Quantifying the impact of correlated failures on system reliability by a simulation approach

Most reliability models assume that components and systems experience one failure mode. Several systems such as hardware, however, are prone to more than one mode of failure. Past two-failure mode research derives equations to maximize reliability or minimize cost by identifying the optimal number of components. However, many if not all of these equations are derived from models that make the simplifying assumption that components fail in a statistically independent manner. In this paper, models to assess the impact of correlation on two-failure mode system reliability and cost are developed and corresponding expressions for reliability and cost optimal designs derived. Our illustrations demonstrate that, despite correlation, the approach identifies reliability and cost optimal designs.

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Simulation approach to estimate the system reliability of a time-based capacitated flow network susceptible to correlated failures

Simulation Modelling Practice and Theory ◽

10.1016/j.simpat.2013.04.008 ◽

2013 ◽

Vol 36 ◽

pp. 74-83 ◽

Cited By ~ 1

Author(s):

Yi-Kuei Lin ◽

Lance Fiondella ◽

Ping-Chen Chang

Keyword(s):

System Reliability ◽

Simulation Approach ◽

Flow Network ◽

Correlated Failures

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Stochastic simulation for determining the design flood of cascade reservoir systems

Hydrology Research ◽

10.2166/nh.2011.002 ◽

2012 ◽

Vol 43 (1-2) ◽

pp. 54-63 ◽

Cited By ~ 6

Author(s):

Baohong Lu ◽

Huanghe Gu ◽

Ziyin Xie ◽

Jiufu Liu ◽

Lejun Ma ◽

...

Keyword(s):

Simulation Model ◽

Stochastic Simulation ◽

Southern China ◽

Flow Simulation ◽

Simulation Method ◽

Simulation Approach ◽

Design Flood ◽

Design Values ◽

Stochastic Simulation Model ◽

The Impact

Stochastic simulation is widely applied for estimating the design flood of various hydrosystems. The design flood at a reservoir site should consider the impact of upstream reservoirs, along with any development of hydropower. This paper investigates and applies a stochastic simulation approach for determining the design flood of a complex cascade of reservoirs in the Longtan watershed, southern China. The magnitude of the design flood when the impact of the upstream reservoirs is considered is less than that without considering them. In particular, the stochastic simulation model takes into account both systematic and historical flood records. As the reliability of the frequency analysis increases with more representative samples, it is desirable to incorporate historical flood records, if available, into the stochastic simulation model. This study shows that the design values from the stochastic simulation method with historical flood records are higher than those without historical flood records. The paper demonstrates the advantages of adopting a stochastic flow simulation approach to address design-flood-related issues for a complex cascade reservoir system.

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A Novel Design of Landing Gear Oleo Strut Damper Using MR Fluid for Aircraft and UAV’s

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.225.275 ◽

2012 ◽

Vol 225 ◽

pp. 275-280

Author(s):

Chandra B. Asthana ◽

Rama B. Bhat

Keyword(s):

Shock Absorber ◽

Fluid Viscosity ◽

Simulation Approach ◽

Body Frame ◽

Mr Fluid ◽

Orifice Area ◽

Aerial Vehicle ◽

Impact Kinetic Energy ◽

The Impact ◽

Novel Design

Most landing gears used in aircraft employ very efficient oleo-pneumatic dampers to absorb and dissipate the impact kinetic energy of the aircraft body frame. A single-acting shock absorber is most commonly used in the oleo strut that has a metering pin extending through the orifice, which can vary the orifice area upon compression and extension of the strut. This variation is adjusted by shaping the metering pin so that the strut load is fairly constant under dynamic loading. In this paper, it is proposed to further change the damping coefficient as a function of time in order to achieve a semi-active control of the aircraft vibrations during landing by using Magnetorheological (MR) fluid in the Oleo. With the metering pin designed for a nominal flight condition, further variation in the fluid viscosity would help achieve the optimal performance in off-nominal flight conditions. A simulation approach is employed to show the effect of different profiles for viscosity variation in the MR fluid. The utility of such a damper can be very well exploited to include different criteria such as the landing distance after touchdown. This type of system can be used also in Unmanned Aerial Vehicle (UAV) application where the focus of design may be to accomplish the task without the consideration of passenger comfort.

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Modeling multi-state system reliability analysis in a power station under fatal and nonfatal shocks: a simulation approach

International Journal of Quality & Reliability Management ◽

10.1108/ijqrm-07-2020-0244 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Mohammad Reza Pourhassan ◽

Sadigh Raissi ◽

Arash Apornak

Keyword(s):

Reliability Analysis ◽

System Reliability ◽

System Performance ◽

Failure Process ◽

State System ◽

Failure Behavior ◽

Simulation Approach ◽

Critical System ◽

Content Type ◽

System Reliability Analysis

PurposeIn some environments, the failure rate of a system depends not only on time but also on the system condition, such as vibrational level, efficiency and the number of random shocks, each of which causes failure. In this situation, systems can keep working, though they fail gradually. So, the purpose of this paper is modeling multi-state system reliability analysis in capacitor bank under fatal and nonfatal shocks by a simulation approach.Design/methodology/approachIn some situations, there may be several levels of failure where the system performance diminishes gradually. However, if the level of failure is beyond a certain threshold, the system may stop working. Transition from one faulty stage to the next can lead the system to more rapid degradation. Thus, in failure analysis, the authors need to consider the transition rate from these stages in order to model the failure process.FindingsThis study aims to perform multi-state system reliability analysis in energy storage facilities of SAIPA Corporation. This is performed to extract a predictive model for failure behavior as well as to analyze the effect of shocks on deterioration. The results indicate that the reliability of the system improved by 6%.Originality/valueThe results of this study can provide more confidence for critical system designers who are engaged on the proper system performance beyond economic design.

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THE MATRIX PROCEDURES FOR CALCULATION OF IMPORTANCE MEASURES

RADIOELECTRONIC AND COMPUTER SYSTEMS ◽

10.32620/reks.2019.4.08 ◽

2019 ◽

pp. 71-78

Author(s):

Elena Zaitseva ◽

Peter Sedlacek ◽

Andrej Forgac

Keyword(s):

Structure Function ◽

System Reliability ◽

Boolean Logic ◽

Mathematical Representation ◽

Complex Concept ◽

System Components ◽

The Matrix ◽

Importance Analysis ◽

The Impact ◽

Fixed System

System reliability/availability is a complex concept that is evaluated based on numerous indices and measures. There are different methods for the calculation of these indices and measures in reliability analysis. Some of the most used indices are important measures. These measures allow us to evaluate the influence of fixed system components or set of components to the system reliability/availability. Importance measures are used today to allow for various aspects of the impact of system elements on its failure or operability. Analysis of element importance is used in the system design, diagnosis, and optimization. In this paper new algorithms for the calculation, some of the important measures are developed based on the matrix procedures. This paper's goal is the development of a new algorithm to calculate importance measures of the system based on the matrix procedures that can be transformed in the parallel procedures/algorithms. These algorithms are developed based on the application of Logical Differential Calculus of Boolean logic for the important analysis of the system. The application of parallel algorithms in importance analysis allows the evaluation of the system of large dimensions. Importance specific of the proposed matrix procedures for calculation of importance measures is the application of structure-function for the mathematical representation of the investigated system. This function defined the correlation of the system components states and system reliability/ availability. The structure-function, in this case, is defined as a truth vector to be used in the matrix transformation. The truth vector of a Boolean function is a column of the truth table of function if the values of the variables are lexicographically ordered. Therefore, the structure-function of any system can be represented by the truth vector of 2n elements un-ambiguously.

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The impact of nonresponse in different survey stages on the precision of prevalence estimates for multi-stage survey studies

BMC Research Notes ◽

10.1186/s13104-021-05840-0 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Ming Ma ◽

Sophie Rosenberg ◽

Alexander M. Kaizer

Keyword(s):

Survey Research ◽

State Level ◽

Simulation Approach ◽

Multi Stage ◽

Margin Of Error ◽

Prevalence Estimates ◽

Three Stages ◽

Nonresponse Rate ◽

The Mean ◽

The Impact

Abstract Objective While it is known that nonresponse might produce biased results and impair the precision of results in survey research studies, the pattern of the impact on the precision of estimates due to the nonresponse in different survey stages is historically overlooked. Having this type of information is essential when creating recruitment plans. This study proposes to examine and compare the effect of nonresponse in different stages on the precision of prevalence estimates in multi-stage survey studies. Based on data from a state level survey, a simulation approach was used to generate datasets with different nonresponse rates in three stages. The margin of error was then compared between the datasets with nonresponse at three different survey stages for 12 outcomes. Results At the same nonresponse rate, the mean margin of error was greater for the data with nonresponse at higher stages. Additionally, as the nonresponse rate increased, precision was more inflated within the data with higher stage nonresponse. This suggests that the effort used to recruit the primary sampling units is more crucial to improve the precision of estimates in multi-stage survey studies.

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An Overview of Various Importance Measures of Reliability System

International Journal of Mathematical Engineering and Management Sciences ◽

10.33889/ijmems.2017.2.3-014 ◽

2017 ◽

Vol 2 (3) ◽

pp. 150-171 ◽

Cited By ~ 6

Author(s):

Kalpesh P. Amrutkar ◽

Kirtee K. Kamalja

Keyword(s):

Reliability Analysis ◽

System Reliability ◽

System Failure ◽

Numerical Rank ◽

Reliability Improvement ◽

System Reliability Analysis ◽

Component Importance ◽

Critical Components ◽

The Impact ◽

Reliability Systems

One of the purposes of system reliability analysis is to identify the weaknesses or the critical components in a system and to quantify the impact of component’s failures. Various importance measures are being introduced by many researchers since 1969. These component importance measures provide a numerical rank to determine which components are more important to system reliability improvement or more critical to system failure. In this paper, we overview various components importance measures and briefly discuss them with examples. We also discuss some other extended importance measures and review the developments in study of various importance measures with respect to some of the popular reliability systems.

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Measuring Market Risk of Commercial Banks Implementing VaR with Historical Simulation Approach

10.47260/jafb/1144 ◽

2021 ◽

pp. 79-99

Author(s):

Minhaz-Ul Haq

Keyword(s):

Stock Prices ◽

Commercial Banks ◽

Value At Risk ◽

First Generation ◽

Market Risk ◽

Jel Classification ◽

Simulation Approach ◽

Share Prices ◽

Historical Simulation ◽

The Impact

This paper attempts to picture the impact of the market risk of ten commercial banks located in Bangladesh with the help of a non-parametric model known as the Historical Simulation Approach over the course of eight years. These banks' daily stock prices were used as inputs and analyzed in Microsoft Excel by means of Percentile and LN function. The study revealed market risk exposure as third, second-and first-generation banks from the least to the highest. It also pointed out the ups and downs of these banks' share prices in the selected period. Further analysis showed the portfolio VaR estimation for different time intervals. JEL classification numbers: G32. Keywords: Value-at-risk, Historical Simulation, Market Risk, Confidence Interval.

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