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At least 649 records · Page 36

Control of Initialized Fractional-Order Systems

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex Airplane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex Airplane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Hartly, Tom T.↗

Photogrammetry Methodology Development for Gossamer Spacecraft Structures

Photogrammetry--the science of calculating 3D object coordinates from images--is a flexible and robust approach for measuring the static and dynamic characteristics of future ultra-lightweight and inflatable space structures (a.k.a., Gossamer structures), such as large membrane reflectors, solar sails, and thin-film solar arrays. Shape and dynamic measurements are required to validate new structural modeling techniques and corresponding analytical models for these unconventional systems. This paper summarizes experiences at NASA Langley Research Center over the past three years to develop or adapt photogrammetry methods for the specific problem of measuring Gossamer space structures. Turnkey industrial photogrammetry systems were not considered a cost-effective choice for this basic research effort because of their high purchase and maintenance costs. Instead, this research uses mainly off-the-shelf digital-camera and software technologies that are affordable to most organizations and provide acceptable accuracy.

Pappa, Richard S.↗

Control of Initialized Fractional-Order Systems

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex w-plane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex w-plane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Hartley, Tom T.↗

Photogrammetry Methodology Development for Gossamer Spacecraft Structures

Photogrammetry--the science of calculating 3D object coordinates from images-is a flexible and robust approach for measuring the static and dynamic characteristics of future ultralightweight and inflatable space structures (a.k.a., Gossamer structures), such as large membrane reflectors, solar sails, and thin-film solar arrays. Shape and dynamic measurements are required to validate new structural modeling techniques and corresponding analytical models for these unconventional systems. This paper summarizes experiences at NASA Langley Research Center over the past three years to develop or adapt photogrammetry methods for the specific problem of measuring Gossamer space structures. Turnkey industrial photogrammetry systems were not considered a cost-effective choice for this basic research effort because of their high purchase and maintenance costs. Instead, this research uses mainly off-the-shelf digital-camera and software technologies that are affordable to most organizations and provide acceptable accuracy.

Pappa, Richard S.↗

Autonomous Aerobraking at Mars

Aerobraking has become a proven approach for orbital missions at Mars. A launch of a 1000 kg class spacecraft on a Delta class booster saves 90% of the post-MOI fuel otherwise required to circularize the orbit. In 1997, Mars Global Surveyor demonstrated the feasibility and Mars 2001 Odyssey completed a nearly trouble free aerobraking phase in January 2002. In 2006, Mars Reconnaissance Orbiter will also utilize aerobraking. From the flight operations standpoint, however, aerobraking is labor intensive and high risk due to the large density variability in the Mars thermosphere. The maximum rate of aerobraking is typically limited by the maximum allowable temperature of the solar array which is the primary drag surface. Prior missions have used a surrogate variable, usually maximum free stream heat flux, as a basis for performing periapsis altitude corridor control maneuvers. This paper provides an adaptive sequential method for operationally relating measured temperatures to heat flux profile characteristics and performing maneuvers based directly on measured temperatures and atmospheric properties derived from the heat flux profiles. Simulations of autonomous aerobraking are performed using Odyssey mission data.

Hanna, Jill L.↗

Multichannel spatial auditory display for speech communications

A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degrees azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degrees azimuth positions.

NASA Discipline Space Human Factors↗

Innovative Language-Based & Object-Oriented Structured AMR Using Fortran 90 and OpenMP

Parallel adaptive mesh refinement (AMR) is an important numerical technique that leads to the efficient solution of many physical and engineering problems. In this paper, we describe how AMR programing can be performed in an object-oreinted way using the modern aspects of Fortran 90 combined with the parallelization features of OpenMP.

software↗

Noninvasive Medical Diagnostics & Treatment Using Ultrasonics

In parallel to the industrial application of NDE to flaw detection and material property determination, the medical community has succesfully adapted such methods to the noninvasaive diagnostics and treatment of many conditions and disorders of the human body.

NDE noninvasive diagnostics destruction of blood c↗

Evaluation of TRMM Ground-Validation Radar-Rain Errors Using Rain Gauge Measurements

Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) spaced-based rain estimates, and hence, quantitative evaluation of the GV radar-rain product error characteristics is vital. This study uses quality-controlled gauge data to compare with TRMM GV radar rain rates in an effort to provide such error characteristics. The results show that significant differences of concurrent radar-gauge rain rates exist at various time scales ranging from 5 min to 1 day, despite lower overall long-term bias. However, the differences between the radar area-averaged rain rates and gauge point rain rates cannot be explained as due to radar error only. The error variance separation method is adapted to partition the variance of radar-gauge differences into the gauge area-point error variance and radar rain estimation error variance. The results provide relatively reliable quantitative uncertainty evaluation of TRMM GV radar rain estimates at various times scales, and are helpful to better understand the differences between measured radar and gauge rain rates. It is envisaged that this study will contribute to better utilization of GV radar rain products to validate versatile spaced-based rain estimates from TRMM, as well as the proposed Global Precipitation Measurement, and other satellites.

Wang, Jianxin↗

Progressive Classification Using Support Vector Machines

An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user can halt this reclassification process at any point, thereby obtaining the best possible result for a given amount of computation time. Alternatively, the results can be displayed as they are generated, providing the user with real-time feedback about the current accuracy of classification.

Wagstaff, Kiri↗

Adaptive Nulling for Interferometric Detection of Planets

An adaptive-nulling method has been proposed to augment the nulling-optical- interferometry method of detection of Earth-like planets around distant stars. The method is intended to reduce the cost of building and aligning the highly precise optical components and assemblies needed for nulling. Typically, at the mid-infrared wavelengths used for detecting planets orbiting distant stars, a star is millions of times brighter than an Earth-sized planet. In order to directly detect the light from the planet, it is necessary to remove most of the light coming from the star. Nulling interferometry is one way to suppress the light from the star without appreciably suppressing the light from the planet. In nulling interferometry in its simplest form, one uses two nominally identical telescopes aimed in the same direction and separated laterally by a suitable distance. The light collected by the two telescopes is processed through optical trains and combined on a detector. The optical trains are designed such that the electric fields produced by an on-axis source (the star) are in anti-phase at the detector while the electric fields from the planet, which is slightly off-axis, combine in phase, so that the contrast ratio between the star and the planet is greatly decreased. If the electric fields from the star are exactly equal in amplitude and opposite in phase, then the star is effectively nulled out. Nulling is effective only if it is complete in the sense that it occurs simultaneously in both polarization states and at all wavelengths of interest. The need to ensure complete nulling translates to extremely tight demands upon the design and fabrication of the complex optical trains: The two telescopes must be highly symmetric, the reflectivities of the many mirrors in the telescopes and other optics must be carefully tailored, the optical coatings must be extremely uniform, sources of contamination must be minimized, optical surfaces must be nearly ideal, and alignments must be extremely precise. Satisfaction of all of these requirements entails substantial cost.

Lay, Oliver P.↗

NASA Risk-Informed Decision Making Handbook

This handbook provides guidance for conducting risk-informed decision making in the context of NASA risk management (RM), with a focus on the types of direction-setting key decisions that are characteristic of the NASA program and project life cycles, and which produce derived requirements in accordance with existing systems engineering practices that flow down through the NASA organizational hierarchy. The guidance in this handbook is not meant to be prescriptive. Instead, it is meant to be general enough, and contain a sufficient diversity of examples, to enable the reader to adapt the methods as needed to the particular decision problems that he or she faces. The handbook highlights major issues to consider when making decisions in the presence of potentially significant uncertainty, so that the user is better able to recognize and avoid pitfalls that might otherwise be experienced.

Dezfuli, Homayoon↗

Adaptive Fault Detection on Liquid Propulsion Systems with Virtual Sensors: Algorithms and Architectures

Prior to the launch of STS-119 NASA had completed a study of an issue in the flow control valve (FCV) in the Main Propulsion System of the Space Shuttle using an adaptive learning method known as Virtual Sensors. Virtual Sensors are a class of algorithms that estimate the value of a time series given other potentially nonlinearly correlated sensor readings. In the case presented here, the Virtual Sensors algorithm is based on an ensemble learning approach and takes sensor readings and control signals as input to estimate the pressure in a subsystem of the Main Propulsion System. Our results indicate that this method can detect faults in the FCV at the time when they occur. We use the standard deviation of the predictions of the ensemble as a measure of uncertainty in the estimate. This uncertainty estimate was crucial to understanding the nature and magnitude of transient characteristics during startup of the engine. This paper overviews the Virtual Sensors algorithm and discusses results on a comprehensive set of Shuttle missions and also discusses the architecture necessary for deploying such algorithms in a real-time, closed-loop system or a human-in-the-loop monitoring system. These results were presented at a Flight Readiness Review of the Space Shuttle in early 2009.

Matthews, Bryan L.↗

NASA Risk Management Handbook

The purpose of this handbook is to provide guidance for implementing the Risk Management (RM) requirements of NASA Procedural Requirements (NPR) document NPR 8000.4A, Agency Risk Management Procedural Requirements [1], with a specific focus on programs and projects, and applying to each level of the NASA organizational hierarchy as requirements flow down. This handbook supports RM application within the NASA systems engineering process, and is a complement to the guidance contained in NASA/SP-2007-6105, NASA Systems Engineering Handbook [2]. Specifically, this handbook provides guidance that is applicable to the common technical processes of Technical Risk Management and Decision Analysis established by NPR 7123.1A, NASA Systems Engineering Process and Requirements [3]. These processes are part of the \Systems Engineering Engine. (Figure 1) that is used to drive the development of the system and associated work products to satisfy stakeholder expectations in all mission execution domains, including safety, technical, cost, and schedule. Like NPR 7123.1A, NPR 8000.4A is a discipline-oriented NPR that intersects with product-oriented NPRs such as NPR 7120.5D, NASA Space Flight Program and Project Management Requirements [4]; NPR 7120.7, NASA Information Technology and Institutional Infrastructure Program and Project Management Requirements [5]; and NPR 7120.8, NASA Research and Technology Program and Project Management Requirements [6]. In much the same way that the NASA Systems Engineering Handbook is intended to provide guidance on the implementation of NPR 7123.1A, this handbook is intended to provide guidance on the implementation of NPR 8000.4A. 1.2 Scope and Depth This handbook provides guidance for conducting RM in the context of NASA program and project life cycles, which produce derived requirements in accordance with existing systems engineering practices that flow down through the NASA organizational hierarchy. The guidance in this handbook is not meant to be prescriptive. Instead, it is meant to be general enough, and contain a sufficient diversity of examples, to enable the reader to adapt the methods as needed to the particular risk management issues that he or she faces. The handbook highlights major issues to consider when managing programs and projects in the presence of potentially significant uncertainty, so that the user is better able to recognize and avoid pitfalls that might otherwise be experienced.

Dezfuli, Homayoon↗

CFD Technology for Rotorcraft Gearbox Windage Aerodynamics Simulation

A computational fluid dynamics (CFD) method is adapted, validated and applied to spinning gear systems with emphasis on predicting windage losses. Several spur gears and a disc are studied. The CFD simulations return good agreement with measured windage power loss. Turbulence modeling choices, the relative importance of viscous and pressure torques with gear speed and the physics of the complex 3-D unsteady flow field in the vicinity of the gear teeth are studied.

Handschuh, Robert↗

Fault Mitigation Schemes for Future Spaceflight Multicore Processors

Future planetary exploration missions demand significant advances in on-board computing capabilities over current avionics architectures based on a single-core processing element. The state-of-the-art multi-core processor provides much promise in meeting such challenges while introducing new fault tolerance problems when applied to space missions. Software-based schemes are being presented in this paper that can achieve system-level fault mitigation beyond that provided by radiation-hard-by-design (RHBD). For mission and time critical applications such as the Terrain Relative Navigation (TRN) for planetary or small body navigation, and landing, a range of fault tolerance methods can be adapted by the application. The software methods being investigated include Error Correction Code (ECC) for data packet routing between cores, virtual network routing, Triple Modular Redundancy (TMR), and Algorithm-Based Fault Tolerance (ABFT). A robust fault tolerance framework that provides fail-operational behavior under hard real-time constraints and graceful degradation will be demonstrated using TRN executing on a commercial Tilera(R) processor with simulated fault injections.

software based↗

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Functional near infrared spectroscopy (fNIRS) is an emerging optical neuroimaging technology that indirectly measures neuronal activity in the cortex via neurovascular coupling. It quantifies hemoglobin concentration ([Hb]) and thus measures the same hemodynamic response as functional magnetic resonance imaging (fMRI), but is portable, non-confining, relatively inexpensive, and is appropriate for long-duration monitoring and use at the bedside. Like fMRI, it is noninvasive and safe for repeated measurements. Patterns of [Hb] changes are used to classify cognitive state. Thus, fNIRS technology offers much potential for application in operational contexts. For instance, the use of fNIRS to detect the mental state of commercial aircraft operators in near real time could allow intelligent flight decks of the future to optimally support human performance in the interest of safety by responding to hazardous mental states of the operator. However, many opportunities remain for improving robustness and reliability. It is desirable to reduce the impact of motion and poor optical coupling of probes to the skin. Such artifacts degrade signal quality and thus cognitive state classification accuracy. Field application calls for further development of algorithms and filters for the automation of bad channel detection and dynamic artifact removal. This work introduces a novel adaptive filter method for automated real-time fNIRS signal quality detection and improvement. The output signal (after filtering) will have had contributions from motion and poor coupling reduced or removed, thus leaving a signal more indicative of changes due to hemodynamic brain activations of interest. Cognitive state classifications based on these signals reflect brain activity more reliably. The filter has been tested successfully with both synthetic and real human subject data, and requires no auxiliary measurement. This method could be implemented as a real-time filtering option or bad channel rejection feature of software used with frequency domain fNIRS instruments for signal acquisition and processing. Use of this method could improve the reliability of any operational or real-world application of fNIRS in which motion is an inherent part of the functional task of interest. Other optical diagnostic techniques (e.g., for NIR medical diagnosis) also may benefit from the reduction of probe motion artifact during any use in which motion avoidance would be impractical or limit usability.

Harrivel, Angela↗

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Functional near infrared spectroscopy (fNIRS) is an emerging optical neuroimaging technology that indirectly measures neuronal activity in the cortex via neurovascular coupling. It quantifies hemoglobin concentration ([Hb]) and thus measures the same hemodynamic response as functional magnetic resonance imaging (fMRI), but is portable, non-confining, relatively inexpensive, and is appropriate for long-duration monitoring and use at the bedside. Like fMRI, it is noninvasive and safe for repeated measurements. Patterns of [Hb] changes are used to classify cognitive state. Thus, fNIRS technology offers much potential for application in operational contexts. For instance, the use of fNIRS to detect the mental state of commercial aircraft operators in near real time could allow intelligent flight decks of the future to optimally support human performance in the interest of safety by responding to hazardous mental states of the operator. However, many opportunities remain for improving robustness and reliability. It is desirable to reduce the impact of motion and poor optical coupling of probes to the skin. Such artifacts degrade signal quality and thus cognitive state classification accuracy. Field application calls for further development of algorithms and filters for the automation of bad channel detection and dynamic artifact removal. This work introduces a novel adaptive filter method for automated real-time fNIRS signal quality detection and improvement. The output signal (after filtering) will have had contributions from motion and poor coupling reduced or removed, thus leaving a signal more indicative of changes due to hemodynamic brain activations of interest. Cognitive state classifications based on these signals reflect brain activity more reliably. The filter has been tested successfully with both synthetic and real human subject data, and requires no auxiliary measurement. This method could be implemented as a real-time filtering option or bad channel rejection feature of software used with frequency domain fNIRS instruments for signal acquisition and processing. Use of this method could improve the reliability of any operational or real-world application of fNIRS in which motion is an inherent part of the functional task of interest. Other optical diagnostic techniques (e.g., for NIR medical diagnosis) also may benefit from the reduction of probe motion artifact during any use in which motion avoidance would be impractical or limit usability.

Harrivel, Angela↗