Multiobjective optimization of an industrial styrene reactor

Abstract

The paper describes a multiobjective optimization study for industrial styrene reactors using non-dominated sorting genetic algorithm (NSGA). Several two-and three-objective functions, namely, production, yield and selectivity of styrene, are considered for adiabatic as well as steam-injected styrene reactors. Pareto optimal (a set of equally good) solutions are obtained due to conflicting effect of either ethyl benzene feed temperature or flow rate. The results provide extensive range of optimal operating conditions, from which a suitable operating point can be selected based on the specific requirements in the plant. #

Optimal design of an autothermal membrane reactor coupling the dehydrogenation of ethylbenzene to styrene with the hydrogenation of nitrobenzene to aniline

“…The feed molar flowrate of ethylbenzene on the dehydrogenation side is taken to be between -25% and 10% of the nominal value of 10.24 moles/s. These bounds are consistent with the industrial case since the plant can operate at a much lower capacity, but not at a much higher capacity (Yee et al 2003).…”

“…At the same time, too much steam cannot be 10 used because it would make the process economically unfeasible. As for industrial practice, the upper limit is set to 20 (Yee, et al, 2003). 20 7   SOR (19) 3.…”

Multiobjective optimization of an industrial styrene monomer manufacturing process

“…: +65-6874-8049; fax: +65-6779-1936. (Yee et al, 2003), where an effort was made to optimize a styrene reactor unit, maximizing the styrene flow, yield and selectivity, using a genetic algorithm, the non-dominated sorting genetic algorithm (NSGA) (Srinivas and Deb, 1995), developed for multi-objective optimization. Encouraged by the outcome of this effort, we have carried out an optimization study on a styrene manufacturing process, with a more recent algorithm-the elitist non-dominated sorting genetic algorithm or NSGA-II (Deb et al, 2002).…”

“…Encouraged by the outcome of this effort, we have carried out an optimization study on a styrene manufacturing process, with a more recent algorithm-the elitist non-dominated sorting genetic algorithm or NSGA-II (Deb et al, 2002). Although NSGA was successfully applied to many multi-objective optimization problems (Yee et al, 2003;Rajesh et al, 2001;Bhaskar et al, 2000), Deb et al (2002) reported that its computational complexity can be drastically reduced and by applying elitism, a method of preserving good solutions, its performance can be still increased. This revision in NSGA resulted in NSGA-II which was shown to be able to achieve better convergence near the true Pareto-optimal front and find much better spread of Pareto-optimal solutions (Deb et al, 2002).…”

“…The most popular method of adding heat is to indirectly warm up the reactants between the beds, although, in some other plant designs, steam is directly injected at the entrances of the reactor beds to provide reheat for the subsequent section(s). Although steam is added mainly to provide the heat of reaction, there are other reasons for its use; a detailed discussion of which can be found in our previous publication (Yee et al, 2003). Usually, a steam to EB ratio (SOR) of 15:1 is maintained at the reactor inlet.…”