Modeling Simulation And Optimization Of GK-V Naphtha Pyrolysis Furnace

Focusing that there are contradictions between the maximizing of target products yield and minimizing of coking rate, a stringent mechanism model is established, and the PSO algorithm (Particle Swarm Optimization, PSO) is applied in the model. By selecting and the establishment of integrated yield and profit optimal target function, optimal parameters are imported. The method is applied to the optimization study of the KTI Gk-V Ethylene Pyrolysis Furnace radiative section entrance and results show that the method is good, the yield of target products and the coking rate is reasonable adjusted and maximizing profits are found. Main work as follows:1. In this paper, considering the chemical kinetic reaction model, heat transfer model of the radiative section, the internal and external heat transfer and chemical reaction within the thermal effects, pressure drop of the pyrolysis gas flow and the coking model in the cracking furnace, applied to KTI GK-V cracking furnace, based on the naphtha cracking process Kumar molecular kinetic models, a common naphtha cracking furnace process mathematical model is established. Using this model, the clean naphtha cracker pyroslis process is simulated; in conjunction with the coking kinetic model, the cracking furnace model of the entire operation is also established.2. The characteristics of GK-V naphtha cracking furnace optimization problem is analyzed. Through the analysis of optimization objectives and constraints, ethylene, propylene and butadiene are selected as target products; naphtha feed flow, dilution ratio and steam cracking gas exit temperature are chosen as the decision variables; naphtha cracking furnace process optimization model is established. Particle Swarm Optimization algorithm using its operational optimization can improve the overall efficiency of 8.13%. Research shows that, there is a certain degree of optimization potential for the naphtha cracking furnace.