Results for “model diagnostics and development” — Page 7

NASA NTRS1987

The KATE shell: An implementation of model-based control, monitor and diagnosis

The conventional control and monitor software currently used by the Space Center for Space Shuttle processing has many limitations such as high maintenance costs, limited diagnostic capabilities and simulation support. These limitations have caused the development of a knowledge based (or model based) shell to generically control and monitor electro-mechanical systems. The knowledge base describes the system's structure and function and is used by a software shell to do real time constraints checking, low level control of components, diagnosis of detected faults, sensor validation, automatic generation of schematic diagrams and automatic recovery from failures. This approach is more versatile and more powerful than the conventional hard coded approach and offers many advantages over it, although, for systems which require high speed reaction times or aren't well understood, knowledge based control and monitor systems may not be appropriate.

Cornell, Matthew↗

NASA NTRS1999

Development of Optical Diagnostic Techniques for Microgravity Materials Processing

Materials processing including crystal growth, either under a gravity environment on ground or a microgravity environment in space, involves complicated phenomena of fluid motions in gas or liquid phases as well as interaction of various species. To obtain important physical insight, it is very necessary to provide gross-field optical diagnostics for monitoring various physical properties. Materials processing inhibits easy access by ordinary instruments and thus characterizing gross-field physical properties is very challenging. Typical properties of importance can be fluid velocity, temperature, and species concentration for fluids, and surface topology and defects for solids. Observing surface grow rate during crystal growth is also important. Material microstructures, i.e., integrity of crystal structures, is strongly influenced by the existence of thermally-induced flow as well as local nucleation of particles during solidification, which may act in many detrimental ways. In both ground-based and microgravity experiments, the nature of product property changes resulting from three-dimensional fluid or particle motions need be characterized. Gross-field diagnostics is thus required to identify their effects on product defects and process deficiencies. The quantitative visualization techniques can also be used for validation of numerical modeling. For optical nonintrusive gross-field diagnostic techniques, two approaches were developed as summer projects. One optical approach allows us to provide information of species concentration and temperature for monitoring in real time. The other approach, that is, the concept which is formulated for detection of surface topography measurement can provide unprecedented spatial resolution during crystal growth.

Cha, Soyoung Stephen↗

NASA NTRS1967

A study of a non-developing easterly wave

Dynamical structure of tropical atmosphere based on experiments with diagnostic numerical model

MATHEMATICAL MODEL↗

NASA NTRS2009

Airframe Icing Research Gaps: NASA Perspective

qCurrent Airframe Icing Technology Gaps: Development of a full 3D ice accretion simulation model. Development of an improved simulation model for SLD conditions. CFD modeling of stall behavior for ice-contaminated wings/tails. Computational methods for simulation of stability and control parameters. Analysis of thermal ice protection system performance. Quantification of 3D ice shape geometric characteristics Development of accurate ground-based simulation of SLD conditions. Development of scaling methods for SLD conditions. Development of advanced diagnostic techniques for assessment of tunnel cloud conditions. Identification of critical ice shapes for aerodynamic performance degradation. Aerodynamic scaling issues associated with testing scale model ice shape geometries. Development of altitude scaling methods for thermal ice protections systems. Development of accurate parameter identification methods. Measurement of stability and control parameters for an ice-contaminated swept wing aircraft. Creation of control law modifications to prevent loss of control during icing encounters. 3D ice shape geometries. Collection efficiency data for ice shape geometries. SLD ice shape data, in-flight and ground-based, for simulation verification. Aerodynamic performance data for 3D geometries and various icing conditions. Stability and control parameter data for iced aircraft configurations. Thermal ice protection system data for simulation validation.

Potapczuk, Mark↗

NASA NTRS2016

Exploration Clinical Decision Support System: Medical Data Architecture

The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear dimension biomarkers that enable image content-based retrieval and criteria assessment. In addition, a data mining engine (DME) is applied to cross-sectional adult surveys for predicting occurrence of renal calculi, ranked by statistical significance of demographics and specific food ingestion. In addition to this precursor space flight algorithm training, the DME will utilize a feature-engineering capability for unstructured clinical text classification health discovery. The ECDS backbone is a proposed multi-tier modular architecture providing data messaging protocols, storage, management and real-time patient data access. Technology demonstrations and success metrics will be finalized in FY16.

Biomedical support↗

NASA NTRS2018

A Laser-Induced Fluorescence Diagnostic for HERMeS and High-Power Electric Propulsion

NASA is continuing the development of a 12.5-kW Hall thruster system, which is baselined in a phased exploration concept to expand human presence to cis-lunar space and eventually to Mars. The development team is transitioning knowledge gained from the testing of the government-built Technology Development Unit (TDU) to the contractor-built Engineering Development Unit (EDU). A new laser-induced fluorescence diagnostic that is compatible with the testing of engineering hardware was developed to obtain data for thruster model validation in the lowest background pressure achievable. Prior to performing the test on the EDU, the team performed a functional checkout test of this new diagnostic using the TDU. In addition to providing a checkout of the diagnostic, this test provided data that can be correlated to electron mobility for comparison to the EDU at a later date. A number of technical challenges related to large test facilities and interfacing with engineering hardware were overcome while implementing the new laser diagnostic system. The initial data set was in good agreement with prior optical and non-optical diagnostics data collected on the TDU thrusters. This data set also revealed the spatial origin of high angle ions that have been of concern for spacecraft integration.

Huang, Wensheng↗

NASA NTRS2018

Ion Velocity in the Discharge Channel and Near-Field of the HERMeS Hall Thruster

NASA is continuing the development of a 12.5-kW Hall thruster system, which is baselined in a phased exploration concept to expand human presence to cis-lunar space and eventually to Mars. The development team is transitioning knowledge gained from the testing of the government-built Technology Development Unit (TDU) to the contractor-built Engineering Development Unit (EDU). A new laser-induced fluorescence diagnostic that is compatible with the testing of engineering hardware was developed to obtain data for thruster model validation in the lowest background pressure achievable. Prior to performing the test on the EDU, the team performed a functional checkout test of this new diagnostic using the TDU. In addition to providing a checkout of the diagnostic, this test provided data that can be correlated to electron mobility for comparison to the EDU at a later date. A number of technical challenges related to large test facilities and interfacing with engineering hardware were overcome while implementing the new laser diagnostic system. The initial data set was in good agreement with prior optical and non-optical diagnostics data collected on the TDU thrusters. This data set also revealed the spatial origin of high angle ions that have been of concern for spacecraft integration.

Huang, Wensheng↗

NASA NTRS2018

A Laser-Induced Fluorescence Diagnostic for HERMeS and High-Power Electric Propulsion

NASA is continuing the development of a 12.5-kW Hall thruster system, which is baselined in a phased exploration concept to expand human presence to cis-lunar space and eventually to Mars. The development team is transitioning knowledge gained from the testing of the government-built Technology Development Unit (TDU) to the contractor-built Engineering Development Unit (EDU). A new laser-induced fluorescence diagnostic that is compatible with the testing of engineering hardware was developed to obtain data for thruster model validation in the lowest background pressure achievable. Prior to performing the test on the EDU, the team performed a functional checkout test of this new diagnostic using the TDU. In addition to providing a checkout of the diagnostic, this test provided data that can be correlated to electron mobility for comparison to the EDU at a later date. A number of technical challenges related to large test facilities and interfacing with engineering hardware were overcome while implementing the new laser diagnostic system. The initial data set was in good agreement with prior optical and non-optical diagnostics data collected on the TDU thrusters. This data set also revealed the spatial origin of high angle ions that have been of concern for spacecraft integration.

Huang, Wensheng↗

NASA NTRS2018

Ion Velocity in the Discharge Channel and Near-Field of the HERMeS Hall Thruster

NASA is continuing the development of a 12.5-kW Hall thruster system, which is baselined in a phased exploration concept to expand human presence to cis-lunar space and eventually to Mars. The development team is transitioning knowledge gained from the testing of the government-built Technology Development Unit (TDU) to the contractor-built Engineering Development Unit (EDU). A new laser-induced fluorescence diagnostic that is compatible with the testing of engineering hardware was developed to obtain data for thruster model validation in the lowest background pressure achievable. Prior to performing the test on the EDU, the team performed a functional checkout test of this new diagnostic using the TDU. In addition to providing a checkout of the diagnostic, this test provided data that can be correlated to electron mobility for comparison to the EDU at a later date. A number of technical challenges related to large test facilities and interfacing with engineering hardware were overcome while implementing the new laser diagnostic system. The initial data set was in good agreement with prior optical and non-optical diagnostics data collected on the TDU thrusters. This data set also revealed the spatial origin of high angle ions that have been of concern for spacecraft integration.

Huang, Wensheng↗

NASA NTRS2018

Ion Velocity in the Discharge Channel and Near-Field of the HERMeS Hall Thruster

NASA is continuing the development of a 12.5-kW Hall thruster system, which is baselined in a phased exploration concept to expand human presence to cis-lunar space and eventually to Mars. The development team is transitioning knowledge gained from the testing of the government-built Technology Development Unit (TDU) to the contractor-built Engineering Development Unit (EDU). A new laser-induced fluorescence diagnostic that is compatible with the testing of engineering hardware was developed to obtain data for thruster model validation in the lowest background pressure achievable. Prior to performing the test on the EDU, the team performed a functional checkout test of this new diagnostic using the TDU. In addition to providing a checkout of the diagnostic, this test provided data that can be correlated to electron mobility for comparison to the EDU at a later date. A number of technical challenges related to large test facilities and interfacing with engineering hardware were overcome while implementing the new laser diagnostic system. The initial data set was in good agreement with prior optical and non-optical diagnostics data collected on the TDU thrusters. This data set also revealed the spatial origin of high angle ions that have been of concern for spacecraft integration.

Huang, Wensheng↗

NASA NTRS2007

Automated Diagnosis and Control of Complex Systems

Livingstone2 is a reusable, artificial intelligence (AI) software system designed to assist spacecraft, life support systems, chemical plants, or other complex systems by operating with minimal human supervision, even in the face of hardware failures or unexpected events. The software diagnoses the current state of the spacecraft or other system, and recommends commands or repair actions that will allow the system to continue operation. Livingstone2 is an enhancement of the Livingstone diagnosis system that was flight-tested onboard the Deep Space One spacecraft in 1999. This version tracks multiple diagnostic hypotheses, rather than just a single hypothesis as in the previous version. It is also able to revise diagnostic decisions made in the past when additional observations become available. In such cases, Livingstone might arrive at an incorrect hypothesis. Re-architecting and re-implementing the system in C++ has increased performance. Usability has been improved by creating a set of development tools that is closely integrated with the Livingstone2 engine. In addition to the core diagnosis engine, Livingstone2 includes a compiler that translates diagnostic models written in a Java-like language into Livingstone2's language, and a broad set of graphical tools for model development.

Kurien, James↗

NASA NTRS1989

CONFIG - Adapting qualitative modeling and discrete event simulation for design of fault management systems

CONFIG is a modeling and simulation tool prototype for analyzing the normal and faulty qualitative behaviors of engineered systems. Qualitative modeling and discrete-event simulation have been adapted and integrated, to support early development, during system design, of software and procedures for management of failures, especially in diagnostic expert systems. Qualitative component models are defined in terms of normal and faulty modes and processes, which are defined by invocation statements and effect statements with time delays. System models are constructed graphically by using instances of components and relations from object-oriented hierarchical model libraries. Extension and reuse of CONFIG models and analysis capabilities in hybrid rule- and model-based expert fault-management support systems are discussed.

Malin, Jane T.↗

NASA NTRS2009

Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study

Automated diagnosis and reconfiguration are important computational techniques that aim to minimize human intervention in autonomous systems. In this paper, we develop novel techniques and models in the context of diagnosis and reconfiguration reasoning using causal Bayesian networks (BNs). We take as starting point a successful diagnostic approach, using a static BN developed for a real-world electrical power system. We discuss in this paper the extension of this diagnostic approach along two dimensions, namely: (i) from a static BN to a dynamic BN; and (ii) from a diagnostic task to a reconfiguration task. More specifically, we discuss the auto-generation of a dynamic Bayesian network from a static Bayesian network. In addition, we discuss subtle, but important, differences between Bayesian networks when used for diagnosis versus reconfiguration. We discuss a novel reconfiguration agent, which models a system causally, including effects of actions through time, using a dynamic Bayesian network. Though the techniques we discuss are general, we demonstrate them in the context of electrical power systems (EPSs) for aircraft and spacecraft. EPSs are vital subsystems on-board aircraft and spacecraft, and many incidents and accidents of these vehicles have been attributed to EPS failures. We discuss a case study that provides initial but promising results for our approach in the setting of electrical power systems.

Knox, W. Bradley↗

NASA NTRS1999

Control of Mixing and Reactive Flow Processes

The interdisciplinary field of reactive flow control is one that holds a great deal of promise for the optimization of complex phenomena occurring in many practical systems, ranging from automobile and gas turbine engines to environmental thermal destruction systems. The fundamental underpinnings of combustion control, however, require a detailed level of understanding of complex reactive flow phenomena, and, in the case of closed-loop active control, require the ability to sense (monitor) and actuate (manipulate) flow processes in a spatially distributed manner in "near real time". Hence the ultimate growth and success of the field of reactive flow control is intimately linked: 1) to advances in the understanding, simulation, and model reduction for complex reactive flows, 2) to the development of experimental diagnostic techniques, in particular, to the development of physically robust sensors, and 3) to the development of a framework or frameworks for generation of closed loop control algorithms suitable for unsteady, nonlinear reactive flow systems. The present paper seeks to outline the potential benefits and technical challenges that exist for mixing and combustion control in fundamental as well as practical systems and to identify promising research directions that could help meet these challenges.

Karagozian, A. R.↗

NASA NTRS2008

Inductive System Monitors Tasks

The Inductive Monitoring System (IMS) software developed at Ames Research Center uses artificial intelligence and data mining techniques to build system-monitoring knowledge bases from archived or simulated sensor data. This information is then used to detect unusual or anomalous behavior that may indicate an impending system failure. Currently helping analyze data from systems that help fly and maintain the space shuttle and the International Space Station (ISS), the IMS has also been employed by data classes are then used to build a monitoring knowledge base. In real time, IMS performs monitoring functions: determining and displaying the degree of deviation from nominal performance. IMS trend analyses can detect conditions that may indicate a failure or required system maintenance. The development of IMS was motivated by the difficulty of producing detailed diagnostic models of some system components due to complexity or unavailability of design information. Successful applications have ranged from real-time monitoring of aircraft engine and control systems to anomaly detection in space shuttle and ISS data. IMS was used on shuttle missions STS-121, STS-115, and STS-116 to search the Wing Leading Edge Impact Detection System (WLEIDS) data for signs of possible damaging impacts during launch. It independently verified findings of the WLEIDS Mission Evaluation Room (MER) analysts and indicated additional points of interest that were subsequently investigated by the MER team. In support of the Exploration Systems Mission Directorate, IMS is being deployed as an anomaly detection tool on ISS mission control consoles in the Johnson Space Center Mission Operations Directorate. IMS has been trained to detect faults in the ISS Control Moment Gyroscope (CMG) systems. In laboratory tests, it has already detected several minor anomalies in real-time CMG data. When tested on archived data, IMS was able to detect precursors of the CMG1 failure nearly 15 hours in advance of the actual failure event. In the Aeronautics Research Mission Directorate, IMS successfully performed real-time engine health analysis. IMS was able to detect simulated failures and actual engine anomalies in an F/A-18 aircraft during the course of 25 test flights. IMS is also being used in colla

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NASA NTRS1993

Chemistry and transport in a multi-dimensional model

The focus of our research program is the achievement of a quantitative understanding of the spatial distribution and temporal variation of chemical species in the terrestrial middle atmosphere, with emphasis on ozone. Although not directed at assessments of anthropogenic impacts, our activities contribute to a refinement of model descriptions of chemical and dynamical processes that are needed for assessment tasks. A unique feature of our research effort is a close interaction with the chemical kinetics group at JPL and the field measurement groups at JPL. The principal tools used in our investigations are l-D and 2-D photochemical models. The advective component of the meridional transport in these models is approximated by the diabatic circulation, which is derived diagnostically from the net radiative heating rates. We are developing accurate radiative transfer algorithms to find the net heating rates and the diabatic circulation for use in the 2-D model.

Yung, Yuk L.↗

NASA NTRS1984

A relational approach to the development of expert diagnostic systems

The proposition that, given a structural and/or functional description of any real or abstract system, an expert system can be built based on this description is examined. First, a model is developed for a microprocessor-controlled end effector/sensor system using a modeling approach called a relational Knowledge-Base Machine (RKBM). Next, an explanation of how the end effector model could be used for the error diagnosis on the operational end effector is given and two versions of an error diagnosis algorithm based on the model are presented. Finally, areas of further research are described that are necessary before an expert system using this approach becomes a reality.

Ames, K. R.↗

NASA NTRS2002

Project to Interface Climate Modeling on Global and Regional Scales with Earth Observing (EOS) Observations

This ten-year NASA IDS project began in 1990. Its initial work plan adopted the NASA provided timeline that data would become available for new Earth Observing System (EOS) platforms beginning in 1995. Over its first phase, it was based at NCAR, which had submitted the original proposal and involved activities of a substantial number of co-investigators at NCAR who engaged in research over several areas related to the observations expected to be received from the EOS platforms. Their focus was the theme of use of EOS data for improving climate models for projecting global change. From the climate system viewpoint, the IDS addressed land, clouds-hydrological cycle, radiative fluxes and especially aerosol impacts, ocean and sea-ice, and stratosphere. Other research addressed issues of data assimilation, diagnostic analyses, and data set development from current satellite systems, especially use of SAR data for climate models.

Dickinson, Robert E.↗