Multi-objective Genetic Optimization of Ethane Thermal Cracking Reactor
Volume 5, Issue 3, Summer 2008, Pages 29-39
D. Salari, A. Niaei, R. Nabavi
Abstract An industrial ethane thermal cracking reactor was modeled assuming a molecular mechanism for the reaction kinetics coupled with material, energy, and momentum balances of the reactant-product flow along the reactor. To carry out the multi-objective optimization for two objectives such as conversion and ethylene selectivity, the elitist non-dominated sorting genetic algorithm was used. The Pareto optimum set was obtained successfully and finally the effect of the decision variable was discussed.
An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis
Volume 5, Issue 1, Winter 2008, Pages 22-33
E. Rezaei, S. Shafiei
Abstract Synthesis of heat exchanger networks (HENs) is inherently a mixed integer and nonlinear programming (MINLP) problem. Solving such problems leads to difficulties in the optimization of continuous and binary variables. This paper presents a new efficient and robust method in which structural parameters are optimized by genetic algorithm (G.A.) and continuous variables are handled due to a modified objective function for maximum energy recovery (MER). Node representation is used for addressing the exchangers and networks are considered as a sequence of genes. Each gene consists of nodes for generating different structures within a network. Results show that this method may find new or near optimal solutions with a less than 2% increase in Hen annual costs.
Investigation of CO2 and H2O Addition to Natural Gas for Production of Synthesis Gas
Volume 2, Issue 1, Winter 2005, Pages 31-54
M. Din Mohammad, M. Khoshnoodi
Abstract General modeling and optimization of syngas production via noncatalytic autothermal partial oxidation of methane are carried out using our developed scientific software which was based on the minimization of total Gibbs energy. In this work, a novel application of the direct search and Newton-Raphson methods was introduced to apply to optimization of a complex chemical reaction. Sensitivity analysis was done to investigate the effect of several parameters on the quality of syngas and the production yield. The acceptable concentrations of CO2 and H2O injected into the methane feed are optimized in the specified temperature and pressure range, while H2/CO ratio in the product stream is set to remain at 1.5 or 2, methane slip in the syngas is less than 1.5% and the non-endothermic conversion area of reaction prevail, simultaneously. This facilitates monetizing CO2 in the petrochemical and steel industries. The output from this software is comparable both with the experimental results, cited in Ref [1] , and with that from ASPEN PLUS in simulating the experiments mentioned in Ref [2]