We investigate fatigue of materials, especially thermal effects, and analyze fracture mechanims under of influence of various factors, such as static, fatigue, impact loading, enviromental influence.
We use various NDT techniques in our research, including infrared thermography, acoustic emission, ultrasonic testing, shearography, X-ray computed tomography.
Our group is specializing in modal analysis and related algorithmic topics, like sensor integration, optimal sensor placement, and damage identification.
Unique signal and image processing algorithms developed by the group allow enhancing non-destructive testing and structural health monitoring results.
Andrzej Katunin was awarded with the commemorative medal on the occasion of the 80th anniversary of the Faculty of Mechanical Engineering of the Silesian University of Technology, awarded for contribution to the development of science at the national and international level and for involvement in the development of the Faculty.
Andrzej Katunin was awarded by the Division IV of Technical Sciences of the Polish Academy of Sciences for his studies on self-heating effect occurring during fatigue of polymer-matrix composite materials.
During the last weeks, Andrzej Katunin implemented his internship at the Xi'an Jiaotong Univeristy, where he was focused on evaluation of fatigue damage in composites using X-ray computed tomography.
The group is focusing on the wide range of structural integrity problems. We believe that only proper integration of theoretical, numerical, and experimental results provides valuable input for the scientific community and society.
In our research we are focusing on numerous specific problems, like fatigue of composite materials under the presence of the self-heating effect, analysis of low-velocity impact damage, evaluation of structural residual life, enhancement of existing non-destructive testing techniques and development the new ones, data fusion and integration of non-destructive testing techniques, damage identification and monitoring of structures, development of signal and image processing algorithms and machine learning approaches for early damage detection and identification. This allows us to approach the problems of structural integrity in a comprehensive way.