Fatigue Life Prognosis of Concrete Using Extended Grey Markov Model

Abstract:

The fatigue life prognosis of concrete is becoming more important with the development for demanding higher quality and safety in industrial. However, effective methods for this prognosis are still in need now, due to the feature of concrete. This paper proposes the extended grey Markov model (i.e. EGMM) for fatigue life prognosis of concrete. Firstly, the GM (1, 1, λ1, λ2) (i.e. EGM) is proposed by integrating the particle swarm optimization algorithm (PSOA) with GM (1, 1) (i.e. GM). Then the Markov model is integrated with EGM and a novel prognosis method of the extended grey Markov model is proposed. The EGMM is used to combine the health states and transition probability. And a real case study is used to demonstrate the implementation and potential applications of the proposed fatigue life prognosis approach on concrete.

• Periodical: Applied Mechanics and Materials (Volumes 275-277)
• Pages: 1225-1228
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.275-277.1225
• Online since: January 2013
• Authors: Chao Zhu, Wen Bing Yang, Hui Long Wang
• Keywords: Building Material, Fatigue, Grey Model, Particle Swarm Optimization Algorithm, Prognosis

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