PSI - Issue 5

Martin Krejsa et al. / Procedia Structural Integrity 5 (2017) 1283–1290

1290

Martin Krejsa et al. / Structural Integrity Procedia 00 (2017) 000 – 000

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were obtained for three basic phenomena, which are related to propagation of the fatigue cracks. On the basis of those data, the probability of failure can be calculated for each year of operation of the structural element. When determining the required degree of reliability, it is possible to specify the time of the first inspection of the structure, which will focus on the fatigue damage. Using a conditional probability, times for subsequent inspections can be determined. The article describes how to design the system of regular structural inspections in case of the simple demonstration example. The DOProC method and its application in probabilistic prediction of fatigue crack damage can considerably improve estimation of maintenance costs for the structures and bridges subject to cyclic loads. This methodology is developed further. The goal of investigations seems to be, in particular, application of Bayesian networks in the computational model, such as e.g. in Mahadevan et al. (2001), which describes propagation of fatigue cracks in the system. Acknowledgements This contribution has been developed as a part of the research project GACR 17- 01589S “Advanced computational and probabilistic modelling of steel structures taking account fatigue damage” supported by the Czech Grant Agency and also has been completed thanks to the financial support provided to VSB-Technical University of Ostrava by the Czech Ministry of Education, Youth and Sports from the budget for conceptual development of science, research and innovations for the 2017 year. References Guan, X., Jha, R., Liu, Y., 2011. Model Selection, Updating, and Averaging for Probabilistic Fatigue Damage Prognosis. Structural Safety 33(3), 242 – 249. Halama, R., Fusek, M., Poruba, Z., 2016. Influence of mean stress and stress amplitude on uniaxial and biaxial ratcheting of ST52 steel and its prediction by the AbdelKarim-Ohno model. International Journal of Fatigue 91(2), 313-321. Kala, Z., 2007. Influence of partial safety factors on design reliability of steel structures - Probability and fuzzy probability assessments. Journal of Civil Engineering and Management 13(4), 291-296. Kralik, J., 2013. Deterministic and probabilistic analysis of steel frame bracing system efficiency. Applied Mechanics and Materials 390, 172-177. Krejsa, M., Janas, P., Krejsa, V., 2016. Structural Reliability Analysis Using DOProC Method. Procedia Engineering 142, 34-41. Krejsa, M., Koubova, L., Flodr, J., Protivinsky, J., Nguyen, Q.T., 2017. Probabilistic prediction of fatigue damage based on linear fracture mechanics. Frattura ed Integrita Strutturale 11(39), 143-159. Krejsa, M., Tomica, V., 2011. Determination of Inspections of Structures Subject to Fatigue. Transactions of the VSB – Technical University of Ostrava, Civil Engineering Series 11(1), 1-9. Kruml, T., Hutar, P., Nahlik, L., Seitl, S., Polak, J., 2011. Fatigue cracks in Eurofer 97 steel: Part II. Comparison of small and long fatigue crack growth. Journal of Nuclear Materials 412(1), 7-12. Lu, N., Noori, M., Liu, Y., 2017. Fatigue reliability assessment of welded steel bridge decks under stochastic truck loads via machine learning. Journal of Bridge Engineering 22(1). Mahadevan, S., Zhang, R., Smith, N., 2001. Bayesian networks for system reliability reassessment. Structural Safety 23, 231-251. Melchers, R., 1999. Structural Reliability Analysis and Prediction. John Wiley, New York, pp. 437. Paris, P., Erdogan, F., 1963. A Critical Analysis of Crack Propagation Laws. Journal of Basic Engineering 85(4), 528-534. Sanches, R.F., De Jesus, A.M.P., Correia, J.A.F.O., Da Silva, A.L.L., Fernandes, A.A., 2015. A Probabilistic Fatigue Approach for Riveted Joints using Monte Carlo Simulation. Journal of Constructional Steel Research 110, 149 – 162. Schneider, R., Thöns, S., Straub, D., 2017. Reliability analysis and updating of deteriorating systems with subset simulation. Structural Safety 64(1), 20-36. Tong, C., Sun, Z.L., Chai, X.D., Wang, J., 2016. Gear contact fatigue reliability based on response surface and MCMC. Dongbei Daxue Xuebao/Journal of Northeastern University 37(4), 532-537 Vican, J., Gocal, J., Odrobinak, J., Kotes, P., 2016. Analysis of Existing Steel Railway Bridges. Procedia Engineering 156, 507-514. Wang, C.S., Zhai, M.S., Duan, L., Wang, Q., 2015. Fatigue service life evaluation of existing steel and concrete bridges. Advanced Steel Construction 11(3), 305-321. Xiang, Y., Liu, Y., 2011. Application of Inverse First-order Reliability Method for Probabilistic Fatigue Life Prediction. Probabilistic Engineering Mechanics 26(2), 148 – 156. Ye, X.W., Su, Y.H., Han, J.P., 2014. A State-of-the-Art Review on Fatigue Life Assessment of Steel Bridges. Mathematical Problems in Engineering 2014, 1 – 13.