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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 1,639 records · Page 91

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NASA NTRS1997

Independent Analysis of the Space Station Node Modal Test Data

With complex structures, comparison of independently derived sets of experimental modal parameters is an excellent way to increase confidence in the results. This paper presents modal identification results using the Eigensystem Realization Algorithm (ERA) on frequency response functions from the modal test of the Space Station Resource Node. The Resource Node is the first U.S.-built structure for the International Space Station. The modal test was conducted by the NASA Marshall Space Flight Center (MSFC) in January 1997 for the Boeing Company, who designed and built the Node. The ERA-calculated parameters are compared with independent results obtained by the MSFC test team using commercial software. There was excellent correlation of mode shapes between the two sets of results for the first 21 vibration modes of the structure up to 35 Hz. From 35 to 50 Hz, about 60 percent of 25 additional modes had excellent correlation. Natural frequencies and damping factors of most modes agreed within 0.1 Hz and 0.2 percent, respectively.

Pappa, Richard S.↗

NASA NTRS2004

A View from Above Without Leaving the Ground

In order to deliver accurate geospatial data and imagery to the remote sensing community, NASA is constantly developing new image-processing algorithms while refining existing ones for technical improvement. For 8 years, the NASA Regional Applications Center at Florida International University has served as a test bed for implementing and validating many of these algorithms, helping the Space Program to fulfill its strategic and educational goals in the area of remote sensing. The algorithms in return have helped the NASA Regional Applications Center develop comprehensive semantic database systems for data management, as well as new tools for disseminating geospatial information via the Internet.

Source record↗

NASA NTRS2003

Flight Test Results for a Turbulence Detection Radar

This viewgraph presentation provides an overview of flight tests conducted on an aircraft turbulence detection radar system. Topics covered include: flight operations summary, radar data collection, baseline algorithm methodology, radar hazard tables and proposed alert criteria. Flight tests results are presented and summarized. Data analysis from these flight tests are also included.

Schaffner, Phil↗

NASA NTRS1982

Interconnect fatigue design for terrestrial photovoltaic modules

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Mon, G. R.↗

DOE OSTI2022

Joint Inversion of Body Wave Arrival Times, Surface Wave Dispersion Data and Receiver Functions: Method and Application to South China

In this work, we have developed a new joint inversion method that incorporates body wave arrival times, surface wave dispersion and receiver functions to simultaneously update earthquake locations and constrain three-dimensional P-wave (Vp) and S-wave velocity (Vs) models. Due to complementary sensitivities of the three types of data, the proposed joint inversion algorithm can reduce the intrinsic non-uniqueness of inversions using fewer types of data and better determine smooth velocity variations and velocity discontinuities. Synthetic tests demonstrate the advantages of this new joint inversion algorithm in resolving velocity structures, especially in constraining velocity gradients across the Moho interface. We have applied the proposed joint inversion algorithm to image the lithosphere velocity structure of south China. The inverted Vp and Vs models fit body wave arrival times, surface wave dispersion and receiver functions well. We further analyzed the distribution of Vs gradients across the Moho interface in detail, which helps us better understand tectonics in south China.

58 GEOSCIENCES↗

NASA NTRS1989

Adaptive antenna arrays for satellite communication

The feasibility of using adaptive antenna arrays to provide interference protection in satellite communications was studied. The feedback loops as well as the sample matric inversion (SMI) algorithm for weight control were studied. Appropriate modifications in the two were made to achieve the required interference suppression. An experimental system was built to test the modified feedback loops and the modified SMI algorithm. The performance of the experimental system was evaluated using bench generated signals and signals received from TVRO geosynchronous satellites. A summary of results is given. Some suggestions for future work are also presented.

Gupta, Inder J.↗

NASA NTRS1997

Design Protocols and Analytical Strategies that Incorporate Structural Reliability Models

Ceramic matrix composites (CMC) and intermetallic materials (e.g., single crystal nickel aluminide) are high performance materials that exhibit attractive mechanical, thermal, and chemical properties. These materials are critically important in advancing certain performance aspects of gas turbine engines. From an aerospace engineers perspective the new generation of ceramic composites and intermetallics offers a significant potential for raising the thrust/weight ratio and reducing NO(sub x) emissions of gas turbine engines. These aspects have increased interest in utilizing these materials in the hot sections of turbine engines. However, as these materials evolve and their performance characteristics improve a persistent need exists for state-of-the-art analytical methods that predict the response of components fabricated from CMC and intermetallic material systems. This need provided the motivation for the technology developed under this research effort. Continuous ceramic fiber composites exhibit an increase in work of fracture, which allows for 'graceful' rather than catastrophic failure. When loaded in the fiber direction these composites retain substantial strength capacity beyond the initiation of transverse matrix cracking despite the fact that neither of its constituents would exhibit such behavior if tested alone. As additional load is applied beyond first matrix cracking, the matrix tends to break in a series of cracks bridged by the ceramic fibers. Any additional load is born increasingly by the fibers until the ultimate strength of the composite is reached. Thus modeling efforts supported under this research effort have focused on predicting this sort of behavior. For single crystal intermetallics the issues that motivated the technology development involved questions relating to material behavior and component design. Thus the research effort supported by this grant had to determine the statistical nature and source of fracture in a high strength, NiAl single crystal turbine blade material; map a simplistic future strength envelope of the material; develop a statistically based reliability computer algorithm; verify the reliability model and computer algorithm-, and model stator vanes for rig tests. Thus establishing design protocols that enable the engineer to analyze and predict the mechanical behavior of ceramic composites and intermetallics would mitigate the prototype (trial and error) approach currently used by the engineering community. The primary objective of the research effort supported by this short term grant is the continued creation of enabling technologies for the macro-analysis of components fabricated from ceramic composites and intermetallic material systems. The creation of enabling technologies aids in shortening the product development cycle of components fabricated from the new high technology materials.

Duffy, Stephen F.↗

NASA NTRS1997

Design Protocols and Analytical Strategies that Incorporate Structural Reliability Models

Ceramic matrix composites (CMC) and intermetallic materials (e.g., single crystal nickel aluminide) are high performance materials that exhibit attractive mechanical, thermal and chemical properties. These materials are critically important in advancing certain performance aspects of gas turbine engines. From an aerospace engineer's perspective the new generation of ceramic composites and intermetallics offers a significant potential for raising the thrust/weight ratio and reducing NO(x) emissions of gas turbine engines. These aspects have increased interest in utilizing these materials in the hot sections of turbine engines. However, as these materials evolve and their performance characteristics improve a persistent need exists for state-of-the-art analytical methods that predict the response of components fabricated from CMC and intermetallic material systems. This need provided the motivation for the technology developed under this research effort. Continuous ceramic fiber composites exhibit an increase in work of fracture, which allows for "graceful" rather than catastrophic failure. When loaded in the fiber direction, these composites retain substantial strength capacity beyond the initiation of transverse matrix cracking despite the fact that neither of its constituents would exhibit such behavior if tested alone. As additional load is applied beyond first matrix cracking, the matrix tends to break in a series of cracks bridged by the ceramic fibers. Any additional load is born increasingly by the fibers until the ultimate strength of the composite is reached. Thus modeling efforts supported under this research effort have focused on predicting this sort of behavior. For single crystal intermetallics the issues that motivated the technology development involved questions relating to material behavior and component design. Thus the research effort supported by this grant had to determine the statistical nature and source of fracture in a high strength, NiAl single crystal turbine blade material; map a simplistic failure strength envelope of the material; develop a statistically based reliability computer algorithm, verify the reliability model and computer algorithm, and model stator vanes for rig tests. Thus establishing design protocols that enable the engineer to analyze and predict the mechanical behavior of ceramic composites and intermetallics would mitigate the prototype (trial and error) approach currently used by the engineering community. The primary objective of the research effort supported by this short term grant is the continued creation of enabling technologies for the macroanalysis of components fabricated from ceramic composites and intermetallic material systems. The creation of enabling technologies aids in shortening the product development cycle of components fabricated from the new high technology materials.

Duffy, Stephen F.↗

NASA NTRS2014

Adaptive Augmenting Control Flight Characterization Experiment on an F/A-18

The NASA Marshall Space Flight Center (MSFC) Flight Mechanics and Analysis Division developed an Adaptive Augmenting Control (AAC) algorithm for launch vehicles that improves robustness and performance by adapting an otherwise welltuned classical control algorithm to unexpected environments or variations in vehicle dynamics. This AAC algorithm is currently part of the baseline design for the SLS Flight Control System (FCS), but prior to this series of research flights it was the only component of the autopilot design that had not been flight tested. The Space Launch System (SLS) flight software prototype, including the adaptive component, was recently tested on a piloted aircraft at Dryden Flight Research Center (DFRC) which has the capability to achieve a high level of dynamic similarity to a launch vehicle. Scenarios for the flight test campaign were designed specifically to evaluate the AAC algorithm to ensure that it is able to achieve the expected performance improvements with no adverse impacts in nominal or nearnominal scenarios. Having completed the recent series of flight characterization experiments on DFRC's F/A-18, the AAC algorithm's capability, robustness, and reproducibility, have been successfully demonstrated. Thus, the entire SLS control architecture has been successfully flight tested in a relevant environment. This has increased NASA's confidence that the autopilot design is ready to fly on the SLS Block I vehicle and will exceed the performance of previous architectures.

VanZwieten, Tannen S.↗

DOE OSTI2020

Integrating Predictions for Improving Defect Classification Accuracy in NDT-based Assessment of Concrete - 20229

There is an increasing need to create predictive models for defect classification in concrete using the output of non-destructive testing (NDT) techniques. Recent advancement of machine-learning algorithms has offered several techniques for developing classification models for different types of data sets. However, the performance of these algorithms is very uncertain, mainly when applied to small and noisy datasets. For example, when human access is limited (e.g., nuclear facility), robot-based NDT is preferred. But compared to manual tests with humans present on site, the data sets are small, and more noise can exist. Therefore, it is imperative to develop new approaches to ensure a consistently high classification accuracy for inadequate data sets. This study explores the classification performance on NDT dataset using classifiers from different machine-learning algorithms, namely k-Nearest Neighbor (kNN), Decision Tree, Naive Bayes, Logistic Regression, and Support Vector Machine (SVM). The authors further integrated the predictions from these classifiers using proposed methods. The integration strategy combines the output of the classifiers based on two different measures, accuracy, and performance (ACC and PERF), using equations such as sum, average, and square-root-of-sums-of-squares (SRSS). Our results reveal varying classification accuracies across individual classifiers with different misclassifications across the test data set. The integration strategy provided significant improvement in the classification accuracy compared to the individual classifiers. Furthermore, the results indicate minimal variation across the integration methods as compared to the variation across the individual classifiers. To conclude, prediction integration offers a unique approach for combining the output of multiple classifiers to create redundancies with the potential of achieving high classification performance and improved reliability in predictive models for defect detection in concrete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1989

A survey of upwind methods for flows with equilibrium and non-equilibrium chemistry and thermodynamics

Several versions of flux-vector split and flux-difference split algorithms were compared with regard to general applicability and complexity. Test computations were performed using curve-fit equilibrium air chemistry for an M = 5 high-temperature inviscid flow over a wedge, and an M = 24.5 inviscid flow over a blunt cylinder for test computations; for these cases, little difference in accuracy was found among the versions of the same flux-split algorithm. For flows with nonequilibrium chemistry, the effects of the thermodynamic model on the development of flux-vector split and flux-difference split algorithms were investigated using an equilibrium model, a general nonequilibrium model, and a simplified model based on vibrational relaxation. Several numerical examples are presented, including nonequilibrium air chemistry in a high-temperature shock tube and nonequilibrium hydrogen-air chemistry in a supersonic diffuser.

Grossman, B.↗

NASA NTRS1994

An algorithm for the Italian atomic time scale

During the past twenty years, the time scale at the IEN has been realized by a commercial cesium clock, selected from an ensemble of five, whose rate has been continuously steered towards UTC to maintain a long term agreement within 3 x 10(exp -13). A time scale algorithm, suitable for a small clock ensemble and capable of improving the medium and long term stability of the IEN time scale, has been recently designed taking care of reducing the effects of the seasonal variations and the sudden frequency anomalies of the single cesium clocks. The new time scale, TA(IEN), is obtained as a weighted average of the clock ensemble computed once a day from the time comparisons between the local reference UTC(IEN) and the single clocks. It is foreseen to include in the computation also ten cesium clocks maintained in other Italian laboratories to further improve its reliability and its long term stability. To implement this algorithm, a personal computer program in Quick Basic has been prepared and it has been tested at the IEN time and frequency laboratory. Results obtained using this algorithm on the real clocks data relative to a period of about two years are presented.

Cordara, F.↗

DOE OSTI2021

Heuristic Dispatch Based on Price Signals for Behind-the-Meter PV-Battery Systems in the System Advisor Model

The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM’s existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2021

Heuristic Dispatch Based on Price Signals for Behind-the-Meter PV-Battery Systems in the System Advisor Model: Preprint

41 EE - Solar Energy Technologies Office (EE-4S)↗

NASA NTRS1982

Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping.

Molusis, J. A.↗

DOE OSTI2021

Computational Framework for Machine-Learning-Enabled 13 C Fluxomics

13 C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13 C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical 13 C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

13C metabolic flux analysis↗

NASA NTRS2001

Satellite Retrieval of Atmospheric Water Budget over Gulf of Mexico- Caribbean Basin: Seasonal Variability

This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of hourly-sampled monthly datasets derived from the GOES-8 5 Imager and the DMSP 7-channel passive microwave radiometer (SSM/I) have been acquired for the Gulf of Mexico-Caribbean Sea basin. Whereas the methodology is being tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the SSM/I passive microwave signals in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, we have sought to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is partly validated by first cross-checking all the algorithm components through multiple-algorithm retrieval intercomparisons. More fundamental validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithm to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin. Total columnar atmospheric water budget results will be presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98, October-98, and January-1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons will also be presented in the context of sensitivity testing to help understand the intrinsic uncertainties in the water budget terms.

Smith, Eric A.↗

NASA NTRS1984

An objective method for forecasting tropical cyclone motion using Nimbus and NOAA-2 infrared measurements

A statistical method for predicting tropical cyclone positions 12, 24, 48 and 72 hours after initial observation is described. Satellite measurements were at the 11.0 micron channel and at equivalent blackbody temperatures which give representations of the structure of the cyclones, as well as the circulation features surrounding them. In all, 197 individual measurements for blackbody temperature were made. Algorithms prepared from a single satellite image included 14 climatological and persistence type variables, and are based on eigenvector preprocessing and a series of independent screening tests. The independent tests showed that the average error made by the algorithms from the single satellite observation were comparable to the 48 hr Joint Typhoon Warning Center (JTWC) forecast and were about 10 percent better for 72 hr forecasts. Forecasts using only climatological persistence variables were found to be 20 percent worse than JTWC for 24 hr forecasts and 10 percent worse for 48 and 72 hr forecasts. When both satellite and nonsatellite variables were included, it was found that the method was comparable to JTWC for the 24 and 48 hr forecasts and about 25 percent better for the 72 hr forecasts.

Hunter, H. E.↗