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.
Structural Integrity Assessment Research Group is looking for a PhD candidate to implement research on non-destructive testing using self-heating based vibrothermography technique on fully-funded PhD position. Candidates from all countries are welcomed. For details see Opportunities.
Jafar Amraei gave a lecture ent. "Structural integrity assessment of polymer-matrix composites through termomechanical fatigue and mondestructive evaluation" during the Open Seminar of the Department of Fundamentals of Machinery Design.
Jafar Amraei in the group of 32 young researchers from across Europe and neighbouring countries participated in the 3rd Edition of the HISTRATE Training School focused on structural health monitoring and non-destructive testing for composite structures.
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.