Optimal design of a non-prismatic reinforced concrete box girder bridge with three meta-heuristic algorithms

Document Type : Article

Authors

1 School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

2 Department of Civil Engineering, Imam Khomeini International University, Qazvin, Iran

Abstract

In this paper a parametric study is applied to investigate the effect of the number of cells in optimal cost of the non-prismatic reinforced concrete (RC) box girder bridges. The variables are geometry of cross section, tapered length, concrete strength and reinforcement of the box girders and slabs that are obtained with ECBO metaheuristic algorithm. The design is based on AASHTO standard specification. The constraints are the bending and shear strength, geometric limitations and superstructure deflection. The link of CSiBridge and MATLAB software are used for the optimization process. The methodology is carried out for two-cell, three-cell and four-cell box girder bridges. The results show that the total cost of concrete, bars and formwork for two-cell box girder is less than three- and four-cell box girder bridges.

Keywords

References

References:
[1]      Goldberg, D. E. and Holland, J. H. “Genetic Algorithms and Machine Learning”,  Mach Learn., 3, pp. 95–99 (1988).
[2]      Eberhart , R. and Kennedy, J. “A new optimizer using particle swarm theory”,  Proc. sixth Int. Symp. micro Mach. Hum. Sci., pp. 1942–1948 (1995). https://doi.org/10.1109/MHS.1995.494215.
[3]      Colorni, A., Dorigo, M. and Maniezzo, V. “Distributed Optimization by ant colonies”, Proceeding ECAL- Eur. Conf. Artif. Life., pp. 134–142 (1991).
[4]      Yang, X. S. “Firefly algorithm, stochastic test functions and design optimization”, Int. J. Bio-Inspired Comput.,  2(2), pp. 78–84 (2010). https://doi.org/10.1504/IJBIC.2010.032124.
[5]      Yang, X. S. and Deb, S. “Cuckoo search via Lévy flights”, 2009 World Congr. Nat. Biol. Inspired Comput. NABIC., pp. 210–214 (2009).          https ://doi.org/10.1109/NABIC.2009.5393690.
[6]      Kaveh , A. and Talatahari, S. “A novel heuristic optimization method: Charged system search”, Acta Mech., 213(3-4), pp. 267–289 (2010).          https ://doi.org/10.1007/s00707-009-0270-4.
[7]      Kirkpatrick, S., Gelatt, C. D. and Vecchi, M. P. “Optimization by simulated annealing”, Science., 220(4598), pp. 671–680 (1983).          https ://doi.org/10.1126/science.220.4598.671.
[8]      Kazemzadeh Azad, S. “Monitored convergence curve: a new framework for metaheuristic structural optimization algorithms”, Struct. Multidiscip. Optim., 60(2), pp. 481–499 (2019). https://doi.org/10.1007/s00158-019-02219-5
[9]      Kaveh, A., Izadifard, R. A. and Mottaghi, L. “Cost Optimization of RC Frames Using Automated Member Grouping”, Int. J. Optim. Civ. Eng., 10(1), pp. 91–100 (2020).
[10]    Kaveh, A. "Advances in Metaheuristic Algorithms for Optimal Design of Structures",  Springer, Cham., 3th Edn., pp. XIX-881, Switzerland (2021). https://doi.org/10.1007/978-3-030-59392-6.
[11]    Paya-Zaforteza, I., Yepes, V., Hospitaler, A. and González-Vidosa, F. “CO2-optimization of reinforced concrete frames by simulated annealing”, Eng. Struct., 31(7), pp. 1501–1508  (2009). https://doi.org/10.1016/j.engstruct.2009.02.034.
[12]    Park, H. S., Kwon, B., Shin, Y., Kim, Y., Hong, T. and Choi, S. W. “Cost and CO2 emission optimization of steel reinforced concrete columns in high-rise buildings”, Energies., 6(11), pp. 5609–5624 (2013).  https://doi.org/10.3390/en6115609.
[13]    Camp, C. V. and Assadollahi, A. “CO2 and cost optimization of reinforced concrete footings using a hybrid big bang-big crunch algorithm”, Struct. Multidiscip. Optim., 48(2), pp. 411–426 (2013). https://doi.org/10.1007/s00158-013-0897-6.
[14]    Camp, C. V. and Assadollahi, A. “CO2 and cost optimization of reinforced concrete footings subjected to uniaxial uplift”, J. Build. Eng., 3, pp. 171–183 (2015). https://doi.org/10.1016/j.jobe.2015.07.008.
[15]    Kaveh, A., Mottaghi, L. and Izadifard, R. A. “Sustainable design of reinforced concrete frames with non-prismatic beams”,  Eng. Comput., (2020). https://doi.org/10.1007/s00366-020-01045-4.
[16]    Park, H. S., Hwang, J. W. and Oh, B. K. “Integrated analysis model for assessing CO2 emissions, seismic performance, and costs of buildings through performance-based optimal seismic design with sustainability”, Energy Build., 158, pp. 761–775 (2018). https://doi.org/10.1016/j.enbuild.2017.10.070.
[17]    Eleftheriadis, S., Duffour, P., Greening, P., James, J., Stephenson, B. and Mumovic, D. “Investigating relationships between cost and CO2 emissions in reinforced concrete structures using a BIM-based design optimisation approach”, Energy Build., 166, pp. 330–346 (2018). https://doi.org/10.1016/j.enbuild.2018.01.059.
[18]    Mottaghi, L., Izadifard, R. A. and Kaveh, A. “Factors in the Relationship Between Optimal CO2 Emission and Optimal Cost of the RC Frames”, Period. Polytech. Civ. Eng., 65(1), pp. 1–14 (2020). https://doi.org/10.3311/PPci.16790.
[19]    Mergos, P. E. “Seismic design of reinforced concrete frames for minimum embodied CO2emissions,” Energy Build., 162, pp. 177–186 (2018). https://doi.org/10.1016/j.enbuild.2017.12.039.
[20]    Kaveh, A., Izadifard, R. A. and Mottaghi, L. “Optimal design of planar RC frames considering CO2 emissions using ECBO , EVPS and PSO metaheuristic algorithms”, J. Build. Eng., 28, (2020). https://doi.org/10.1016/j.jobe.2019.101014.
[21]    Fan, W., Chen,Y., Li, J., Sun, Y., Feng, J., Hassanin, H. and  Sareh, P. “Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications”, Structures, 33, pp. 3954–3963 (2021). https://doi.org/10.1016/j.istruc.2021.06.110.
[22]    Perea,C., Alcala, J., Yepes, V., Gonzalez-Vidosa, F. and Hospitaler, A. “Design of reinforced concrete bridge frames by heuristic optimization”, Adv. Eng. Softw., 39(8), pp. 676–688  (2008). https://doi.org/10.1016/j.advengsoft.2007.07.007.
[23]    Aydin, Z. and Ayvaz, Y. “Overall cost optimization of prestressed concrete bridge using genetic algorithm”, KSCE J. Civ. Eng., 17(4), pp. 769–776 (2013). https://doi.org/10.1007/s12205-013-0355-4.
[24]    Pedro, R. L., Demarche, J., Miguel, L. F. F. and Lopez, R. H. “An efficient approach for the optimization of simply supported steel-concrete composite I-girder bridges”, Adv. Eng. Softw., 112, pp. 31–45 (2017). https://doi.org/10.1016/j.advengsoft.2017.06.009.
[25]    Yepes,V., Pérez-lópez, E., García-segura,T. and Alcalá, J. “Optimization of High-Performance Concrete Post-Tensioned Box-Girder Pedestrian Bridge”, Int. J. Comp. Meth. Exp. Meas, 7(2), pp. 118–129 (2019). https://doi.org/10.2495/CMEM-V7-N2-118-129.
[26]    Yepes,V., Martí, J. V. and García-Segura, T. “Cost and CO2 emission optimization of precast-prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm”, Autom. Constr., 49, pp. 123–134 (2015). https://doi.org/10.1016/j.autcon.2014.10.013.
[27]    García-Segura, T., Yepes, V., Alcalá, J. and Pérez-López, E. “Hybrid harmony search for sustainable design of post-tensioned concrete box-girder pedestrian bridges”, Eng. Struct., 92, pp. 112–122 (2015). https://doi.org/10.1016/j.engstruct.2015.03.015.
[28]    García-Segura, T. and Yepes, V. “Multiobjective optimization of post-tensioned concrete box-girder road bridges considering cost, CO2 emissions, and safety”, Eng. Struct., 125, pp. 325–336 (2016). https://doi.org/10.1016/j.engstruct.2016.07.012.
[29]    Kaveh, A. and Dadras Eslamlou, A. “Water strider algorithm: A new metaheuristic and applications”, Structures, 25, pp. 520–541 (2020). https://doi.org/10.1016/j.istruc.2020.03.033.
[30]    Kaveh, A. and Mahdavi,V. R. “Colliding bodies optimization : A novel meta-heuristic method”,  Comput. Struct., 139, pp. 18–27 (2014). https://doi.org/10.1016/j.compstruc.2014.04.005.
[31]    Kaveh, A. and Ilchi Ghazaan, M. “Enhanced colliding bodies optimization for design problems with continuous and discrete variables”, Adv. Eng. Softw., 77, pp. 66–75 (2014). https://doi.org/10.1016/j.advengsoft.2014.08.003.
[32]    Kaveh, A. and Ilchi Ghazaan, M. "Meta-heuristic algorithms for optimal design of real-size structures”, Springer, Cham., 1th Edn., pp. XI-168 (2018). https://doi.org/10.1007/978-3-319-78780-0.
[33]    Kaveh, A. and Ilchi Ghazaan, M. “A new meta-heuristic algorithm : vibrating particles system”, Sci. Iran., 24(2), pp. 551–566 (2017). https://doi.org/10.24200/sci.2017.2417.
[34]    Kaveh, A., Hoseini Vaez, S. R. and Hosseini, P. “Enhanced vibrating particles system algorithm for damage identification of truss structures”, Sci. Iran., 26(1), pp. 246–256, (2019). https://doi.org/10.24200/SCI.2017.4265.
[35]    AASHTO, "Standard Specifications for Highway Bridges", American Association of State Highway and Transportation Officials; Washington, (2002).
[36]    Kazemzadeh Azad, S. “Seeding the initial population with feasible solutions in metaheuristic optimization of steel trusses”, Eng. Optim., 50(1) , pp. 89–105 (2017). http://dx.doi.org/10.1080/0305215X.2017.1284833.
[37]    Kazemzadeh Azad, S., Hasançebi, O. and Kazemzadeh Azad, S. “Upper bound strategy for metaheuristic based design optimization of steel frames”, Adv. Eng. Softw., 57, pp. 19–32 (2013). https://doi.org/10.1016/j.advengsoft.2012.11.016.
[38]    Kazemzadeh Azad, S., Hasançebi, O. and Kazemzadeh Azad, S. “Computationally Efficient Optimum Design of Large Scale Steel Frames”, Int. J. Optim. Civ. Eng., 4(2), pp. 233–259 (2014).
Scientia Iranica
Volume 29, Issue 3
Transactions on Civil Engineering (A)
May and June 2022
Pages 1154-1167

Files

History

  • Receive Date: 28 October 2021
  • Revise Date: 27 November 2021
  • Accept Date: 13 December 2021

Share

How to cite

Statistics