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— 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

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
Depositing User: Prof Dr Kurian V John
Date Deposited: 27 Oct 2011 00:31
Last Modified: 19 Jan 2017 08:22

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