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.
Mohammed Abdulkedir Alfeki successfully finished intensive courses within the Summer School for PhD students organized at the Silesian University of Technology in Gliwice, gaining knowledge on using modern tools in academic work.
Andrzej Katunin, Tomasz Rogala, and Dominik Wachla visited Technical University of Košice within the implemented bilateral Polish-Slovak project related to high-speed 3D DIC and its application for structural damage identification, as a part of the project team.
Within the DFG project related to ultrasonic fatigue of composites implemented by UniFreiburg and Fraunhofer IWM, Andrzej Katunin visited Freiburg as a guest researcher.
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.