Abstract

Optimization of mechanical components is an important aspect of the engineering process; a well designed system will lead to money saving during the production phase and better machine life. In oil refineries and petrochemical plants, furnaces are incorporated into the process to supply thermal energy (heat) generated by fuel combustion, which is transmitted to a fluid flowing within a tube bundle, i.e., a coil. An important internal component of the furnace oil refinery is the system that supports the tube coil. This work is part of a research whose goal is to generate a new methodology for the investigation and search of the supports of the radiation zone refining furnace. This methodology represents as a whole the possibility of application of some evolutionary algorithms in the area of mechanical design of furnaces. For the optimization of the lateral supports two evolutionary algorithms are used, genetic algorithm and particle swarm algorithm. In this work a comparison between the two optimization methods chosen is carried out. Recent techniques of dynamic penalty, specifically adaptive penalty method are incorporated into the algorithms. The serviceability and strength requirements are considered in the design problem as specified in API560. The results show that the model converges to a very efficient solution without any engineer intervention. A real example is included to demonstrate the efficiency of the algorithm.