that separates these two regions. This flexibility is critical, because in the absence of any calibration, the threshold temperature can vary significantly from image to image. Using the identified threshold, the algorithm classifies each pixel in the image as "polar cap" or "not polar cap," then identifies the image row that contains the spatial transition from "polar cap" to "not polar cap." While this method is useful for analyzing data that has already been returned by THEMIS, it has even more significance with respect to data that has not yet been collected. Instead of seeking the polar cap only in specific, targeted images, the simplicity and efficiency of this method makes it feasible for direct, onboard use. That is, THEMIS could continuously monitor its observations for any detections of the polar-cap edge, producing detections over a wide range of spatial and temporal conditions. This effort can greatly contribute to our understanding of long-term climatic change on Mars.

Wagstaff, Kiri L.↗