scholarly journals RELIABILITY-BASED APPROACH FOR RESIDUAL LIFE PREDICTION OF BRIDGES SUBJECTED TO EARTHQUAKE SHOCKS DEGRADATION

Teras Jurnal ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 63
Author(s):  
Maizuar Maizuar ◽  
Said Jalalul Akbar ◽  
Wesli Wesli
Keyword(s):  
Extreme Events ◽  
Life Prediction ◽  
Residual Life ◽  
Numerical Procedure ◽  
Probability Of Failure ◽  
Time Dependent ◽  
Key Factors ◽  
Structural Capacity ◽  
Residual Life Prediction ◽  
Dependent Probability

<p>Structural degradation caused by sudden damaging extreme events (<em>e.g. </em>earthquake) has significant impact on residual life of bridges and ultimately the collapse of bridges. This paper presents a reliability-based approach of a bridge subjected to shock degradation caused by earthquake events. In particular, this study develops a numerical procedure for assessing time dependent probability of failure to estimate the residual life a bridge. Key factors that govern the residual life of a bridge (e.g., damage size caused by earthquake shocks and loss of initial structural capacity) were investigated. The results of study show that both damage size caused by earthquake shocks and loss of initial structural capacity are key factors that govern residual life of a bridge.</p><p> </p><p>Keywords: <em>residual life, earthquake, shock degradation, bridge</em>.</p>

PEMFC Residual Life Prediction Using Sparse Autoencoder-Based Deep Neural Network

2019 ◽  
Vol 5 (4) ◽  
pp. 1279-1293 ◽  
Author(s):  
Jiawei Liu ◽  
Qi Li ◽  
Ying Han ◽  
Guorui Zhang ◽  
Xiang Meng ◽  
...  
Keyword(s):  
Neural Network ◽  
Life Prediction ◽  
Deep Neural Network ◽  
Residual Life ◽  
Sparse Autoencoder ◽  
Residual Life Prediction

Time-Dependent Reliability Analysis of Vibratory Systems With Random Parameters

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
Zissimos P. Mourelatos ◽  
Monica Majcher ◽  
Vasileios Geroulas
Keyword(s):  
Large Scale ◽  
Probability Of Failure ◽  
Time Dependent ◽  
Total Probability ◽  
Conditional Probabilities ◽  
Random Parameters ◽  
Random Vibrations ◽  
Input Parameters ◽  
Total Probability Theorem ◽  
Dependent Probability

The field of random vibrations of large-scale systems with millions of degrees-of-freedom (DOF) is of significant importance in many engineering disciplines. In this paper, we propose a method to calculate the time-dependent reliability of linear vibratory systems with random parameters excited by nonstationary Gaussian processes. The approach combines principles of random vibrations, the total probability theorem, and recent advances in time-dependent reliability using an integral equation involving the upcrossing and joint upcrossing rates. A space-filling design, such as optimal symmetric Latin hypercube (OSLH) sampling, is first used to sample the input parameter space. For each design point, the corresponding conditional time-dependent probability of failure is calculated efficiently using random vibrations principles to obtain the statistics of the output process and an efficient numerical estimation of the upcrossing and joint upcrossing rates. A time-dependent metamodel is then created between the input parameters and the output conditional probabilities allowing us to estimate the conditional probabilities for any set of input parameters. The total probability theorem is finally applied to calculate the time-dependent probability of failure. The proposed method is demonstrated using a vibratory beam example.

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