Identifying Bridges With High Damage Risk Using The Taguchi Test Design Method(Case Study: Concrete Road Bridges in Zanjan Province)

Document Type : Research Paper

Authors

1 Department of Civil Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

2 Department of Civil Engineering, Qazvin Branch, Islamic Azad University, Qazvin, IRan

Abstract

Conducting evaluation studies on the bridges used on the road surface is one of the most important time-consuming and costly processes, especially considering the high number of bridges in Iran, i.e., more than 35 thousand in the whole country and 8658 bridges in Zanjan province. On the other hand, the time and cost of these studies can cause delays in carrying out studies for all bridges and cause irreparable damages due to a lack of proper management of bridge repair and maintenance. Taguchi's test design method is one of the methods that predict the desired combination with the help of statistical and mathematical models, by defining its orthogonal arrays, instead of performing all possible evaluation options, by performing a limited number of evaluations. In this research, based on the Taguchi method, instead of examining 8658 bridges with 13 different criteria, only 27 combinations of the physical characteristics of bridges and atmospheric, climatic and traffic conditions affecting concrete road bridges in 5 main axes of Zanjan province were determined the deterioration indices of bridges with these combinations were calculated.

It showed that the combination of bridges with 2-3 times of snow along the axis, 91-100 days of frost during the year, 26-30% of heavy vehicles passing over the bridge and a length of 7.1-12 meters has the highest structure failure index with an estimated average of 76.2725, which will lead to the highest failure risk. This means that this combination has created the highest risk of damage. Also, the most important factor in the failure of bridges is the percentage of passing heavy vehicles compared to the total traffic.

Keywords

Main Subjects


Aita, C. A. G., Goss, I. C., Rosendo, T. S., Tier, M. D., Wiedenheoft, A. and Reguly, A. 2020. “Shear strength optimization for FSSW AA6060-T5 joints by Taguchi and full factorial design”. J. Mater. Res. Technol., 9: 16072e9. https://doi.org/10.1016/j.jmrt.2020.11.062
Alonso Medina, P., León González, F. J. and Todisco, L. 2022. “Data-driven prediction of long-term deterioration of RC bridges”. Constr. Build. Mater. 317: 125790. https://doi.org/10.1016/j.conbuildmat.2 021.125790
Antony, J. 2003. “Design of experiments for engineers and scientists”. Elsevier Science & Technology Books.
Baharudin, B. T. H. T., Ibrahim, M. R., Ismail, N., Leman, Z., Ariffin, M. K. A. and Majid, D. L. 2012. “Experimental investigation of HSS face milling to AL6061 using Taguchi method”. Proc. Eng., 50: 933-941.
Calvert, G., Neves, L., Andrews, J. and Hamer, M. 2020. “Multi-defect modeling of bridge deterioration using truncated inspection records”. Reliab. Eng. Syst. Safe., 200: 106962.  https://doi.org/10.1016/j.ress.2020. 106962
COWI Consultant Engineers. 2004. “Bridge management system”. Technical Report.
Frangopol, D. M., Dong, Y. and Sabatino, S. 2017. “Bridge life-cycle performance and cost: Analysis, prediction, optimisation and decision-making”. Struct. Infrastruct. Eng., 13(10): 1239-1257.  https://doi.org /10.1080/15732479.2016.1267772
Furtak, K. 2021. “Contemporary challenges of science and technology– selected reflections”. Cement Wapno  Beton, 26(5): 413-430.
Hikmat, M., Rostam, S. and Ahmed, Y. M. 2021. “Investigation of tensile property-based Taguchi method of PLA parts fabricated by FDM 3D printing technology”. Res. Eng., 11: 100264. https://doi.org/10.1016/ j.rineng.2021.100264
Hong, C. W. 2012. “Using the Taguchi method for effective market segmentation”. Exp. Syst. Appl., 39: 5451-5459.
Kaewunruen, S., Sresakoolchai, J. and Zhou, Z. 2020. “Sustainability-based lifecycle management for bridge infrastructure using 6D BIM”. Sustain., 12(6): 2436. https://doi.org/10.3390/su12062436
Kumar, R., Kumar, K. and Bhowmik, S. 2014. “Optimization of mechanical properties of epoxy based wood dust reinforced green composite using Taguchi method”. Proc. Mater. Sci. 5:  688-696. https://doi.org/10.1016/j.mspro.2014.07.316
Lyu, S. R., Wu, W. T., Hou, C. C. and Hsieh, W. H. 2010. “Study of cryopreservation of particular chondrocytes using the Taguchi method”. Cryobiol., 60: 165-176.
Mustapha, A. N., Zhang, Y., Zhang, Z., Ding, Y., Yuan, Q. and Li, Y. 2021. “Taguchi and ANOVA analysis for the optimization of the microencapsulation of a volatile phase change material”. J. Mater. Res. Technol., 11: 667e80. https://doi.org/10.1016/j.jmrt.2021.01.02518
Natrayan, L., Anand, R. and Santhosh Kumar, S. 2020. “Optimization of process parameters in TIG welding of AISI 4140 stainless steel using Taguchi technique”. Mater.: Proc.. https://doi.org/10.1016/j.matpr.2020. 07.150
Nuruddin, M. and Bayuaji, R. 2009. “Application of Taguchi’s approach in the optimization of mix proportion for microwave incinerated rice husk ash foamed concrete”. IJCEE, 9: 121-129.
Ogbonna, O. S., Akinlabi, S. A., Madushele, N., Fatoba, O. S. and Akinlabi, E. T. 2023. “Grey-based Taguchi method for multi-weld quality optimization of gas metal arc dissimilar joining of mild steel and 316 stainless steel”. Results Eng., 100963.
Perno, M., Hvam, L. and Haug, A. 2022. “Implementation of digital twins in the process industry: A systematic literature review of enablers and barriers”. Comput. Ind., 134: 103558. https://doi.org/10.1016/j.compind. 2021.103558
Ranjit, K. and Roy, A. 2010. “Primer on the Taguchi method”. Second ed., Society of Manufacturing Engineers.
Rashidi, M., Hoshyar, A. N., Smith, L., Bijan, S. and Siddique, R. 2020. “A comprehensive taxonomy for structure and material deficiencies, preventions and remedies of timber bridges”. J. Build. Eng. 34: 101624. https://doi.org/10.1016/j.jobe.2020.101624
Roy, R. K. 2011. “Design of experiments using the Taguchi approach: 16 steps to product and process improvement”. John Wiley & Sons, Inc., New York, pp. 369-402.
Ryall, M. J., Parke, G. A. R. and Harding, J. E. 2000. “Bridge management: Inspection, maintenance, assessment & Repair”. Department of Civil Engineering, University of Surrey, UK.
Semeraro, C., Lezoche, M., Panetto, H. and Dassisti, M. 2021. “Digital twin paradigm: A systematic literature review”. Comput. Ind., 130: 103469. https://doi.org/10.1016/j.compind.2021.103469
Singh, M. and Singh, S. 2021. “Multiple response optimization of ultrasonic assisted electric discharge Machining of Nimonic 75: A Taguchi-Grey relational analysis approach”. Mater.: Proc., 173: 1-6. https://doi.org/10.1016/j.matpr.2021.01.173
Suji, D., Adesina, A. and Mirdula, R. 2021. “Optimization of self-compacting composite composition using Taguchi-Grey relational analysis”. Materialia, B, 15. https://doi.org/10.1016/j.mtla.2021.101027
Taguchi, G. 1986. “Introduction to quality engineering”. Asian Productivity Organization/UNIPUB, White Plains.
Tan, Y. H., Abdullah, M. O., Nolasco-hipolito, C. and Zauzil, N. A. 2017. “Application of RSM and Taguchi methods for optimizing the transesterification of waste cooking oil catalyzed by solid ostrich and chicken-eggshell derived CaO”. Renew. Energy 114: 437-447.
Tonias, D. E. 1995. “Bridge Engineering: Design, rehabilitation and maintenance of modern highway bridges". McGraw-Hill, N. Y.
 Turski, R. and Rogala, W. 2022. “Current situation and further development of AAC in Europe”. Cement Wapno Beton, 27(3): 154-165.
Yusuff, A. S. 2019. “Adsorption of hexavalent chromium from aqueous solution by Leucaena leucocephala seed pod activated carbon: Equilibrium kinetic and thermodynamic studies”. Arab J. Basic Appl. Sci. 26(1): 89-102. https://doi.org/10.1080/25765299.2019.1567656.
Yuvaraj Ramesh, K. 2021. “Experimental investigation on strength properties of concrete incorporating ground pond ash”. Cement Wapno  Beton, 26: 253-262.
Zhang, M., Zhao, H., Fan, L. and Yi, J. 2022. “Dynamic modulus prediction model and analysis of factors influencing asphalt mixtures using gray relational analysis methods”. J. Mater. Res. Technol., 19: 1312e21. https://doi.org/10.1016/j.jmrt.2022.05.120