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NASA NTRS1992

Thermal Expert System (TEXSYS): Systems autonomy demonstration project, volume 2. Results

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS testbed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Glass, B. J.↗
NASA NTRS1997

A Comprehensive Reliability Methodology for Assessing Risk of Reusing Failed Hardware Without Corrective Actions with and Without Redundancy

This paper deals with the development of a reliability methodology to assess the consequences of using hardware, without failure analysis or corrective action, that has previously demonstrated that it did not perform per specification. The subject of this paper arose from the need to provide a detailed probabilistic analysis to calculate the change in probability of failures with respect to the base or non-failed hardware. The methodology used for the analysis is primarily based on principles of Monte Carlo simulation. The random variables in the analysis are: Maximum Time of Operation (MTO) and operation Time of each Unit (OTU) The failure of a unit is considered to happen if (OTU) is less than MTO for the Normal Operational Period (NOP) in which this unit is used. NOP as a whole uses a total of 4 units. Two cases are considered. in the first specialized scenario, the failure of any operation or system failure is considered to happen if any of the units used during the NOP fail. in the second specialized scenario, the failure of any operation or system failure is considered to happen only if any two of the units used during the MOP fail together. The probability of failure of the units and the system as a whole is determined for 3 kinds of systems - Perfect System, Imperfect System 1 and Imperfect System 2. in a Perfect System, the operation time of the failed unit is the same as that of the MTO. In an Imperfect System 1, the operation time of the failed unit is assumed as 1 percent of the MTO. In an Imperfect System 2, the operation time of the failed unit is assumed as zero. in addition, simulated operation time of failed units is assumed as 10 percent of the corresponding units before zero value. Monte Carlo simulation analysis is used for this study. Necessary software has been developed as part of this study to perform the reliability calculations. The results of the analysis showed that the predicted change in failure probability (P(sub F)) for the previously failed units is as high as 49 percent above the baseline (perfect system) for the worst case. The predicted change in system P(sub F) for the previously failed units is as high as 36% for single unit failure without any redundancy. For redundant systems, with dual unit failure, the predicted change in P(sub F) for the previously failed units is as high as 16%. These results will help management to make decisions regarding the consequences of using previously failed units without adequate failure analysis or corrective action.

Putcha, Chandra S.↗
NASA NTRS1992

Thermal Expert System (TEXSYS): Systems automony demonstration project, volume 1. Overview

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS test bed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Glass, B. J.↗
NASA NTRS2010

NASA-DoD Lead-Free Electronics Project: Vibration Test

Vibration testing was conducted by Boeing Research and Technology (Seattle) for the NASA-DoD Lead-Free Electronics Solder Project. This project is a follow-on to the Joint Council on Aging Aircraft/Joint Group on Pollution Prevention (JCAA/JG-PP) Lead-Free Solder Project which was the first group to test the reliability of lead-free solder joints against the requirements of the aerospace/miLItary community. Twenty seven test vehicles were subjected to the vibration test conditions (in two batches). The random vibration Power Spectral Density (PSD) input was increased during the test every 60 minutes in an effort to fail as many components as possible within the time allotted for the test. The solder joints on the components were electrically monitored using event detectors and any solder joint failures were recorded on a Labview-based data collection system. The number of test minutes required to fail a given component attached with SnPb solder was then compared to the number of test minutes required to fail the same component attached with lead-free solder. A complete modal analysis was conducted on one test vehicle using a laser vibrometer system which measured velocities, accelerations, and displacements at one . hundred points. The laser vibrometer data was used to determine the frequencies of the major modes of the test vehicle and the shapes of the modes. In addition, laser vibrometer data collected during the vibration test was used to calculate the strains generated by the first mode (using custom software). After completion of the testing, all of the test vehicles were visually inspected and cross sections were made. Broken component leads and other unwanted failure modes were documented.

Woodrow, Thomas A.↗
NASA NTRS2011

Mars Science Laboratory Flight Software Internal Testing

The Mars Science Laboratory (MSL) team is sending the rover, Curiosity, to Mars, and therefore is physically and technically complex. During my stay, I have assisted the MSL Flight Software (FSW) team in implementing functional test scripts to ensure that the FSW performs to the best of its abilities. There are a large number of FSW requirements that have been written up for implementation; however I have only been assigned a few sections of these requirements. There are many stages within testing; one of the early stages is FSW Internal Testing (FIT). The FIT team can accomplish this with simulation software and the MSL Test Automation Kit (MTAK). MTAK has the ability to integrate with the Software Simulation Equipment (SSE) and the Mission Processing and Control System (MPCS) software which makes it a powerful tool within the MSL FSW development process. The MSL team must ensure that the rover accomplishes all stages of the mission successfully. Due to the natural complexity of this project there is a strong emphasis on testing, as failure is not an option. The entire mission could be jeopardized if something is overlooked.

entry, descent, and landing (EDL)↗
NASA NTRSDate not supplied

Application of the NASA Multiscale Analysis Tool: Multiscale Integration and Interoperability

In order to demonstrate NASMAT’s multiscale operability, a series of illustrative examples will be presented that focus on the application of NASMAT to practical problems. First, the multiscale integration and data recursion is demonstrated by performing a multiscale analysis using only built-in micromechanics methods. NASMAT’s integration is then highlighted by running a multiscale analysis where an external finite element software calls NASMAT. In this case, at each integration point within the finite element model, a local NASMAT analysis is performed to account for failure behavior at the constituent scale. In a similar example, an external program is called from within NASMAT. This case would be relevant for a user wanting to implement an outside micromechanics technique. A combination of these examples is then presented to further illustrate the code’s flexibility when interfacing with outside codes in a multiscale framework. For all examples, data is presented using a custom-developed visualization tool. Additional potential use cases are also addressed. Finally, the plan for upcoming features and added capabilities is discussed.

NASMAT↗
NASA NTRS2016

Tool for Generation of MAC/GMC Representative Unit Cell for CMC/PMC Analysis

This document describes a recently developed analysis tool that enhances the resident capabilities of the Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) 4.0. This tool is especially useful in analyzing ceramic matrix composites (CMCs), where higher fidelity with improved accuracy of local response is needed. The tool, however, can be used for analyzing polymer matrix composites (PMCs) as well. MAC/GMC 4.0 is a composite material and laminate analysis software developed at NASA Glenn Research Center. The software package has been built around the concept of the generalized method of cells (GMC). The computer code is developed with a user friendly framework, along with a library of local inelastic, damage, and failure models. Further, application of simulated thermomechanical loading, generation of output results, and selection of architectures to represent the composite material have been automated to increase the user friendliness, as well as to make it more robust in terms of input preparation and code execution. Finally, classical lamination theory has been implemented within the software, wherein GMC is used to model the composite material response of each ply. Thus, the full range of GMC composite material capabilities is available for analysis of arbitrary laminate configurations as well. The primary focus of the current effort is to provide a graphical user interface (GUI) capability that generates a number of different user-defined repeating unit cells (RUCs). In addition, the code has provisions for generation of a MAC/GMC-compatible input text file that can be merged with any MAC/GMC input file tailored to analyze composite materials. Although the primary intention was to address the three different constituents and phases that are usually present in CMCs-namely, fibers, matrix, and interphase-it can be easily modified to address two-phase polymer matrix composite (PMC) materials where an interphase is absent. Currently, the tool capability includes generation of RUCs for square packing, hexagonal packing, and random fiber packing as well as RUCs based on actual composite micrographs. All these options have the fibers modeled as having a circular cross-sectional area. In addition, a simplified version of RUC is provided where the fibers are treated as having a square cross section and are distributed randomly. This RUC facilitates a speedy analysis using the higher fidelity version of GMC known as HFGMC. The first four mentioned options above support uniform subcell discretization. The last one has variable subcell sizes due to the primary intention of keeping the RUC size to a minimum to gain the speed ups using the higher fidelity version of MAC. The code is implemented within the MATLAB (The Mathworks, Inc., Natick, MA) developmental framework; however, a standalone application that does not need a priori MATLAB installation is also created with the aid of the MATLAB compiler.

Materials Engineering↗
NASA NTRS1994

Flight test of takeoff performance monitoring system

The Takeoff Performance Monitoring System (TOPMS) is a computer software and hardware graphics system that visually displays current runway position, acceleration performance, engine status, and other situation advisory information to aid pilots in their decision to continue or to abort a takeoff. The system was developed at the Langley Research Center using the fixed-base Transport Systems Research Vehicle (TSRV) simulator. (The TSRV is a highly modified Boeing 737-100 research airplane.) Several versions of the TOPMS displays were evaluated on the TSRV B-737 simulator by more than 40 research, United States Air Force, airline and industry and pilots who rated the system satisfactory and recommended further development and testing. In this study, the TOPMS was flight tested on the TSRV. A total of 55 takeoff and 30 abort situations were investigated at 5 airfields. TOPMS displays were observed on the navigation display screen in the TSRV research flight deck during various nominal and off-nominal situations, including normal takeoffs; reduced-throttle takeoffs; induced-acceleration deficiencies; simulated-engine failures; and several gross-weight, runway-geometry, runway-surface, and ambient conditions. All tests were performed on dry runways. The TOPMS software executed accurately during the flight tests and the displays correctly depicted the various test conditions. Evaluation pilots found the displays easy to monitor and understand. The algorithm provides pretakeoff predictions of the nominal distances that are needed to accelerate the airplane to takeoff speed and to brake it to a stop; these predictions agreed reasonably well with corresponding values measured during several fully executed and aborted takeoffs. The TOPMS is operational and has been retained on the TSRV for general use and demonstration.

Middleton, David B.↗
NASA NTRS2006

Numerical Evaluation of Mode 1 Stress Intensity Factor as a Function of Material Orientation For BX-265 Foam Insulation Material

Foam; a cellular material, is found all around us. Bone and cork are examples of biological cell materials. Many forms of man-made foam have found practical applications as insulating materials. NASA uses the BX-265 foam insulation material on the external tank (ET) for the Space Shuttle. This is a type of Spray-on Foam Insulation (SOFI), similar to the material used to insulate attics in residential construction. This foam material is a good insulator and is very lightweight, making it suitable for space applications. Breakup of segments of this foam insulation on the shuttle ET impacting the shuttle thermal protection tiles during liftoff is believed to have caused the space shuttle Columbia failure during re-entry. NASA engineers are very interested in understanding the processes that govern the breakup/fracture of this complex material from the shuttle ET. The foam is anisotropic in nature and the required stress and fracture mechanics analysis must include the effects of the direction dependence on material properties. Material testing at NASA MSFC has indicated that the foam can be modeled as a transversely isotropic material. As a first step toward understanding the fracture mechanics of this material, we present a general theoretical and numerical framework for computing stress intensity factors (SIFs), under mixed-mode loading conditions, taking into account the material anisotropy. We present mode I SIFs for middle tension - M(T) - test specimens, using 3D finite element stress analysis (ANSYS) and FRANC3D fracture analysis software, developed by the Cornel1 Fracture Group. Mode I SIF values are presented for a range of foam material orientations. Also, NASA has recorded the failure load for various M(T) specimens. For a linear analysis, the mode I SIF will scale with the far-field load. This allows us to numerically estimate the mode I fracture toughness for this material. The results represent a quantitative basis for evaluating the strength and fracture properties of anisotropic foam insulation material.

Knudsen, Erik↗
NASA NTRS1978

SIFT - Design and analysis of a fault-tolerant computer for aircraft control

SIFT (Software Implemented Fault Tolerance) is an ultrareliable computer for critical aircraft control applications that achieves fault tolerance by the replication of tasks among processing units. The main processing units are off-the-shelf minicomputers, with standard microcomputers serving as the interface to the I/O system. Fault isolation is achieved by using a specially designed redundant bus system to interconnect the processing units. Error detection and analysis and system reconfiguration are performed by software. Iterative tasks are redundantly executed, and the results of each iteration are voted upon before being used. Thus, any single failure in a processing unit or bus can be tolerated with triplication of tasks, and subsequent failures can be tolerated after reconfiguration. Independent execution by separate processors means that the processors need only be loosely synchronized, and a novel fault-tolerant synchronization method is described.

Wensley, J. H.↗
NASA NTRS1983

Fault detection, isolation and reconfiguration in FTMP Methods and experimental results

The Fault-Tolerant Multiprocessor (FTMP) is a highly reliable computer designed to meet a goal of 10 to the -10th failures per hour and built with the objective of flying an active-control transport aircraft. Fault detection, identification, and recovery software is described, and experimental results obtained by injecting faults in the pin level in the FTMP are presented. Over 21,000 faults were injected in the CPU, memory, bus interface circuits, and error detection, masking, and error reporting circuits of one LRU of the multiprocessor. Detection, isolation, and reconfiguration times were recorded for each fault, and the results were found to agree well with earlier assumptions made in reliability modeling.

Lala, J. H.↗
NASA NTRS1993

The systems engineering overview and process (from the Systems Engineering Management Guide, 1990)

The past several decades have seen the rise of large, highly interactive systems that are on the forward edge of technology. As a result of this growth and the increased usage of digital systems (computers and software), the concept of systems engineering has gained increasing attention. Some of this attention is no doubt due to large program failures which possibly could have been avoided, or at least mitigated, through the use of systems engineering principles. The complexity of modern day weapon systems requires conscious application of systems engineering concepts to ensure producible, operable and supportable systems that satisfy mission requirements. Although many authors have traced the roots of systems engineering to earlier dates, the initial formalization of the systems engineering process for military development began to surface in the mid-1950s on the ballistic missile programs. These early ballistic missile development programs marked the emergence of engineering discipline 'specialists' which has since continued to grow. Each of these specialties not only has a need to take data from the overall development process, but also to supply data, in the form of requirements and analysis results, to the process. A number of technical instructions, military standards and specifications, and manuals were developed as a result of these development programs. In particular, MILSTD-499 was issued in 1969 to assist both government and contractor personnel in defining the systems engineering effort in support of defense acquisition programs. This standard was updated to MIL-STD499A in 1974, and formed the foundation for current application of systems engineering principles to military development programs.

Source record↗
NASA NTRS1995

Generic Health Management: A System Engineering Process Handbook Overview and Process

Health Management, a System Engineering Process, is one of those processes-techniques-and-technologies used to define, design, analyze, build, verify, and operate a system from the viewpoint of preventing, or minimizing, the effects of failure or degradation. It supports all ground and flight elements during manufacturing, refurbishment, integration, and operation through combined use of hardware, software, and personnel. This document will integrate Health Management Processes (six phases) into five phases in such a manner that it is never a stand alone task/effort which separately defines independent work functions.

Wilson, Moses Lee↗
NASA NTRS2010

Application of Diagnostic Analysis Tools to the Ares I Thrust Vector Control System

The NASA Ares I Crew Launch Vehicle is being designed to support missions to the International Space Station (ISS), to the Moon, and beyond. The Ares I is undergoing design and development utilizing commercial-off-the-shelf tools and hardware when applicable, along with cutting edge launch technologies and state-of-the-art design and development. In support of the vehicle s design and development, the Ares Functional Fault Analysis group was tasked to develop an Ares Vehicle Diagnostic Model (AVDM) and to demonstrate the capability of that model to support failure-related analyses and design integration. One important component of the AVDM is the Upper Stage (US) Thrust Vector Control (TVC) diagnostic model-a representation of the failure space of the US TVC subsystem. This paper first presents an overview of the AVDM, its development approach, and the software used to implement the model and conduct diagnostic analysis. It then uses the US TVC diagnostic model to illustrate details of the development, implementation, analysis, and verification processes. Finally, the paper describes how the AVDM model can impact both design and ground operations, and how some of these impacts are being realized during discussions of US TVC diagnostic analyses with US TVC designers.

Maul, William A.↗
NASA NTRS2005

Quadratic Programming for Allocating Control Effort

A computer program calculates an optimal allocation of control effort in a system that includes redundant control actuators. The program implements an iterative (but otherwise single-stage) algorithm of the quadratic-programming type. In general, in the quadratic-programming problem, one seeks the values of a set of variables that minimize a quadratic cost function, subject to a set of linear equality and inequality constraints. In this program, the cost function combines control effort (typically quantified in terms of energy or fuel consumed) and control residuals (differences between commanded and sensed values of variables to be controlled). In comparison with prior control-allocation software, this program offers approximately equal accuracy but much greater computational efficiency. In addition, this program offers flexibility, robustness to actuation failures, and a capability for selective enforcement of control requirements. The computational efficiency of this program makes it suitable for such complex, real-time applications as controlling redundant aircraft actuators or redundant spacecraft thrusters. The program is written in the C language for execution in a UNIX operating system.

Singh, Gurkirpal↗
NASA NTRS2012

Software Programs Derive Measurements from Photographs

Even under the most unfortunate circumstances, NASA continues on a path of innovation. After the Space Shuttle Columbia reentered the atmosphere on February 1, 2003, it experienced a catastrophic failure, and the entire crew and vehicle were lost. For the two weeks prior to the accident, Columbia STS-107 was on a mission to perform physical, life, and space sciences research in the unique environment of microgravity. Following the accident, the remaining shuttles - Endeavor, Atlantis, and Discovery - were grounded, and an intense investigation ensued. The Columbia Accident Investigation Board spent nearly 7 months examining the cause of the accident and determining what would ensure a safe return to flight. To this end, investigators performed an extensive review down five analytic paths: aerodynamic, thermodynamic, sensor data timeline, debris reconstruction, and imaging. As part of the evaluation of all the available imagery from Columbia's ascent, orbit, and entry, investigators needed a new method for analyzing still video images to determine the size of the material that fell from Columbia, as well as the distance that the material traveled. John Lane, a scientist at Kennedy Space Center, devised a software program to calculate the unknown dimension of the material in the images, and soon after the investigation was complete, continued to enhance the technology. Eventually, the program that assisted in the Columbia investigation became available for licensing.

Source record↗
NASA NTRS2007

Automated Detection of Events of Scientific Interest

A report presents a slightly different perspective of the subject matter of Fusing Symbolic and Numerical Diagnostic Computations (NPO-42512), which appears elsewhere in this issue of NASA Tech Briefs. Briefly, the subject matter is the X-2000 Anomaly Detection Language, which is a developmental computing language for fusing two diagnostic computer programs one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for real-time detection of events. In the case of the cited companion NASA Tech Briefs article, the contemplated events that one seeks to detect would be primarily failures or other changes that could adversely affect the safety or success of a spacecraft mission. In the case of the instant report, the events to be detected could also include natural phenomena that could be of scientific interest. Hence, the use of X- 2000 Anomaly Detection Language could contribute to a capability for automated, coordinated use of multiple sensors and sensor-output-data-processing hardware and software to effect opportunistic collection and analysis of scientific data.

James, Mark↗