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[1] Flower, D.J.M. & Sanjayan, J.G., Green house gas emissions due to concrete manufacture. International Journal of Life Cycle Assessment, 12(5), pp. 282–288, 2007. [Crossref]
[2] Collins, F., Inclusion of carbonation during the life cycle of built and recycled concrete: influence on their carbon footprint. International Journal of Life Cycle Assessment, 15(6), pp. 549–556, 2010. [Crossref]
[3] Gartner, E.M., Industrially interesting approaches to “low-CO2” cements. Cement and Concrete Research, 34(9), pp. 1489–1498, 2004. [Crossref]
[4] García-Segura, T., Yepes, V. & Alcalá, J., Life cycle greenhouse gas emissions of blended cement concrete including carbonation and durability, International Journal of Life Cycle Assessment, 19(1), pp. 3–12, 2014. [Crossref]
[5] Wong, J.K.W., Li, H., Wang, H., Huang, T., Luo, E. & Li, V., Toward low-carbon construction processes: the visualisation of predicted emission via virtual prototyping technology. Automation in Construction, 33, pp. 72–78, 2013. [Crossref]
[6] Yee, A.A., Social and environmental benefits of precast concrete technology. PCI Journal, 46(3), pp. 14–20, 2001. [Crossref]
[7] de la Fuente, A., Domingues de Figueiredo, A., Aguado, A., Molins, C. & Chama Neto, P.J., Experimentation and numerical simulation of steel fiber reinforced concrete pipes. Materiales de Construcción, 61(302), pp. 275–288, 2011. [Crossref]
[8] Kirch, U., Optimized prestressing by linear programming. International Journal for Numerical Methods in Engineering, 7(2), pp. 125–136, 1973. [Crossref]
[9] Hernández, S., Fontan, A.N., Díaz, J. & Marcos, D., VTOP. An improved software for design optimization of prestressed concrete beams. Advances in Engineering Software, 41(3), pp. 415–421, 2010. [Crossref]
[10] Ohkubo, S., Dissanayake, P.B.R. & Taniwaki, K., An approach to multicriteria fuzzy optimization of a prestressed concrete bridge system considering cost and aesthetic feeling. Structural Optimization, 15(2), pp. 132–140, 1998. [Crossref]
[11] Sirca, G.F. & Adeli, H., Cost optimization of prestressed concrete bridges. Journal of Structural Engineering, 131(3), pp. 380–388, 2005. [Crossref]
[12] Ahsan, R., Rana, S. & Nurul Ghani, S., Cost optimum design of posttensioned I-girder bridge using global optimization algorithm. Journal of Structural Engineering, 138(2), pp. 273–284, 2012. [Crossref]
[13] Martí, J.V., González-Vidosa, F., Yepes, V. & Alcalá, J., Design of prestressed concrete precast road bridges with hybrid simulated annealing. Engineering Structures, 48, pp. 342–352, 2013. [Crossref]
[14] Martí, J.V., García-Segura, T. & Yepes, V., Structural design of precast-prestressed concrete U-beam road bridges based on embodied energy. Journal of Cleaner Production, 120, pp. 231–240, 2016. [Crossref]
[15] Carbonell, A., Gonzalez-Vidosa, F. & Yepes, V., Design of reinforced concrete road vaults by heuristic optimization. Advances in Engineering Software, 42(4), pp. 151–159, 2011. [Crossref]
[16] Yepes, V., González-Vidosa, F., Alcalá, J. & Villalba, P., CO2-optimization design of reinforced concrete retaining walls based on a VNS-threshold acceptance strategy. Journal of Computing in Civil Engineering, 26(3), pp. 378–386, 2012. [Crossref]
[17] Camp, C.V. & Assadollahi, A., CO2 and cost optimization of reinforced concrete footings using a hybrid big bang-big crunch algorithm. Structural and Multidisciplinary Optimization, 48(2), pp. 411–426, 2013. [Crossref]
[18] Kripka, M., de Medeiros, G.F. & Lemonge, C.C., Use of optimization for automatic grouping of beam cross-section dimensions in reinforced concrete building structures. Engineering Structures, 99, pp. 311–318, 2015. [Crossref]
[19] Luz, A., Yepes, V., González-Vidosa, F. & Martí, J.V., Design of open reinforced concrete abutments road bridges with hybrid stochastic hill climbing algorithms. Informes de la Construcción, 67(540), pp. 3114, 2015.
[20] Sarma, K.C. & Adeli, H., Cost optimization of concrete structures. Journal of Structural Engineering, 124(5), pp. 570–579, 1998. [Crossref]
[21] Hassanain, M.A. & Loov, R.E., Cost optimization of concrete bridge infrastructure. Canadian Journal of Civil Engineering, 30(5), pp. 841–849, 2003. [Crossref]
[22] García-Segura, T., Yepes, V., Alcalá, J. & Pérez-López, E., Hybrid harmony search for sustainable design of post-tensioned concrete box-girder pedestrian bridges. Engineering Structures, 92, pp. 112–122, 2015. [Crossref]
[23] Yepes, V., Martí, J.V. & García-Segura, T., Cost and CO2 emission optimization of precast-prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm. Automation in Construction, 49, pp. 123–134, 2015. [Crossref]
[24] Baykasoglu, A., Oztas, A. & Ozbay, E., Prediction and multi-objective optimization of high-strength concrete parameters via soft computing approaches. Expert Systems with Applications, 36(3), pp. 6145–6155, 2009. [Crossref]
[25] Ayan, E., Saatçioglu, Ö. & Turanli, L., Parameter optimization on compressive strength of steel fiber reinforced high strength concrete. Construction and Building Materials, 25(6), pp. 2837–2844, 2011. [Crossref]
[26] Ezeldin, A. & Hsu, C., Optimization of reinforced fibrous concrete beams. ACI Structuctural Journal, 89(1), pp. 106–114, 1992.
[27] Suji, D., Natesan, S.C., Murugesan, R. & Sanjai Prabhu, R., Optimal design of fibrous concrete beams through simulated annealing. Asian Journal of Civil Engineering, 9(2), pp. 193–213, 2008.
[28] Martí, J.V., Yepes, V. & González-Vidosa, F., Memetic algorithm approach to designing of precast-prestressed concrete road bridges with steel fiber-reinforcement. Journal of Structural Engineering, 141(2), pp. 04014114, 2015. [Crossref]
[29] BEDEC. Institute of Construction Technology of Catalonia. Barcelona, Spain, available at: www.itec.cat
[30] Fomento, M., IAP-98: Code on the actions for the design of road bridges, Madrid, Spain, 1998. (in Spanish).
[31] Fomento, M., EHE-08: Code on structural concrete, Ministerio de Fomento, Madrid, Spain, 2008. (in Spanish).
[32] Moscato, P., On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms, Technical Report Caltech Concurrent Computation Program Report 826, Caltech, Pasadena, California, USA, 1989.
[33] Blum, C., Puchinger, J., Raidl, G.R. & Roli, A., Hybrid metaheuristics in combinatorial optimization: A survey. Applied Soft Computing, 11, pp. 4135–4151, 2011. [Crossref]
[34] Krasnogor, N. & Smith, J., A tutorial for competent memetic algorithms: model, taxonomy, and design issues. IEEE Transactions on Evolutionary Computation, 9, pp. 474–488, 2005. [Crossref]
[35] Ahuja, R.K., Ergun, Ö., Orlin, J.B. & Punnen, A.P., A survey of very large-scale neighborhood search techniques. Discrete Applied Mathematics, 123, pp. 75–102, 2002. [Crossref]
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Open Access
Research article

Design Optimization of Precast-Prestressed Concrete Road Bridges with Steel Fiber-Reinforcement by a Hybrid Evolutionary Algorithm

v. yepes,
j.v. martí,
t. garcía-segura
Institute of Concrete Science and Technology (ICITECH), Universitat Politècnica de València, Spain
International Journal of Computational Methods and Experimental Measurements
|
Volume 5, Issue 2, 2017
|
Pages 179-189
Received: N/A,
Revised: N/A,
Accepted: N/A,
Available online: N/A
View Full Article|Download PDF

Abstract:

In this paper, the influence of steel fiber-reinforcement when designing precast-prestressed concrete (PPC) road bridges with a double U-shape cross-section is studied through heuristic optimization. A hybrid evolutionary algorithm (EA) combining a genetic algorithm (GA) with variable-depth neighborhood search (VDNS) is formulated to minimize the economic cost and CO2 emissions, while imposing constraints on all the relevant limit states. The case study proposed is a 30-m span-length with a deck width of 12 m. The problem involved 41 discrete design variables. The algorithm requires the initial calibration. Moreover, the heuristic is run nine times so as to obtain statistical information about the minimum, average and deviation of the results. The evolution of the objective function during the opti- mization procedure is highlighted. Findings show that heuristic optimization is a forthcoming option for the design of real-life prestressed structures. This paper provides useful knowledge that could offer a better understanding of the steel fiber-reinforcement in U-beam road bridges.

Keywords: Hybrid evolutionary algorithm, Precast-prestressed concrete, Steel fiber-reinforcement, U-shape cross-section

1. Introduction

2. Bridge Optimization

3. Structural Evaluation

4. Heuristic Algorithm

5. Results

6. Conclusions

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Acknowledgments

The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (BRIDLIFE Project: BIA2014-56574-R) and the Research and Development Support Program of Polytechnic University of Valencia (PAID-02-15).

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References
[1] Flower, D.J.M. & Sanjayan, J.G., Green house gas emissions due to concrete manufacture. International Journal of Life Cycle Assessment, 12(5), pp. 282–288, 2007. [Crossref]
[2] Collins, F., Inclusion of carbonation during the life cycle of built and recycled concrete: influence on their carbon footprint. International Journal of Life Cycle Assessment, 15(6), pp. 549–556, 2010. [Crossref]
[3] Gartner, E.M., Industrially interesting approaches to “low-CO2” cements. Cement and Concrete Research, 34(9), pp. 1489–1498, 2004. [Crossref]
[4] García-Segura, T., Yepes, V. & Alcalá, J., Life cycle greenhouse gas emissions of blended cement concrete including carbonation and durability, International Journal of Life Cycle Assessment, 19(1), pp. 3–12, 2014. [Crossref]
[5] Wong, J.K.W., Li, H., Wang, H., Huang, T., Luo, E. & Li, V., Toward low-carbon construction processes: the visualisation of predicted emission via virtual prototyping technology. Automation in Construction, 33, pp. 72–78, 2013. [Crossref]
[6] Yee, A.A., Social and environmental benefits of precast concrete technology. PCI Journal, 46(3), pp. 14–20, 2001. [Crossref]
[7] de la Fuente, A., Domingues de Figueiredo, A., Aguado, A., Molins, C. & Chama Neto, P.J., Experimentation and numerical simulation of steel fiber reinforced concrete pipes. Materiales de Construcción, 61(302), pp. 275–288, 2011. [Crossref]
[8] Kirch, U., Optimized prestressing by linear programming. International Journal for Numerical Methods in Engineering, 7(2), pp. 125–136, 1973. [Crossref]
[9] Hernández, S., Fontan, A.N., Díaz, J. & Marcos, D., VTOP. An improved software for design optimization of prestressed concrete beams. Advances in Engineering Software, 41(3), pp. 415–421, 2010. [Crossref]
[10] Ohkubo, S., Dissanayake, P.B.R. & Taniwaki, K., An approach to multicriteria fuzzy optimization of a prestressed concrete bridge system considering cost and aesthetic feeling. Structural Optimization, 15(2), pp. 132–140, 1998. [Crossref]
[11] Sirca, G.F. & Adeli, H., Cost optimization of prestressed concrete bridges. Journal of Structural Engineering, 131(3), pp. 380–388, 2005. [Crossref]
[12] Ahsan, R., Rana, S. & Nurul Ghani, S., Cost optimum design of posttensioned I-girder bridge using global optimization algorithm. Journal of Structural Engineering, 138(2), pp. 273–284, 2012. [Crossref]
[13] Martí, J.V., González-Vidosa, F., Yepes, V. & Alcalá, J., Design of prestressed concrete precast road bridges with hybrid simulated annealing. Engineering Structures, 48, pp. 342–352, 2013. [Crossref]
[14] Martí, J.V., García-Segura, T. & Yepes, V., Structural design of precast-prestressed concrete U-beam road bridges based on embodied energy. Journal of Cleaner Production, 120, pp. 231–240, 2016. [Crossref]
[15] Carbonell, A., Gonzalez-Vidosa, F. & Yepes, V., Design of reinforced concrete road vaults by heuristic optimization. Advances in Engineering Software, 42(4), pp. 151–159, 2011. [Crossref]
[16] Yepes, V., González-Vidosa, F., Alcalá, J. & Villalba, P., CO2-optimization design of reinforced concrete retaining walls based on a VNS-threshold acceptance strategy. Journal of Computing in Civil Engineering, 26(3), pp. 378–386, 2012. [Crossref]
[17] Camp, C.V. & Assadollahi, A., CO2 and cost optimization of reinforced concrete footings using a hybrid big bang-big crunch algorithm. Structural and Multidisciplinary Optimization, 48(2), pp. 411–426, 2013. [Crossref]
[18] Kripka, M., de Medeiros, G.F. & Lemonge, C.C., Use of optimization for automatic grouping of beam cross-section dimensions in reinforced concrete building structures. Engineering Structures, 99, pp. 311–318, 2015. [Crossref]
[19] Luz, A., Yepes, V., González-Vidosa, F. & Martí, J.V., Design of open reinforced concrete abutments road bridges with hybrid stochastic hill climbing algorithms. Informes de la Construcción, 67(540), pp. 3114, 2015.
[20] Sarma, K.C. & Adeli, H., Cost optimization of concrete structures. Journal of Structural Engineering, 124(5), pp. 570–579, 1998. [Crossref]
[21] Hassanain, M.A. & Loov, R.E., Cost optimization of concrete bridge infrastructure. Canadian Journal of Civil Engineering, 30(5), pp. 841–849, 2003. [Crossref]
[22] García-Segura, T., Yepes, V., Alcalá, J. & Pérez-López, E., Hybrid harmony search for sustainable design of post-tensioned concrete box-girder pedestrian bridges. Engineering Structures, 92, pp. 112–122, 2015. [Crossref]
[23] Yepes, V., Martí, J.V. & García-Segura, T., Cost and CO2 emission optimization of precast-prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm. Automation in Construction, 49, pp. 123–134, 2015. [Crossref]
[24] Baykasoglu, A., Oztas, A. & Ozbay, E., Prediction and multi-objective optimization of high-strength concrete parameters via soft computing approaches. Expert Systems with Applications, 36(3), pp. 6145–6155, 2009. [Crossref]
[25] Ayan, E., Saatçioglu, Ö. & Turanli, L., Parameter optimization on compressive strength of steel fiber reinforced high strength concrete. Construction and Building Materials, 25(6), pp. 2837–2844, 2011. [Crossref]
[26] Ezeldin, A. & Hsu, C., Optimization of reinforced fibrous concrete beams. ACI Structuctural Journal, 89(1), pp. 106–114, 1992.
[27] Suji, D., Natesan, S.C., Murugesan, R. & Sanjai Prabhu, R., Optimal design of fibrous concrete beams through simulated annealing. Asian Journal of Civil Engineering, 9(2), pp. 193–213, 2008.
[28] Martí, J.V., Yepes, V. & González-Vidosa, F., Memetic algorithm approach to designing of precast-prestressed concrete road bridges with steel fiber-reinforcement. Journal of Structural Engineering, 141(2), pp. 04014114, 2015. [Crossref]
[29] BEDEC. Institute of Construction Technology of Catalonia. Barcelona, Spain, available at: www.itec.cat
[30] Fomento, M., IAP-98: Code on the actions for the design of road bridges, Madrid, Spain, 1998. (in Spanish).
[31] Fomento, M., EHE-08: Code on structural concrete, Ministerio de Fomento, Madrid, Spain, 2008. (in Spanish).
[32] Moscato, P., On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms, Technical Report Caltech Concurrent Computation Program Report 826, Caltech, Pasadena, California, USA, 1989.
[33] Blum, C., Puchinger, J., Raidl, G.R. & Roli, A., Hybrid metaheuristics in combinatorial optimization: A survey. Applied Soft Computing, 11, pp. 4135–4151, 2011. [Crossref]
[34] Krasnogor, N. & Smith, J., A tutorial for competent memetic algorithms: model, taxonomy, and design issues. IEEE Transactions on Evolutionary Computation, 9, pp. 474–488, 2005. [Crossref]
[35] Ahuja, R.K., Ergun, Ö., Orlin, J.B. & Punnen, A.P., A survey of very large-scale neighborhood search techniques. Discrete Applied Mathematics, 123, pp. 75–102, 2002. [Crossref]
Cite this:
APA Style
IEEE Style
BibTex Style
MLA Style
Chicago Style
GB-T-7714-2015
Yepes, V., Martí, J., & García-segura, T. (2017). Design Optimization of Precast-Prestressed Concrete Road Bridges with Steel Fiber-Reinforcement by a Hybrid Evolutionary Algorithm. Int. J. Comput. Methods Exp. Meas., 5(2), 179-189. https://doi.org/10.2495/CMEM-V5-N2-179-189
V. Yepes, J. Martí, and T. García-segura, "Design Optimization of Precast-Prestressed Concrete Road Bridges with Steel Fiber-Reinforcement by a Hybrid Evolutionary Algorithm," Int. J. Comput. Methods Exp. Meas., vol. 5, no. 2, pp. 179-189, 2017. https://doi.org/10.2495/CMEM-V5-N2-179-189
@research-article{Yepes2017DesignOO,
title={Design Optimization of Precast-Prestressed Concrete Road Bridges with Steel Fiber-Reinforcement by a Hybrid Evolutionary Algorithm},
author={V. Yepes and J.V. Martí and T. GarcíA-Segura},
journal={International Journal of Computational Methods and Experimental Measurements},
year={2017},
page={179-189},
doi={https://doi.org/10.2495/CMEM-V5-N2-179-189}
}
V. Yepes, et al. "Design Optimization of Precast-Prestressed Concrete Road Bridges with Steel Fiber-Reinforcement by a Hybrid Evolutionary Algorithm." International Journal of Computational Methods and Experimental Measurements, v 5, pp 179-189. doi: https://doi.org/10.2495/CMEM-V5-N2-179-189
V. Yepes, J.V. Martí and T. GarcíA-Segura. "Design Optimization of Precast-Prestressed Concrete Road Bridges with Steel Fiber-Reinforcement by a Hybrid Evolutionary Algorithm." International Journal of Computational Methods and Experimental Measurements, 5, (2017): 179-189. doi: https://doi.org/10.2495/CMEM-V5-N2-179-189
YEPES V， MARTÍ JV， GARCÍA-SEGURA T. Design Optimization of Precast-Prestressed Concrete Road Bridges with Steel Fiber-Reinforcement by a Hybrid Evolutionary Algorithm[J]. International Journal of Computational Methods and Experimental Measurements， 2017， 5(2)： 179-189. https://doi.org/10.2495/CMEM-V5-N2-179-189