TC19

Data-driven methods and machine learning applied to structural integrity

Chairpersons

Chao Gao

NTNU, Norway

Andrea Tridello

Politecnico di Torino, Italy

Marco Davo’

DecHit S.p.A., Italy

Secretary

Prof. Filippo Berto

Università La Sapienza, Roma

Department of Chemical Engineering, Materials and Environment 

e-mail: filippo.berto@uniroma1.it

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TC19 Scope

Data driven methods are becoming very useful tools in structural integrity. Direct design or inverse design allow to assess efficiently the performances of existing structures or to open new design space proposing new materials or structures to achieve targeted performances.

The aim of this TC is to follow these methods in connection to Structural Integrity opening new research possibilities that will strongly impact on applications.