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Base Shear and Collapse Capacity Statistical Analysis

Azman, Mohd Fadly and Kurian, V.J. and Liew, Mohd Shahir (2011) Base Shear and Collapse Capacity Statistical Analysis. In: International Symposium on Business, Engineering and Industrial applications ISBEIA 2011, 25-28 September 2011, Langkawi.

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Abstract

Abstract— As part of structural reliability assessment, the statistical analysis provides engineers with good estimation of distribution and statistical properties for both load and resistance. This study involved modelling of eight (8) offshore structures with the corresponding environmental conditions for ten (10), fifty (50) and hundred (100) years in order to perform non-linear push over analysis for getting the ultimate strength. The environmental condition covers three main oil and gas regions in Malaysia. The collective results of base shear and collapse capacity were used for statistical analysis. The data were analyzed using probability density function with central limit theorem under Gaussian distribution. All the statistical parameters such as mean value (μ), standard deviation (σ) and variance (V) were calculated. The average base shear from the statistical analysis has been obtained as 3.03 MN with a standard deviation of 3.35 and variance of 11.26. For the resistance part, the mean collapse capacity has been obtained as 18.28 MN with a standard deviation of 18.10 and variance of 327.93. This meant that for general case, the structural resistance is higher than the environmental loading. Using probability density function, the reliability index (β) was estimated through robust calculation between statistical parameters of load and resistance. From this calculation, reliability index (β) has been estimated as 3.97. I

Item Type:Conference or Workshop Item (Paper)
Subjects:T Technology > TC Hydraulic engineering. Ocean engineering
T Technology > TA Engineering (General). Civil engineering (General)
Departments / MOR / COE:Departments > Civil Engineering
ID Code:6555
Deposited By: Prof Dr Kurian V John
Deposited On:27 Oct 2011 00:31
Last Modified:19 Jan 2017 08:22

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