This paper proposes a stochastic optimal technique based on Genetic Algorithm (GA) for the calculation of multiphase and multicomponent chemical equilibrium by minimization of Gibbs free energy. Three aspects are impr...This paper proposes a stochastic optimal technique based on Genetic Algorithm (GA) for the calculation of multiphase and multicomponent chemical equilibrium by minimization of Gibbs free energy. Three aspects are improved based on the drawbacks of the conventional GA.An alternative decimal encoding strategy is adopted to enhance the precision of calculation.A dynamic encoding method that can limit the bounds of optimized variables within their feasible regions is developed to cope with the complex constraints of the problem.Finally,sequential search technique is applied to improve GA to approach global optima.It is shown through the calculation of complex chemical systems,in which non-ideal,multireaction and multiphase coexistence are simultaneously involved,that the presented GA is general and efficient for the addressed problem.展开更多
Synthesis of chemical processes is of non-convex and multi-modal. Deterministic strategies often fail to find global optimum within reasonable time scales. Stochastic methodologies generally approach global solution i...Synthesis of chemical processes is of non-convex and multi-modal. Deterministic strategies often fail to find global optimum within reasonable time scales. Stochastic methodologies generally approach global solution in probability. In recogniting the state of art status in the discipline, a new approach for global optimization of processes, based on sequential number theoretic optimization (SNTO), is proposed. In this approach, subspaces and feasible points are derived from uniformly scattered points, and iterations over passing the corner of local optimum are enhanced via parallel strategy. The efficiency of the approach proposed is verified by results obtained from various case studies.展开更多
文摘This paper proposes a stochastic optimal technique based on Genetic Algorithm (GA) for the calculation of multiphase and multicomponent chemical equilibrium by minimization of Gibbs free energy. Three aspects are improved based on the drawbacks of the conventional GA.An alternative decimal encoding strategy is adopted to enhance the precision of calculation.A dynamic encoding method that can limit the bounds of optimized variables within their feasible regions is developed to cope with the complex constraints of the problem.Finally,sequential search technique is applied to improve GA to approach global optima.It is shown through the calculation of complex chemical systems,in which non-ideal,multireaction and multiphase coexistence are simultaneously involved,that the presented GA is general and efficient for the addressed problem.
文摘采用醇胺法脱除沼气中的CO_(2),使之达到可液化制取LNG的标准。通过Aspen Hysys模拟该工艺流程,利用Matlab进行遗传算法和序贯法优化。优化后的结果表明,原料气中含30%、40%、50%CO_(2)时,生产单位CH4的电耗分别为0.163、0.191、0.235 k Wh/m^(3),降低了0.85%、1.59%、0.91%;再生热耗分别为2.29、3.02、4.34 GJ/m^(3),降低了5.68%、7.69%、8.49%。将优化结果与现有工厂、实验、模拟数据对比,可为高碳含量天然气脱除CO_(2)提供参考。
文摘Synthesis of chemical processes is of non-convex and multi-modal. Deterministic strategies often fail to find global optimum within reasonable time scales. Stochastic methodologies generally approach global solution in probability. In recogniting the state of art status in the discipline, a new approach for global optimization of processes, based on sequential number theoretic optimization (SNTO), is proposed. In this approach, subspaces and feasible points are derived from uniformly scattered points, and iterations over passing the corner of local optimum are enhanced via parallel strategy. The efficiency of the approach proposed is verified by results obtained from various case studies.
