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Structural Reliability: An Assessment Using a New and Efficient Two-Phase Method Based on Artificial Neural Network and a Harmony Search Algorithm | ||
| Civil Engineering Infrastructures Journal | ||
| مقاله 1، دوره 49، شماره 1، شهریور 2016، صفحه 1-20 اصل مقاله (882.21 K) | ||
| نوع مقاله: Research Papers | ||
| شناسه دیجیتال (DOI): 10.7508/ceij.2016.01.001 | ||
| نویسندگان | ||
| Naser Kazemi Elaki* 1؛ Naser Shabakhty2؛ Mostafa Abbasi Kia3؛ Soroosh Sanayee Moghaddam4 | ||
| 1M.Sc. of Structural Engineering, University of Sistan and Baluchestan | ||
| 2PhD of Civil Engineering Department of Civil Engineering University of Sistan and Baluchetsan | ||
| 3Msc of Computer science. Department of Mathematics, university of Lorestan | ||
| 4M.Sc. of Hydrolic Structures, University of Sistan and Baluchestan | ||
| چکیده | ||
| In this research, a two-phase algorithm based on the artificial neural network (ANN) and a harmony search (HS) algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. The proposed method involves the generation of datasets to be used specifically for training by Finite Element analysis, to establish an ANN model using a proven ANN model in the reliability assessment process as an analyzer for structures, and finally estimate the reliability index and failure probability by using the HS algorithm, without any requirements for the explicit form of limit state function. The proposed algorithm is investigated here, and its accuracy and efficiency are demonstrated by using several numerical examples. The results obtained show that the proposed algorithm gives an appropriate estimate for the assessment of reliability of structures. | ||
| کلیدواژهها | ||
| Artificial Neural Network؛ Failure Probability؛ Harmony Search Algorithm؛ Implicit Limit State Function؛ Reliability Index | ||
| مراجع | ||
|
Adhikari, S. (2010). “Sensitivity based reduced approaches for structural reliability analysis”, Sadhana Academy Proceeding in Engineering Science, 35(3), 319-339.
Allaix, D.L. and Carbone, V.I. (2011). “An improvement of the response surface method”, Structural Safety, 33(2), 165-172.
Bucher, C.G. (1998). “Adaptive sampling– an iterative fast Monte Carlo procedure”, Structural Safety, 5(2), 119-126.
Castillo, E., Mínguez, R. and Castillo, C. (2008). “Sensitivity analysis in optimization and reliability problems”, Reliability Engineering & System Safety, 93(12), 1788-1800.
Cheng, J. (2010). “An artificial neural network based genetic algorithm for estimating the reliability of long span suspension bridges”, Finite Elements in Analysis and Design, 46(8), 657-668.
Cheng, J. and Li, Q.S. (2008). “Reliability analysis of structures using artificial neural network based genetic algorithms”, Computer Methods in Applied Mechanics and Engineering, 197(45), 3742-3750.
Cheng, J. (2007). “Hybrid genetic algorithms for structural reliability analysis”, Computers and Structures, 85(19), 1524-1533.
Cheng, J., Zhang, J., Cai, C.S. and Xiao, R.C. (2007). “A new approach for solving inverse reliability problems with implicit response functions”, Engineering Structures, 29(1), 71-79.
Coelho, L.S. (2009). “An efficient particle swarm approach for mixed-integer programming in reliability–redundancy optimization applications”, Reliability Engineering and System Safety, 94(4), 830-837.
Deng, J., Gu, D., Li, X. and Yue, Z. (2005). “Structural reliability analysis for implicit performance functions using artificial neural network”, Structural Safety, 27(1), 25-48.
Elegbede, C. (2005). “Structural reliability assessment based on particles swarm optimization”, Structural Safety, 27(2), 171-186.
Fiacco, A.V. and McCormick, G.P. (1968). Nonlinear programming: sequential unconstrained minimization techniques, Wiley, New York.
Geem, Z.W., Kim, J.H. and Loganathan, G.V. (2001). “A new heuristic optimization algorithm: harmony search”, Simulations, 76(2), 60-68.
Haldar, A. (2006). Recent developments in reliability-based civil engineering, World Scientific Publishing, Arizona, USA.
Harbiz, A. (1986). “An efficient sampling method for probability of failure calculation”, Structural Safety, 3(2), 109-116.
Hasofer, A.M. and Lind, N. (1974). “An exact and invariant First-Order Reliability Format”, Engineering Mechanics, ASCE, 100, 111-121.
Huang, C.L. (2015). “A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems”, Reliability Engineering & System Safety, 142, 221-230.
Lebrun, R. and Dutfoy, A. (2009). “Do Rosenblatt and Natafiso probabilistic transformations really differ?”, Probabilistic Engineering Mechanics, 24(4), 577-584.
Lee, K.S. and Geem, Z.W. (2004). “A new meta-heuristic algorithm for continues engineering optimization: harmony search theory and practice”, Computer Method Applied Mechanic and Engineering, 194(36), 3902-3933.
Liu, P.L. and Der Kiureghian, A. (1991). “Optimization algorithms for structural reliability”, Structural Safety, 9(3), 161-177.
Lopez, R.H., Torii, A.J., Miguel, L.F.F. and Souza Cursi, J.E. (2015). “Overcoming the drawbacks of the FORM using a full characterization method”, Structural Safety, 54, 57-63.
Mahdavi, M., Fesanghary, M. and Damangir, E. (2007). “An improved harmony search algorithm for solving optimization problems”, Applied Mathematics and Computation, 188(2), 1567-1579.
Marti, K. (2008). Stochastic optimization methods. SpringerVerlag, Berlin Heidelberg.
McCulloch, W.S. and Pitts, W. (1943). “A logical calculus of ideas immanent in nervous activity”, Bull Math Biophysics, 5(4), 115-33.
Moore, J.C., Glenncross-Grant, R., Mahini, S.S. and Patterson, R. (2012). “Regional timber bridge girder reliability: Structural health monitoring and reliability strategies”, Advances in Structural Engineering, 15(5), 793-806.
Mucherino, A. and Seref, O. (2009). “Modeling and solving real life global optimization problems with meta-heuristic methods”, Advances in Modeling Agricultural Systems, 25, 1-17.
Mun, S. and Cho, Y.H. (2012). “Modified harmony search optimization for constrained design problems”, Expert Systems with Applications, 39(1), 419-423.
Ramirez-Marquez, J.E. (2008). “Port-of-entry safety via the reliability optimization of container inspection strategy through an evolutionary approach”, Reliability Engineering and System Safety, 93(11), 1698-1709.
Rodrigues, M., de Lima, B.S.L.P. and Guimarães, S. (2016). “Balanced ranking method for constrained optimization problems using evolutionary algorithms”, Information Sciences, 327(C), 71-90.
Shao, S. and Murotsu, Y. (1997). “Structural reliability using a neural network”, JSME International, 40, 242-246.
Stapelberg and Rudolph, F. (2009). Handbook of reliability, availability, maintainability and safety in engineering design, Springer-Verlag, London.
Zhang, Z., Jiang, C., Wang, G.G. and Han, X. (2015). “First and second order approximate reliability analysis methods using evidence theory”, Reliability Engineering & System Safety, 137, 40-49.
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