Bridge Quality Appraisal Methodology: Application in The Strimonas Bridge. Case Study
Abstract
In the current utilization of Performance Indicators for bridge Quality Control, there is no correlation between observed and benchmarked Performance Indicator values, and an ambiguity of deliverables due to the diverse nature of Performance Indicators. For the alleviation of those above, this paper presents a methodology that appraises the quality of bridges. This methodology builds on the adaptation of the Sustainable Building Method and its combination with expert input solicitation methods and the research findings of COST Action TU1406. In addition, it features an adaptation of the Analytical Hierarchy Process. The methodology is presented regarding its general procedural steps and calculating requirements, and then it is tailored to the case study of Strimonas Bridge in Greece.
Keywords: |
analytical hierarchy process; bridges; performance; project management; quality control
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References
Alonso, J. A., & Lamata, M. T. (2006). Consistency in the analytic hierarchy process: a new approach. International journal of uncertainty, fuzziness and knowledge-based systems, 14(04), 445-459. https://doi.org/10.1142/S0218488506004114
Amado, J. (2015). Road Asset Management System. Infraestruturas de Portugal IP.MOD.033.V01 report. 3 p.
Barone, G., & Frangopol, D. M. (2014). Reliability, risk and lifetime distributions as performance indicators for life-cycle maintenance of deteriorating structures. Reliability Engineering & System Safety, 123, 21-37. https://doi.org/10.1016/j.ress.2013.09.013
Frangopol, D. M., Dong, Y., & Sabatino, S. (2017). Bridge life-cycle performance and cost: analysis, prediction, optimisation and decision-making. Structure and Infrastructure Engineering, 13(10), 1239-1257. https://doi.org/10.1080/15732479.2016.1267772
Frangopol, D. M., Strauss, A., & Kim, S. (2008). Bridge reliability assessment based on monitoring. Journal of Bridge Engineering, 13(3), 258-270. https://doi.org/10.1061/(ASCE)1084-0702(2008)13:3(258)
Ghosn, M., Dueñas-Osorio, L., Frangopol, D. M., McAllister, T. P., Bocchini, P., Manuel, L., ... & Akiyama, M. (2016). Performance indicators for structural systems and infrastructure networks. Journal of Structural Engineering, 142(9), F4016003. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001542
Goepel, K. D. (2013, June). Implementing the analytic hierarchy process as a standard method for multi-criteria decision making in corporate enterprises–a new AHP excel template with multiple inputs. In Proceedings of the international symposium on the analytic hierarchy process (Vol. 2013, pp. 1-10). Creative Decisions Foundation Kuala Lumpur.
International Initiative for a Sustainable Built Environment (iiSBE) Portugal (2009). Evaluation Guide SBToolPT – H V2009/2. Editions iiSBE Portugal, Guimarães, Portugal.
Ishizaka, A., & Labib, A. (2011). Review of the main developments in the analytic hierarchy process. Expert systems with applications, 38(11), 14336-14345. https://doi.org/10.1016/j.eswa.2011.04.143
Liang, Y., Wu, D., Huston, D., Liu, G., Li, Y., Gao, C., & Ma, Z. J. (2018). Civil Infrastructure Serviceability Evaluation Based on Big Data. In Guide to Big Data Applications (pp. 295-325). Springer, Cham. https://doi.org/10.1007/978-3-319-53817-4_12
Mateus, R., & Bragança, L. (2011). Sustainability assessment and rating of buildings: Developing the methodology SBToolPT–H. Building and environment, 46(10), 1962-1971. https://doi.org/10.1016/j.buildenv.2011.04.023
Padgett, J. E., & Tapia, C. (2013). Sustainability of natural hazard risk mitigation: Life cycle analysis of environmental indicators for bridge infrastructure. Journal of Infrastructure Systems, 19(4), 395-408. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000138
Panetsos, P. (2017). Work Group 4 – Sub Group B1: Detailed description of the existing data of the “Strimonas River Bridge”, Greece and the suggested PI and KPI to be used and their values. Research report for the COST Action TU1406 WG4 meeting, Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux (IFSTTAR) 2017, Marne-la-Vallée, France, 12 May, 2017. 104 p.
Shao, Y., Yuan, J., & Li, Q. (2017). Identification of the residual value risk factors for road PPP projects in China: Questionnaire survey and analysis. In Proceedings of the 20th International Symposium on Advancement of Construction Management and Real Estate (pp. 379-389). Springer, Singapore. https://doi.org/10.1007/978-981-10-0855-9_33
Strauss, A., Ivankovic, A. M., Matos, J. C., & Casas, J. R. (2016). WG1 technical report: Performance indicators for roadway bridges of COST Action 1406.
Xu, Z. (2000). On consistency of the weighted geometric mean complex judgement matrix in AHP1. European Journal of Operational Research, 126(3), 683-687. https://doi.org/10.1016/S0377-2217(99)00082-X
Zhang, W., & Wang, N. (2017). Bridge network maintenance prioritization under budget constraint. Structural safety, 67, 96-104. https://doi.org/10.1016/j.strusafe.2017.05.001
DOI: 10.7250/bjrbe.2018-13.420
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Copyright (c) 2018 Dimosthenis Kifokeris, Yiannis Xenidis, Panagiotis Panetsos, José António Campos E Matos, Luķs Braganēa
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