Probabilistic Modeling and Structural Reliability based Monte Carlo Simulation: A Case Study
Probabilistic Modeling and Structural Reliability based Monte Carlo Simulation: A Case Study |
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| © 2024 by IJETT Journal | ||
| Volume-72 Issue-5 |
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| Year of Publication : 2024 | ||
| Author : Hicham Lamouri, Mouna El Mkhalet, Nouzha Lamdouar |
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| DOI : 10.14445/22315381/IJETT-V72I5P133 | ||
How to Cite?
Hicham Lamouri, Mouna El Mkhalet, Nouzha Lamdouar, "Probabilistic Modeling and Structural Reliability based Monte Carlo Simulation: A Case Study," International Journal of Engineering Trends and Technology, vol. 72, no. 5, pp. 321-331, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I5P133
Abstract
The paper presents the Monte Carlo method and its applications. According to several studies, the method has been found to be a powerful, simple tool and has been widely utilized for a broad range of approaches to civil engineering problems. The paper also aims to explore the method for reliability analysis and probabilistic modeling. It provides an understanding through two practical cases of study, with a discussion of its fundamental advantages and drawbacks. The first application focuses on modeling the strength characteristics of a reinforced concrete cross-section, including bending moment and shear resistances. In contrast, the second case concentrates on the reliability analysis of a flanged bridge beam in accordance with the prescriptions of the European standard of reinforced concrete design, EUROCODE 2. The variations and uncertainties in geometrical parameters and material properties are modeled by deterministic and random variables using site measurements and the Joint Committee of Structural Safety (JCSS) Probabilistic Code, as well as the proposed models in the literature. This study offers significant contributions to the field of reliability, with a specific focus on structural engineering, and paves the way for further advancements in the use of artificial intelligence techniques, providing valuable insight for researchers and civil engineering practitioners.
Keywords
Monte Carlo simulation, Probability distribution, Structural reliability, FORM, Reinforced concrete, Bridges.
References
[1] Andrzej S. Nowak, and Kevin R. Collins, Reliability of Structures, 2nd Ed., CRC Press, pp. 1-407, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Gislaine Cristina Batistela, and Danilo Simoes, “Monte Carlo Simulation in the Assessment of Economic-Financial Uncertainties of a Manufacturing Industry,” Current Journal of Applied Science and Technology, vol. 25, no. 1, pp. 1-7, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Daniel J. Arenas et al., “A Monte Carlo Simulation Approach for Estimating the Health and Economic Impact of Interventions Provided at a Studentrun Clinic,” PLoS One, vol. 12, no. 12, pp. 1-12, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Goran Avlijas et al., “Examining the Value of Monte Carlo Simulation for Project Time Management,” Management: Journal of Sustainable Business and Management Solutions in Emerging Economies, vol. 24, no. 1, pp. 11-23, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Robert E. Melchers, and André T. Beck, Structural Reliability Analysis and Prediction, 3rd Ed., John Wiley & Sons Ltd, pp. 1-528, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Srinivasan Chandrasekaran, Offshore Structural Engineering: Reliability and Risk Assessment, 1st Ed., CRC Press, pp. 1-274, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Ehsan Jahani, Mohsen A. Shayanfar, and Mohammad A. Barkhordari, “A New Adaptive Importance Sampling Monte Carlo Method for Structural Reliability,” KSCE Journal of Civil Engineering, vol. 17, pp. 210-215, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Mehmet F. Yilmaz, “Reliability Analysis of Bridge with Monte-Carlo Simulation,” PACE 2021- International Congress on the Phenomenological Aspect of Civil Engineering, vol. 1, no. 1, pp. 1-6, 2021.
[Google Scholar] [Publisher Link]
[9] Yubao Liu, Hanxiong Liu, and Shouyi Sun, “Study on Structural Reliability of Prestressed Reinforced Concrete Beam Bridges Based on Full Probability Analysis,” IOP Conference Series: Materials Science and Engineering, vol. 1210, pp. 1-8, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[10] M.R. Machado, and J.M.C. Dos Santos, “Reliability Analysis of Damaged Beam Spectral Element with Parameter Uncertainties,” Shock and Vibration, vol. 2015, pp. 1-12, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Joao B. Cardoso, “Structural Reliability Analysis using Monte Carlo Simulation and Neural Networks,” Advances in Engineering Software, vol. 39, no. 6, pp. 505-513, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Alberto Bordallo-Ruiz et al., “The Structural Reliability of Bridges Subject to Time-Dependent Deterioration,” Proceedings of the 11th Conference on Civil, Structural and Environmental Engineering Computing, pp. 1-18, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Chul-Woo Kim, Mitsuo Kawatani, Effect of Dynamic Wheel Loads on Fatigue Performance on RC Slabs, Reliability and Optimization of Structural Systems: Assessment, Design, and Life-Cycle Performance, 1st Ed., pp. 1-10, 2007.
[Google Scholar] [Publisher Link]
[14] Mbarka Selmi, Mounir Ltifi, and Nizar Bel Hadj Ali, “Application of the Monte Carlo Method in Slope Stability Analysis,” National Days of Geotechnics and Engineering Geology, pp. 89-96, 2006.
[Google Scholar] [Publisher Link]
[15] Mark G. Stewart, and David V. Rosowsky, “Time-Dependent Reliability of Deteriorating Reinforced Concrete Bridge Decks,” Structural Safety, vol. 20, no. 1, pp. 91-109, 1998.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Ilya M. Sobol, A Primer for the Monte Carlo Method, CRC Press, pp. 1-1269, 1994.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Mohamed Abdallah El-Reedy, Reinforced Concrete Structural Reliability, 1st Edition, CRC Press, pp. 1-376, 2012.
[Google Scholar] [Publisher Link]
[18] Achintya Haldar, and Sankaran Mahadevan, Probability, Reliability and Statistical Method in Engineering Design, John Wiley & Sons, pp. 1-304, 2000.
[Google Scholar] [Publisher Link]
[19] Michael Havbro Faber, Risk and Safety in Civil, Surveying and Environmental Engineering, Swiss Federal Institute of Technology, pp. 1-69, 2005.
[Google Scholar] [Publisher Link]
[20] “Probabilistic Model Code,” Joint Committee on Structural Safety, 2001.
[Google Scholar] [Publisher Link]
[21] Sher Ali Mirza, James G. MacGregor, and Michael Hatzinikolas, “Statistical Descriptions of Strength of Concrete,” Journal of the Structural Division, vol. 105, no. 6, pp. 1021-1037, 1979.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Mark G. Stewart, “Workmanship and its Influence on Probabilistic Models of Concrete Compressive Strength,” ACI Materials Journal, vol. 92, no. 4, pp. 361-372, 1995.
[CrossRef] [Google Scholar] [Publisher Link]
[23] L. Pham, “Reliability Analyses of Reinforced Concrete and Composite Column Sections Under Concentric Loads,” Institution of Engineers, vol. CE2, no. 1, pp. 68-72, 1985.
[Google Scholar] [Publisher Link]
[24] Dawid F. Wisniewski, “Safety Formats for the Assessment of Concrete Bridges,” University of Minho Guimaraes, pp. 1-378, 2007.
[Google Scholar] [Publisher Link]
[25] W.H. Mosley, J.H. Bungey, and R. Hulse, Reinforced Concrete Design, Red Globe Press London, no. 5, pp. 1-385, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[26] CSA-S6:19, Canadian Highway Bridge Design Code, CSA Group. [Online]. Available: https://www.csagroup.org/canadian-highway-bridge-design-code/
[27] Anne-Marie Langlois, “Influence of Damage on the Structural Reliability of Reinforced Concrete Bridges: Case Studies,” Master's Thesis, Laval University, pp. 1-234, 2010.
[Google Scholar] [Publisher Link]
[28] Ferhat Akgül, and Dan M. Frangopol, “Lifetime Performance Analysis of Existing Reinforced Concrete Bridges. II: Application,” Journal of Infrastructure Systems, vol. 11, no. 2, pp. 129-141, 2005.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Abdulhakim Adeoye Shittu, Athanasios Kolios, and Ali Mehmanparast, “A Systematic Review of Structural Reliability Methods for Deformation and Fatigue Analysis of Offshore Jacket Structures,” Metals, vol. 11, no. 1, pp. 1-37, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[30] Terry Williams, “The Contribution of Mathematical Modelling to the Practice of Project Management,” IMA Journal of Management Mathematics, vol. 14, no. 1, pp. 3-30, 2003.
[CrossRef] [Google Scholar] [Publisher Link]
[31] Applied R&M Manual for Defence Systems, Part D-Supporting Theory, Safety and Reliability Society, pp. 1-2, 2012.
[Publisher Link]
[32] El Ghoulbzouri Abdelouafi, Kissi Benaissa, and Khamlichi Abdellatif, “Reliability Analysis of Reinforced Concrete Buildings: Comparison between FORM and ISM,” Procedia Engineering, vol. 114, pp. 650-657, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[33] Victor Platon, and Andreea Constantinescu, “Monte Carlo Method in Risk Analysis for Investment Projects,” Procedia Economics and Finance, vol. 15, pp. 393-400, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[34] T.H. Nguyen et al., “Reliability-based Design Optimization of Steel Concrete Composite Beams Using Genetic Algorithm and Monte Carlo Simulation,” Engineering, Technology & Applied Science Research, vol. 12, no. 6, pp. 9766-9770, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[35] Lambros K. Mitropoulos et al., “A Fuzzy and a Monte Carlo Simulation Approach to Assess Sustainability and Rank Vehicles in Urban Environment,” Transportation Research Procedia, vol. 24, pp. 296-303, 2017.
[CrossRef] [Google Scholar] [Publisher Link]