Dr. Raad Jamal Jassim and Dr. Rahim Khazal Masawil, lecturers at the University of Basra, College of Engineering, Department of Mechanical Engineering, in cooperation with graduate student Mahdi Saleh Madhkur, published a joint scientific research in the Manufacturing and Materials Processing Journal Q2 Impact factor 3.3 Open Access by MDPI entitled Application of Pattern Search Algorithm and Genetic Algorithm to Improve Dimensions and Strength of Welded Joints for High Density Polyethylene Pipes in the Thermal Fusion Welding Process. The research included the use of high-density polyethylene (HDPE) pipes worldwide in applications such as main water networks, gas networks, sewage networks, fire system supply lines, electricity and communications channels, rainwater and sewage pipes due to their excellent mechanical and chemical features such as polyethylene's hardness and resistance to chemicals, as well as its corrosion resistance and light weight, increasing its use in situations that require cost-effective and durable fluid and gas pipe systems. The study addressed the developments of butt fusion welding (BFW) of high-density polyethylene (HDPE) pipes by exploring the relationship between the performance of welding joints by studying the ultimate tensile strength and exploring the dimensions of the weld joint. The effects of welding pressure, heater temperature, storage time and cooling time on the weld quality were studied. Analysis and artificial neural network were used to analyze the experimental results and predict the outputs. Two optimization techniques (pattern search and genetic algorithms) were applied to obtain the optimal operating conditions and compare their performances. The results showed that pattern search and genetic algorithms can identify the optimal output results.
