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A hybrid multi-objective algorithm to predict the characteristics of soil profiles from seismic ground motion records

Zamila Harichane, Mourad A. Khellafi, Amina Sadouki


DOI: https://doi.org/10.20528/cjsmec.2017.09.015

Abstract


The underlying goal of this study is to present an efficient algorithm to identify soil parameters such as thicknesses, shear wave velocities, damping and others parameters of subsurface layers, and site amplification characteristics (natural frequencies, peak amplitudes) from a given pair of seismic records. It is a hybrid procedure combining the stochastic genetic algorithms (GAs) optimization method, to find a point close to the global optimum in the global search phase, and a gradient based local determinist method (Levenberg-Marquardt: LM), to refine the solution. To improve the performance of the global search phase, a multi-objective optimization algorithm is used to minimize the errors between some characteristics of the theoretical amplification function and the experimental one of vertical array records. The weighted sum method which combines the weighted objectives into a single objective function is used to solve the optimization problem. The efficiency of the present algorithm is proven by several examples. Results show that the scheme works well and the curve fitting was always satisfying. Also, the proposed procedure leads to good approximations, requiring a lower computational effort, yet with good rates of convergence. Moreover, neither the growing number of parameters nor the vastness of the search space reduces the efficiency of the algorithm in predicting the characteristics of soil profiles and site amplification commonly required in seismic risk mitigation.


Keywords


soil parameter; amplification function; genetic algorithm; seismic record; HMO

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References


Deb K (2001). Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Inc. New York, NY, USA.

Djilali Berkane H, Khellafi MA, Harichane Z, Kouici W (2014). Stochastic study of the spatial variation of ground response spectrum. Electronic Journal of Geotechnical Engineering, 19, 4345-4361.

Dunning T (1998). Recorded Step Directional Mutation for Faster Convergence. In Evolutionary Programming VII. Springer Berlin Heidelberg, Germany.

Guellil ME, Harichane Z, Djilali Berkane H, Sadouki A (2017). Soil and structure uncertainty effects on the soil-foundation-structure dynamic response. Earthquakes and Structures, 12(2), 153-163.

Goldberg DE (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA.

Govindaraju L, Bhattacharya S (2012). Site-specific earthquake response study for hazard assessment in Kolkata city, India. Natural Hazards, 61(3), 943–965.

Harichane Z, Afra H, Elachachi SM (2005). An identification procedure of soil profile characteristics from two free field accelerometer records. Soil Dynamics and Earthquake Engineering, 25(6), 431-438.

Harichane Z, Afra H, Bahar R (2012). Experimental validation of an identification procedure of soil profile characteristics from free field acceleration records, International Journal of Geotechnical Earthquake Engineering, 3(1), 1-17.

Ince GC (2011). The relationship between the performance of soil conditions and damage following an earthquake: a case study in Istanbul, Turkey. Natural Hazards and Earth System Sciences, 11(6), 1745-1758.

Jones AL, Kramer SL, Arduino P (2002). Estimation of uncertainty in geotechnical properties for performance-based earthquake engineering. PEER Report 16, Pacific Earthquake Engineering Research Center, University of California, Berkeley, USA.

Kao CY, Chung JK, Yeh YT (2010). A comparative study of the least squares method and the genetic algorithm in deducing peak ground acceleration attenuation relationships. Terrestrial, Atmospheric and Oceanic Sciences, 21(6), 869-878.

Khellafi MA, Harichane Z, Hamid A, Sadouki A (2013). A case study of accelerometric records analysis of May 21st, 2003, Boumerdes (Algeria) Earthquake. International Journal of Geotechnical Earthquake Engineering, 4(2), 34-52.

Khellafi MA, Harichane Z, Hamid A, Erken A (2016). Prediction of parameters of soil stratums and earthen dams from free field acceleration records. International Journal of Geotechnical Earthquake Engineering, 7(1), 33-56.

Koh CG, Perry MJ (2007). Structural damage quantification by system identification. Journal of Earthquake and Tsunami, 1(3), 211-231.

Kokusho T, Aoyagi T, Wakynam A (2005). In situ soil-specific nonlinear properties back-calculated from vertically array records during 1995 Kobe earthquake. Journal of Geotechnical and Geoenvironmental Engineering, 131(12), 1509-1521.

Koza JR (1992). Genetic Programming, On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, MA, USA.

Li Z (2014). Uncertainty of soil properties in earthquake ground-motion site response analyses. Tenth U.S. National Conference on Earthquake Engineering Frontiers of Earthquake Engineering, Anchorage, Alaska, USA, July.

Marquardt DW (1963). An algorithm for least-squares estimation of nonlinear parameters. Journal of the Society for Industrial and Applied Mathematics, 11, 431-441.

Mercado V, El-Sekelly W, Zeghal M, Abdoun T (2015). Identification of soil dynamic properties through an optimization analysis. Computers and Geoterchnics, 65, 175–186

Pecker A, Mohammadioun B (1991). Downhole instrumentation for the evaluation of non-linear soil response on ground surface motion. Proceedings of the 11th Structural Mechanics in Reactor Technology Conference, Tokyo, Japan, August.

Pezeshk S, Zarrabi M (2005). A new inversion procedure for spectral analysis of surface waves using a genetic algorithm. Bulletin of the Seismological Society of America, 95(5), 1801-1808.

Rathje EM, Navidi S (2013). Identification of site parameters that improve predictions of site amplification, PEER Report 18; University of California, Berkeley, USA.

Rodríguez-Zúñiga JL, Ortiz-Alemán C, Padilla G (1997). Application of genetic algorithms to constrain shallow elastic parameters using in situ measurements. Soil Dynamics and Earthquake Engineering, 16(3), 223-234.

Rokonuzzaman MD, Sakai T (2010). Calibration of the parameters for a hardening-softening constitutive model using genetic algorithms. Computers and Geotechnics, 37(4), 573-579.

Sadouki A, Harichane Z, Chehat A (2012). Response of a randomly inhomogeneous layered media to harmonic excitations. Soil Dynamics and Earthquake Engineering, 36, 84-95.

Sato T, Yoshida I, Adachi Y (2013). Optimization of seismic sensor locations along highway links. Journal of Earthquake and Tsunami, 7(2), 11p.

SHAKE (2000). A computer program for conducting equivalent-linear seismic response analyses for horizontally layered soil deposits, A modified PC version of the original SHAKE program published in 1972 by Schnabel, Lysmer and Seed (modifications made by Idriss IM, Sum JI). EERI, University of California, Berkley, USA.

Steidl JH, Tumarkin AG, Archuleta RJ (1996). What is a reference site?. Bulletin of the Seismological Society of America, 86(6), 1733-1748.

Şafak E (1995). Discrete-time analysis of seismic site amplification. Journal of Engineering Mechanics, 121(7), 801-809.

Tallett-Williams S, Gosh B, Wilkinson S, Fenton C, Burton P, Whitworth M, Datla S, Franco G, Trieu A, Dejong M, Novellis V, White T, Lloyd T (2016). Site amplification in the Kathmandu valley during the 2015 M7.6 Gorkha, Nepal earthquake. Bulletin of Earthquake Engineering, 14, 3301–3315.

Walter E, Pronzato L (1997). Identification of Parametric Model From Experimental Data. Springer-Verlag, London, UK.

Wolf JP (1985). Dynamic Soil-structure Interaction. Prentice-Hall, Inc., Englewood Cliffs, New Jersey, USA.

Zerva A, Harada T (1997). Effect of surface layer stochasticity on seismic ground motion coherence and strain estimates. Soil Dynamics and Earthquake Engineering, 16(7), 445-457.


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