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At least 19 records

Reliability estimation procedures and CARE: The Computer-Aided Reliability Estimation Program

Ultrareliable fault-tolerant onboard digital systems for spacecraft intended for long mission life exploration of the outer planets are under development. The design of systems involving self-repair and fault-tolerance leads to the companion problem of quantifying and evaluating the survival probability of the system for the mission under consideration and the constraints imposed upon the system. Methods have been developed to (1) model self-repair and fault-tolerant organizations; (2) compute survival probability, mean life, and many other reliability predictive functions with respect to various systems and mission parameters; (3) perform sensitivity analysis of the system with respect to mission parameters; and (4) quantitatively compare competitive fault-tolerant systems. Various measures of comparison are offered. To automate the procedures of reliability mathematical modeling and evaluation, the CARE (computer-aided reliability estimation) program was developed. CARE is an interactive program residing on the UNIVAC 1108 system, which makes the above calculations and facilitates report preparation by providing output in tabular form, graphical 2-dimensional plots, and 3-dimensional projections. The reliability estimation of fault-tolerant organization by means of the CARE program is described.

Mathur, F. P.↗

Inverter Reliability Estimation for Advanced Inverter Functionality

In the near future, grid operators are expected to regularly use advanced distributed energy resource (DER) functions, defined in IEEE 1547-2018, to perform a range of grid-support operations. Many of these functions adjust the active and reactive power of the device through commanded or autonomous modes, which will produce new stresses on the grid-interfacing power electronics components, such as DC/AC inverters. In previous work, multiple DER devices were instrumented to evaluate additional component stress under multiple reactive power setpoints. We utilize quasi-static time-series simulations to determine voltage-reactive power mode (volt-var) mission profile of inverters in an active power system. Mission profiles and loss estimates are then combined to estimate the reduction of the useful life of inverters from different reactive power profiles. It was found that the average lifetime reduction was approximately 0.15% for an inverter between standard unity power factor operation and the IEEE 1547 default volt-var curve based on thermal damage due to switching in the power transistors. For an inverter with an expected 20-year lifetime, the 1547 volt-var curve would reduce the expected life of the device by 12 days. This framework for determining an inverter's useful life from experimental and modeling data can be applied to any failure mechanism and advanced inverter operation.

component degradation↗

Computer-Aided Reliability Estimation

CARE III (Computer-Aided Reliability Estimation, Third Generation) helps estimate reliability of complex, redundant, fault-tolerant systems. Program specifically designed for evaluation of fault-tolerant avionics systems. However, CARE III general enough for use in evaluation of other systems as well.

Bavuso, S. J.↗

Computer-aided reliability estimation

Computer-aided reliability estimation (CARE) programs are developed to improve the tools available for estimating the reliability of fault-tolerant systems. A description is presented of a program, called CARE II, which was developed after the first program reported by Mathur (1971). Attention is given to the CARE II reliability model, the CARE II coverage model, and CARE II limitations which are to be rectified in CARE III. It is pointed out that the present coverage model in CARE II is extremely versatile. The major limitation is related to the burden placed on the user to determine the basic parameters from which the coverage calculations are made.

Stiffler, J. J.↗

User's guide to the Reliability Estimation System Testbed (REST)

The Reliability Estimation System Testbed is an X-window based reliability modeling tool that was created to explore the use of the Reliability Modeling Language (RML). RML was defined to support several reliability analysis techniques including modularization, graphical representation, Failure Mode Effects Simulation (FMES), and parallel processing. These techniques are most useful in modeling large systems. Using modularization, an analyst can create reliability models for individual system components. The modules can be tested separately and then combined to compute the total system reliability. Because a one-to-one relationship can be established between system components and the reliability modules, a graphical user interface may be used to describe the system model. RML was designed to permit message passing between modules. This feature enables reliability modeling based on a run time simulation of the system wide effects of a component's failure modes. The use of failure modes effects simulation enhances the analyst's ability to correctly express system behavior when using the modularization approach to reliability modeling. To alleviate the computation bottleneck often found in large reliability models, REST was designed to take advantage of parallel processing on hypercube processors.

Nicol, David M.↗

Program for computer aided reliability estimation

A computer program for estimating the reliability of self-repair and fault-tolerant systems with respect to selected system and mission parameters is presented. The computer program is capable of operation in an interactive conversational mode as well as in a batch mode and is characterized by maintenance of several general equations representative of basic redundancy schemes in an equation repository. Selected reliability functions applicable to any mathematical model formulated with the general equations, used singly or in combination with each other, are separately stored. One or more system and/or mission parameters may be designated as a variable. Data in the form of values for selected reliability functions is generated in a tabular or graphic format for each formulated model.

Mathur, F. P.↗

Mission Reliability Estimation for Repairable Robot Teams

A mission reliability estimation method has been designed to translate mission requirements into choices of robot modules in order to configure a multi-robot team to have high reliability at minimal cost. In order to build cost-effective robot teams for long-term missions, one must be able to compare alternative design paradigms in a principled way by comparing the reliability of different robot models and robot team configurations. Core modules have been created including: a probabilistic module with reliability-cost characteristics, a method for combining the characteristics of multiple modules to determine an overall reliability-cost characteristic, and a method for the generation of legitimate module combinations based on mission specifications and the selection of the best of the resulting combinations from a cost-reliability standpoint. The developed methodology can be used to predict the probability of a mission being completed, given information about the components used to build the robots, as well as information about the mission tasks. In the research for this innovation, sample robot missions were examined and compared to the performance of robot teams with different numbers of robots and different numbers of spare components. Data that a mission designer would need was factored in, such as whether it would be better to have a spare robot versus an equivalent number of spare parts, or if mission cost can be reduced while maintaining reliability using spares. This analytical model was applied to an example robot mission, examining the cost-reliability tradeoffs among different team configurations. Particularly scrutinized were teams using either redundancy (spare robots) or repairability (spare components). Using conservative estimates of the cost-reliability relationship, results show that it is possible to significantly reduce the cost of a robotic mission by using cheaper, lower-reliability components and providing spares. This suggests that the current design paradigm of building a minimal number of highly robust robots may not be the best way to design robots for extended missions.

Trebi-Ollennu, Ashitey↗

Using Finite-Element Analysis In Estimating Reliability

Method of estimating design survivability of structural component incorporates finite-element and probabilistic properties of materials. Involves evaluation of design parameters through direct comparisons of survivability of component expressed in terms of percentages of like components that survive at various lifetimes. Probabilistic properties of materials, given in terms of Weibull parameters, coupled with stress field computed by finite-element analysis to determine fatigue life based on initiation of cracks. Method applied to rotating disk containing bolt holes, representative of disks used in aerospace propulsion turbines. Also used in early stages of design process to optimize life-based designs, reducing testing of full-sized components needed to validate designs.

Zaretsky, Erwin V.↗

Reliability Estimation for One-Shot Devices (Rev. 1)

We present an engineering-oriented summary of statistical methods for estimation of the reliability (or equivalently, failure probability) of one-shot devices such as explosive detonators and other weapon components. Estimates may be given as single points or intervals, based on pass/fail tests, margin analysis, computational models, expert judgment, or a combination of these. We focus on highly reliable devices for which few or no failures are expected to occur in testing.

42 ENGINEERING↗

Automation of reliability evaluation procedures through CARE - The computer-aided reliability estimation program.

Description of an on-line interactive computer program called CARE (Computer-Aided Reliability Estimation) which can model self-repair and fault-tolerant organizations and perform certain other functions. Essentially CARE consists of a repository of mathematical equations defining the various basic redundancy schemes. These equations, under program control, are then interrelated to generate the desired mathematical model to fit the architecture of the system under evaluation. The mathematical model is then supplied with ground instances of its variables and is then evaluated to generate values for the reliability-theoretic functions applied to the model.

Mathur, F. P.↗

Reliability Estimation for Mission Extension NASA Approach/Recommendations

Present NASA's current and recommended concepts for Mission Extension and De-orbit reliability Methodologies. NASA's current and recommended approaches ensuring de-orbit requirements are not unnecessarily driving mission design efforts or adding incresed costs or risks to manufacturing solutions without providing benefit to missionsand will assist in moving reliability estimation from piece part performance estimates to component history and system-level testing based estimations.

SMA↗

Software analysis handbook: Software complexity analysis and software reliability estimation and prediction

This handbook documents the three software analysis processes the Space Station Software Analysis team uses to assess space station software, including their backgrounds, theories, tools, and analysis procedures. Potential applications of these analysis results are also presented. The first section describes how software complexity analysis provides quantitative information on code, such as code structure and risk areas, throughout the software life cycle. Software complexity analysis allows an analyst to understand the software structure, identify critical software components, assess risk areas within a software system, identify testing deficiencies, and recommend program improvements. Performing this type of analysis during the early design phases of software development can positively affect the process, and may prevent later, much larger, difficulties. The second section describes how software reliability estimation and prediction analysis, or software reliability, provides a quantitative means to measure the probability of failure-free operation of a computer program, and describes the two tools used by JSC to determine failure rates and design tradeoffs between reliability, costs, performance, and schedule.

Computer systems design↗

The conservativeness of reliability estimates based on instantaneous coverage

Reliability modeling must take into account two different types of phenomena, including the fault-occurrence behavior and the fault/error-handling behavior of a system. The effectiveness of the fault/error-handling behavior can be captured by instantaneous coverage probabilities. This paper has the objective to show that the assumption of instantaneous coverage leads to conservative predictions of system reliability for systems characterized by relatively long interevent times for fault occurrences and relatively short interevent times for fault/error-handling actions. The importance of this result is related to the fact that it can now be shown that model predictions based on instantaneous coverage are lower bounds on the true system reliability. Attention is given to a semi-Markov reliability model, instantaneous coverage approximations, the proof of conservative prediction, and the computation of coverage probabilities.

Mcgough, J.↗

Machine Learning-Driven Reliability Estimation of PV Inverters Considering Alert-Ambient Variability

Weather-induced spatio-temporal degradation limits outdoor PV inverter lifetime and reliability, necessitating advanced data analysis. This study employs a top-down, data-driven approach utilizing multiple machine learning (ML) algorithms to estimate inverter reliability in a 1.4 MW PV power plant, considering factors such as irradiance, humidity, temperature, time of day, and weather conditions. An extensive alert dataset from 17 identical inverters, including alert types, propagation, and frequency, reveals significant correlations with environmental factors and inverter output power, enabling the construction of a performance reliability model. Dual-stage supervised-ML models are evaluated for accuracy, with the ‘classification-regression’ model by an artificial neural network (ANN) tested on the averaged “Alert-Ambient” dataset, which is outperformed by ‘clustering-regression’ models using random forest (RF) and K-Nearest Neighbors (KNN) on individual inverter datasets. K-means clustering applies principal component analysis to reduce dimensions, achieving improved accuracy beyond the 80% achieved by ANN on the averaged dataset. Second-stage regression estimates inverter reliability with a mean square error of 0.0195 on the averaged dataset and as low as 0.002 on individual inverter datasets using RF. Furthermore, these findings highlight the method's suitability for estimating PV inverter output reliability under ambient conditions, essential for digital twin development and related applications.

14 SOLAR ENERGY↗