Minimizing piston mass of Neuman Esser reciprocating compressors using genetic algorithm

Double action horizontal Neuman Esser reciprocating compressors are utilized during three steps of compressing hydrogen in gasoline production section of many refineries including Esfahan refinery. Since application of any lubricant during compression process are not permitted in these compressors, Teflon ridder rings are placed between piston and cylinders to act as a lubricant and prevent any direct contact between pistons and cylinders. The wearing rate of the ridder rings in these three stages are not equal and consequently the time for their maintenance is not the same. In this research it is intended to increase the life of ridders by reducing the weight of pistons. After studying the effects of replacing the cast iron material of pistons by 7075 aluminum alloy, genetic algorithm is implemented to optimize the design of these pistons. Maximum von-Misses stress and minimum allowable thickness of various sections of piston are the constraints considered during optimization process and Abaqus finite element technique using Python script are utilized during optimization. Replacement of the material reduces the piston weight from 780 kg down to 271 kg and by optimizing the piston design, it was further reduced down to 261 kg which totally could considerably reduce the wearing rate of riders by reducing the total normal force on riders.