Contribution of AI and machining learning in advanced material characterization

Artificial intelligence (AI) includes many mathematical methods such as optimization algorithms, approximation technics (surface response), etc. Some methods brought more focus especially in machine learning (ML) and deep learning (DL) algorithms. Their applications is becoming an important tool in the fields of materials and mechanical engineering. It is due to their incredible capability of predictions of parameters and mechanics behaviours. This allows design of new materials and optimal structures beyond intuitions. Parameter identification of complex materiel for instance, involves massive design spaces that are intractable for conventional methods. In addition, simulation of such model under different loading often required days of finite element analysis with high performing computer.