Evaluation of the Efficiency of Metaheuristic Algorithms in the Optimal Design of Pile Wall Retaining Systems

Document Type : Research Note

Author

Assistant professor, Department of Civil Engineering, Technical and Vocational University (TVU), Tehran, Iran.

Abstract

The effectiveness of the application of metaheuristic algorithms in the optimal design of retaining structures is investigated in this paper. For this purpose, an ongoing Tabriz metro station project with a deep excavation pit is selected here as a case study. The retaining system of the project consists of secant pile walls supported by a layer of struts. The piles have a circular section consisting of reinforced concrete cores covered by steel sleeves, and the struts are made of steel rectangular hollow sections. A detailed finite element model is developed in the OpenSees platform, including all the construction processes, in order to perform static analyses. Four different metaheuristic algorithms, namely Genetic, Particle swarm optimization, Bee, and Biogeography-based algorithms, are chosen for the optimization problem. The pile external diameter, the steel tube stiffness, the number of longitudinal bars inside the concrete core and their diameters, the center-to-center spaces of the pile elements, the dimensions of structs and their center-to-center spaces, the location of the structs in depth and the buried depth of pile elements are selected as optimization variables. The total cost of the retaining system is considered as an objective function that should be minimized in the design space of the variables. For optimization purposes, an integration of the OpenSees software with the MATLAB platform is done to join the modeling space with the mentioned optimization algorithms. The number of iterations for each run is assumed to be 400, which is also considered a termination criterion. The optimization process is performed 50 times, and the best response is reported here. The results demonstrate an excellent performance of the Genetic algorithm in obtaining the optimum solution with respect to the other three considered algorithms. It exhibits a proper standard deviation and convergence rate in producing the optimum response. It is shown that the soil stress is increased in the depth where struts are installed, while they are reduced near the ground level, where the deflection of piles creates an active situation for the soil. This is true considering the results of all algorithms. Proceeding with the excavation phase increases the soil stress as well as the pile deformation. It can also be obtained that providing a layer of strut seems necessary for reducing pile movements as well as their buried depth.

Keywords

Main Subjects

References

1. Peck, R.B., 1969. Deep excavations and tunneling in soft ground.State of the art volume, In 7th ICSMFE, pp.225-290.
2. Terzaghi, K., Peck, R.B. and Mesri, G., 1996.Soil Mechanics in Engineering Practice. John Wiley & Sons.
3. Chang, J.D. and Wong, K.S., 1996. Apparent pressure diagram for braced excavations in soft clay with diaphragm wall. In Geotechnical Aspects of Underground Construction in Soft Ground, pp.87-92.
4. Rechards Jr, R. and Elms, D.G., 1979. Seismic behavior of gravity retaining walls. Journal of the Geotechnical Engineering Division, 105(4), pp.449-464. doi.org/10.1061/AJGEB6.0000783
5. Gazetas, G., Psarropoulos, P.N., Anastasopoulos, I. and Gerolymos, N., 2004. Seismic behaviour of flexible retaining systems subjected to short-duration moderately strong excitation. Soil Dynamics and Earthquake Engineering, 24(7), pp.537-550. doi.org/10.1016/j.soildyn.2004.02.005
6. Madabhushi, S.P.G. and Zeng, X., 2006. Seismic response of flexible cantilever retaining walls with dry backfill.Geomechanics and Geoengineering: An International Journal, 1(4), pp.275-289.
doi.org/10.1080/17486020601039170
7. Qu, H.L., Luo, H., Liu, L. and Liu, Y., 2017. Analysis of dynamic coupling characteristics of the slope reinforced by sheet pile wall.Shock and Vibration, pp.1-10. doi.org/10.1155/2017/9043518
8. Lin, Y.L., Cheng, X.M., Yang, G.L. and Li, Y., 2018. Seismic response of a sheet-pile wall with anchoring frame beam by numerical simulation and shaking table test.Soil Dynamics and Earthquake Engineering, 115, pp.352-364.
doi.org/10.1016/j.soildyn.2018.07.028
9. Hashash, Y.M. and Whittle, A.J., 1996. Ground movement prediction for deep excavations in soft clay.Journal of Geotechnical Engineering, 122(6), pp.474-486. doi.org/10.1061/(ASCE)07339410(1996)122:6(474)
10. Mu, L. and Huang, M., 2016. Small strain based method for predicting three-dimensional soil displacements induced by braced excavation.Tunnelling and Underground Space Technology, 52, pp.12-22. doi.org/10.1016/j.tust.2015.11.001
11. Zhang, W., Goh, A.T. and Xuan, F., 2015. A simple prediction model for wall deflection caused by braced excavation in clays.Computers and Geotechnics, 63, pp.67-72. doi.org/10.1016/j.compgeo.2014.09.001
12. Gandomi, A.H., Kashani, A.R., Roke, D.A. and Mousavi, M., 2015. Optimization of retaining wall design using recent swarm intelligence techniques.Engineering Structures, 103, pp.72-84. doi.org/10.1016/j.engstruct.2015.08.034
13. Khajehzadeh, M., Taha, M.R., El-Shafie, A. and Eslami, M., 2010. Economic design of retaining wall using particle swarm optimization with passive congregation. Australian Journal of Basic and Applied Sciences, 4(11), pp.5500–5507.
14. Khajehzadeh, M. and Eslami, M., 2012. Gravitational search algorithm for optimization of retaining structures. Indian Journal of Science and Technology, 5(1), pp.1821-1827.
15. Ceranic, B., Fryer, C. and Baines, R.W., 2001. An application of simulate annealing to the optimum design of reinforced concrete retaining structures. Computers and Structures, 79(17), pp.1569–1581.
doi.org/10.1016/S0045-7949(01)00037-2
16. Yepes, V., Alcala, J., Perea, C. and Gonzalez-Vidosa, F., 2008. A parametric study of optimum earth-retaining walls by simulated annealing. Engineering Structures, 30(3), pp.821–830. doi.org/10.1016/j.engstruct.2007.05.023
17. Kaveh, A. and Shakouri, M.A.A., 2011. Harmony search based algorithm for the optimum cost design of reinforced concrete cantilever retaining walls. International Journal of Civil Engineering, 9(1), pp.1–8.
18. Öztürk, H.T., Dede, T. and Türker, E., 2020. Optimum design of reinforced concrete counterfort retaining walls using TLBO, Jaya algorithm. Structures, 25, pp.285-296. doi.org/10.1016/j.istruc.2020.03.020
19. Camp, C.V. and Akin, A., 2012. Design of retaining walls using big bang-big crunch optimization. Journal of Structural Engineering, 138(3), pp.438–448. doi.org/10.1061/(ASCE)ST.1943-541X.0000461
20. Kaveh, A., Biabani Hamedani, K. and Zaerreza, A., 2021. A set theoretical shuffled shepherd optimization algorithm for optimal design of cantilever retaining wall structures.Engineering with Computers, 37, pp.3265-3282.
doi.org/10.1007/s00366-020-00999-9
21. Kalemci, E.N., İkizler, S.B., Dede, T. and Angın, Z., 2020. Design of reinforced concrete cantilever retaining wall using Grey wolf optimization algorithm.Structures, 23, pp.245-253. doi.org/10.1016/j.istruc.2019.09.013
22. Koopialipoor, M., Murlidhar, B.R., Hedayat, A., Armaghani, D.J., Gordan, B. and Mohamad, E.T., 2020. The use of new intelligent techniques in designing retaining walls.Engineering with Computers, 36, pp.283-294.
doi.org10.1007/s00366-018-00700-1
23. Aydogdu, I., 2017. Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights.Engineering Optimization, 49(3), pp.381-400.
doi.org/10.1080/0305215X.2016.1191837
24. Gordan, B., Koopialipoor, M., Clementking, A., Tootoonchi, H. and Mohamad, E., 2019. Estimating and optimizing safety factors of retaining wall through neural network and bee colony techniques.Engineering with Computers, 35, pp.945-954. doi.org/10.1007/s00366-018-0642-2
25. Taiyari, F., Kharghani, M. and Hajihassani, M., 2020. Optimal design of pile wall retaining system during deep excavation using swarm intelligence technique. Structures, 28, pp.1991-1999. doi.org/10.1016/j.istruc.2020.10.044
26. Taiyari, F., Hajihassani, M. and Kharghani, M., 2022. Efficiency of the evolutionary methods on the optimal design of secant pile retaining systems in a deep excavation. Neural Computing and Applications, 34(22), pp.20313-20325.
doi.org/10.1007/s00521-022-07591-w
27. Iranian National Building Codes Compilation Office, 2020. Iranian National Building Code, Part 9: Reinforced Concrete Buildings Design, Ministry of Housing and Urban Development (MHUD).
28. Goldberg, D.E., 2010. Genetic algorithms in search, optimization and machine learning. MA: Addison-Wesley, Reading.
29. Kennedy, J. and Eberhart, R., 1995. Particle swarm optimization. In Proceeding of the ICNN’95-international conference on neural networks, 4, pp.1942–1948.
30. Pham, D.T., Ghanbarzadeh, A., Koc, E., Otri, S., Rahim, S. and Zaidi, M., 2006. The bees algorithm-a novel tool for complex optimization problems. In Intelligent Production Machines and Systems, pp. 454-459.
doi.org/10.1016/B978-008045157-2/50081-X
31. Simon, D., 2008. Biogeography-based optimizatio. IEEE Transactions on Evolutionary Computation,12(6), pp.702–713.
32. Jeong, S., 1992. Nonlinear three-dimensional analysis of downdrag on pile groups. PhD Thesis, Texas A&M University.
33. Jeong, S., Lee, J. and Lee, C.J., 2004. Slip effect at the pile–soil interface on dragload.Computers and Geotechnics, 31(2), pp.115-126. doi.org/10.1016/j.compgeo.2004.01.009
34. Yang, Z., Lu, J. and Elgamal, A., 2008. OpenSees soil models and solid-fluid fully coupled elements. user’s manual, 1(27).
35. Mander, J.B., Priestley, M.J. and Park, R., 1988. Theoretical stress-strain model for confined concrete.Journal of Structural Engineering, 114(8), pp.1804-1826. doi.org/10.1061/(ASCE)07339445(1988)114:8(1804
36. Randolph, M.F. and Wroth, C.P., Application of the failure state in undrained simple shear to the shaft capacity of driven piles.Geotechnique, 31(1), pp.143-157. doi.org/10.1680/geot.1981.31.1.143
37. Loukidis, D. and Salgado, R., 2008. Analysis of the shaft resistance of non-displacement piles in sand.Géotechnique, 58(4), pp.283-296.doi.org/10.1680/geot.2008.58.4.283
 

Files

Share

How to cite

Statistics