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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Automation and robotics considerations for a lunar base

An envisioned lunar outpost shares with other NASA missions many of the same criteria that have prompted the development of intelligent automation techniques with NASA. Because of increased radiation hazards, crew surface activities will probably be even more restricted than current extravehicular activity in low Earth orbit. Crew availability for routine and repetitive tasks will be at least as limited as that envisioned for the space station, particularly in the early phases of lunar development. Certain tasks are better suited to the untiring watchfulness of computers, such as the monitoring and diagnosis of multiple complex systems, and the perception and analysis of slowly developing faults in such systems. In addition, mounting costs and constrained budgets require that human resource requirements for ground control be minimized. This paper provides a glimpse of certain lunar base tasks as seen through the lens of automation and robotic (A&R) considerations. This can allow a more efficient focusing of research and development not only in A&R, but also in those technologies that will depend on A&R in the lunar environment.

Sliwa, Nancy E.↗
NASA NTRS1988

An intelligent tutoring system for space shuttle diagnosis

An Intelligent Tutoring System (ITS) transcends conventional computer-based instruction. An ITS is capable of monitoring and understanding student performance thereby providing feedback, explanation, and remediation. This is accomplished by including models of the student, the instructor, and the expert technician or operator in the domain of interest. The space shuttle fuel cell is the technical domain for the project described below. One system, Microcomputer Intelligence for Technical Training (MITT), demonstrates that ITS's can be developed and delivered, with a reasonable amount of effort and in a short period of time, on a microcomputer. The MITT system capitalizes on the diagnostic training approach called Framework for Aiding the Understanding of Logical Troubleshooting (FAULT) (Johnson, 1987). The system's embedded procedural expert was developed with NASA's C-Language Integrated Production (CLIP) expert system shell (Cubert, 1987).

Johnson, William B.↗
NASA NTRS2009

High-Performance Algorithm for Solving the Diagnosis Problem

An improved method of model-based diagnosis of a complex engineering system is embodied in an algorithm that involves considerably less computation than do prior such algorithms. This method and algorithm are based largely on developments reported in several NASA Tech Briefs articles: The Complexity of the Diagnosis Problem (NPO-30315), Vol. 26, No. 4 (April 2002), page 20; Fast Algorithms for Model-Based Diagnosis (NPO-30582), Vol. 29, No. 3 (March 2005), page 69; Two Methods of Efficient Solution of the Hitting-Set Problem (NPO-30584), Vol. 29, No. 3 (March 2005), page 73; and Efficient Model-Based Diagnosis Engine (NPO-40544), on the following page. Some background information from the cited articles is prerequisite to a meaningful summary of the innovative aspects of the present method and algorithm. In model-based diagnosis, the function of each component and the relationships among all the components of the engineering system to be diagnosed are represented as a logical system denoted the system description (SD). Hence, the expected normal behavior of the engineering system is the set of logical consequences of the SD. Faulty components lead to inconsistencies between the observed behaviors of the system and the SD. Diagnosis the task of finding faulty components is reduced to finding those components, the abnormalities of which could explain all the inconsistencies. The solution of the diagnosis problem should be a minimal diagnosis, which is a minimal set of faulty components. The calculation of a minimal diagnosis is inherently a hard problem, the solution of which requires amounts of computation time and memory that increase exponentially with the number of components of the engineering system. Among the developments to reduce the computational burden, as reported in the cited articles, is the mapping of the diagnosis problem onto the integer-programming (IP) problem. This mapping makes it possible to utilize a variety of algorithms developed previously for IP to solve the diagnosis problem. In the IP approach, the diagnosis problem can be formulated as a linear integer optimization problem, which can be solved by use of well-developed integer-programming algorithms. This concludes the background information.

Fijany, Amir↗
NASA NTRS1975

A study of subsonic fan noise sources

Sources of noise in a 1.4 m (4.6 ft) diameter subsonic tip speed propulsive fan were studied using a combination of theoretical, experimental, and computer plotting techniques developed specially for noise diagnosis. To assess the structure of inlet turbulence, signals measured from pressure transducers on a rotor blade were plotted in a format to show the space-time history of inlet distortion. Ingested turbulence contained long, thin eddies which produce a tone-like noise component. Turbulence generated in the shroud boundary layer upstream of the rotor tips was found not to be an important noise source. However, this boundary layer does contain large amplitude disturbances caused by inlet turbulence which could be important in fans with thicker boundary layers. Theoretical calculations based on measured blade pressures show that rotor/inlet turbulence interaction and rotor/stator interaction are equally important sources of noise near the first three harmonics of blade passing frequency. At higher frequencies (above 2000 Hz) the rotor noise is dominant.

Hanson, D. B.↗
NASA NTRS1987

Applications of a detailed model of cardiac conduction to ventricular dysrhythmogenesis

In order to study transitions from normal patterns of electrical activity to abnormal patterns, such as ventricular activation, one requires a means to represent the state of myocardial electrical activation in a few parameters. Two parameters are presented here: 1) the net vorticity index (NVI) which is a measure of the net vorticity in a given region, and 2) the wavefront fractionation index (WFI), which is a measure of perturbations in the propagation of the electrical activation through the myocardium. Both parameters are topological measures in that normal propagation is condensed to a zero state, irrespective of smooth changes in wavefront orientation or shape. Several examples are demonstrated using a computer simulation of cardiac conduction. Potential applications to clinical diagnosis using experimentally obtainable data are discussed.

NASA Discipline Cardiopulmonary↗
NASA NTRS1972

Design of automata theory of cubical complexes with applications to diagnosis and algorithmic description

Methods for development of logic design together with algorithms for failure testing, a method for design of logic for ultra-large-scale integration, extension of quantum calculus to describe the functional behavior of a mechanism component-by-component and to computer tests for failures in the mechanism using the diagnosis algorithm, and the development of an algorithm for the multi-output 2-level minimization problem are discussed.

Roth, J. P.↗
NASA NTRS1989

Knowledge representation and user interface concepts to support mixed-initiative diagnosis

The Remote Maintenance Monitoring System (RMMS) provides automated support for the maintenance and repair of ModComp computer systems used in the Launch Processing System (LPS) at Kennedy Space Center. RMMS supports manual and automated diagnosis of intermittent hardware failures, providing an efficient means for accessing and analyzing the data generated by catastrophic failure recovery procedures. This paper describes the design and functionality of the user interface for interactive analysis of memory dump data, relating it to the underlying declarative representation of memory dumps.

Sobelman, Beverly H.↗
NASA NTRS1990

Autonomous control

KSC has been developing the Knowledge-Based Autonomous Test Engineer (KATE), which is a tool for performing automated monitoring, diagnosis, and control of electromechanical devices. KATE employs artificial intelligence computing techniques to perform these functions. The KATE system consists of a generic shell and a knowledge base. The KATE shell is the portion of the system which performs the monitoring, diagnosis, and control functions. It is generic in the sense that it is application independent. This means that the monitoring activity, for instance, will be performed with the same algorithms regardless of the particular physical device being used. The knowledge base is the portion of the system which contains specific functional and behavorial information about the physical device KATE is working with. Work is nearing completion on a project at KSC to interface a Texas Instruments Explorer running a LISP version of KATE with a Generic Checkout System (GCS) test-bed to control a physical simulation of a shuttle tanking system (humorously called the Red Wagon because of its color and mobility). The Autonomous Control System (ACS) project supplements and extends the KATE/GCS project by adding three other major activities. The activities include: porting KATE from the Texas Instruments Explorer machine to an Intel 80386-based UNIX workstation in the LISP language; rewriting KATE as necessary to run on the same 80386 workstation but in the Ada language; and investigating software and techniques to translate ANSI Standard Common LISP to Mil Standard Ada. Primary goals of this task are as follows: (1) establish the advantages of using expert systems to provide intelligent autonomous software for Space Station Freedom applications; (2) determine the feasibility of using Ada as the run-time environment for model-based expert systems; (3) provide insight into the advantages and disadvantagesof using LISP or Ada in the run-time environment for expert systems; and (4) compare the performance of the 80386 processor to a symbolic processor as a delivery vehicle for expert systems.

Brown, Barbara↗
NASA NTRS2010

An Event-Based Approach to Distributed Diagnosis of Continuous Systems

Distributed fault diagnosis solutions are becoming necessary due to the complexity of modern engineering systems, and the advent of smart sensors and computing elements. This paper presents a novel event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, based on a qualitative abstraction of measurement deviations from the nominal behavior. We systematically derive dynamic fault signatures expressed as event-based fault models. We develop a distributed diagnoser design algorithm that uses these models for designing local event-based diagnosers based on global diagnosability analysis. The local diagnosers each generate globally correct diagnosis results locally, without a centralized coordinator, and by communicating a minimal number of measurements between themselves. The proposed approach is applied to a multi-tank system, and results demonstrate a marked improvement in scalability compared to a centralized approach.

Daigle, Matthew↗
NASA NTRS1990

Fault diagnosis

The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to examine pilot mental models of the aircraft subsystems and their use in diagnosis tasks. Future research plans include piloted simulation evaluation of the diagnosis decision aiding concepts and crew interface issues. Information is given in viewgraph form.

Abbott, Kathy↗
DOE OSTI2021

PHYSICS-BASED AUTOMATED REASONING FOR HEALTH MONITORING: SENSOR SET SELECTION

This paper addresses the problem of how to select a sensor set for equipment health monitoring that meets the needs of advanced O&M tasks that target cost reduction. They include maintenance optimization and asset management for the existing fleet and near-autonomous operation as currently envisioned for advanced reactors. The method uses physics-based automated reasoning to provide for a more “explainable” diagnosis. The algorithm is described along with its implementation on a computational cluster. Preliminary results for application to a use case in the current fleet are described.

diagnosis↗
NASA NTRS1990

Object-oriented fault tree models applied to system diagnosis

When a diagnosis system is used in a dynamic environment, such as the distributed computer system planned for use on Space Station Freedom, it must execute quickly and its knowledge base must be easily updated. Representing system knowledge as object-oriented augmented fault trees provides both features. The diagnosis system described here is based on the failure cause identification process of the diagnostic system described by Narayanan and Viswanadham. Their system has been enhanced in this implementation by replacing the knowledge base of if-then rules with an object-oriented fault tree representation. This allows the system to perform its task much faster and facilitates dynamic updating of the knowledge base in a changing diagnosis environment. Accessing the information contained in the objects is more efficient than performing a lookup operation on an indexed rule base. Additionally, the object-oriented fault trees can be easily updated to represent current system status. This paper describes the fault tree representation, the diagnosis algorithm extensions, and an example application of this system. Comparisons are made between the object-oriented fault tree knowledge structure solution and one implementation of a rule-based solution. Plans for future work on this system are also discussed.

Iverson, David L.↗
NASA NTRS1997

Sequential Test Strategies for Multiple Fault Isolation

In this paper, we consider the problem of constructing near optimal test sequencing algorithms for diagnosing multiple faults in redundant (fault-tolerant) systems. The computational complexity of solving the optimal multiple-fault isolation problem is super-exponential, that is, it is much more difficult than the single-fault isolation problem, which, by itself, is NP-hard. By employing concepts from information theory and Lagrangian relaxation, we present several static and dynamic (on-line or interactive) test sequencing algorithms for the multiple fault isolation problem that provide a trade-off between the degree of suboptimality and computational complexity. Furthermore, we present novel diagnostic strategies that generate a static diagnostic directed graph (digraph), instead of a static diagnostic tree, for multiple fault diagnosis. Using this approach, the storage complexity of the overall diagnostic strategy reduces substantially. Computational results based on real-world systems indicate that the size of a static multiple fault strategy is strictly related to the structure of the system, and that the use of an on-line multiple fault strategy can diagnose faults in systems with as many as 10,000 failure sources.

Shakeri, M.↗
NASA NTRS1979

Monitoring and decision making by people in man machine systems

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Johannsen, G.↗
NASA NTRS1993

Program Diagnoses Nickel/Cadmium Batteries

Nickel Cadmium Battery Expert System-2 (NICBES2) computer program is prototype expert-system program for diagnosis and management of health of nickel/cadmium batteries. Intended to support evaluation of performance of batteries in Hubble Space Telescope spacecraft and to alert personnel to possible malfunctions. Oversees status of batteries by evaluating data gathered in orbit packets, and when so merits, raises alarm and provides diagnosis of faults as well as advice on actions to be taken to remedy condition giving rise to alarm. Provides history of statuses of batteries pertaining to health of batteries, and graphical display to help operator assimilate information generated. Written in C language.

Johnson, Yvette B.↗
NASA NTRS2005

Two Methods for Efficient Solution of the Hitting-Set Problem

A paper addresses much of the same subject matter as that of Fast Algorithms for Model-Based Diagnosis (NPO-30582), which appears elsewhere in this issue of NASA Tech Briefs. However, in the paper, the emphasis is more on the hitting-set problem (also known as the transversal problem), which is well known among experts in combinatorics. The authors primary interest in the hitting-set problem lies in its connection to the diagnosis problem: it is a theorem of model-based diagnosis that in the set-theory representation of the components of a system, the minimal diagnoses of a system are the minimal hitting sets of the system. In the paper, the hitting-set problem (and, hence, the diagnosis problem) is translated from a combinatorial to a computational problem by mapping it onto the Boolean satisfiability and integer- programming problems. The paper goes on to describe developments nearly identical to those summarized in the cited companion NASA Tech Briefs article, including the utilization of Boolean-satisfiability and integer- programming techniques to reduce the computation time and/or memory needed to solve the hitting-set problem.

Vatan, Farrokh↗
NASA NTRS2015

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

Leser, Patrick E.↗