Comparison Of Uncertainty Methods For Pipe Deflection Calculation

Abstract

Reliability of pipe structure is one aspect to be considered in reactor safety analysis. MSC NASTRAN is a computer code that can be used to calculate pipe deflection for reliability evaluation. MSC PATRAN can be used to generate input for this code. Uncertainty evaluation needs to be done in the input variable to understand uncertainty range in the analysis results. A computer code for evaluating structure reliability has been developed in our previous study. The code has implemented latin hypercube sampling (LHS) to assess uncertainty in the input variable, such as load and modulus of elasticity. In this study, comparison of two uncertainty methods, i.e. simple random sampling (SRS) and LHS, was carried out for the developed software. The comparison was subjected to pipe deflection calculation using 100 samples. Comparison analysis shows that LHS method produces a robust mean of variance for all sample size. The results also confirm that variance of pipe deflection using LHS is smaller by 3% than SRS one. It can be concluded that LHS is appropriate to be implemented for uncertainty analysis in the developed code.

 

References
D. P VAKHARIA, MOHD FAROOQ A, “Determination of maximum span between pipe supports using maximum bending stress theory”, International Journal of Recent Trends in Engineering Vol. 1, No. 6, 2009.


[2] ENTIN HARTINI, ROZIQ HIMAWAN dan N. A Wahanani, “Pengembangan Perangkat Lunak Analisis Ketidakpastian Pada Perhitungan Struktur Material”, Prosiding Seminar Nasional MIPA 2014, Seminar Nasional MIPA 2014 FMIPA Universitas Padjadjaran.


[3] M. R. M AKRAMIN, A. ZULKIFLI, A. K AMIRUDIN, N. A ALANG dan M. S JADIN, “Hybrid Finite Element and Monte Carlo Analysis of Cracked Pipe, National Conference in Mechanical Engineering Research and Postgraduate Studies (2nd NCMER 2010), 2010.


[4] J. C HELTON, F. J DAVIS, J. D JHONSON, “A Comparison of uncertainty and sensitivity analysis results obtained with random and Latin hypercube sampling “, Reliability Engineering and System Safety 89 (2005) 305 -330.


[5] J. C HELTON, J. D JOHNSON, C. J SALLABERRY, C. B STORLIE, “Survey of Sampling based method for uncertainty and sensitivity analysis”, Reliability Engineering and System Safety 91 (2006) 1175 – 1209.


[6] PAUL E. HESS, DANIEL BRUCHMAN,IBRAHIM A. ASSAKKAF, BILAL M. AYYUB, “Uncertainties in Material Strength, Geometric, and Load Variables”,Naval Engineer Journal, Volume 114, Issue 2, pages 139-166, April 2002.


[7] M. V RAMA RAO dan R. RAMESH REDDY, “Fuzzy finite element analysis of structures with uncertainty in load material properties”, Journal of Structural Engineering, Vol.33 No.2,pp. 129-137, 2006.

[8] A. OLSSON, G. SANDBERG, O. DAHLBLOM, “On Latin hypercube sampling for structural reliability analysis, Structural Safety 25 (2003) 47-68.


[9] N. A. WAHANANI, A. PURWANINGSIH dan T.SETIADIPURA, “Latin Hypercube Sampling for Uncertainty Analysis, Journal of Theoretical and Computational Studies, Volume 8 Number 0408, ISSN 1979-3898, 2009.


[10] IAIN A MACDONALD, “Comparison of Sampling Techniques on the Performance of Monte Carlo Based Sensitivity Analysis”, Elevent International IBPSA Conference, Glasglow, Scotland (2009).


[11] XIANGRUL MENG, “Scalable Simple Random Sampling and Stratified Sampling”, Proceeding of the 30th International Conference on Machine Learning, Atlanta, Georgia, USA, 2013.


[12] GREGORY D. WYSS, KELLY H. JORGENSEN, “A User’s Guide to LHS : Sandia’s Latin Hypercube Sampling Software, Risk Assessment and Systems Modeling Department Sandia National Laboratories, 1998.


[13] CLIFFORD W. HANSEN, JON C. HELTON, CEDRIC J. SALLABERRY, “ Use of Replicated Latin Hypercube Sampling to Estimate Sampling Variance in Uncertainty and Sensitivity Analysis Results for the Geological Disposal of Radioative Waste”, Procedia Social and Behavioral Sciences 2 (2010), 7674-7675.