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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Doppler parameter estimation techniques for spaceborne SAR with applications to ocean current measurement

The problems of Doppler parameter estimation in the processing of spaceborne synthetic aperture radar (SAR) data are examined. The phase history of a target can be approximated by a linear FM signal with two parameters: the Doppler centroid and the Doppler frequency rate. Two methods to estimate these parameters automatically from the radar echo are presented. The accuracies of these methods were evaluated using the SEASAT SAR data. It is shown that the method for Doppler centroid determination may be applicable in the measurement of ocean current velocities. The concept behind this technique is presented and the accuracies of the measurements required are examined. Some preliminary results of testing this technique with the SEASAT data are presented.

Li, F.↗
NASA NTRS2019

Developing a soil inversion model framework for regional permafrost monitoring

Currently, the community lacks capabilities to assess and monitor landscape scale permafrost active layer dynamics over large extents. To address this need, we developed a concept of a remote sensing based Soil Inversion Model for regional Permafrost (SIM-P) monitoring. The current SIM-P framework includes a satellite-based soil process model and a soil dielectric model. We are also working on incorporating a radar scattering model for Arctic tundra into the SIM-P framework. A unified soil parameterization scheme was developed to harmonize key soil thermal, hydraulic and dielectric parameters in the soil process and radar models that can be used in the joint soil-radar inversion framework. The soil parameter retrievals of the SIM-P framework include soil organic content (SOC) and active layer thickness (ALT). Initial tests of SIM-P using in-situ soil permittivity observations showed reasonable accuracy in predicting site-level SOC and soil temperature profiles at an Alaska tundra site and ALT in Arctic Alaska. SIM-P will be further tested using airborne P- and L-band radar data collected during NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) to evaluate the sensitivity of longwave radar to active layer properties.

Miller, Charles E.↗
NASA NTRS1976

Modeling laser velocimeter signals as triply stochastic Poisson processes

Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

Mayo, W. T., Jr.↗
NASA NTRS1980

Development of processes for the production of solar grade silicon from halides and alkali metals

High temperature reactions of silicon halides with alkali metals for the production of solar grade silicon in volume at low cost were studied. Experiments were performed to evaluate product separation and collection processes, measure heat release parameters for scaling purposes, determine the effects of reactants and/or products on materials of reactor construction, and make preliminary engineering and economic analyses of a scaled-up process.

Dickson, C. R.↗
NASA NTRS1993

Method for defect free keyhole plasma arc welding

A plasma arc welding process for welding metal of increased thickness with one pass includes operating the plasma arc welding apparatus at a selected plasma gas flow rate, travel speed and arc current, to form a weld having a penetration ratio to weld height to weld width, and maintaining the penetration ratio at less than 0.74. Parameters for the plasma gas flow rate, travel speed and arc current are adjusted to a steady state condition during a start up period and maintained during the steady state condition to complete a weld. During a terminal stopping period, the travel speed is stopped and instantaneously replaced by filler wire which adds material to fill the keyhole that had been formed by the welding process. Parameters are subsequently adjusted during the stopping period to terminate the weld in a sound manner.

Harwig, Dennis D.↗
NASA NTRS1975

A note on the consistency of maximum likelihood estimates for finite families of stochastic processes

The note considers families of stochastic processes indexed by a finite number of alternative parameter values. For general classes of stochastic processes, it is shown that maximum-likelihood estimates converge almost surely to the correct parameter value. This is established by use of a submartingale property of the sequence of maximized-likelihood ratios together with a technique first employed by Wald (1949) in the case of independent identically distributed random variables.

Caines, P. E.↗
NASA NTRS1980

Storage peak gas-turbine power unit

A storage gas-turbine power plant using a two-cylinder compressor with intermediate cooling is studied. On the basis of measured characteristics of a .25 Mw compressor computer calculations of the parameters of the loading process of a constant capacity storage unit (05.3 million cu m) were carried out. The required compressor power as a function of time with and without final cooling was computed. Parameters of maximum loading and discharging of the storage unit were calculated, and it was found that for the complete loading of a fully unloaded storage unit, a capacity of 1 to 1.5 million cubic meters is required, depending on the final cooling.

Tsinkotski, B.↗
NASA NTRS1994

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

Litt, Jonathan↗
NASA NTRS1984

Geographic Distribution of Wetland Parameters: the Foundation of a Data Base

Few quantitative estimates exist concerning the large fluxes of various materials between wetlands and adjacent bodies of water and the atmosphere. Three areas research were identified which will aid in the quantitative assessment of wetland biogeochemical processes: (1) geographic distribution of wetland parameters, (2) the processes involved in wetland material fluxes, and (3) the extrapolation of local measurements of material fluxes and storage to large geographic areas.

Source record↗
NASA NTRS2001

Microstructure, Mechanical Properties, Hot-Die Forming, and Joining of 47XD Gamma TiAl Rolled Sheets

The microstructure and mechanical properties, along with the hot-die forming and joining of Ti-47Al-2Nb-2Mn-0.8 vol% TiB, sheets (known as 47XD), produced by a low-cost rolling process, were evaluated. A near-gamma microstructure was obtained in the as-rolled condition. The microstructures of heat-treated sheets ranged from a recrystallized equiaxed near-gamma microstructure at 1,200 to 1,310 C, to a duplex microstructure at 1,350 C, to a fully lamellar microstructure at 1,376 C. Tensile behavior was determined for unidirectionally rolled and cross-rolled sheets for room temperature (RT) to 816 C. Yield stress decreased gradually with increasing deformation temperature up to 704 C; above 704 C, it declined rapidly. Ultimate tensile strength exhibited a gradual decrease up to 537 C before peaking at 704 C, followed by a rapid decline at 816 C. The modulus showed a gradual decrease with temperature, reaching approximately 72% of the RT value at 816 C. Strain to failure increased slowly from RT to 537 C; between 537 C and 704 C it exhibited a phenomenal increase, suggesting that the ductile-brittle transition temperature was below 704 C. Fracture mode changed from transgranular fracture at low temperature, to a mixture of transgranular and intergranular fracture at intermediate temperature, to ductile fracture at 816 C, coupled with dynamic recrystallization at large strains. Creep rupture response was evaluated between 649 and 816 C over the stress range of 69 to 276 MPa. Deformation parameters for steady-state creep rate and time-to-rupture were similar: activation energies of approximately 350 kJ/mol and stress exponents of approximately 4.5. Hot-die forming of sheets into corrugations was done at elevated temperatures in vacuum. The process parameters to join sheets by diffusion bonding and brazing with TiCuNi 70 filler alloy were optimized for test coupons and successfully used to fabricate large truss-core and honeycomb structures. Nondestructive evaluation methods, e.g., ultrasonic C-scans and thermography along with metallography, were used to characterize bond quality. Microstructural evaluation during heat treatment, identification of phases at the braze/matrix interface, determination of shear strengths of brazed joints, and deformation mechanisms during tensile and creep processes will be discussed.

Das, G.↗
NASA NTRS1991

Basic research on design analysis methods for rotorcraft vibrations

The objective of the present work was to develop a method for identifying physically plausible finite element system models of airframe structures from test data. The assumed models were based on linear elastic behavior with general (nonproportional) damping. Physical plausibility of the identified system matrices was insured by restricting the identification process to designated physical parameters only and not simply to the elements of the system matrices themselves. For example, in a large finite element model the identified parameters might be restricted to the moduli for each of the different materials used in the structure. In the case of damping, a restricted set of damping values might be assigned to finite elements based on the material type and on the fabrication processes used. In this case, different damping values might be associated with riveted, bolted and bonded elements. The method itself is developed first, and several approaches are outlined for computing the identified parameter values. The method is applied first to a simple structure for which the 'measured' response is actually synthesized from an assumed model. Both stiffness and damping parameter values are accurately identified. The true test, however, is the application to a full-scale airframe structure. In this case, a NASTRAN model and actual measured modal parameters formed the basis for the identification of a restricted set of physically plausible stiffness and damping parameters.

Hanagud, S.↗
NASA NTRS1994

The development and operation of the international solar-terrestrial physics central data handling facility

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) International Solar-Terrestrial Physics (ISTP) Program is committed to the development of a comprehensive, multi-mission ground data system which will support a variety of national and international scientific missions in an effort to study the flow of energy from the sun through the Earth-space environment, known as the geospace. A major component of the ISTP ground data system is an ISTP-dedicated Central Data Handling Facility (CDHF). Acquisition, development, and operation of the ISTP CDHF were delegated by the ISTP Project Office within the Flight Projects Directorate to the Information Processing Division (IPD) within the Mission Operations and Data Systems Directorate (MO&DSD). The ISTP CDHF supports the receipt, storage, and electronic access of the full complement of ISTP Level-zero science data; serves as the linchpin for the centralized processing and long-term storage of all key parameters generated either by the ISTP CDHF itself or received from external, ISTP Program approved sources; and provides the required networking and 'science-friendly' interfaces for the ISTP investigators. Once connected to the ISTP CDHF, the online catalog of key parameters can be browsed from their remote processing facilities for the immediate electronic receipt of selected key parameters using the NASA Science Internet (NSI), managed by NASA's Ames Research Center. The purpose of this paper is twofold: (1) to describe how the ISTP CDHF was successfully implemented and operated to support initially the Japanese Geomagnetic Tail (GEOTAIL) mission and correlative science investigations, and (2) to describe how the ISTP CDHF has been enhanced to support ongoing as well as future ISTP missions. Emphasis will be placed on how various project management approaches were undertaken that proved to be highly effective in delivering an operational ISTP CDHF to the Project on schedule and within budget. Examples to be discussed include: the development of superior teams; the use of Defect Causal Analysis (DCA) concepts to improve the software development process in a pilot Total Quality Management (TQM) initiative; and the implementation of a robust architecture that will be able to support the anticipated growth in the ISTP Program science requirements with only incremental upgrades to the baseline system. Further examples include the use of automated data management software and the implementation of Government and/or industry standards, whenever possible, into the hardware and software development life-cycle. Finally, the paper will also report on several new technologies (for example, the installation of a Fiber Data Distribution Interface network) that were successfully employed.

Lehtonen, Kenneth↗
NASA NTRSDate not supplied

A Novel Machine Learning Method for Surface PM2.5 Estimations from Geostationary Satellites

Particulate matter (PM) with a diameter of less or equal to 2.5 μm, known as PM , affects human health as it penetrates the respiratory system. The Environmental Protection Agency (EPA) measures the atmospheric concentration of PM using air quality monitors stationed throughout the Continental United States (CONUS). Such measurements are points on a spatial domain and therefore, might not be representative of the air quality at nearby areas considering that the composition of the atmosphere is highly variable from place to place. Satellite based AOD permits a spatially uniform means of estimating PM and new geostationary satellites provide high temporal and spatial resolution estimation of AOD. However, the concentration of PM is non-linearly dependent on other atmospheric parameters that include relative humidity, temperature, and height of the planetary boundary layer. This information may be estimated at similar spatial and temporal resolutions as AOD from numerical modeling such as from the National Oceanic and Atmospheric Administration’s (NOAA) High Resolution Rapid Refresh (HRRR) model which resolves near real-time atmospheric conditions over the CONUS. The estimation of PM concentration is a multi-parametric problem that considers the effect of temporal dependencies among the different parameters. Deep learning approaches are appropriate for such complex estimation problems as they intrinsically capture relations among multiple non-linear parameters. This study compares deep-learning methods to traditional regression analysis to demonstrate the capabilities of these methods in predicting PM2.5 concentrations. Additionally, a novel ensemble learning approach is employed to identify scientific processes that could further improve the estimation of PM concentration. Utilizing Long Short-Term Memory (LSTM) neural networks, which are suitable for multivariate time series estimation problems as they are capable of learning long-term dependencies, individual models are created for each EPA station and trained on the aforementioned dataset collocated over each station. Individual station models are merged if the model's performance is improved by reducing the root mean squared error (RMSE) metric. This ensemble training method ultimately reduces the RMSE value. Evaluation of these results provide insights into physical processes and related observable parameters that may contribute to PM concentrations. Identified parameters evaluated to be statistically different between the merged and unmerged models are expected to improve overall performance. These new parameters are then utilized for reevaluation of the deep learning methods with an extreme gradient boosting model with an RMSE of 5.5 providing the best results.

George Priftis↗
NASA NTRS1975

Instrumentation requirements for aircraft parameter identification with application to the helicopter

The extent to which instrumentation errors cause degradation in the knowledge of stability and control derivatives identified for flight tests was studied along with the resultant degradation of the flight system performance base on these derivatives. The error in measurement and data processing systems used for parameter identification, error analysis techniques, and the effects of instrumentation, errors on the accuracy of parameter estimates are discussed. The analysis programs were used to study instrumentation error effects on the accuracy of the identified stability and control derivatives of the CH-46 helicopter.

Sorensen, J. A.↗
NASA NTRS1974

Space processing of chalcogenide glasses

Manufacture of chalcogenide glasses in space will eliminate many of the causes of optical non-homogeneity and contamination that are inherent in earth-bound manufacture. A program is outlined to demonstrate the feasibility of various techniques and processes that will be utilized to manufacture chalcogenide glasses in space. Amorphous character, purity, and homogeneity parameters are being investigated at various stages of the glass forming process. These parameters in merit index form will serve to provide guidelines for the design of the actual melting experiment in space, and for the optimization of the exact chalcogenide composition to be included in the space experiments.

Larsen, D. C.↗