System reliability analysis of spatial variance frames based on random field and stochastic elastic modulus reduction method

2011 ◽  
Vol 223 (1) ◽  
pp. 109-124 ◽  
Author(s):  
Lu Feng Yang ◽  
Bo Yu ◽  
J. Woody Ju
Keyword(s):  
Elastic Modulus ◽  
Random Field ◽  
Reliability Analysis ◽  
System Reliability ◽  
Reduction Method ◽  
Spatial Variance ◽  
System Reliability Analysis ◽  
Modulus Reduction

Computationally Efficient Reliability Analysis of Mechanisms Based on a Multiplicative Dimensional Reduction Method

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Xufang Zhang ◽  
Mahesh D. Pandey ◽  
Yimin Zhang
Keyword(s):  
Reliability Analysis ◽  
Dimensional Reduction ◽  
System Reliability ◽  
Reduction Method ◽  
Maximum Output ◽  
Computationally Efficient ◽  
Output Error ◽  
System Reliability Analysis ◽  
Dimensional Reduction Method ◽  
Fractional Moments

The paper presents a computationally efficient method for system reliability analysis of mechanisms. The reliability is defined as the probability that the output error remains within a specified limit in the entire target trajectory of the mechanism. This mechanism reliability problem is formulated as a series system reliability analysis that can be solved using the distribution of maximum output error. The extreme event distribution is derived using the principle maximum entropy (MaxEnt) along with the constraints specified in terms of fractional moments. To optimize the computation of fractional moments of a multivariate response function, a multiplicative form of dimensional reduction method (M-DRM) is developed. The main benefit of the proposed approach is that it provides full probability distribution of the maximal output error from a very few evaluations of the trajectory of mechanism. The proposed method is illustrated by analyzing the system reliability analysis of two planar mechanisms. Examples presented in the paper show that the results of the proposed method are fairly accurate as compared with the benchmark results obtained from the Monte Carlo simulations.

Time-Dependent System Reliability Analysis Using Random Field Discretization

2015 ◽  
Vol 137 (10) ◽  
Author(s):  
Zhen Hu ◽  
Sankaran Mahadevan
Keyword(s):  
Random Field ◽  
Reliability Analysis ◽  
System Reliability ◽  
Probability Of Failure ◽  
Two Dimensions ◽  
Time Dependent ◽  
Time Interval ◽  
System Reliability Analysis ◽  
Reliability Method ◽  
Time Dependent System

This paper proposes a novel and efficient methodology for time-dependent system reliability analysis of systems with multiple limit-state functions of random variables, stochastic processes, and time. Since there are correlations and variations between components and over time, the overall system is formulated as a random field with two dimensions: component index and time. To overcome the difficulties in modeling the two-dimensional random field, an equivalent Gaussian random field is constructed based on the probability equivalency between the two random fields. The first-order reliability method (FORM) is employed to obtain important features of the equivalent random field. By generating samples from the equivalent random field, the time-dependent system reliability is estimated from Boolean functions defined according to the system topology. Using one system reliability analysis, the proposed method can get not only the entire time-dependent system probability of failure curve up to a time interval of interest but also two other important outputs, namely, the time-dependent probability of failure of individual components and dominant failure sequences. Three examples featuring series, parallel, and combined systems are used to demonstrate the effectiveness of the proposed method.

scholarly journals ANALISIS KEANDALAN DAN SUSUT DAYA PENYULANG TABANAN SETELAH REKONFIGURASI

2018 ◽  
Vol 5 (2) ◽  
pp. 139
Author(s):  
Salman Al Farisi ◽  
Rukmi Sari Hartati ◽  
I Wayan Sukerayasa
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Reliability Index ◽  
Power Loss ◽  
Electrical System ◽  
Reliable System ◽  
Global Era ◽  
System Reliability Analysis ◽  
Interference Frequency ◽  
Index Value

The need for electricity in this global era is increasing, so that a more reliable electrical system is needed. A reliable system cannot be separated from interference, so there needs to be a system reliability analysis and power loss to the feeder by configuring the network. This research was conducted to find the reliability index value in the form of interference frequency and duration of interference (SAIFI and SAIDI). In one Tabanan feeder the results obtained exceed the standard so reconfiguration is performed Based on the analysis obtained before reconfiguration, the reliability index for SAIFI is 6,7456 (failure / year) and SAIDI is 11,4767 (hour / year) and power loss by 6,27 %. After reconfiguration of Tabanan feeder, the reliability index was better, for SAIFI is 5.2475 (disturbance / year) and SAIDI is 9,8798 (hour / year), the power loss was 2.82%. Sanggulan feeder is a new feeder reconfiguration result from Tabanan feeder, where the analysis was carried out to find out the reliability index of Sanggulan feeder, it was obtained the SAIFI value of 4.5753 (disturbance / year) and SAIDI of 9.5297 (hour / year) and power loss of 4,80%.

Sign in / Sign up

Export Citation Format

Share Document