Multi-Objective Optimization of the Depth and Cementation of Liquefiable Soil Surrounding Tunnels
محورهای موضوعی : Structural Engineering
Mohammad Shabani Soltan Moradi
1
,
Mohammad Azadi
2
,
Homayoun Jahanian
3
1 - PhD Candidate, Department of Civil Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
2 - Associate Professor, Department of Civil Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
3 - Department of Civil Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
کلید واژه: Multi-Objective Optimization, Liquefaction, Pore Water Pressure, Neural Network, Uplift,
چکیده مقاله :
Designing tunnels in liquefiable sandy soils presents a significant challenge in determining the optimal depth and extent of soil cementation around them. Reducing the depth of the tunnel decreases both the bending anchor force and the axial load on the tunnel's shell, yet it leads to an increase in ground surface settlement, and the opposite is true when depth is increased. Enhancing the cementation level at the tunnel's optimal depth reduces both structural uplift and shear forces exerted on the tunnel lining, but it also leads to an increase in axial loads and vice versa. Given the contradictory nature of these outcomes, the FLAC software was employed to simulate tunnels in liquefiable soils to address this dilemma. Subsequently, a neural network was utilized to identify correlations between the inputs and outputs of the simulation. This network was the objective function for identifying optimal values by applying a genetic algorithm. Optimal design parameters were derived using the NSGA-II modified algorithm, a multi-objective optimization technique based on the objective functions. Ultimately, Pareto charts generated from the multi-objective optimization process enabled designers to select the most suitable tunnel location according to their specific requirements concerning depth and soil cementation in liquefied soils.
Designing tunnels in liquefiable sandy soils presents a significant challenge in determining the optimal depth and extent of soil cementation around them. Reducing the depth of the tunnel decreases both the bending anchor force and the axial load on the tunnel's shell, yet it leads to an increase in ground surface settlement, and the opposite is true when depth is increased. Enhancing the cementation level at the tunnel's optimal depth reduces both structural uplift and shear forces exerted on the tunnel lining, but it also leads to an increase in axial loads and vice versa. Given the contradictory nature of these outcomes, the FLAC software was employed to simulate tunnels in liquefiable soils to address this dilemma. Subsequently, a neural network was utilized to identify correlations between the inputs and outputs of the simulation. This network was the objective function for identifying optimal values by applying a genetic algorithm. Optimal design parameters were derived using the NSGA-II modified algorithm, a multi-objective optimization technique based on the objective functions. Ultimately, Pareto charts generated from the multi-objective optimization process enabled designers to select the most suitable tunnel location according to their specific requirements concerning depth and soil cementation in liquefied soils.
[1] M. Azadi and S. M. M. Hosseini, "Analyses of the effect of seismic behavior of shallow tunnels in liquefiable grounds," Tunnelling and underground space technology, vol. 25, no. 5, pp. 543-552, 2010.
[2] H. Liu and E. Song, "Seismic response of large underground structures in liquefiable soils subjected to horizontal and vertical earthquake excitations," Computers and Geotechnics, vol. 32, no. 4, pp. 223-244, 2005.
[3] J.-L. Hu and H.-B. Liu, "The uplift behavior of a subway station during different degree of soil liquefaction," Procedia engineering, vol. 189, pp. 18-24, 2017.
[4] G. Zheng, W. Zhang, W. Zhang, H. Zhou, and P. Yang, "Neural network and support vector machine models for the prediction of the liquefaction-induced uplift displacement of tunnels," Underground Space, vol. 6, no. 2, pp. 126-133, 2021.
[5] Q. Liao, Q.-Q. Fan, and J.-J. Li, "Translation control of an immersed tunnel element using a multi-objective differential evolution algorithm," Computers & Industrial Engineering, vol. 130, pp. 158-165, 2019.
[6] S. Nokande, A. Haddad, and Y. Jafarian, "Shaking Table Test on Mitigation of Liquefaction-Induced Tunnel Uplift by Helical Pile," International Journal of Geomechanics, vol. 23, no. 1, p. 04022243, 2023.
[7] A. Rashiddel, M. Abedi, D. Dias, and A. Ramesh, "Seismic analysis of segmental shallow tunnels adjacent to building foundations under soil liquefaction and its mitigation," Soil Dynamics and Earthquake Engineering, vol. 178, p. 108479, 2024.
[8] X.-c. ZHONG, B.-b. YI, W.-b. ZHU, S.-r. ZHU, S.-y. LUO, and Q. WANG, "Uplift mode of shield tunnel caused by seismic liquefaction in liquefiable soil," Journal of Chang'an University (Natural Science Edition) [ISSN: 1006-6977/CN: 61-1281/TN], no. 1, pp. 80-90, 2024.
[9] M. Azadi and S. M. M. Hosseini, "The uplifting behavior of shallow tunnels within the liquefiable soils under cyclic loadings," Tunnelling and Underground Space Technology, vol. 25, no. 2, pp. 158-167, 2010.
[10] H. Sharafi and P. Parsafar, "Numerical analysis of effective parameters on liquefaction occurance result from earthquake on site of buried pipelines," Modares Civil Engineering journal, vol. 16, no. 3, pp. 111-120, 2016.
[11] G. W. Clough, J. Iwabuchi, N. S. Rad, and T. Kuppusamy, "Influence of cementation on liquefaction of sands," Journal of geotechnical engineering, vol. 115, no. 8, pp. 1102-1117, 1989.
[12] R. Liang, X. Bai, and J. Wang, "Effect of clay particle content on liquefaction of soil," in 12th World Conference on Earthquake Engineering, Auckland, New Zealand, 2000, pp. 1560-1564.
[13] Z. Haiyang et al., "Seismic responses of a subway station and tunnel in a slightly inclined liquefiable ground through shaking table test," Soil Dynamics and Earthquake Engineering, vol. 116, pp. 371-385, 2019.
[14] V. Pareto and D. Cours, "Economic politique," Lausanne, Switzerland, Rouge, 1896.
[15] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II," IEEE transactions on evolutionary computation, vol. 6, no. 2, pp. 182-197, 2002.
[16] N. Nariman-Zadeh, K. Atashkari, A. Jamali, A. Pilechi, and X. Yao, "Inverse modelling of multi-objective thermodynamically optimized turbojet engines using GMDH-type neural networks and evolutionary algorithms," Engineering Optimization, vol. 37, no. 5, pp. 437-462, 2005.
[17] J. Lysmer and R. L. Kuhlemeyer, "Finite dynamic model for infinite media," Journal of the engineering mechanics division, vol. 95, no. 4, pp. 859-877, 1969.
[18] F. Khoshnoudian and I. Shahrour, "Numerical analysis of the seismic behavior of tunnels constructed in liquefiable soils," Soils and foundations, vol. 42, no. 6, pp. 1-8, 2002.
[19] M. Shabani SoltanMoradi, M. Azadi, and H. Jahanian, "Multi-objective optimisation of tunnel parameters in a liquefied sand lens under seismic loads," Geotechnical Research, vol. 9, no. 4, pp. 196-210, 2022.
[20] R. Popescu and J. H. Prevost, "Comparison between VELACS numerical ‘class A’predictions and centrifuge experimental soil test results," Soil Dynamics and Earthquake Engineering, vol. 14, no. 2, pp. 79-92, 1995.
[21] G. R. Martin, H. B. Seed, and W. L. Finn, "Fundamentals of liquefaction under cyclic loading," Journal of the Geotechnical Engineering Division, vol. 101, no. 5, pp. 423-438, 1975.
[22] S. C. Chian, K. Tokimatsu, and S. P. G. Madabhushi, "Soil liquefaction–induced uplift of underground structures: physical and numerical modeling," Journal of Geotechnical and Geoenvironmental Engineering, vol. 140, no. 10, p. 04014057, 2014.
[23] M. Alborzi, Genetic Algorithm, First Edition ed. Tehran: Sharif University of Technology Publishing Institute, 2009.
