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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Evaluation of passive microwave precipitation algorithms in wintertime midlatitude situations

The second intercomparison project of the Global Precipitation Climatology Project (GPCP) examined the estimation of midlatitude, cool-season precipitation. As part of that effort, the authors report here on the results of two microwave techniques, the Goddard scattering algorithm and the physical retrieval algorithm of Kummerow. Results from the estimation of instantaneous rain rate for five overpasses of the Special Sensor Microwave/Imager (SSM/I) are presented in a case study mode to illustrate both the strong and weak points of each technique. These five cases represent a sampling of the various types of precipitating systems observed. Results for the complete set of 20 swaths chosen by the United Kingdom Meteorological Office (UKMO) are then categorized by scatterplots and statistics of instantaneous radar versus microwave-estimated rain rate, rain no-rain contingency tables, and scatterplots of areal coverage of rainfall. Neither algorithm produced a good statistical correlation with the radar data, yet in general, both did well at determining rainy areas. Two reasons are suggested for the low correlation coefficients between both algorithms and the radar data. Time differences between the SSM/I overpass and the radar observations can occasionally account for some of the differences. The primary reason for the low correlations, however, appears to be the predominance of very light rain in the area of interest during the winter. Both algorithms are in good spatial agreement with the radar when the radar data are restricted to rates above 1 mm/h. When all radar rain rates are included, the radar areal coverage increases by as much as a factor of 10 in some cases. Because the Kummerow algorithm does not handle such low rain rates over land very well, and because the Goddard scattering algorithm uses 1 mm/h as the minimum reliably detectable rain rate, regimes that contain large areas of very light rain present inherent difficulties for these retrieval methods. Therefore, the proliferation of low rain rates observed during the experiment is the main contributor to low correlation coefficients and high root-mean-square differences. Mididentification of cold surface (e.g., snow cover) as precipitation was also a problem in several instances.

Negri, Andrew J.↗
NASA NTRS2004

Processing Spacecraft Data Without Confusion

Producing multiple versions of the same data product for the same time frame with the same remotely sensed inputs can be a recipe for disaster. Yet, amidst the commotion of satellite launch and early operations (LEO), such data processing is needed. After LEO, the situation gets worse. Processing newly arriving data ("forward processing") is augmented with reprocessing and algorithm development, comparison, evaluation, and testing -- often happening all at the same time. The problem can be analyzed in three main parts -- maintaining multiple versions of algorithms and data so that end-product users are not overwhelmed,allocating computer resources efficiently, and simplifying production operations so that va st amounts of data can be processed with minimal staff and fewer errors. OMIDAPS provides a framework for execution of algorithms that transform lower level data acquired by OMI on NASA's Aura satellite into higher level science data products. In contrast to traditional science data processing systems, we address all parts of the problem with an innovative approach allowing multiple data processing to run within a single physical system. The data products, imports, exports, and execution planning are all segregated into distinct "ArchiveSets." This paper describes reasons for multiple concurrent productions on a typical satellite data processing project using OMI as an example. It describes the virtual data processing system concept and its advantages over separate physical processing strings. It explores the specific implementation of the virtual systems within OMIDAPS and discusses some of the implications of our approach and describes how virtual processing is used to accomplish the overall mission of OMI data processing.

Tilmes, Curt↗
NASA NTRSDate not supplied

Analysis of Probe Surveys Conducted in the 10-MW TP3 Arc-Jet Facility 15-Inch Nozzle Flow

Computational simulations and analysis of flow characterization tests in a high enthalpy arc-jet facility at NASA Ames Research Center are reported. These tests were conducted in the 10-MW TP3 facility 15-inch conical nozzle, and pitot pressure and heat flux probes are used to survey test flow downstream of the nozzle exit. Two 1.59-cm (0.625 in) diameter hemisphere probes were used: one with a stagnation-point pressure port, the other with a Gardon heat flux gage. Calibration data were also obtained using 10.16-cm iso-q and 20.32-cm flat-faced slug calorimeters. Experimental surveys of arc-jet test flow with pitot pressure and heat flux probes were obtained at eight arc-heater conditions, covering wide ranges in arc current (316–1756 A) and mass flow rate (32–500 g/s, without any cold-gas injection at the arc-heater plenum) and providing assessment of the flow uniformity in the facility. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle and test box, including the models tested. These simulations take into account non-uniform total enthalpy and mass flux profiles at the nozzle inlet as well as the expansion waves emanating from the nozzle exit and their effects on the model flowfields. Comparisons of computations with the experimental measurements are presented, showing reasonably good agreement. The probe survey data and accompanying analysis show that the test flow in the TP3 15-inch nozzle is highly non-uniform at most conditions, and the extent of flow non-uniformity depends on arc current and mass flow rate.

Arc-jets↗
NASA NTRS2001

Modeling and Test Data Analysis of a Tank Rapid Chill and Fill System for the Advanced Shuttle Upper Stage (ASUS) Concept

The Advanced Shuttle Upper Stage (ASUS) concept addresses safety concerns associated .with cryogenic stages by launching empty, and filling on ascent. The ASUS employs a rapid chill and fill concept. A spray bar is used to completely chill the tank before fill, allowing the vent valve to be closed during the fill process. The first tests of this concept, using a flight size (not flight weight) tank. were conducted at Marshall Space Flight Center (MSFC) during the summer of 2000. The objectives of the testing were to: 1) demonstrate that a flight size tank could be filled in roughly 5 minutes to accommodate the shuttle ascent window, and 2) demonstrate a no-vent fill of the tank. A total of 12 tests were conducted. Models of the test facility fill and vent systems, as well as the tank, were constructed. The objective of achieving tank fill in 5 minutes was met during the test series. However, liquid began to accumulate in the tank before it was chilled. Since the tank was not chilled until the end of each test, vent valve closure during fill was not possible. Even though the chill and fill process did not occur as expected, reasonable model correlation with the test data was achieved.

Flachbart, Robin↗
NASA NTRS2000

Evaluation of Non-Ozone-Depleting-Chemical Cleaning Methods for Space Mechanisms Using a Vacuum Spiral Orbit Rolling Contact Tribometer

Because CFC 113, an ozone depleting chemical (ODC), can no longer be produced, alternative bearing cleaning methods must be studied. The objective of this work was to study the effect of the new cleaning methods on lubricant lifetime using a vacuum bearing simulator (spiral orbit rolling contact tribometer). Four alternative cleaning methods were studied: ultra-violet (UV) ozone, aqueous levigated alumina slurry (ALAS), super critical fluid (SCF) CO2 and aqueous Brulin 815GD. Baseline tests were done using CFC 113. Test conditions were the following: a vacuum of at least 1.3 x 10(exp -6) Pa, 440C steel components, a rotational speed of 10 RPM, a lubricant charge of between 60-75 micrograms, a perfluoropolyalkylether lubricant (Z-25), and a load of 200N (44.6 lbs., a mean Hertzian stress of 1.5 GPa). Normalized lubricant lifetime was determined by dividing the total number of ball orbits by the amount of lubricant. The failure condition was a friction coefficient of 0.38. Post-test XPS analysis was also performed, showing slight variations in post-cleaning surface chemistry. Statistical analysis of the resultant data was conducted and it was determined that the data sets were most directly comparable when subjected to a natural log transformation. The natural log life (NL-Life) data for each cleaning method were reasonably normally (statistically) distributed and yielded standard deviations that were not significantly different among the five cleaning methods investigated. This made comparison of their NL-Life means very straightforward using a Bonferroni multiple comparison of means procedure. This procedure showed that the ALAS, UV-ozone and CFC 113 methods were not statistically significantly different from one another with respect to mean NL-Life. It also found that the SCF CO2 method yielded a significantly higher mean NL-Life than the mean NL-Lives of the ALAS, UV-ozone and CFC 113 methods. It also determined that the aqueous Brulin 815GD method yielded a mean NL-Life that was statistically significantly higher than the mean NL-Lives of each of the other four methods. Baseline tests using CFC 113 cleaned parts yielded a mean NL-Life 3.62 orbits/micro-g. ALAS and UV-ozone yielded similar mean NL-Life (3.31 orbits/mg and 3.33 orbits/micro-g, respectively). SCF CO2, gave a mean NL-Life of 4.08 orbits/mg and aqueous Brulin 8l5GD data yielded the longest mean NL-Life (4.66 orbits/micro-g).

Jansen, Mark J.↗
DOE OSTI2026

Reliability Assessment of Cooling Fans for PV Inverters: Testing, Modeling, and Case Studies

The reliability of photovoltaic (PV) inverters is critical for long-term solar system performance, with cooling fan failures frequently leading to costly downtime. While much research exists on general cooling fan reliability, little attention has been given to fans operating within PV inverters and their unique environmental challenges. Here, this article proposes a comprehensive methodology to address this gap. First, a failure mode and effects analysis is performed on fans to identify the key failure mechanisms in PV applications, their corresponding stressors, and the models necessary for lifetime prediction. Second, an accelerated life test is designed and conducted to collect valuable experimental data for PV inverter fans in a reasonable amount of time. Third, a mathematical conversion of dynamic mission profiles into effective constant stress levels is derived. Fourth, case studies are given, showcasing lifetime estimates that account for geographic variations in mission profile data. The results demonstrate that this integrated approach leads to an accurate reliability assessment for PV inverter cooling fans.

accelerated life testing (ALT)↗
DOE OSTI2020

Benchmark Modeling and Simulation of the FFTF LOFWOS Test #13 Using SAM

The Fast Flux Test Facility (FFTF) was a 400 MW thermal powered, oxide-fueled, liquid sodium cooled test reactor, built to assist development and testing of advanced fuels and materials for fast breeder reactors. In July 1986, a series of unprotected Loss of Flow Without Scram (LOFWOS) transients were performed in FFTF as part of the Passive Safety Testing (PST) program. The LOFWOS Test #13, which was initiated at 50% power and 100% flow with the pump pony motors left off, has been chosen as a benchmark case by IAEA to support collaborative efforts within international partnerships on the validation of simulation tools and models in the area of sodium fast reactor passive safety in an IAEA Coordinated Research Project (CRP), launched in October 2018. The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR safety analysis. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. To participate the IAEA CRP and enhance the SAM validation base for advanced reactor transient safety analysis, benchmark simulations of the FFTF LOFWOS Test #13 are performed using the SAM code. In this first phase of the validation effort, the thermal-hydraulic behavior of the reactor system is the focus and the reactor kinetics is not considered in the SAM FFTF model. Instead, the results of Argonne’s neutronics calculations are directly used, including the power shape of the active core region and the power history during the transient. The simulation results of FFTF at steady state agreed well with the measured data from the test. During the transient, reasonably good agreement were also obtained. Future work to improve the model will focus on introducing the reactivity predictions into the model, as well as better understanding or resolving the current discrepancies with the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1982

KC-135 wing and winglet flight pressure distributions, loads, and wing deflection results with some wind tunnel comparisons

A full-scale winglet flight test on a KC-135 airplane with an upper winglet was conducted. Data were taken at Mach numbers from 0.70 to 0.82 at altitudes from 34,000 feet to 39,000 feet at stabilized flight conditions for wing/winglet configurations of basic wing tip, 15/-4 deg, 15/-2 deg, and 0/-4 deg winglet cant/incidence. An analysis of selected pressure distribution and data showed that with the basic wing tip, the flight and wind tunnel wing pressure distribution data showed good agreement. With winglets installed, the effects on the wing pressure distribution were mainly near the tip. Also, the flight and wind tunnel winglet pressure distributions had some significant differences primarily due to the oilcanning in flight. However, in general, the agreement was good. For the winglet cant and incidence configuration presented, the incidence had the largest effect on the winglet pressure distributions. The incremental flight wing deflection data showed that the semispan wind tunnel model did a reasonable job of simulating the aeroelastic effects at the wing tip. The flight loads data showed good agreement with predictions at the design point and also substantiated the predicted structural penalty (load increase) of the 15 deg cant/-2 deg incidence winglet configuration.

Montoya, L. C.↗
NASA NTRS1991

Engine Data Interpretation System (EDIS), phase 2

A prototype of an expert system was developed which applies qualitative constraint-based reasoning to the task of post-test analysis of data resulting from a rocket engine firing. Data anomalies are detected and corresponding faults are diagnosed. Engine behavior is reconstructed using measured data and knowledge about engine behavior. Knowledge about common faults guides but does not restrict the search for the best explanation in terms of hypothesized faults. The system contains domain knowledge about the behavior of common rocket engine components and was configured for use with the Space Shuttle Main Engine (SSME). A graphical user interface allows an expert user to intimately interact with the system during diagnosis. The system was applied to data taken during actual SSME tests where data anomalies were observed.

Cost, Thomas L.↗
NASA NTRS2004

A Model for Shear Layer Effects on Engine Noise Radiation

Prediction of aircraft engine noise is an important aspect of addressing the issues of community noise and cabin noise control. The development of physics based methodologies for performing such predictions has been a focus of Computational Aeroacoustics (CAA). A recent example of code development in this area is the ducted fan noise propagation and radiation code CDUCT-LaRC. Included within the code is a duct radiation model that is based on the solution of FfowcsWilliams-Hawkings (FW-H) equation with a penetrable data surface. Testing of this equation for many acoustic problems has shown it to provide generally better results than the Kirchhoff formula for moving surfaces. Currently, the data surface is taken to be the inlet or exhaust plane for inlet or aft-fan cases, respectively. While this provides reasonable results in many situations, these choices of data surface location lead to a few limitations. For example, the shear layer between the bypass ow and external stream can refract the sound waves radiated to the far field. Radiation results can be improved by including this effect, as well as the rejection of the sound in the bypass region from the solid surface external to the bypass duct surrounding the core ow. This work describes the implementation, and possible approximation, of a shear layer boundary condition within CDUCT-LaRC. An example application also illustrates the improvements that this extension offers for predicting noise radiation from complex inlet and bypass duct geometries, thereby providing a means to evaluate external treatments in the vicinity of the bypass duct exhaust plane.

Nark, Douglas M.↗
NASA NTRS1994

Galactic cosmic ray modulation and interplanetary medium perturbations due to a long-living active region during October 1989

During October 1989, three very energetic flares were ejected by the same active region at longitudes 9 deg E, 32 deg W, and 57 deg W, respectively. The shape of the galactic cosmic ray variations suggests the presence of large magnetic cloud structures (Nagashima et al., 1990) following the shock-associated perturbations. In spite of long data gaps the interplanetary observations at Interplanetary Monitoring Platform (IMP) 8 (near the Earth) and International Cometary Explorer (ICE)(approximately 1 AU, approximately 65 deg W) confirm this possibility for the event related to the 9 deg E flare; the principal axes analysis shows that the interplanetary magnetic field variations at both spacecraft locations are mainly confined on a meridian plane. This result suggests that the western longitudinal extension of this cloud is indeed very large (greater than or equal to 5 deg). The nonnegligible depression in the cosmic ray intensity observed inside the possible cloud related to the 57 deg W flare indicates that also the eastern extension could be very wide. The analysis of neutron monitor data shows clearly the cosmic ray trapping effect of magnetic clouds; this mechanism seems to be responsible for the enhanced diurnal effect often observed during the recovery phase of Forbush decreases. We give an interpretation for the anisotropic cosmic ray peak occurring in the third event, and, related to that, we suggest that the Forbush decrease modulated region at the Earth's orbit could be somewhat wider than the magnetic cloud, as already anticipated by Nagashima et al. (1990). By this analysis, based mainly on cosmic ray data, we show that it is possible to do reasonable inferences on the large-scale structure of flare-related interplanetary perturbations when interplanetary medium data are not completely present.

Bavassano, B.↗
NASA NTRS2013

Data Mining for Anomaly Detection

The Vehicle Integrated Prognostics Reasoner (VIPR) program describes methods for enhanced diagnostics as well as a prognostic extension to current state of art Aircraft Diagnostic and Maintenance System (ADMS). VIPR introduced a new anomaly detection function for discovering previously undetected and undocumented situations, where there are clear deviations from nominal behavior. Once a baseline (nominal model of operations) is established, the detection and analysis is split between on-aircraft outlier generation and off-aircraft expert analysis to characterize and classify events that may not have been anticipated by individual system providers. Offline expert analysis is supported by data curation and data mining algorithms that can be applied in the contexts of supervised learning methods and unsupervised learning. In this report, we discuss efficient methods to implement the Kolmogorov complexity measure using compression algorithms, and run a systematic empirical analysis to determine the best compression measure. Our experiments established that the combination of the DZIP compression algorithm and CiDM distance measure provides the best results for capturing relevant properties of time series data encountered in aircraft operations. This combination was used as the basis for developing an unsupervised learning algorithm to define "nominal" flight segments using historical flight segments.

Biswas, Gautam↗
NASA NTRS1980

Chemical kinetic models for combustion of hydrocarbons and formation of nitric oxide

The formation of nitrogen oxides NOx during combustion of methane, propane, and a jet fuel, JP-4, was investigated in a jet stirred combustor. The results of the experiments were interpreted using reaction models in which the nitric oxide (NO) forming reactions were coupled to the appropriate hydrocarbon combustion reaction mechanisms. Comparison between the experimental data and the model predictions reveals that the CH + N2 reaction process has a significant effect on NO formation especially in stoichiometric and fuel rich mixtures. Reaction models were assembled that predicted nitric oxide levels that were in reasonable agreement with the jet stirred combustor data and with data obtained from a high pressure (5.9 atm (0.6 MPa)), prevaporized, premixed, flame tube type combustor. The results also suggested that the behavior of hydrocarbon mixtures, like JP-4, may not be significantly different from that of pure hydrocarbons. Application of the propane combustion and nitric oxide formation model to the analysis of NOx emission data reported for various aircraft gas turbines showed the contribution of the various nitric oxide forming processes to the total NOx formed.

Jachimowski, C. J.↗
NASA NTRS2011

Fast Image Texture Classification Using Decision Trees

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

Thompson, David R.↗
DOE OSTI2025

Data as a Key Resource in Catalysis: A Community Account

The deployment of artificial intelligence (AI) is transforming the scientific fields central to interdisciplinary catalysis research. By enabling more effective use of data, AI (including simpler machine learning and data science tools) holds great promise for accelerating discoveries. However, progress has so far been modest, largely due to the lack of standardized, machine-readable, and openly shared catalysis data. This perspective, accounting for community insights emerging at conferences, analyses the underlying reasons for these challenges and proposes solutions to a future whereFAIR data management becomes an integral part of research in catalysis. In the short-term, we deem that mandatory FAIR data depositing prior to scientific publications along with consensualized top-down guidelines on data sharing powered by ease-to-use tools can make the necessary step change happen to catalyse data as key resource in our community.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Concurrent Precipitation of Nb(C,N) and Metastable M 23 C 6 in Alloy 347H at 700°C and 750°C: Computer Simulations and Comparison to Experiment

Here, we present our results for the concurrent precipitation of metastable M 23 C 6 , Nb(C,N) secondary precipitates, and the Nb(C,N) primary crystals in 347H austenitic stainless steel. For precipitation modeling, we have accounted for the elastic contribution to interfacial energy, and for the Fe-spin-polarization for NbC/Fe and M 23 C 6 /Fe interfacial energy values: for NbC/Fe ~ 0.63 J/m 2 . For M 23 C 6 precipitates, an error function was used to describe the interfacial energy growth with particle size. In precipitation simulations, the average size of the primary Nb(C,N) particles remained ~ 1 μm at 700°C and ~ 0.3 μm at 750°C. The M 23 C 6 precipitates at 750°C dissolved after 120 h (our simulations) compared to 300 h (experiments). The Nb(C,N)/Fe interfacial energy was not affected by the nitrogen additions. With these modifications, reasonable agreement with the available experimental data was obtained, which allows using them in the development of the 2nd-phase particle-informed creep theory.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Optical Response of Soda-Lime Glass Shocked to 14 GPa

To investigate the potential use of soda-lime glass (SLG) as an optical window in shock wave experiments, laser interferometry (VISAR) was used to determine the window correction and the refractive index in SLG samples subjected to plane shock wave compression. Symmetric plate impact experiments were conducted at peak stresses varying between 4 and 14 GPa and laser interferometry ($λ_0$ = 532$\textit {nm}$ wavelength) measurements were used to monitor the particle velocity histories at the impact surface. The higher stress experiments displayed a constant state prior to stress unloading. In contrast, the lower stress experiments (4.3 and 7.8 GPa) displayed an initial constant state followed by weakly time-dependent response prior to stress unloading. Because the actual particle velocities were independently known from the projectile velocity measurements, the window correction factor and the refractive index changes were determined over the stress range examined. Above 7.5 GPa, our window correction and refractive index results show significant differences with previously published data for the same material. Potential reasons for these differences are indicated.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Causality guided machine learning model on wetland CH 4 emissions across global wetlands

Wetland CH 4 emissions are among the most uncertain components of the global CH 4 budget. The complex nature of wetland CH 4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH 4 emissions. In this study, we used the flux measurements of CH 4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH 4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH 4 emissions in all studied wetland types. Ecosystem respiration (CO 2 ) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH 4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH 4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH 4 emissions within earth system land models.

54 ENVIRONMENTAL SCIENCES↗