Calibration of damage parameters for Y5 and G91 steels in use of genetic algorithm

In the present paper, a multi-island genetic algorithm is adopted into well-known Rousselier model to resolve variableness and complexity of previous calibration methods since reliability of damage parameters significantly depended on the calibration method - trial and error method, neural network method and so on combined with notched bar tests or small punch (SP) tests - and analyzer's experiences. SP test data of typical nuclear materials such as a low alloy steel (Y5) and a high Cr steel (G91) are used to determine damage parameters and, then, resulting values are applied to predict corresponding fracture toughnesses. Load-displacement curves and fracture resistance curves are compared with those obtained from a conventional estimation method as well as standard fracture tests, which show effectiveness of the proposed method