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The Research on Low-cycle Fatigue Crack Growth Rate of Steam Turbine Rotor Steel Based on Immune-Genetic Algorithm

Author: WangZuo
Tutor: ChenJian
School: Changsha University of Science and Technology
Course: Power Machinery and Engineering
Keywords: steam turbine rotor 30CrlMolV steel low cycle fatigue load ratio creep aging immune-genetic algorithm
CLC: TK263.61
Type: Master's thesis
Year: 2009
Downloads: 97
Quote: 0
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Abstract


Steam turbine rotor is one of the steam turbine core parts. During long-term operation, the turbine is suffered high temperature, starting-up to stopping, changing load, it is easy to initiate low cycle fatigue crack. Lifetime of steam turbine rotor is mainly depended on low cycle fatigue crack growth rate, therefore the study of low cycle fatigue crack growth rate has significant meaning to analyze steam turbine rotor life.In this dissertation, crack growth macroscopic and microscopic law of steam turbine steel was analyzed and three famous formulas(Paris formula, Forman formula and Zheng-Hirt formula) of fracture mechanics principle of crack growth rate was cited, meanwhile, affect of considered temperature, load ratio, creep and aging of low cycle fatigue crack growth was researched deeply, the result shows crack growth rate obviously quicker than that at room when the temperature is 538℃;Load ratio increased, crack growth rate also accelerate; Creep influencing fatigue crack subcritical growth of steam turbine rotor steel is a thermal activation process of the receptors diffusion controlled. By 200h, 600h, 800h, 1200h of different aging time, the hardness of the steam turbine rotor material reduces gradually, causing FATT to go up, so affect crack growth rate.It is on the foundation of preceding theory and experiment data, the multi-parameter and nonlinear function model for low cycle fatigue crack growth rate of steam turbine rotor steel was put forward. Immunity systematic principle was combined and immunity-genetic algorithm was put forward based on the foundation of genetic-algorithm. In this dissertation, immunity-genetic algorithm was used to optimize model characteristic parameters of low cycle fatigue crack growth rate. According to immune-genetic algorithm and the partial data of low cycle fatigue experiment of the steam turbine rotor steel (30Cr1Mo1V), optimization calculation was carried out. In actual operation condition restraint, the algorithm was used to optimize the rate model, finally the best parameters value was obtained, and the optimal curve of crack growth rate was described. The optimal curve of rate is compared with experiment, it is anastomosis fairly in the crack growth specific stage, the result shows the immunity-genetic algorithm high effectiveness, robustness and parallelism in search course, for the multivariate nonlinear model of different load ratio and lack enough experiment data that the low cycle fatigue crack growth rate of steam turbine rotor has better treatment.In this dissertation, correct low cycle fatigue crack growth rate law of steam turbine rotor was imitated by simple and convenient computer intelligent algorithm, this method has direct realistic meaning and project application value to predict lifetime and evaluate state of the steam turbine rotor and the other high temperature equipments.

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CLC: > Industrial Technology > Energy and Power Engineering > Steam Power Engineering > Steam turbine (steam turbine,steam turbine ) > Structure > Interlocks and twist > Rotor
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