Results for “identification problem” — Page 38

NASA NTRS1979

A Ganymede lander mission

The paper addresses the dynamical problem and question of technical feasibility associated with delivering a simple, semi-hard lander to one of the Galilean satellites, Ganymede. Emphasis is placed on the identification of a viable, not necessarily optimal, baseline trajectory and maneuver sequence. Simplicity is stressed in the lander's use of two fixed-impulse solid rockets for landing maneuvers. It is shown through an error analysis that navigation and maneuver execution errors can be compensated on the baseline descent trajectory by controlling just the thrust direction. Finally, specific subsystem capabilities needed on the lander to achieve a successful touchdown within a specific performance envelope are also identified.

Boain, R. J.↗

NASA NTRS1985

Robust detection-isolation-accommodation for sensor failures

The results of a one year study to: (1) develop a theory for Robust Failure Detection and Identification (FDI) in the presence of model uncertainty, (2) develop a design methodology which utilizes the robust FDI ththeory, (3) apply the methodology to a sensor FDI problem for the F-100 jet engine, and (4) demonstrate the application of the theory to the evaluation of alternative FDI schemes are presented. Theoretical results in statistical discrimination are used to evaluate the robustness of residual signals (or parity relations) in terms of their usefulness for FDI. Furthermore, optimally robust parity relations are derived through the optimization of robustness metrics. The result is viewed as decentralization of the FDI process. A general structure for decentralized FDI is proposed and robustness metrics are used for determining various parameters of the algorithm.

Weiss, J. L.↗

NASA NTRS1992

High performance interconnection between high data rate networks

The bridge/gateway system needed to interconnect a wide range of computer networks to support a wide range of user quality-of-service requirements is discussed. The bridge/gateway must handle a wide range of message types including synchronous and asynchronous traffic, large, bursty messages, short, self-contained messages, time critical messages, etc. It is shown that messages can be classified into three basic classes, synchronous and large and small asynchronous messages. The first two require call setup so that packet identification, buffer handling, etc. can be supported in the bridge/gateway. Identification enables resequences in packet size. The third class is for messages which do not require call setup. Resequencing hardware based to handle two types of resequencing problems is presented. The first is for a virtual parallel circuit which can scramble channel bytes. The second system is effective in handling both synchronous and asynchronous traffic between networks with highly differing packet sizes and data rates. The two other major needs for the bridge/gateway are congestion and error control. A dynamic, lossless congestion control scheme which can easily support effective error correction is presented. Results indicate that the congestion control scheme provides close to optimal capacity under congested conditions. Under conditions where error may develop due to intervening networks which are not lossless, intermediate error recovery and correction takes 1/3 less time than equivalent end-to-end error correction under similar conditions.

Foudriat, E. C.↗

NASA NTRS1992

An improved classification tree analysis of high cost modules based upon an axiomatic definition of complexity

Identification of high cost modules has been viewed as one mechanism to improve overall system reliability, since such modules tend to produce more than their share of problems. A decision tree model was used to identify such modules. In this current paper, a previously developed axiomatic model of program complexity is merged with the previously developed decision tree process for an improvement in the ability to identify such modules. This improvement was tested using data from the NASA Software Engineering Laboratory.

Tian, Jianhui↗

NASA NTRS2000

Risk-Based Object Oriented Testing

Software testing is a well-defined phase of the software development life cycle. Functional ("black box") testing and structural ("white box") testing are two methods of test case design commonly used by software developers. A lesser known testing method is risk-based testing, which takes into account the probability of failure of a portion of code as determined by its complexity. For object oriented programs, a methodology is proposed for identification of risk-prone classes. Risk-based testing is a highly effective testing technique that can be used to find and fix the most important problems as quickly as possible.

Rosenberg, Linda H.↗

NASA NTRS1975

Minimum-fuel rocket trajectories involving intermediate-thrust arcs

The optimal trajectories in the neighborhood of an optimal intermediate-thrust arc are investigated for the minimum-fuel orbit rendezvous problem with fixed specific impulse. Since such an arc is singular, the thrust acceleration magnitude being the singular control component, a second-variation analysis leads to the identification of a field of neighboring, singular arcs in a state space of dimension four rather than six, provided that a suitable Jacobi condition is met. A given neighboring initial six-dimensional state vector does not generally lie on a neighboring singular arc, and junction onto the appropriate singular arc must be accomplished by a short period of strong variations in the acceleration. The neighboring singular arc meets the final condition in 4 dimensions, rather than 6 dimensions, and rendezvous must be completed by another, terminal short period of strong variations in the acceleration. Implications for midcourse guidance near a singular arc are discussed.

Breakwell, J. V.↗

NASA NTRS1976

Experiment design for pilot identification in compensatory tracking tasks

A design criterion for input functions in laboratory tracking tasks resulting in efficient parameter estimation is formulated. The criterion is that the statistical correlations between pairs of parameters be reduced in order to minimize the problem of nonuniqueness in the extraction process. The effectiveness of the method is demonstrated for a lower order dynamic system.

Wells, W. R.↗

NASA NTRS1988

System identification in the microcomputer environment

An implementation of an algorithm for system identification, the eigenvalue realization algorithm (ERA), on a microcomputer is reported. Test results are presented to show that accurate structural identification can be performed in a microcomputer environment. It is also shown that the memory limits (640 K) of small machines are generally adequate for solving large scale problems (e.g., Hankel matrices with 15,000 elements), with run times being on the order of several minutes.

Garcia, Ephrahim↗

NASA NTRS1988

The preparation of high quality machine-readable classical catalogs for incorporation into astronomical databases

The merging of data from various catalogs and their incorporation into existing databases such as SIMBAD is a demanding task, mainly because of the diverse and inconsistent astronomical nomenclature that has developed over the years. Although the cross identification of objects by computer is in principle an extremely simple procedure, numerous pitfalls have been encountered in practice because of errors and mutually exclusive identifications in existing catalogs. The incorporation of classical and new data into SIMBAD is clearly simplified if machine versions of catalogs are prepared with a view toward this problem. New versions of a number of important catalogs have been prepared and fully documented at the Astronomical Data Center, NASA Goddard Space Flight Center with consideration of both independent use and data integration. Recently completed catalogs and current projects will be reviewed in this presentation.

Warren, Wayne H., Jr.↗

NASA NTRS2005

Development as adaptation: a paradigm for gravitational and space biology

Adaptation is a central precept of biology; it provides a framework for identifying functional significance. We equate mammalian development with adaptation, by viewing the developmental sequence as a series of adaptations to a stereotyped sequence of habitats. In this way development is adaptation. The Norway rat is used as a mammalian model, and the sequence of habitats that is used to define its adaptive-developmental sequence is (a) the uterus, (b) the mother's body, (c) the huddle, and (d) the coterie of pups as they gain independence. Then, within this framework and in relation to each of the habitats, we consider problems of organismal responses to altered gravitational forces (micro-g to hyper-g), especially those encountered during space flight and centrifugation. This approach enables a clearer identification of simple "effects" and active "responses" with respect to gravity. It focuses our attention on functional systems and brings to the fore the manner in which experience shapes somatic adaptation. We argue that this basic developmental approach is not only central to basic issues in gravitational biology, but that it provides a natural tool for understanding the underlying processes that are vital to astronaut health and well-being during long duration flights that will involve adaptation to space flight conditions and eventual re-adaptation to Earth's gravity.

Non-NASA Center↗

NASA NTRSDate not supplied

Frequency Domain Quasi-Maximum Likelihood Identification of Low Order Aeroservoelastic Models from Flight-Test Data

Background and Motivation - Low Order Equivalent System (LOES) - From handling qualities analysis - Traditionally simplifying complex control law and plant - More easily understood form - Extend LOES to a complex model due to aeroelasticity - Maximum likelihood (Filter Error) System Identification - Z = H_loes (U + W) + V - There are a lot of parameters - System identification usually simplifies by assuming a value - Output Error and Equation Error - Results in biased estimates of the parameters - We are proposing a new method to solving this problem

Jeffrey Ouellette↗

NASA NTRSDate not supplied

The Air Quality Monitor “Benzene” Anomaly: Ground Testing and On-going Effects

The International Space Station (ISS) Air Quality Monitors (AQMs) have provided targeted in-flight analysis of volatile organic compounds (VOCs) in the ISS atmosphere since early 2013. During their initial half decade of use covering multiple sets of units, the AQMs performed well, meeting their validation criteria and showing excellent accuracy compared to archival samples. In addition to routine environmental monitoring, the AQMs have also been used during a number of contingency situations and investigations related to Environmental Control and Life Support Systems (ECLSS). These include a potential ammonia leak, increases in atmospheric ethanol, and efforts to locate potential sources of polydimethylsiloxanes that lead to the production of dimethylsilanediol (DMSD) in the US Water Processor Assembly (WPA). As the fleet of AQMs has aged, several issues have arisen. These have ranged from pervasive problems on electronics boards to loss of sensitivity due to operating in an elevated CO2 environment. The most notable issue encountered during on-orbit operations was incorrect identification of compounds. This initially occurred in mid-2020, when AQM1 reported the presence of benzene. While the AQM team questioned the validity of these results, the concentration of the “benzene” continued to increase and eventually exceeded the 30- and 180-day Spacecraft Maximum Allowable Concentration (SMAC). This led to wide-ranging efforts by a number of groups aimed at understanding the situation and identifying the source of the “benzene.” AQM1 failed after being relocated to the Russian Segment as part of the investigation, and the unit was returned for evaluation. When archive samples collected while the AQM was measuring elevated benzene showed no detectable benzene, the focus of the investigation shifted to determining the cause of the false positive readings. Here, we will discuss the results of this investigation by the AQM team, potential causes of the interference, and subsequent reporting of AQM1 results.

W T Wallace↗

NASA NTRS2024

The Air Quality Monitor “Benzene” Anomaly: Ground Testing and On-going Effects

The International Space Station (ISS) Air Quality Monitors (AQMs) have provided targeted in-flight analysis of volatile organic compounds (VOCs) in the ISS atmosphere since early 2013. During their initial half decade of use covering multiple sets of units, the AQMs performed well, meeting their validation criteria and showing excellent accuracy compared to archival samples. In addition to routine environmental monitoring, the AQMs have also been used during a number of contingency situations and investigations related to Environmental Control and Life Support Systems (ECLSS). These include a potential ammonia leak, increases in atmospheric ethanol, and efforts to locate potential sources of polydimethylsiloxanes that lead to the production of dimethylsilanediol (DMSD) in the US Water Processor Assembly (WPA). As the fleet of AQMs has aged, several issues have arisen. These have ranged from pervasive problems on electronics boards to loss of sensitivity due to operating in an elevated CO2 environment. The most notable issue encountered during on-orbit operations was incorrect identification of compounds. This initially occurred in mid-2020, when AQM1 reported the presence of benzene. While the AQM team questioned the validity of these results, the concentration of the “benzene” continued to increase and eventually exceeded the 30- and 180-day Spacecraft Maximum Allowable Concentration (SMAC). This led to wide-ranging efforts by a number of groups aimed at understanding the situation and identifying the source of the “benzene.” AQM1 failed after being relocated to the Russian Segment as part of the investigation, and the unit was returned for evaluation. When archive samples collected while the AQM was measuring elevated benzene showed no detectable benzene, the focus of the investigation shifted to determining the cause of the false positive readings. Here, we will discuss the results of this investigation by the AQM team, potential causes of the interference, and subsequent reporting of AQM1 results.

W T Wallace↗

NASA NTRSDate not supplied

The Air Quality Monitor “Benzene” Anomaly: Ground Testing and On-going Effects

The International Space Station (ISS) Air Quality Monitors (AQMs) have provided targeted in-flight analysis of volatile organic compounds (VOCs) in the ISS atmosphere since early 2013. During their initial half decade of use covering multiple sets of units, the AQMs performed well, meeting their validation criteria and showing excellent accuracy compared to archival samples. In addition to routine environmental monitoring, the AQMs have also been used during a number of contingency situations and investigations related to Environmental Control and Life Support Systems (ECLSS). These include a potential ammonia leak, increases in atmospheric ethanol, and efforts to locate potential sources of polydimethylsiloxanes that lead to the production of dimethylsilanediol (DMSD) in the US Water Processor Assembly (WPA). As the fleet of AQMs has aged, several issues have arisen. These have ranged from pervasive problems on electronics boards to loss of sensitivity due to operating in an elevated CO2 environment. The most notable issue encountered during on-orbit operations was incorrect identification of compounds. This initially occurred in mid-2020, when AQM1 reported the presence of benzene. While the AQM team questioned the validity of these results, the concentration of the “benzene” continued to increase and eventually exceeded the 30- and 180-day Spacecraft Maximum Allowable Concentration (SMAC). This led to wide-ranging efforts by a number of groups aimed at understanding the situation and identifying the source of the “benzene.” AQM1 failed after being relocated to the Russian Segment as part of the investigation, and the unit was returned for evaluation. When archive samples collected while the AQM was measuring elevated benzene showed no detectable benzene, the focus of the investigation shifted to determining the cause of the false positive readings. Here, we will discuss the results of this investigation by the AQM team, potential causes of the interference, and subsequent reporting of AQM1 results.

William T Wallace↗

NASA NTRS2023

The High Energy X-Ray Probe (HEX-P): Galactic PeVatrons, Star Clusters, Superbubbles, Microquasar Jets, and Gamma-Ray Binaries

HEX-P is a probe-class mission concept that will combine high spatial resolution X-ray imaging (<10"FWHM) and broad spectral coverage (0.2--80 keV) with an effective area far superior to current facilities (including XMM-Newton and NuSTAR) to enable revolutionary new insights into a variety of important astrophysical problems. With the recent discoveries of over 40 ultra-high-energy gamma-ray sources (detected above 100 TeV) and neutrino emission in the Galactic Plane, we have entered a new era of multi-messenger astrophysics facing the exciting reality of Galactic PeVatrons. In the next decade, as more Galactic PeVatrons and TeV gamma-ray sources are expected to be discovered, the identification of their acceleration and emission mechanisms will be the most pressing issue in both particle and high-energy astrophysics. In this paper, along with its companion papers (Reynolds et al. 2023, Mori et al. 2023), we will present that HEX-P is uniquely suited to address important problems in various cosmic-ray accelerators, including Galactic PeVatrons, through investigating synchrotron X-ray emission of TeV--PeV electrons produced by both leptonic and hadronic processes. For Galactic PeVatron candidates and other TeV gamma-ray sources, HEX-P can fill in a large gap in the spectral-energy distributions (SEDs) of many objects observed in radio, soft X-rays, and gamma rays, constraining the maximum energies to which electrons can be accelerated, with implications for the nature of the Galactic PeVatrons and their contributions to the spectrum of Galactic cosmic rays beyond the knee at $\sim3$ PeV. In particular, X-ray observation with HEX-P and TeV observation with CTA will provide the most powerful multi-messenger diagnostics to identify Galactic PeVatrons and explore a variety of astrophysical shock mechanisms. We present simulations of each class of Galactic TeV--PeV sources, demonstrating the power of both the imaging and spectral capabilities of HEX-P to advance our knowledge of Galactic cosmic-ray accelerators. In addition, we discuss HEX-P’s unique and complementary roles to upcoming gamma-ray and neutrino observatories in the 2030s.

particle accelerators↗

NASA NTRS2011

Experiences with Text Mining Large Collections of Unstructured Systems Development Artifacts at JPL

Often repositories of systems engineering artifacts at NASA's Jet Propulsion Laboratory (JPL) are so large and poorly structured that they have outgrown our capability to effectively manually process their contents to extract useful information. Sophisticated text mining methods and tools seem a quick, low-effort approach to automating our limited manual efforts. Our experiences of exploring such methods mainly in three areas including historical risk analysis, defect identification based on requirements analysis, and over-time analysis of system anomalies at JPL, have shown that obtaining useful results requires substantial unanticipated efforts - from preprocessing the data to transforming the output for practical applications. We have not observed any quick 'wins' or realized benefit from short-term effort avoidance through automation in this area. Surprisingly we have realized a number of unexpected long-term benefits from the process of applying text mining to our repositories. This paper elaborates some of these benefits and our important lessons learned from the process of preparing and applying text mining to large unstructured system artifacts at JPL aiming to benefit future TM applications in similar problem domains and also in hope for being extended to broader areas of applications.

text mining↗

DOE OSTI2024

Overview of RFID Applications Utilizing Neural Networks

As Radio Frequency Identification (RFID) methods continue to evolve to higher levels of complexity, one form of machine learning is making its appearance. The use of Neural Networks (NN) in the RFID field is steadily increasing, and in the fields of localization and activity recognition, promising results are being shown from a variety of research. RFID applications fall primarily under two types of problems including regression and classification. We analyze RIFD localization techniques which fall under regression, and activity recognition which falls under classification. Many works don’t classify themselves as activity recognition methods, but because they fall under the classification category, we still consider them as activity recognition techniques. This research overviews the Neural Network models in the localization field based on whether they can perform independently of the environment in which they were tested. For activity recognition and accessory fields, the major methods involve tag-based and tag-free approaches. In conclusion, after the models are surveyed, a comparison study is given to examine what may be the cause for increased accuracy between different Neural Network models.

42 ENGINEERING↗

DOE OSTI2026

Navigating Large Chemical Spaces Using Graph Theory and Integer Programming

Navigating and analyzing large chemical spaces are necessary to accelerate the design and discovery of new molecules and chemical processes. In this work, we introduce a computational framework that integrates graph theory and integer programming to enable the efficient navigation of large chemical spaces. Our framework represents the chemical space as a graph, wherein nodes represent molecules and edges represent the degree of similarity or connectivity based on domain-specific information. Using the graph representation, we identify representative molecules by computing the so-called minimum dominating set (MDS), which in our context is the minimum set of molecules that is connected to all other molecules. We present a suite of solution strategies for the MDS problem including heuristic and rigorous integer programming (IP) approaches. We show that these approaches allow us to capture physicochemical properties and domain-specific logic and constraints, facilitating the identification of molecules with the target properties. We demonstrate the effectiveness of the proposed approach by navigating the chemical space of per- and polyfluoroalkyl substances (PFAS); this comprises approximately 15,000 molecular structures. We compare our framework against traditional dimensionality reduction and clustering methods such as t-SNE and K-means clustering.

Chemical structure↗