Comparison evolutionary algorithms with Metropolis-Hastings method exemplified by high-fatigue Wohler curve parameter identification

• Autorzy: Woch M.
• Języki publikacji: EN

Abstrakty

EN

In this work, evolutionary algorithms together with the Metropolis-Hastings sampling technique have been used for parameter identification of the Wohler curve of duraluminum alloy 2024-T3. An evolutionary algorithm is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. The Metropolis-Hasting algorithm is one of the most widespread Markov chain Monte Carlo methods for posterior distribution estimation. In this contribution, both algorithms have been presented to estimate the probability density functions using Wohler parameters as a case study. Results were shown in terms of distribution shape and parameter correlations and the differences, arising from applied algorithms, have been compared. The information about parameter distributions of Wohler equation is useful to prepare risk analyses based on statistical safe life approach. The safe life approach can be met, for instance, in assessing the reliability of an aircraft.

Słowa kluczowe

EN

Wohler curve; Metropolis-Hastings; evolutionary algorithms probabilistic; fatigue

• Wydawca: Polskie Towarzystwo Bezpieczeństwa i Niezawodności
• Czasopismo: Journal of Polish Safety and Reliability Association
• Rocznik: 2015
• Tom: Vol. 6, No. 2
• Strony: 153--158
• Opis fizyczny: Bibliogr. 8 poz., rys., tab., wykr.

Twórcy

autor

Woch M.

• Air Force Institute of Technology, Warsaw, Poland

Bibliografia

• [1] Ayyub, B. M. (2011). Vulnerability, Uncertainty, and Risk - Analysis, Modeling, and Management. American Society of Civil Engineers (ASCE).
• [2] DEF STAN 00-970, Part 1/3 Section Leaflet 35 Fatigue. Safe-life substantiation.
• [3] DOT/FAA/AR-MMPDS-01. (2003). Metallic Materials Properties Development and Standardization (MMPDS). U.S. Department of Transportation, Federal Aviation Administration.
• [4] Gwiazda, T. (2007). Algorytmy genetyczne. Kompendium. Warszawa, Wydawnictwo Naukowe PWN SA.
• [5] Jędrzejewski, T. (2007). Algorytmy ewolucyjne. Wakacyjne Warsztaty Wielodyscyplinarne.
• [6] Leski, A., et. al. (2009). Oszacowanie indywidualnego zużycia zmęczeniowego struktur określonej populacji statków powietrznych. ITWL, Warsaw.
• [7] Mattrand, C., Bourinet, J.M. & Theret, D. (2011). Analysis of Fatigue Crack Growth under Random Load Sequences Derived from Military In-flight Load Data. 26th ICAF Symposium, Montreal.
• [8] Sbarufatti, C. (2013). Fatigue crack monitoring of helicopter fuselages and life evaluation through sensor network. Politecnico di Milano, Dipartimento di Meccanica, PhD thesis.