Pipeline Network Calculation Based on Improved IN-IGA Algorithm

Abstract

Chemical process simulation can provide a more comprehensive description and analysis of chemical processes, and the solution of chemical pipeline network systems calculation is an important problem in the chemical simulation research. Therefore, an improved interval Newton-immune genetic algorithm (IN-IGA) is proposed in this paper for better self-solution of relevant parameters in chemical pipeline network system transport process simulation. The improved immune genetic algorithm is applied to determine the approximate range of solutions by fast search. Then the interval Newton method is used to obtain the nonlinear equations and calculate the high-precision results. Finally, the proposed method is applied in the calculation of chemical process pipeline networks. In comparison with the traditional Newton-Raphson (NR) method, the IN-IGA avoids the limitation of initial value selection, improves the convergence speed of the algorithm and optimizes the convergence effect, which is of great significance for chemical process simulation and modeling.