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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Large modal survey testing using the Ibrahim time domain /ITD/ identification technique

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

Ibrahim, S. R.↗
NASA NTRS1985

Large Modal Survey Testing Using the Ibrahim Time Domain Identification Technique

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

Ibrahim, S. R.↗
NASA NTRS2018

Generating Exploration Mission-3 Trajectories to a 9:2 NRHO using Machine Learning

The purpose of this thesis is to design a machine learning algorithm platform that provides expanded knowledge of mission availability through a launch season by improving trajectory resolution and introducing launch mission forecasting. The specific scenario addressed in this paper is one in which data is provided for four deterministic translational maneuvers through a mission to a Near Rectilinear Halo Orbit (NRHO) with a 9:2 synodic frequency. Current launch availability knowledge under NASA's Orion Orbit Performance Team is established by altering optimization variables associated to given reference launch epochs. This current method can bean abstract task and relies on an orbit analyst to structure a mission based on an established mission design methodology associated to the performance of Orion and NASA's Space Launch System. Introducing a machine learning algorithm trained to construct mission scenarios within the feasible range of known trajectories reduces the required interaction of the orbit analyst by removing the needed step of optimizing the orbit to fit an expected translational response required of the spacecraft. In this study, k-Nearest Neighbor and Bayesian Linear Regression successfully predicted classical orbital elements for the launch windows observed. However both algorithms had limitations due to their approaches to model fitting. Training machine learning algorithms off of classical orbital elements introduced a repetitive approach to reconstructing mission segments for different arrival opportunities through the launch window and can prove to be a viable method of launch window scan generation for future missions.

Guzman, Esteban↗
NASA NTRS1998

High Performance, Robust Control of Flexible Space Structures: MSFC Center Director's Discretionary Fund

Many spacecraft systems have ambitious objectives that place stringent requirements on control systems. Achievable performance is often limited because of difficulty of obtaining accurate models for flexible space structures. To achieve sufficiently high performance to accomplish mission objectives may require the ability to refine the control design model based on closed-loop test data and tune the controller based on the refined model. A control system design procedure is developed based on mixed H2/H(infinity) optimization to synthesize a set of controllers explicitly trading between nominal performance and robust stability. A homotopy algorithm is presented which generates a trajectory of gains that may be implemented to determine maximum achievable performance for a given model error bound. Examples show that a better balance between robustness and performance is obtained using the mixed H2/H(infinity) design method than either H2 or mu-synthesis control design. A second contribution is a new procedure for closed-loop system identification which refines parameters of a control design model in a canonical realization. Examples demonstrate convergence of the parameter estimation and improved performance realized by using the refined model for controller redesign. These developments result in an effective mechanism for achieving high-performance control of flexible space structures.

Whorton, M. S.↗
NASA NTRS1989

Investigations into a new algorithm for calculating H infinity optimal controllers

A new algorithm for calculating H (sup infinity) optimal controllers is investigated. The algorithm is significantly simpler than existing approaches and yields much simpler controllers. The design equations are first presented. Special system transformations required to apply the algorithm are then presented. The use of the algorithm with sampled-data systems is outlined in detail. Several constraints on the characteristics of the problem formulation are required for the application of the design equations. The consequences of these constraints are investigated by applying the algorithm to a simplified design for a subsystem of a large space structure ground test facility. The investigation of these constraints is continued by application of the design equations and constraints to an extremely simple tracking problem. The result of these investigations is the development of a frequency dependent weighting strategy that allows realistic control problems to be cast in a form compatible with the new algorithm. Further work is indicated in the area of developing strategies for choosing frequency-dependent weights to achieve specific design goals. The use of the freedom in problem formulation to achieve robustness/performance tradeoffs should also be investigated. It is not clear that the algorithm always leads to simpler controllers. The more restrictive formulation may dictate that frequency-dependent weighting adds to the controller order disproportionately. This effect must also be investigated.

Irwin, R. Dennis↗
NASA NTRS1991

Transonic adaptive flutter suppression using approximate unsteady time domain aerodynamics

A digital adaptive controller is applied to the active flutter suppression problem of a wing under time varying flight conditions in subsonic and transonic flow. Linear quadratic controller gain at each time step is obtained using an iterative Riccati solver. The digital adaptive optimal controller is robust with respect to the unknown external loads. Flutter and divergence instabilities are simultaneously suppressed using a trailing-edge control surface and displacement sensing. A new transonic unsteady aerodynamic approximation methodology is developed which enables one to carry out the rapid calculation required for transonic aeroservoelastic applications. This approximation is based on a combination of unsteady subsonic aerodynamics combined with a transonic correction procedure. Aeroservoelastic transient time response is obtained using Roger's approximation, state transition matrices and an iterative time marching algorithm. The aeroservoelastic system in the time domain is modeled using a deterministic ARMA model together with a parameter estimator. Transonic flutter boundaries of a wing structure are computed, in the time domain, using an estimated aeroelastic system matrix and are in good agreement with experimental data for the low transonic Mach number range.

Pak, Chan-Gi↗
NASA NTRS1995

Investigation of air transportation technology at Ohio University: 1993-1994

The Joint University Program (JUP) offers students, faculty, and staff of the Avionics Engineering Center the opportunity to conduct basic research relating to the safety and efficiency of the National Airspace System. During the 1993-1994 year research was continued in a variety of GPS-related technologies and also in a hybrid data uplink system. (1) Processing techniques developed for the GPS attitude determination have been applied to centimeter-level kinematic GPS aircraft positioning for flight reference systems and aircraft autoland and taxiing operations. This resulted in the first real-time kinematic GPS autoland. (2) The fault detection and isolation (FDI) algorithm developed under the Joint University Program has been fully adopted by RTCA Special Committee 159 as the baseline algorithm for sole-means navigation of GPS integrated with GLONASS, LORAN-C, or baro-altimeter. (3) A Satellite Coverage Research Analysis Model (SCRAM) has been developed which provides outage areas, outage dynamics, and availability information for satellite-based navigation systems. RTCA Special Committee 159 has adopted this model for use in their work. (4) A basic receiver structure has been simulated and tested for use with the hybrid data uplink. This uplink utilizes the phase of an existing AM carrier to transmit digital data, thus both amplitude and phase modulation are applied, resulting in a hybrid carrier. The receiver simulation is directly applicable to real-time implementation as a result of the development platform.

Lilley, Robert W.↗
NASA NTRS1985

Characterization of coherent structures in a turbulent mixing layer by digital image analysis

Digital image analysis has been applied to a shadowgraph motion picture of a helium nitrogen mixing layer in order to characterize the coherent vortex structures in the flow. Both the primary spanwise coherent vortices and secondary streamwise vortices are considered. Pattern recognition algorithms were designed to take advantage of the more pronounced features of the vortices and of their temporal coherence to isolate them and to measure their characteristics. The resulting data base permits a deterministic description of the evolution of primary and seconary vortices.

Bernal, L. P.↗
NASA NTRS1993

Experimental evaluation of certification trails using abstract data type validation

Certification trails are a recently introduced and promising approach to fault-detection and fault-tolerance. Recent experimental work reveals many cases in which a certification-trail approach allows for significantly faster program execution time than a basic time-redundancy approach. Algorithms for answer-validation of abstract data types allow a certification trail approach to be used for a wide variety of problems. An attempt to assess the performance of algorithms utilizing certification trails on abstract data types is reported. Specifically, this method was applied to the following problems: heapsort, Hullman tree, shortest path, and skyline. Previous results used certification trails specific to a particular problem and implementation. The approach allows certification trails to be localized to 'data structure modules,' making the use of this technique transparent to the user of such modules.

Wilson, Dwight S.↗
NASA NTRS1993

Calculation of AGARD Wing 445.6 Flutter Using Navier-Stokes Aerodynamics

The flutter characteristics of the first AGARD standard aeroelastic configuration for dynamic response, Wing 445.6, are studied using an unsteady Navier-Stokes algorithm in order to investigate a previously noted discrepancy between Euler flutter characteristics and the experimental data. The algorithm, which is a three-dimensional, implicit, upwind Euler/Navier-Stokes code (CFL3D Version 2.1), was previously modified for the time-marching, aeroelastic analysis of wings using the unsteady Euler equations. These modifications include the incorporation of a deforming mesh algorithm and the addition of the structural equations of motion for their simultaneous time integration with the governing flow equations. In this paper, the aeroelastic method is extended and evaluated for applications that use the Navier- Stokes aerodynamics. The paper presents a brief description of the aeroelastic method and presents unsteady calculations which verify this method for Navier-Stokes calculations. A linear stability analysis and a time-marching aeroelastic analysis are used to determine the flutter characteristics of the isolated 45 deg. swept-back wing. Effects of fluid viscosity, structural damping, and number of modes in the structural model are investigated. For the linear stability analysis, the unsteady generalized aerodynamic forces of the wing are computed for a range of reduced frequencies using the pulse transfer-function approach. The flutter characteristics of the wing are determined using these unsteady generalized aerodynamic forces in a traditional V-g analysis. This stability analysis is used to determine the flutter characteristics of the wing at free-stream Mach numbers of 0.96 and 1.141 using the generalized aerodynamic forces generated by solving the Euler equations and the Navier-Stokes equations. Time-marching aeroelastic calculations are performed at a free-stream Mach number of 1.141 using the Euler and Navier-Stokes equations to compare with the linear V-g flutter analysis method. The V-g analysis, which is used in conjunction with the time-marching analysis, indicates that the fluid viscosity has a significant effect on the supersonic flutter boundary for this wing while the structural damping and number of modes in the structural model have a lesser effect.

Lee-Rausch, Elizabeth M.↗
NASA NTRS2011

Mapping Canopy Damage from Understory Fires in Amazon Forests Using Annual Time Series of Landsat and MODIS Data

Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in separating burning from other types of forest damage in satellite data. We developed a new approach, the Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was applied to time series of Landsat (1997-2004) and MODIS (2000-2005) data covering one Landsat scene (path/row 226/068) in southern Amazonia and the results were compared to field observations, image-derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was essential for detection of burn scars less than 50 ha, yet these small burns contributed only 12% of all burned forest detected during 1997-2002. MODIS data were suitable for mapping medium (50-500 ha) and large (greater than 500 ha) burn scars that accounted for the majority of all fire-damaged forest in this study. Therefore, moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508 square kilometers) were an order of magnitude higher than during the 1997-1998 El Nino event (124 square kilometers and 39 square kilometers, respectively), suggesting a different link between climate and understory fires than previously reported for other Amazon regions. The results in this study illustrate the potential to address critical questions concerning climate and fire risk in Amazon forests by applying the BDR algorithm over larger areas and longer image time series.

Morton, Douglas C.↗
NASA NTRS1980

Adaptive/learning control of large space structures - System identification techniques

Techniques developed for the control of aircraft under changing operating conditions are used to develop a learning control system structure for a multi-configuration, flexible space vehicle. A configuration identification subsystem that is to be used with a learning algorithm and a memory and control process subsystem is developed. Adaptive gain adjustments can be achieved by this learning approach without prestoring of large blocks of parameter data and without dither signal inputs which will be suppressed during operations for which they are not compatible. The Space Shuttle Solar Electric Propulsion (SEP) experiment is used as a sample problem for the testing of adaptive/learning control system algorithms.

Thau, F. E.↗
NASA NTRS1999

Recent Improvements in Estimating Convective and Stratiform Rainfall in Amazonia

In this paper we present results from the application of a satellite infrared (IR) technique for estimating rainfall over northern South America. Our main objectives are to examine the diurnal variability of rainfall and to investigate the relative contributions from the convective and stratiform components. We apply the technique of Anagnostou et al (1999). In simple functional form, the estimated rain area A(sub rain) may be expressed as: A(sub rain) = f(A(sub mode),T(sub mode)), where T(sub mode) is the mode temperature of a cloud defined by 253 K, and A(sub mode) is the area encompassed by T(sub mode). The technique was trained by a regression between coincident microwave estimates from the Goddard Profiling (GPROF) algorithm (Kummerow et al, 1996) applied to SSM/I data and GOES IR (11 microns) observations. The apportionment of the rainfall into convective and stratiform components is based on the microwave technique described by Anagnostou and Kummerow (1997). The convective area from this technique was regressed against an IR structure parameter (the Convective Index) defined by Anagnostou et al (1999). Finally, rainrates are assigned to the Am.de proportional to (253-temperature), with different rates for the convective and stratiform

Negri, Andrew J.↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗
NASA NTRS2012

Software Modules for the Proximity-1 Space Link Interleaved Time Synchronization (PITS) Protocol

The Proximity-1 Space Link Interleaved Time Synchronization (PITS) protocol provides time distribution and synchronization services for space systems. A software prototype implementation of the PITS algorithm has been developed that also provides the test harness to evaluate the key functionalities of PITS with simulated data source and sink. PITS integrates time synchronization functionality into the link layer of the CCSDS Proximity-1 Space Link Protocol. The software prototype implements the network packet format, data structures, and transmit- and receive-timestamp function for a time server and a client. The software also simulates the transmit and receive-time stamp exchanges via UDP (User Datagram Protocol) socket between a time server and a time client, and produces relative time offsets and delay estimates.

Woo, Simon S.↗
NASA NTRS2020

Mapping tree canopy cover and canopy height with L-band SAR using LiDAR data and Random Forests

Light detection and ranging (LiDAR) data can provide direct measurements of vegetation structures but are limited by the sparse spatial coverage. Polarimetric synthetic aperture radar (SAR) can perform large-scale high-resolution mapping without weather constraints but the information about vegetation and ground subsurface are mixed in the backscatter data. In this paper, we adopted the Random Forests algorithm to train an upscaling function using tree canopy cover (TCC) and canopy height model (CHM) derived from Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) data. The regression model is then applied to the L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign to map the TCC and CHM over the Delta Junction area in interior Alaska.

Moghaddam, Mahta↗
NASA NTRS2000

Use of Maps, GTE and UARS-MLS Data in Understanding Tropospheric Processes Critical to Model Development

Two of the major problems in using meteorological models to explain observed tropospheric trace constituent distributions and thereby to understand the global budgets of the tracers are to properly define the vertical layered structure in the free atmosphere, and to understand the contribution of advection processes in generating horizontal inhomogeneities at all scales. We proposed to tackle these problems through the examination of an extensive collection of trace constituent data from research and commercial aircraft in conjunction with meteorological data from the European Center for Medium-Range Weather Forecasts. The physical mechanisms responsible for these advection and layering processes were explored and their implications for theories and models assessed. In addition, we calculated examples of how thin layers (not currently resolved by models) affect the radiative heating/cooling rates. We developed an improved algorithm for trace constituent layer detection, and used it to analyze over 100,000 km of ozone and humidity vertical profiles collected by instruments piggybacked on commercial aircraft. We have also performed radiative heating/cooling calculations on some observed layer structures, and have demonstrated that the sharp edges on humidity layers can have strong local effects of self-stabilization (dry layers) or destabilization (wet layers), and have suggested that clear-air turbulence might result from the latter case through convective instability. We also systematically analyzed the mesoscale variabilities, not only of the trace constituents, but also of the aircraft-measured dynamical variables.

Newell, Reginald E.↗