Abstract

Heavy oil thermal cracking is a complex multivariable and important petrochemical reaction process. The accurate kinetic models are of great significance for the simulation and analysis of this process. In this paper, a membrane computing optimization algorithm with multi-subsystems (MCOA) is proposed to solve parameter estimation problems of the heavy oil thermal cracking model. In MCOA, the nested membrane structure and rewriting rule, the crossover rule, the communication rule, and the transformation rule that are distributed in every subsystem are combined to improve the global search capacities and convergence accuracy. Studies on five benchmark test functions indicate that the MCOA outperforms the other three methods (RNA-GA, SGA, PSOPS) in terms of convergence speed and solution accuracy. Also, the MCOA is a helpful and reliable technique for estimating the heavy oil thermal cracking model parameters. The experimental results demonstrate that model curve gained by the MCOA is in good agreement with the measured data.

中文翻译：

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一种用于稠油热裂解模型参数估计的多子系统膜计算优化算法

摘要

重油热裂解是一个复杂的多变量、重要的石油化工反应过程。准确的动力学模型对这一过程的模拟和分析具有重要意义。针对稠油热裂解模型的参数估计问题，提出了一种多子系统膜计算优化算法（MCOA）。在MCOA中，将分布在每个子系统中的嵌套膜结构和重写规则、交叉规则、通信规则和转换规则结合起来，提高了全局搜索能力和收敛精度。对五个基准测试函数的研究表明，MCOA 在收敛速度和求解精度方面优于其他三种方法（RNA-GA、SGA、PSOPS）。还，MCOA 是估计重油热裂化模型参数的有用且可靠的技术。实验结果表明，MCOA得到的模型曲线与实测数据吻合较好。