My research activities are in the field of Non-destructive testing. Following are some of the research projects that I handled throughout my career.
Passive IRT based Long-term SHM Modelling for subsurface damages in Building materials under solar irradiation in Singapore
Develop a numerical model to predict the thermal response for subsurface delamination in concrete under diverse environmental conditions for the purpose of providing an analytical tool to support thermographic inspection
CMT Weld process monitoring
Numerical model and experimental validation for online monitoring of cold metal transfer joining of aluminium to galvanized steel
Reconstructed image of (variation of width of no-Zn area (15, 10 and 5 mm)).
a Schematic diagram.
b Achieved schematic diagram.
c Real photograph of the weld.
d Radiographic image of the weld.
e Processed image for modelling data.
f Processed image for experimental data
TBC coating thickness inpection
Pulse phase thermography and third order polynomial regression. The results are validated using THz-TDS spectroscopy, Eddy Current Testing and Optical Microscopy.
Simulation assisted Automatic Defect Recognition (Sim-ADR) using deep neural networks
•SimXRAY is a software that has been developed for Simulation of X-ray images
•IMAGIN is a software that has been developed for pre-processing and ADR of images
•SimADR combines these experiences and an ANN to provide a powerful new tool for automation of Digital Radiography for industrial applications
Crack Detection in hot steel billets using Laser Thermography
Scanning of Continuous wave laser on the sample can produce Localized heating near the crack region. An Infrared camera can pic up this indication thereby identify and quantify the surface crack in steel samples at Elevated temperatures.
CW Helium Neon Laser is used using a mechanical scanner.
MWIR FLIR camera is used.
More details can be found in the below publication:
Anisotropic Heat Conduction Phenomena in Polycrystalline microstructure
In this research we studied the nonlinear heat conduction behaviour of Polycrystalline materials through boundary interfaces. Metals shows crystalline nature within their granular microstructure, in which the atoms are arranged on a regular space lattice.
Voronoi Tessellation is used to generate the microstructural lattice structure.
Infinite element method is used to incorporate the size of the specimen.
Thin thermally resistive layer is used as boundary condition between grains.
Heat conduction is solved in the polycrystalline grains with anisotropic material behaviour.
More details can be found in the below publication:
[Link]
Flash Thermography Simulation
Active Thermography Techniques
Numerical and experimental investigations on different active Thermography techniques.
Pulse Thermography
Lock-in Thermography
Induction Thermography
More details can be found in the below publication:
[Link]
Multi-physics modeling of weld pool dynamics
This work is carried out at LMGC (France - Montpellier) under supervision of Prof. Gilles Fras, Dr Sebastien Rouquette and Dr. Fabien Soulie.
Our contribution is threefold:
Proposition of a 2D- axisymmetric finite element model for the prediction of temperature, molten pool velocity and the transient evolution of the weld pool.
The surface tension gradient force (Marangoni force) dominated in the weld pool motion and Lorentz force and Buoyancy force were found as negligible.
The developed model then used to identify the effect of input energy and also for the material composition
Magneto-Thermo-Hydrodynamic Model
Weld pool evolution for different welding energy (SS304L) and for different materials were also studied.
Weld Pool: Expt vs Simulation
The Levenberg-Marquardt used for the minimization of stated cost function.
A sensitivity analysis was performed in order to Guarantee that the temperatures measured at some sensor location were relevant.
Heat flux parameter optimization
An inverse heat transfer problem (IHTP) was developed for the estimation of Efficiency and Gaussian Radii.
A few numerical cases were investigated to confirm that the stated IHTP worked well with exact input data and behaved robustly with noised data. Following are some conclusions:
Robust to noise measurement.
The position of the sensors must carefully checked.
The values of the thermo-physical properties and especially the thermal conductivity must be known quite accurately
More details can be found in the below publication:
[Link]
Domains identified as defective from online IR thermographic images were verified using post fabricated x-ray images (as shown in Figure).
Online weld Quality Monitoring using Infrared thermal Imaging
In this research work, infrared thermal imaging for online weld quality has been evaluated as a potential approach to identify defects.
It is concluded that, the defects could be reliably identified from the online offset IR thermal image data.
More details can be found in the below publication:
U. Sreedhar, K. Balasubramaniam, C. V. Krishnamurthy, V. D. Raghupathy and S. Ravisankar,
"Automatic defect identification using thermal image analysis for online weld quality monitoring",
Journal of Materials Processing Technology. 212(2012) 1557- 1566.