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Report describes approach that uses computer model and can determine configurations with optimum reliability and least cost. Approach in application to modelling computer-controlled data management systems differs from conventional reliability analysis in that it considers systems organized around data base and looks at systems from equipment level rather than from component level.
In order to provide a basis for estimating the expected support required of new systems during their conceptual design phase, Langley Research Center has recently collected Shuttle Orbiter reliability and maintainability data from the various data base sources at Kennedy Space Center. This information was analyzed to provide benchmarks, trends, and distributions to aid in the analysis of new designs. This paper presents a summation of those results and an initial interpretation of the findings.
This paper describes the problems involved in uplink of data from control centers on the ground to spacecraft, and explores the solutions to those problems, past. present. and future. The evolution of this process, from simple commanding to transfer of large volumes of data and commands is traced. The need for reliable end-to-end protocols for commanding and file transfer is demonstrated, and the shortcomings of both existing telecommand protocols and commercial products to meet this need are discussed. Recent developments in commercial protocols that may be adaptable to the mentioned operations environment are surveyed, and current efforts to develop a suite of protocols for reliable transfer in this environment are presented.
Mariner IV Space Data Automation System /SDAS/ computer reliability design, pellet component concept, testing, interconnection and welding techniques
Use of success and failure data in reliability engineering
Mechanized data reduction system has been designed to take advantage of the data handling capacity of computers and to reduce voluminous and unrelated test and performance data to a format useful for the rapid analysis of electronic component reliability.
For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.
Failure data role in management of launch operations reliability program
This document, Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis, is intended to provide guidelines for the collection and evaluation of risk and reliability-related data. It is aimed at scientists and engineers familiar with risk and reliability methods and provides a hands-on approach to the investigation and application of a variety of risk and reliability data assessment methods, tools, and techniques. This document provides both: A broad perspective on data analysis collection and evaluation issues. A narrow focus on the methods to implement a comprehensive information repository. The topics addressed herein cover the fundamentals of how data and information are to be used in risk and reliability analysis models and their potential role in decision making. Understanding these topics is essential to attaining a risk informed decision making environment that is being sought by NASA requirements and procedures such as 8000.4 (Agency Risk Management Procedural Requirements), NPR 8705.05 (Probabilistic Risk Assessment Procedures for NASA Programs and Projects), and the System Safety requirements of NPR 8715.3 (NASA General Safety Program Requirements).
A study undertaken to collect software error data of laboratory quality for use in the development of credible methods for predicting the reliability of software used in life-critical applications is summarized. The software error data reported were acquired through automated repetitive run testing of three independent implementations of a launch interceptor condition module of a radar tracking problem. The results are based on 100 test applications to accumulate a sufficient sample size for error rate estimation. The data collected is used to confirm the results of two Boeing studies reported in NASA-CR-165836 Software Reliability: Repetitive Run Experimentation and Modeling, and NASA-CR-172378 Software Reliability: Additional Investigations into Modeling With Replicated Experiments, respectively. That is, the results confirm the log-linear pattern of software error rates and reject the hypothesis of equal error rates per individual fault. This rejection casts doubt on the assumption that the program's failure rate is a constant multiple of the number of residual bugs; an assumption which underlies some of the current models of software reliability. data raises new questions concerning the phenomenon of interacting faults.
Goddard activities are reported for 1973. An eight-year flight schedule for projected space missions is presented. Data acquired by spacecraft in the following disciplines are described: stellar ultraviolet, stellar X-rays, stellar gamma rays, solar radiation, radio astronomy, particles/fields, magnetosphere, aurora, and the upper atmosphere.
No abstract available
This paper is the continuation of a paper presented at the 13th Probabilistic Safety Assessment and Management Conference, in which a methodology of modeling failure modes of complex components was presented; see Paulos and Smith (2016). This methodology is not particularly helpful in the space industry where there is a lack of failure data, but is more helpful in industries that see a lot of component repairs and improvements, such as in the aircraft or automotive industries. The previous paper demonstrated how the typical approach of treating failure modes as being exponential in nature may yield optimistic predictions when estimating how improvements to components will perform in the future. It is more accurate to model the failure modes as a race in time; unfortunately, this does not give a closed-form solution. This paper uses simulation to solve for the model of the world, and the results compared to the standard methodology of treating the failure modes as being exponential random failures. The standard method is shown to have optimistic predictions, which will lead to prediction errors when failure modes are removed or “fixed.” The failure mode methodology presented in the first paper treated the data as being censored when the test stopped. In this paper, we will compare the results from treating the data as both censored and missing.
A comprehensive study of the characteristics and capabilities of the Pioneer cosmic dust mission is presented to facilitate accurate astronomical adaptations of the data by independent researchers. The characteristics of the sensor and associated electronics as they relate to dynamic range, field of view, and penetration effects in the film are discussed, comparisons are made between flight and simulation data, and statistical analyses are made of the reliability of the flight data. It is shown that the measurements from the Pioneer experiment are highly reliable and provide a valuable contribution to man's knowledge of the meteoroid environment of the solar system.
The design of an automated SCR holding-current measurement system is described. The circuits used in the measurement system were designed to meet the major requirements of automatic data acquisition, reliability, and repeatability. Performance data are presented and compared with calibration data. The data verified the accuracy of the measurement system. Data taken over a 48-hr period showed that the measurement system operated satisfactorily and met all the design requirements.
The real time, low cost data acquisition communication network described features the use of asynchronous ASCII code transmissions operating at 30 characters per second on the dial-up telephone system. The network features an elaborate, but easily generated error checking system, operating in a line-by-line demand-response mode. The system is readily adaptable for any low speed computer-to-computer data transmissions requiring high reliability in data transmission. The network was developed for the acquisition of prelaunch wind data from the Eastern Test Range at Cape Kennedy.
Recursive equation defines probability-density function storing trends in noisy or potentially erroneous data. Part of algorithm for analysis of trends in data. Developed to determine reliability of data from sensor used to guide robot, and mathematical approach that it represents proves valuable in other applications. Enables computation of statistic (called "confidence statistic") indicating level of confidence in new datum. Generates confidence statistic high or low, depending on whether new datum consistent or inconsistent with previous trends.