Creep life assessment method

Abstract

The present invention relates to a creep life assessment method having high precision and accuracy, especially for using in an inspection and assessment of the service life of material at high temperature including easy to apply with the conventional creep assessment. Moreover, said method intends to assess the actual creep life considering the creep life prediction from the model built from machine learning from the factor and operating condition data that affects the creep such as temperature, stress, including Larson-Miller parameter and Larson-Miller constant, which have been adjusted to consider the factor and operating condition, resulting in more precise and accurate creep life prediction. Said method also considers the creep life fraction assessment by considering the physical property of the material together with the accumulated creep condition simulation, so that the creep life fraction assessment of the material from model built from machine learning is more precise. Therefore, the actual creep life can be assessed.