This course will cover the research and development work carried out by Tribikram Kundu (instructor) in
collaboration with his graduate students and international colleagues over the last three decades on structural
health monitoring (SHM) and non-destructive evaluation (NDE) technology. In particular, it will focus on acoustic
source localization (ASL) and damage detection techniques using linear and nonlinear ultrasonic signals. Both
linear and nonlinear ultrasonic techniques are needed for inspecting materials and structures at different scales -
from microscopic fatigue cracks and dislocations to large scale cracks in civil infrastructures made of metal,
composite or concrete. For linear ultrasonic inspections the advantages of guided-wave-based techniques over
body-wave-based techniques will be demonstrated. Then the nonlinear ultrasonic techniques will be introduced.
The nonlinear ultrasonic methodology developed by the instructor, called Sideband Peak Count – Index (or SPCI)
technique will be taught. Advantages of this technique over conventional linear and nonlinear ultrasonic
techniques such as ultrasonic pulse velocity and attenuation measurements and higher harmonic generation
techniques will be demonstrated. A new ASL technique that does not require the knowledge of the material
properties for localizing the acoustic source will be also taught. The mathematical derivation behind this Lshaped
sensor cluster-based technique will be presented. In addition to the experimental investigation, the meshfree
modelling technique called distributed point source method (DPSM) developed jointly by the instructor and
his colleague Prof. D. Placko of ENS, Cachan, France for solving elastic and electromagnetic wave propagation
problems will be also discussed. Advantages of all these newly developed techniques - DPSM, SPC-I, L-shaped
sensor cluster based ASL technique, and guided wave based linear ultrasonic techniques for nondestructive
evaluation and structural health monitoring will be covered in this course.
settembre 2024