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Papers by dinu thomas Thekkuden
Volume 6: Materials and Fabrication
The stress corrosion cracking of tube-to-tubesheet joints is one of the major faults causing heat... more The stress corrosion cracking of tube-to-tubesheet joints is one of the major faults causing heat exchanger failure. After the expansion process, the stresses are developed in a plastically deformed tube around the tube-to-tubesheet joint. These residual stressed joints, exposed to tube and shell side fluids, are the main crack initiation sites. Adequate contact pressure at the tube-to-tubesheet interface is required to produce a quality joint. Insufficient tube-to-tubesheet contact pressure leads to insufficient joint strength. Therefore, a study on the residual stress and contact pressure that have a great significance on the quality of the tube-to-tubesheet joint is highly demanded. In this research, a 2D axisymmetric numerical analysis is performed to study the effect of the presence of grooves in the tubesheet and the expansion pressure length on the distribution of contact pressure and stress during loading and unloading of 400 MPa expansion pressure. The results show that the...
2020 Advances in Science and Engineering Technology International Conferences (ASET)
Engineering Failure Analysis
International Review of Mechanical Engineering (IREME)
SN Applied Sciences
The research paper investigates the prediction capability of the artificial neural network for we... more The research paper investigates the prediction capability of the artificial neural network for weld quality assessment from the captured voltage signals in a gas metal arc welding process. The bead-on-plate welds and v-groove welds were made on SA 516 grade 70 material by altering different parameters such as stickout distance, gas flow rate and travel speed. The voltage signals of each weld were captured using a data acquisition system having 8000 Hz data acquisition rate. The descriptive statistics of the voltage data such as mean, standard error, median, mode, standard deviation, sample variance, kurtosis, skewness, minimum and maximum corresponding to bead-on-plate welds and v-groove welds were used for training and testing the neural network respectively. The quality of the weld was assessed by the visual inspection, and from control charts plotted using voltage data. Overall classification accuracy of 94.7% was achieved in the training process. The feed-forward back propagation neural network predicted the quality of test v-groove welds accurately with a 90.9% prediction rate. The results proved that the developed method is promising for the immediate and early prediction of the weld quality.
SN Applied Sciences
It is an underlying fact for the case of the joining process especially welding to have optimized... more It is an underlying fact for the case of the joining process especially welding to have optimized parameters in order to achieve joints with outstanding mechanical characteristics. In the current work, aluminium 6061 pipes were welded using gas metal arc welding process with appropriate ER 4043 electrode and argon shielding gas. Optimum welding parameters (namely, current, voltage and travel speed) are investigated using analysis of variance ANOVA and grey relational analysis GRA statistical approaches. High tensile strength and low corrosion rate were set as required characteristics of quality welds. Since there are two responses and two objectives, multiple-criteria decision-making approach-GRA, and ANOVA are performed. Optimal parameters from these statistical approaches are converged to 110 A, 19 V and 3 cm/ min, respectively. It is deduced from this study that the optimal parameters are convergent irrespective of the two used techniques for the investigated experimental data.
Volume 6: Materials and Fabrication
The stress corrosion cracking of tube-to-tubesheet joints is one of the major faults causing heat... more The stress corrosion cracking of tube-to-tubesheet joints is one of the major faults causing heat exchanger failure. After the expansion process, the stresses are developed in a plastically deformed tube around the tube-to-tubesheet joint. These residual stressed joints, exposed to tube and shell side fluids, are the main crack initiation sites. Adequate contact pressure at the tube-to-tubesheet interface is required to produce a quality joint. Insufficient tube-to-tubesheet contact pressure leads to insufficient joint strength. Therefore, a study on the residual stress and contact pressure that have a great significance on the quality of the tube-to-tubesheet joint is highly demanded. In this research, a 2D axisymmetric numerical analysis is performed to study the effect of the presence of grooves in the tubesheet and the expansion pressure length on the distribution of contact pressure and stress during loading and unloading of 400 MPa expansion pressure. The results show that the...
2020 Advances in Science and Engineering Technology International Conferences (ASET)
Engineering Failure Analysis
International Review of Mechanical Engineering (IREME)
SN Applied Sciences
The research paper investigates the prediction capability of the artificial neural network for we... more The research paper investigates the prediction capability of the artificial neural network for weld quality assessment from the captured voltage signals in a gas metal arc welding process. The bead-on-plate welds and v-groove welds were made on SA 516 grade 70 material by altering different parameters such as stickout distance, gas flow rate and travel speed. The voltage signals of each weld were captured using a data acquisition system having 8000 Hz data acquisition rate. The descriptive statistics of the voltage data such as mean, standard error, median, mode, standard deviation, sample variance, kurtosis, skewness, minimum and maximum corresponding to bead-on-plate welds and v-groove welds were used for training and testing the neural network respectively. The quality of the weld was assessed by the visual inspection, and from control charts plotted using voltage data. Overall classification accuracy of 94.7% was achieved in the training process. The feed-forward back propagation neural network predicted the quality of test v-groove welds accurately with a 90.9% prediction rate. The results proved that the developed method is promising for the immediate and early prediction of the weld quality.
SN Applied Sciences
It is an underlying fact for the case of the joining process especially welding to have optimized... more It is an underlying fact for the case of the joining process especially welding to have optimized parameters in order to achieve joints with outstanding mechanical characteristics. In the current work, aluminium 6061 pipes were welded using gas metal arc welding process with appropriate ER 4043 electrode and argon shielding gas. Optimum welding parameters (namely, current, voltage and travel speed) are investigated using analysis of variance ANOVA and grey relational analysis GRA statistical approaches. High tensile strength and low corrosion rate were set as required characteristics of quality welds. Since there are two responses and two objectives, multiple-criteria decision-making approach-GRA, and ANOVA are performed. Optimal parameters from these statistical approaches are converged to 110 A, 19 V and 3 cm/ min, respectively. It is deduced from this study that the optimal parameters are convergent irrespective of the two used techniques for the investigated experimental data.