Similar articles

Abstract: The aim of this study was to design and construct an improved response surface method (RSM) based on weighted regression for the anti-slide reliability analysis of concrete gravity dam. The limitation and lacuna of the traditional RSM were briefly analyzed. Firstly, based on small experimental points, research was devoted to an improved RSM with singular value decomposition techniques. Then, the method was used on the basis of weighted regression and deviation coefficient correction to reduce iteration times and experimental points and improve the calculation method of checking point. Finally, a test example was given to verify this method. Compared with other conventional algorithms, this method has some strong advantages: this algorithm not only saves the arithmetic operations but also greatly enhances the calculation efficiency and the storage efficiency.

[1]Chebbah, M.S., 2007. Response surface method for the rapid design of process parameters in tube hydro forming. Material Processing and Design, 7(2):455-460.

[2]Cheng, J., Li, Q.S., Xiao, R.C., 2008. A new artificial neural network-based response surface method for structural reliability analysis. Probabilistic Engineering Mechanics, 23(1):51-63.

[3]Der Kiureghian, A., Dakessian, T., 1998. Multiple design points in first and second-order reliability. Structural Safety, 20(1):37-49.

[4]Gavin, H.P., Yau, S.C., 2008. High-order limit state functions in the response surface method for structural reliability analysis. Structural Safety, 30(2):162-179.

[5]Gomes, H.M., Awruch, A.M., 2004. Comparison of response surface and neural network with other methods for structural reliability analysis. Structural Safety, 26(1):49-67.

[6]Guan, X.L., Melchers, R.E., 2001. Effect of response surface parameter variation on structural reliability estimates. Structural Safety, 23(4):429-444.

[7]Gupta, S., Manohar, C.S., 2004. Improved response surface method for time variant reliability analysis of nonlinear random structures under no stationary excitations. Nonlinear Dynamics, 36(2-4):267-280.

[8]Hong, Y.J., Xing, J., Wang, J.B., 1999. A second-order third-moment method for calculating the reliability of fatigue. International Journal of Pressure Vessels and Piping, 76(8):567-570.

[9]Jiang, J.Q., Wu, C.G., Song, C.Y., 2006. Adaptive and iterative gene selection based on least squares support vector regression. Journal of Information & Computational Science, 3(4):443-451.

[10]Jin, W.L., Yuan, X.X., 2007. Response surface method based on LS-SVM for structural reliability analysis. Journal of Zhejiang University (Engineering Science), 41(1):44-47 (in Chinese).

[11]Kaymaz, I., McMahon, C.A., 2005. A response surface method based on weighted regression for structural reliability analysis. Probabilistic Engineering Mechanics, 20(1):11-17.

[12]Koyluoglu, H.U., Nielsen, S.R.K., 1994. New approximations for SORM integrals. Structural Safety, 13(4):235-246.

[13]Liu, Y.W., Moses, F., 1994. A sequential response surface method and its application in the reliability analysis of aircraft structural system. Structural Safety, 16(1-2):39-46.

[14]Moore, L.J., Ping, S., 1999. Comparisons with the best in response surface methodology. Statistics & Probability Letters, 44(2):189-194.

[15]Nguyen, X.S., Sellier, A., Duprat, F., Pons, G., 2009. Adaptive response surface method based on a double weighted regression technique. Probabilistic Engineering Mechanics, 24(2):135-143.

[16]Qiu, C.C., Orazem, M.E., 2004. A weighted nonlinear regression-based inverse model for interpretation of pipeline survey data. Electrochimica Acta, 49(22-23):3965-3975.

[17]Triantafyllopoulos, K., 2006. Multivariate discount weighted regression and local level models. Computational Statistics & Data Analysis, 50(12):3702-3720.

[18]Wong, S.M., Hobbs, R.E., Onof, C., 2005. An adaptive response surface method for reliability analysis of structures with multiple loading sequences. Structural Safety, 27(4):287-308.

[19]Youn, B.D., Choi, K.K., 2004. A new response surface methodology for reliability-based design optimization. Computers & Structures, 82(2-3):241-256.

[20]Zhao, J., Lu, Z.Z., 2006. Response surface method for reliability analysis of implicit limit state equation based on weighted regression. Journal of Mechanical Strength, 28(4):512-516 (in Chinese).

[21]Zheng, Y., Das, P.K., 2000. Improved response surface method and its application to stiffened plate reliability analysis. Engineering Structures, 22(5):544-551.

[22]Zou, T., Mourelatos, Z.P., Mahadevan, S., Jian, T., 2008. An indicator response surface method for simulation-based reliability analysis. Journal of Mechanical Design, 130(7):071401.