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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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NASA NTRS2003

The Distribution and Abundance of Bird Species: Towards a Satellite, Data Driven Avian Energetics and Species Richness Model

This paper addresses the fundamental question of why birds occur where and when they do, i.e., what are the causative factors that determine the spatio-temporal distributions, abundance, or richness of bird species? In this paper we outline the first steps toward building a satellite, data-driven model of avian energetics and species richness based on individual bird physiology, morphology, and interaction with the spatio-temporal habitat. To evaluate our model, we will use the North American Breeding Bird Survey and Christmas Bird Count data for species richness, wintering and breeding range. Long term and current satellite data series include AVHRR, Landsat, and MODIS.

Smith, James A.↗
NASA NTRS2007

A Support Database System for Integrated System Health Management (ISHM)

The development, deployment, operation and maintenance of Integrated Systems Health Management (ISHM) applications require the storage and processing of tremendous amounts of low-level data. This data must be shared in a secure and cost-effective manner between developers, and processed within several heterogeneous architectures. Modern database technology allows this data to be organized efficiently, while ensuring the integrity and security of the data. The extensibility and interoperability of the current database technologies also allows for the creation of an associated support database system. A support database system provides additional capabilities by building applications on top of the database structure. These applications can then be used to support the various technologies in an ISHM architecture. This presentation and paper propose a detailed structure and application description for a support database system, called the Health Assessment Database System (HADS). The HADS provides a shared context for organizing and distributing data as well as a definition of the applications that provide the required data-driven support to ISHM. This approach provides another powerful tool for ISHM developers, while also enabling novel functionality. This functionality includes: automated firmware updating and deployment, algorithm development assistance and electronic datasheet generation. The architecture for the HADS has been developed as part of the ISHM toolset at Stennis Space Center for rocket engine testing. A detailed implementation has begun for the Methane Thruster Testbed Project (MTTP) in order to assist in developing health assessment and anomaly detection algorithms for ISHM. The structure of this implementation is shown in Figure 1. The database structure consists of three primary components: the system hierarchy model, the historical data archive and the firmware codebase. The system hierarchy model replicates the physical relationships between system elements to provide the logical context for the database. The historical data archive provides a common repository for sensor data that can be shared between developers and applications. The firmware codebase is used by the developer to organize the intelligent element firmware into atomic units which can be assembled into complete firmware for specific elements.

FROM↗
NASA NTRS2007

Fundamental Technology Development for Gas-Turbine Engine Health Management

Integrated vehicle health management technologies promise to dramatically improve the safety of commercial aircraft by reducing system and component failures as causal and contributing factors in aircraft accidents. To realize this promise, fundamental technology development is needed to produce reliable health management components. These components include diagnostic and prognostic algorithms, physics-based and data-driven lifing and failure models, sensors, and a sensor infrastructure including wireless communications, power scavenging, and electronics. In addition, system assessment methods are needed to effectively prioritize development efforts. Development work is needed throughout the vehicle, but particular challenges are presented by the hot, rotating environment of the propulsion system. This presentation describes current work in the field of health management technologies for propulsion systems for commercial aviation.

Mercer, Carolyn R.↗
NASA NTRS2007

EOS Operations Systems: EDOS Implemented Changes to Reduce Operations Costs

The authors describe in this paper the progress achieved to-date with the reengineering of the Earth Observing System (EOS) Data and Operations System (EDOS), the experience gained in the process and the ensuing reduction of ground systems operations costs. The reengineering effort included a major methodology change, applying to an existing schedule driven system, a data-driven system approach.

Cordier, Guy R.↗
NASA NTRS2003

Real-time spatio-temporal coherence estimation for autonomous mode identification and invariance tracking

A general method of anomaly detection from time-correlated sensor data is disclosed. Multiple time-correlated signals are received. Their cross-signal behavior is compared against a fixed library of invariants. The library is constructed during a training process, which is itself data-driven using the same time-correlated signals. The method is applicable to a broad class of problems and is designed to respond to any departure from normal operation, including faults or events that lie outside the training envelope.

James, Mark L.↗
NASA NTRS2008

Statistical Estimation of Orbital Debris Populations with a Spectrum of Object Size

Orbital debris is a real concern for the safe operations of satellites. In general, the hazard of debris impact is a function of the size and spatial distributions of the debris populations. To describe and characterize the debris environment as reliably as possible, the current NASA Orbital Debris Engineering Model (ORDEM2000) is being upgraded to a new version based on new and better quality data. The data-driven ORDEM model covers a wide range of object sizes from 10 microns to greater than 1 meter. This paper reviews the statistical process for the estimation of the debris populations in the new ORDEM upgrade, and discusses the representation of large-size (greater than or equal to 1 m and greater than or equal to 10 cm) populations by SSN catalog objects and the validation of the statistical approach. Also, it presents results for the populations with sizes of greater than or equal to 3.3 cm, greater than or equal to 1 cm, greater than or equal to 100 micrometers, and greater than or equal to 10 micrometers. The orbital debris populations used in the new version of ORDEM are inferred from data based upon appropriate reference (or benchmark) populations instead of the binning of the multi-dimensional orbital-element space. This paper describes all of the major steps used in the population-inference procedure for each size-range. Detailed discussions on data analysis, parameter definition, the correlation between parameters and data, and uncertainty assessment are included.

Xu, Y. -l↗
NASA NTRS2008

The Heliophysics Data Environment Today

Driven by the nature of the research questions now most critical to further progress in heliophysics science, data-driven research has evolved from a model once centered on individual instrument Principal investigator groups and a circle of immediate collaborators into a more inclusive and open environment where data gathered ay great public cost must then be findable and useable throughout the broad national and international research community. In this paper and as an introduction to this special session, we will draw a picture of existing and evolving resources throughout the heliophyscs community, the capabilities and data now available to end users, and the relationships and complementarity of different elements in the environment today. We will cite the relative roles of mission and instrument data centers and resident archives, multi-mission data centers, and the growing importance of virtual discipline observatories and cross-cutting services including the evolution of a common data dictionary. We will briefly summarize our view of the most important challenges still faced by users and providers, and our vision in ow the efforts today can evolve into a more and more enabling data framework for the global research community to tap the widest range of existing missions and their data to address a full range of critical science questions from the scale of microphysics to the heliospheric system as a whole.

Fung, Shing F.↗
NASA NTRS2008

Web Monitoring of EOS Front-End Ground Operations, Science Downlinks and Level 0 Processing

This paper addresses the efforts undertaken and the technology deployed to aggregate and distribute the metadata characterizing the real-time operations associated with NASA Earth Observing Systems (EOS) high-rate front-end systems and the science data collected at multiple ground stations and forwarded to the Goddard Space Flight Center for level 0 processing. Station operators, mission project management personnel, spacecraft flight operations personnel and data end-users for various EOS missions can retrieve the information at any time from any location having access to the internet. The users are distributed and the EOS systems are distributed but the centralized metadata accessed via an external web server provide an effective global and detailed view of the enterprise-wide events as they are happening. The data-driven architecture and the implementation of applied middleware technology, open source database, open source monitoring tools, and external web server converge nicely to fulfill the various needs of the enterprise. The timeliness and content of the information provided are key to making timely and correct decisions which reduce project risk and enhance overall customer satisfaction. The authors discuss security measures employed to limit access of data to authorized users only.

Cordier, Guy R.↗
NASA NTRS2008

Development of Solar Wind Model Driven by Empirical Heat Flux and Pressure Terms

We are developing a time stationary self-consistent 2D MHD model of the solar corona and solar wind as suggested by Sittler et al. (2003). Sittler & Guhathakurta (1999) developed a semiempirical steady state model (SG model) of the solar wind in a multipole 3-streamer structure, with the model constrained by Skylab observations. Guhathakurta et al. (2006) presented a more recent version of their initial work. Sittler et al. (2003) modified the SG model by investigating time dependent MHD, ad hoc heating term with heat conduction and empirical heating solutions. Next step of development of 2D MHD models was performed by Sittler & Ofman (2006). They derived effective temperature and effective heat flux from the data-driven SG model and fit smooth analytical functions to be used in MHD calculations. Improvements of the Sittler & Ofman (2006) results now show a convergence of the 3-streamer topology into a single equatorial streamer at altitudes > 2 R(sub S). This is a new result and shows we are now able to reproduce observations of an equatorially confined streamer belt. In order to allow our solutions to be applied to more general applications, we extend that model by using magnetogram data and PFSS model as a boundary condition. Initial results were presented by Selwa et al. (2008). We choose solar minimum magnetogram data since during solar maximum the boundary conditions are more complex and the coronal magnetic field may not be described correctly by PFSS model. As the first step we studied the simplest 2D MHD case with variable heat conduction, and with empirical heat input combined with empirical momentum addition for the fast solar wind. We use realistic magnetic field data based on NSO/GONG data, and plan to extend the study to 3D. This study represents the first attempt of fully self-consistent realistic model based on real data and including semi-empirical heat flux and semi-empirical effective pressure terms.

Sittler, Edward C., Jr.↗
NASA NTRS2009

Solder Joint Health Monitoring Testbed

A method of monitoring the health of selected solder joints, called SJ-BIST, has been developed by Ridgetop Group Inc. under a Small Business Innovative Research (SBIR) contract. The primary goal of this research program is to test and validate this method in a flight environment using realistically seeded faults in selected solder joints. An additional objective is to gather environmental data for future development of physics-based and data-driven prognostics algorithms. A test board is being designed using a Xilinx FPGA. These boards will be tested both in flight and on the ground using a shaker table and an altitude chamber.

Delaney, Michael M.↗
NASA NTRS2008

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that can be taken to extract relevant features from these high-dimensional data streams. The first set of approaches relies on extracting features using a physics-based paradigm where the underlying physical mechanism that generates the spectra is used to infer the most important features in the data stream. We focus on a complementary methodology that uses a data-driven technique that is informed by the underlying physics but also has the ability to adapt to unmodeled system attributes and dynamics. We discuss the following four algorithms: Spectral Decomposition Algorithm (SDA), Non-Negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and Principal Components Analysis (PCA) and compare their performance on a spectral emulator which we use to generate artificial data with known statistical properties. This spectral emulator mimics the real-world phenomena arising from the plume of the space shuttle main engine and can be used to validate the results that arise from various spectral decomposition algorithms and is very useful for situations where real-world systems have very low probabilities of fault or failure. Our results indicate that methods like SDA and NMF provide a straightforward way of incorporating prior physical knowledge while NMF with a tuning mechanism can give superior performance on some tests. We demonstrate these algorithms to detect potential system-health issues on data from a spectral emulator with tunable health parameters.

Srivastava, Askok N.↗
NASA NTRS2007

C Namelist Facility

C Namelist Facility (CNL) is a package of software that supports the development of data-driven programs that utilize relatively free-form input files (e.g., text files) to control complex operations. The only comparable prior namelist facility is built into Fortran and does not support arrays or records. Newer computing languages, including C and Pascal, do not include built-in namelist facilities. A namelist facility enables a program to utilize relatively free-form input files that contain assignment statements that give values to variables. Variables to which values are not assigned in input files remain unchanged; therefore, it becomes possible to have default values set by static or dynamic initialization of values prior to namelist input and updating of values is optional. Because it is not required to include values of variables in namelist input files, new parameters can be added to evolving programs without rendering old namelist input files obsolete -- provided that the new parameters have useful default values. It should be possible to execute CNL in any operating system that supports the ANSI C programming language. It has been executed in several variants of Unix and in VxWorks.

Bon, Bruce↗
NASA NTRS2007

Simple, Script-Based Science Processing Archive

The Simple, Scalable, Script-based Science Processing (S4P) Archive (S4PA) is a disk-based archival system for remote sensing data. It is based on the data-driven framework of S4P and is used for data transfer, data preprocessing, metadata generation, data archive, and data distribution. New data are automatically detected by the system. S4P provides services such as data access control, data subscription, metadata publication, data replication, and data recovery. It comprises scripts that control the data flow. The system detects the availability of data on an FTP (file transfer protocol) server, initiates data transfer, preprocesses data if necessary, and archives it on readily available disk drives with FTP and HTTP (Hypertext Transfer Protocol) access, allowing instantaneous data access. There are options for plug-ins for data preprocessing before storage. Publication of metadata to external applications such as the Earth Observing System Clearinghouse (ECHO) is also supported. S4PA includes a graphical user interface for monitoring the system operation and a tool for deploying the system. To ensure reliability, S4P continuously checks stored data for integrity, Further reliability is provided by tape backups of disks made once a disk partition is full and closed. The system is designed for low maintenance, requiring minimal operator oversight.

Lynnes, Christopher↗
NASA NTRS2009

Towards a Framework for Evaluating and Comparing Diagnosis Algorithms

Diagnostic inference involves the detection of anomalous system behavior and the identification of its cause, possibly down to a failed unit or to a parameter of a failed unit. Traditional approaches to solving this problem include expert/rule-based, model-based, and data-driven methods. Each approach (and various techniques within each approach) use different representations of the knowledge required to perform the diagnosis. The sensor data is expected to be combined with these internal representations to produce the diagnosis result. In spite of the availability of various diagnosis technologies, there have been only minimal efforts to develop a standardized software framework to run, evaluate, and compare different diagnosis technologies on the same system. This paper presents a framework that defines a standardized representation of the system knowledge, the sensor data, and the form of the diagnosis results and provides a run-time architecture that can execute diagnosis algorithms, send sensor data to the algorithms at appropriate time steps from a variety of sources (including the actual physical system), and collect resulting diagnoses. We also define a set of metrics that can be used to evaluate and compare the performance of the algorithms, and provide software to calculate the metrics.

Kurtoglu, Tolga↗
NASA NTRS2009

Benchmarking Diagnostic Algorithms on an Electrical Power System Testbed

Diagnostic algorithms (DAs) are key to enabling automated health management. These algorithms are designed to detect and isolate anomalies of either a component or the whole system based on observations received from sensors. In recent years a wide range of algorithms, both model-based and data-driven, have been developed to increase autonomy and improve system reliability and affordability. However, the lack of support to perform systematic benchmarking of these algorithms continues to create barriers for effective development and deployment of diagnostic technologies. In this paper, we present our efforts to benchmark a set of DAs on a common platform using a framework that was developed to evaluate and compare various performance metrics for diagnostic technologies. The diagnosed system is an electrical power system, namely the Advanced Diagnostics and Prognostics Testbed (ADAPT) developed and located at the NASA Ames Research Center. The paper presents the fundamentals of the benchmarking framework, the ADAPT system, description of faults and data sets, the metrics used for evaluation, and an in-depth analysis of benchmarking results obtained from testing ten diagnostic algorithms on the ADAPT electrical power system testbed.

Kurtoglu, Tolga↗
NASA NTRS2005

NASA Tech Briefs, March 2005

Topics covered include: Scheme for Entering Binary Data Into a Quantum Computer; Encryption for Remote Control via Internet or Intranet; Coupled Receiver/Decoders for Low-Rate Turbo Codes; Processing GPS Occultation Data To Characterize Atmosphere; Displacing Unpredictable Nulls in Antenna Radiation Patterns; Integrated Pointing and Signal Detector for Optical Receiver; Adaptive Thresholding and Parameter Estimation for PPM; Data-Driven Software Framework for Web-Based ISS Telescience; Software for Secondary-School Learning About Robotics; Fuzzy Logic Engine; Telephone-Directory Program; Simulating a Direction-Finder Search for an ELT; Formulating Precursors for Coating Metals and Ceramics; Making Macroscopic Assemblies of Aligned Carbon Nanotubes; Ball Bearings Equipped for In Situ Lubrication on Demand; Synthetic Bursae for Robots; Robot Forearm and Dexterous Hand; Making a Metal-Lined Composite-Overwrapped Pressure Vessel; Ex Vivo Growth of Bioengineered Ligaments and Other Tissues; Stroboscopic Goggles for Reduction of Motion Sickness; Articulating Support for Horizontal Resistive Exercise; Modified Penning-Malmberg Trap for Storing Antiprotons; Tumbleweed Rovers; Two-Photon Fluorescence Microscope for Microgravity Research; Biased Randomized Algorithm for Fast Model-Based Diagnosis; Fast Algorithms for Model-Based Diagnosis; Simulations of Evaporating Multicomponent Fuel Drops; Formation Flying of Tethered and Nontethered Spacecraft; and Two Methods for Efficient Solution of the Hitting- Set Problem.

Source record↗
NASA NTRS2003

Flight-Test Evaluation of Flutter-Prediction Methods

The flight-test community routinely spends considerable time and money to determine a range of flight conditions, called a flight envelope, within which an aircraft is safe to fly. The cost of determining a flight envelope could be greatly reduced if there were a method of safely and accurately predicting the speed associated with the onset of an instability called flutter. Several methods have been developed with the goal of predicting flutter speeds to improve the efficiency of flight testing. These methods include (1) data-based methods, in which one relies entirely on information obtained from the flight tests and (2) model-based approaches, in which one relies on a combination of flight data and theoretical models. The data-driven methods include one based on extrapolation of damping trends, one that involves an envelope function, one that involves the Zimmerman-Weissenburger flutter margin, and one that involves a discrete-time auto-regressive model. An example of a model-based approach is that of the flutterometer. These methods have all been shown to be theoretically valid and have been demonstrated on simple test cases; however, until now, they have not been thoroughly evaluated in flight tests. An experimental apparatus called the Aerostructures Test Wing (ATW) was developed to test these prediction methods.

Lind, RIck↗