scholarly journals Reassessment of Remaining Strength of Subsea Corroded Pipeline Using Bayesian Updating

2015 ◽  
Vol 773-774 ◽  
pp. 221-225
Author(s):  
Zafarullah Nizamani ◽  
Zahiraniza Mustaffa
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Bayesian Updating ◽  
Probability Of Failure ◽  
Operating Pressure ◽  
Test Results ◽  
Strength Evaluation ◽  
Subsea Pipeline ◽  
Burst Test ◽  
Design Life

System strength evaluation of subsea pipeline, which has already completed its design life, is an important issue to deal with especially when hydrocarbon is the material to be transported. The remaining strength of pipeline in terms of probability of failure can be determined using assessment of maximum operating pressure and its capacity by using burst test results. Monte Carlo simulation is used to find probability of failure and then with burst test results the existing probability of failure can be updated using Bayesian updating technique.

scholarly journals Prediksi Pajak Mineral Non Logam dan Batuan dengan Metode Monte Carlo

2019 ◽  
pp. 32-37
Author(s):  
Julius Santony
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Regional Government ◽  
Test Results ◽  
Accuracy Rate ◽  
Work Plan ◽  
Tax Revenues ◽  
Average Accuracy ◽  
District Government

Regional government in Indonesia annually sets a target for tax revenues of non-metallic minerals and rocks. Setting targets is very important as a guideline in preparing the current year's budget work plan. So far, the target of non-metal mineral and rock tax revenues has been prepared based on a joint agreement between the regional government and the regional legislature. The prediction of non-metal mineral and rock tax revenues using Monte Carlo simulation can be a solution to predict the next few years. This prediction uses data between 2009 - 2018 taken from the tax and retribution management body one of the districts in Indonesia. Testing the results of predictions is done by comparing the results of predictions with data from 2016 - 2018. The test results show that the average accuracy rate reaches 82.05%. So this study greatly helped the district government in setting the target for the acceptance of non-metal minerals and rock taxes.

scholarly journals Non-deterministic Approach for Reliability Evaluation of Steel Portal Frame

2019 ◽  
Vol 5 (8) ◽  
pp. 1684-1697
Author(s):  
Hawraa Qasim Jebur ◽  
Salah Rohaima Al-Zaidee
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Structural Reliability ◽  
Limit State ◽  
Computational Cost ◽  
Probability Of Failure ◽  
Ultimate Limit State ◽  
Axial Forces ◽  
Portal Frame ◽  
Ultimate Limit

In recent years, more researches on structural reliability theory and methods have been carried out. In this study, a portal steel frame is considered. The reliability analysis for the frame is represented by the probability of failure, P_f, and the reliability index, β, that can be predicted based on the failure of the girders and columns. The probability of failure can be estimated dependent on the probability density function of two random variables, namely Capacity R, and Demand Q. The Monte Carlo simulation approach has been employed to consider the uncertainty the parameters of R, and Q. Matlab functions have been adopted to generate pseudo-random number for considered parameters. Although the Monte Carlo method is active and is widely used in reliability research, it has a disadvantage which represented by the requirement of large sample sizes to estimate the small probabilities of failure. This is leading to computational cost and time. Therefore, an Approximated Monte Carlo simulation method has been adopted for this issue. In this study, four performances have been considered include the serviceability deflection limit state, ultimate limit state for girder, ultimate limit state for the columns, and elastic stability. As the portal frame is a statically indeterminate structure, therefore bending moments, and axial forces cannot be determined based on static alone. A finite element parametric model has been prepared using Abaqus to deal with this aspect. The statistical analysis for the results samples show that all response data have lognormal distribution except of elastic critical buckling load which has a normal distribution.

Exit Condition for Probabilistic Assessment Using Monte Carlo Method

2010 ◽  
Vol 10 (1) ◽  
pp. 1-9
Author(s):  
Jakub Valihrach ◽  
Petr Konečný
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Optimization Design ◽  
Random Variable ◽  
Probability Of Failure ◽  
Probabilistic Assessment ◽  
Theoretical Derivation ◽  
The Monte Carlo Method ◽  
The Relationship

Exit Condition for Probabilistic Assessment Using Monte Carlo Method This paper introduces a condition used to exit a probabilistic assessment using the Monte Carlo simulation, and to evaluate it with regard to the relationship between the computed estimate of the probability of failure and the target design probability. The estimation of probability of failure is treated as a random variable, considering its variance that is dependent on the number of performed Monte Carlo simulation steps. After theoretical derivation of the decision condition, it is tested numerically with regard to its accuracy and computational efficiency. The condition is suitable for optimization design using the Monte Carlo method.

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