Master's Thesis at the University of Basrah Explores Simulation and Machine Learning in Temperature Distribution
A master's thesis at the College of Engineering, University of Basrah, explored the use of simulation and machine learning to predict temperature distribution in friction-driven spot welding.
The thesis, submitted by Sajjad Nassif Jassim, aimed to utilize numerical simulation and machine learning techniques to predict temperature distribution and mechanical behavior in friction-driven spot welding.
The thesis, comprised of four chapters, discussed the importance of integrating practical experiments, numerical simulation, and artificial intelligence techniques to improve friction-driven spot welding processes, thereby contributing to the development of more efficient and precise industrial applications.
Department of Media and Government Communication
