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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Aerodynamic loss generation in a low-pressure turbine stage with high lift blading

The present work aims to investigate the loss generation mechanisms in a highly loaded low-pressure turbine (LPT) stage. The turbine employs high-lift airfoils to reduce the number of blades and therefore the overall engine weight. Large Eddy Simulation (LES) is applied to study the detailed flow fields at two representative Reynolds numbers (150,000 and 40,000). The calculated flow fields are compared with available measured data. LES calculates the measured aerodynamic performance of the current turbine stage well. Both the measurements and the CFD simulations indicate that most of the aerodynamic loss is generated by the development of secondary flows near the rotor hub. An area of low momentum and high aerodynamic loss forms at roughly 25 % span above the hub downstream of the rotor. Formation and migration of a vortex system near the hub is the primary source of the loss generation. The hub wall vortex system in this highly loaded turbine stage is quite different from the horse-shoe vortex system in a typical stationary turbine cascade. Calculated instantaneous and time-averaged flow fields at two Reynolds numbers are examined in detail to study Reynolds number effects on the turbine stage performance. Steady and unsteady flow separation on the rotor suction side is calculated at both high and low Reynolds numbers. At the lower Reynolds number of 40,000, thicker blade boundary layers increase the area of flow separation on the rotor suction side, resulting in a 1.9 % increase in aerodynamic loss compared to the higher Reynolds number case.

low pressure turbine↗
DOE OSTI2020

Visualizing group II intron dynamics between the first and second steps of splicing

Group II introns are ubiquitous self-splicing ribozymes and retrotransposable elements evolutionarily and chemically related to the eukaryotic spliceosome, with potential applications as gene-editing tools. Recent biochemical and structural data have captured the intron in multiple conformations at different stages of catalysis. Here, we employ enzymatic assays, X-ray crystallography, and molecular simulations to resolve the spatiotemporal location and function of conformational changes occurring between the first and the second step of splicing. We show that the first residue of the highly-conserved catalytic triad is protonated upon 5’-splice-site scission, promoting a reversible structural rearrangement of the active site (toggling). Protonation and active site dynamics induced by the first step of splicing facilitate the progression to the second step. Our insights into the mechanism of group II intron splicing parallels functional data on the spliceosome, thus reinforcing the notion that these evolutionarily-related molecular machines share the same enzymatic strategy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and resolving their structures at subnanometre resolution [Tegunov et al. (2021)View full citation, Nat. Methods, 18, 186–193]. Despite improvements in data quality as a result of advances in detector technology, microscope stability and stage precision, the analysis and interpretation of tomograms remains challenging due to a low signal-to-noise ratio and reconstruction artifacts stemming from experimental constraints in specimen tilt during data collection resulting in a missing wedge in the Fourier space. Recently, self-supervised deep-learning methods have been proposed for contrast enhancement and reduction of resolution anisotropy in reconstructed tomograms. Here, we evaluate several state-of-the-art deep-learning methods which aim to improve the interpretability of cryo-ET reconstructions, with a focus on their performance on downstream tasks of template matching, sub­tomogram averaging and segmentation. We propose new training architectures and a loss function based on Fourier shell correlation that show improved performance over the standard U-Net with L1/L2 losses. We demonstrate our analysis on four diverse experimental datasets: purified 80S ribosomes, in situ Chlamydomonas reinhardtii, immature HIV-1 virus-like particles and INS-1E cells.

contrast enhancement↗
DOE OSTI2021

Methods for a blind analysis of isobar data collected by the STAR collaboration

In 2018, the STAR collaboration collected data from $_{44}^{96}{\mathrm{Ru}}+_{44}^{96}{\mathrm{Ru}}$ and $_{40}^{96}{\mathrm{Zr}}+_{40}^{96}{\mathrm{Zr}}$ at $\sqrt{s_\text {NN}}=200$ GeV to search for the presence of the chiral magnetic effect in collisions of nuclei. The isobar collision species alternated frequently between $_{44}^{96}{\mathrm{Ru}}+_{44}^{96}{\mathrm{Ru}}$ and $_{40}^{96}{\mathrm{Zr}}+_{40}^{96}{\mathrm{Zr}}$ . In order to conduct blind analyses of studies related to the chiral magnetic effect in these isobar data, STAR developed a three-step blind analysis procedure. Analysts are initially provided a “reference sample” of data, comprised of a mix of events from the two species, the order of which respects time-dependent changes in run conditions. After tuning analysis codes and performing time-dependent quality assurance on the reference sample, analysts are provided a species-blind sample suitable for calculating efficiencies and corrections for individual $\approx 30$-min data-taking runs. For this sample, species-specific information is disguised, but individual output files contain data from a single isobar species. Only run-by-run corrections and code alteration subsequent to these corrections are allowed at this stage. Following these modifications, the “frozen” code is passed over the fully un-blind data, completing the blind analysis. As a check of the feasibility of the blind analysis procedure, analysts completed a “mock data challenge,” analyzing data from Au + Au collisions at $\sqrt{s_\text {NN}}=27$ GeV, collected in 2018. The Au + Au data were prepared in the same manner intended for the isobar blind data. Finally, the details of the blind analysis procedure and results from the mock data challenge are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Evaluating Image Classification Deep Convolutional Neural Network Architectures for Remaining Useful Life Estimation of Turbofan Engines

Accurate estimation of the remaining useful life (RUL) is a key component of condition-based maintenance (CBM) and prognosis and health management (PHM). Data-based models for the estimation of RUL are of particular interest because expert knowledge of systems is not always available, and physical modeling is often not feasible. Additionally, using data-based models, which make decisions based on raw sensor data, allow features to be learned instead of manually determined. In this work, deep convolutional neural network (CNN) architectures are investigated for their ability to estimate the RUL of turbofan engines. To improve the accuracy of the models, CNN architectures, which have proven successful in image classification, are implemented and tested. Specifically, the blocks used in the Visual Geometry Group (VGG) architecture, inception modules used in the GoogLeNet architecture, and residual blocks used in the ResNet architecture are incorporated. To account for varying flight lengths, the input to the models is a window of time series data collected from the engine under test. Window locations at the climb, cruise, and descent stages are considered. To further improve the RUL estimations, multiple overlapping windows at each location are used. This increases the amount of training data available and is found to increase the accuracy of the resulting RUL estimations by averaging the estimates from all overlapping segments. The model is trained and tested using the new Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) data set, and high prognosis accuracy was achieved. Furthermore, this work expands on the model developed and used in the 2021 PHM Society Data Challenge, which received second place.

convolutional neural networks↗
NASA NTRS1987

Investigation into alternative statistical auroral oval models, stage 1

The statistical model sensitivity to different methods of binning the NOAA/TIROS data base was examined. Each partial auroral pass was analyzed to locate the latitude of peak electron energy flux. Then using this location as the final reference latitude, all other data was binned relative to it. The next line of attack was to bin according to where the latitudinal profile center of gravity lay. This procedure overcomes the problem of very narrow intense features controlling the binning. Again the same data sets were analyzed and a binning made. These profiles look better and indeed look similar to the original auroral model. The passes were then binned relative to the equatorward boundary. The problems associated with the equatorward edge were resolved.

Bowline, M.↗
NASA NTRS1987

Experimental and theoretical studies of time-averaged and time resolved rotor heat transfer

Efforts in support of the Space Shuttle Main Engine (SSME) structural durability program have concentrated on obtaining detailed time-averaged and time-resolved (or phase-locked) measurements on a full-scale rotating turbine both with and without cold gas injection and on theoretical studies designed to improve the prediction capability for these turbine flows. The experimental efforts have concentrated on use of the Garrett TFE 731-2 hp turbine. However, it has been possible to apply the theoretical efforts to predicting heat-flux distributions obtained for two additional turbines - i.e., (1) the Garrett low aspect ratio turbine (LART) and (2) the Teledyne 702 turbine. The experimental technique is the short duration, shock-tunnel approach, in which fast-response, thin-film resistance thermometers are used to measure surface temperature histories at prescribed locations on the turbine component parts. Heat-flux values are then inferred from the temperature histories by using standard data reduction procedures. The turbine being used is the Garrett TFE 731-2 hp stage, and both the nozzle guide vanes and the rotor blades are heavily instrumented with thin-film heat-flux gauges. Depending on how the data from a particular heat-flux gauge are recorded, one can get either time-resolved (or phase-locked) or time-averaged results. Both types of data are illustrated.

Dunn, M. G.↗
NASA NTRS2008

Recent Observations of the Early Stage of Solar Eruptions

We examine the onset of two solar eruptions, using data from Hinode STEREO, TRACE, and SOHO, and other sources. One eruption occurred on 2007 March 2, and the other occurred on 2007 May 20. The first eruption involves a filament that erupts, and motions of the filament begin at least 20 min prior to onset of the main eruption; magnetic cancellation occurs beneath the filament among opposite polarity magnetic elements for at least six hours prior to the eruption.. In the second case, a surge-like filament is ejected from a location north of the main erupting magnetic neutral line; in this case magnetic cancellation occurs both along the main neutral line and also at the sight of the surge source north of the main neutral line. Thus in both cases, magnetic cancellation prior to eruption plays a crucial role in releasing the magnetic energy responsible for the respective eruptions.

Sterling, Alphonse↗
NASA NTRS1981

Use of MAGSAT anomaly data for crustal structure and mineral resources in the US midcontinent

While the preliminary magnetic anomaly map for the centra midcontinent is only in the hand-drawn stage, it agrees in broad aspects with the preliminary global MAGSAT map provided by NASA. Because of data evaluation and finer scale averaging, there are more detailed features which hold promise for eventual geological/crustal interpretation. Some current analysis is directed at examining whether a map data feature such as an elongated anomaly or trend, which seems parallel to satellite data tracks, is likely of crustal origin or is an artifact of the data set.

Carmichael, R. S.↗
NASA NTRS1993

A real-time navigation monitoring expert system for the Space Shuttle Mission Control Center

The ONAV (Onboard Navigation) Expert System has been developed as a real time console assistant for use by ONAV flight controllers in the Mission Control Center at the Johnson Space Center. This expert knowledge based system is used to monitor the Space Shuttle onboard navigation system, detect faults, and advise flight operations personnel. This application is the first knowledge-based system to use both telemetry and trajectory data from the Mission Operations Computer (MOC). To arrive at this stage, from a prototype to real world application, the ONAV project has had to deal with not only AI issues but operating environment issues. The AI issues included the maturity of AI languages and the debugging tools, verification, and availability, stability and size of the expert pool. The environmental issues included real time data acquisition, hardware suitability, and how to achieve acceptance by users and management.

Wang, Lui↗
NASA NTRS2017

NASA's Space Launch System Takes Shape

Major hardware and software for NASA's Space Launch System (SLS) began rolling off assembly lines in 2016, setting the stage for critical testing in 2017 and the launch of a major new capability for deep space human exploration. SLS continues to pursue a 2018 first launch of Exploration Mission 1 (EM-1). At NASA's Michoud Assembly Facility near New Orleans, LA, Boeing completed welding of structural test and flight liquid hydrogen tanks, and engine sections. Test stands for core stage structural tests at NASA's Marshall Space Flight Center, Huntsville, AL. neared completion. The B2 test stand at NASA's Stennis Space Center, MS, completed major structural renovation to support core stage green run testing in 2018. Orbital ATK successfully test fired its second qualification solid rocket motor in the Utah desert and began casting the motor segments for EM-1. Aerojet Rocketdyne completed its series of test firings to adapt the heritage RS-25 engine to SLS performance requirements. Production is under way on the first five new engine controllers. NASA also signed a contract with Aerojet Rocketdyne for propulsion of the RL10 engines for the Exploration Upper Stage. United Launch Alliance delivered the structural test article for the Interim Cryogenic Propulsion Stage to MSFC for tests and construction was under way on the flight stage. Flight software testing at MSFC, including power quality and command and data handling, was completed. Substantial progress is planned for 2017. Liquid oxygen tank production will be completed at Michoud. Structural testing at Marshall will get under way. RS-25 hotfire testing will verify the new engine controllers. Core stage horizontal integration will begin. The core stage pathfinder mockup will arrive at the B2 test stand for fit checks and tests. EUS will complete preliminary design review. This paper will discuss the technical and programmatic successes and challenges of 2016 and look ahead to plans for 2017.

Askins, Bruce↗
NASA NTRS2005

Testing the Hypothesis of Young Martian Volcanism: Studies of the Tharsis Volcanoes and Adjacent Lava Plains

We experienced much success in reaching our stated goals in our original MDAP proposal. Our work made substantial contributions towards an integrated understanding of the counting and calibration of crater data on Mars, and changing nature of the Martian surface influenced by craters, water, and wind, and their general relationship to Martian geothermal history. We accomplished this while being to responsive to the rapid changes in the field brought about by several key NASA missions that returned data during the life of the grant. Our integrated effort included three stages: The first major area of research (Crater Count Research) was conducted by Jennifer Grier (P.I.), Lazslo Keszthelyi (Collaborator), William Hartmann (Collaborator), with assistance from Dan Berman (Graduate student) and concerned the mapping and the collection of crater count data on various Martian terrains. The second major area of study (Absolute Age Calibration) was conducted by William Bottke (Co-I) at SWRI, and concerned constraining the nature of the Moon and Mars impactor populations to create better absolute age calibrations for counted areas. The third major area of study was the integration and leverage of this effort with ongoing related Mars crater work at PSI (Integrated and Continuing Studies - Older Volcanoes), headed by David Crown (PSI Scientist), assisted by Les Bleamaster (PSI Scientist) and Dan Berman (Graduate Student).

Grier, Jennifer A.↗
DOE OSTI2023

Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America

This is an hourly future weather dataset for energy modeling applications. The dataset is primarily based on the output of a regional climate model (RCM), i.e., the Weather Research and Forecasting (WRF) model version 3.3.1. The WRF simulations are driven by the output of a general circulation model (GCM), i.e., the Community Climate System Model version 4 (CCSM4). This dataset is in the EPW format, which can be read or translated by more than 25 building energy modeling programs (e.g., EnergyPlus, ESP-r, and IESVE), energy system modeling programs (e.g., System Advisor Model (SAM)), indoor air quality analysis programs (e.g., CONTAM), and hygrothermal analysis programs (e.g., WUFI). It contains 13 weather variables, which are the Dry-Bulb Temperature, Dew Point Temperature, Relative Humidity, Atmospheric Pressure, Horizontal Infrared Radiation Intensity from Sky, Global Horizontal Irradiation, Direct Normal Irradiation, Diffuse Horizontal Irradiation, Wind Speed, Wind Direction, Sky Cover, Albedo, and Liquid Precipitation Depth. The weather data is created for two emissions scenarios: RCP4.5 and RCP8.5 and spans two 10-year time slices in the future: 2045 - 2054 and 2085 - 2094. It offers a spatial resolution of 12 km by 12 km with extensive coverage across most of North America. Due to the enormous size of the entire dataset, in the first stage of its distribution, we provide 20 years of future weather data for the centroid of each Public Use Microdata Area (PUMA), excluding Hawaii. PUMAs are non-overlapping, statistical geographic areas that partition each state or equivalent entity into geographic areas containing no fewer than 100,000 people each. The 2,378 PUMAs as a whole cover the entirety of the U.S. The weather data can be utilized alongside the large-scale energy analysis tools, ResStock and ComStock, developed by National Renewable Energy Laboratory, whose smallest resolution is at the PUMA scale. The data for RCP4.5 is still being processed and will be published soon.

Array↗
NASA NTRS1977

Internal flow characteristics of a multistage compressor with inlet pressure distortion

The measured distribution of compressor interstage pressures and temperatures resulting from a 180 deg inlet-total-pressure distortion for a J85-13 turbojet engine is reported. Extensive inner stage instrumentation combined with stepwise rotation of the inlet distortion gave data of high circumferential resolution. The steady-state pressures and temperatures along with the amplitude, extent, and location of the distorted areas are given. Data for 80, 90, and 100 percent of rotor design speed are compared with clean (undistorted) inlet flow conditions to show pressure and temperature behavior within the compressor. Both overall and stagewise compressor performances vary only slightly when clean and distorted inlet conditions are compared. Total and static pressure distortions increase in amplitude in the first few stages of the compressor and then attenuate fairly uniformly to zero at the discharge. Total-temperature distortion induced by the pressure distortion reached a maximum amplitude by the first two stages and decayed only a little through the rest of the compressor. Distortion amplitude tended to peak in line with the screen edges, and, except for total and static pressure in the tip zone, there was little swirl in the axial direction.

Debogdan, C. E.↗
DOE OSTI2021

Developing Multi-Gene CRISPRa/I Programs to Accelerate DBTL Cycles in ABF Hosts Engineered for Chemical Production (CRADA 468)

Bacterial metabolism is comprised of large and complex gene networks that can produce valuable chemical products. Sophisticated organism engineering efforts are required to optimize production of high-value compounds from these networks. In principle, synthetic multi-gene transcriptional programs could be constructed to reengineer these networks for efficient industrial chemical production. In practice, however, our incomplete ability to understand and model the underlying networks, combined with our limited ability to predictably control the expression of multiple genes makes achieving this goal difficult. To overcome these challenges, we will combine new CRISPR-Cas multi-gene expression programs with computational modeling, machine learning, and multi-omics data to enhance the efficacy of design-build-test-learn (DBTL) cycles. For industrially promising microorganisms in early stages of development, creating technologies for rapidly engineering complex multi-gene programs could be transformative for accelerating data- and model-driven strain design. New CRISPR-Cas tools allow programmable gene activation (CRISPRa) or repression (CRISPRi) at multiple genes simultaneously, using the catalytically inactive Cas9 protein (dCas9) with guide RNAs that recognize DNA targets through predictable Watson-Crick base pairing. To enable accelerated DBTL cycles, we will combine these technologies with advanced Agile BioFoundry (ABF) capabilities for multi-omics data collection and machine learning. We will demonstrate the immediate applicability of these tools by rapidly improving the production of an industrial aromatic in multiple ABF organisms. We recently identified and optimized new transcriptional activators that can be linked to programmable CRISPR-Cas DNA binding domains to activate gene expression in E. coli. We can now use these CRISPRa tools as generalizable trans-acting regulators for combinatorial multi-gene expression tuning that can be easily transferred to new pathways and networks without additional genome engineering. We anticipate these tools will also transfer to new hosts. We have recently found that CRISPRa systems developed in E. coli can be readily ported to Pseudomonas putida, suggesting that multi-gene CRISPRa/i programs for diverse ABF organisms may be within reach.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2010

CFD Models of a Serpentine Inlet, Fan, and Nozzle

Several computational fluid dynamics (CFD) codes were used to analyze the Versatile Integrated Inlet Propulsion Aerodynamics Rig (VIIPAR) located at NASA Glenn Research Center. The rig consists of a serpentine inlet, a rake assembly, inlet guide vanes, a 12-in. diameter tip-turbine driven fan stage, exit rakes or probes, and an exhaust nozzle with a translating centerbody. The analyses were done to develop computational capabilities for modeling inlet/fan interaction and to help interpret experimental data. Three-dimensional Reynolds averaged Navier-Stokes (RANS) calculations of the fan stage were used to predict the operating line of the stage, the effects of leakage from the turbine stream, and the effects of inlet guide vane (IGV) setting angle. Coupled axisymmetric calculations of a bellmouth, fan, and nozzle were used to develop techniques for coupling codes together and to investigate possible effects of the nozzle on the fan. RANS calculations of the serpentine inlet were coupled to Euler calculations of the fan to investigate the complete inlet/fan system. Computed wall static pressures along the inlet centerline agreed reasonably well with experimental data but computed total pressures at the aerodynamic interface plane (AIP) showed significant differences from the data. Inlet distortion was shown to reduce the fan corrected flow and pressure ratio, and was not completely eliminated by passage through the fan

Chima, R. V.↗
NASA NTRS1995

A Unified Air-Sea Visualization System: Survey on Gridding Structures

The goal is to develop a Unified Air-Sea Visualization System (UASVS) to enable the rapid fusion of observational, archival, and model data for verification and analysis. To design and develop UASVS, modelers were polled to determine the gridding structures and visualization systems used, and their needs with respect to visual analysis. A basic UASVS requirement is to allow a modeler to explore multiple data sets within a single environment, or to interpolate multiple datasets onto one unified grid. From this survey, the UASVS should be able to visualize 3D scalar/vector fields; render isosurfaces; visualize arbitrary slices of the 3D data; visualize data defined on spectral element grids with the minimum number of interpolation stages; render contours; produce 3D vector plots and streamlines; provide unified visualization of satellite images, observations and model output overlays; display the visualization on a projection of the users choice; implement functions so the user can derive diagnostic values; animate the data to see the time-evolution; animate ocean and atmosphere at different rates; store the record of cursor movement, smooth the path, and animate a window around the moving path; repeatedly start and stop the visual time-stepping; generate VHS tape animations; work on a variety of workstations; and allow visualization across clusters of workstations and scalable high performance computer systems.

Anand, Harsh↗
NASA NTRS1993

Identification and interpretation of patterns in rocket engine data

A prototype software system was constructed to detect anomalous Space Shuttle Main Engine (SSME) behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. The major task of the research project is to analyze ground test data, to identify patterns associated with the anomalous engine behavior, and to develop a pattern identification and detection system on the basis of this analysis. A prototype expert system which was developed on both PC and Symbolics 3670 lisp machine for detecting anomalies in turbopump vibration data was checked with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine. The neural networks method was also applied to supplement the statistical method utilized in the prototype system to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. In most cases the anomalies detected by the expert system agree with those reported by NASA. On the neural networks approach, the results are given the successful detection rate higher than 95 percent to identify either normal or abnormal running condition based on the experimental data as well as numerical simulation.

Lo, C. F.↗