Santosh K. Gupta

Multi-objective optimization of industrial hydrogen plants

Operating hydrogen plants e

Multiobjective optimization of an industrial wiped film poly(ethylene terephthalate) reactor: some further insights

ciently is a critical issue, central to any energy conservation exercise in petroleum rening and fertilizer industries. To achieve this goal, ‘optimala operating conditions for improved unit performance need to be identied. In this work, an entire industrial hydrogen plant is simulated using rigorous process models for the steam reformer and shift converters. An adaptation of the nondominated sorting genetic algorithm (NSGA) is then employed to perform a multi-objective optimization on the unit performance. Simultaneous maximization of product hydrogen and export steam #ow rates is considered as the two objective functions for a xed feed rate of methane to the existing unit. For the specied plant conguration, Pareto-optimal sets of operating conditions are successfully obtained by NSGA for di!erent process conditions. The results serve as a target for the operator to aim at, in order to achieve cost e!ective operation of hydrogen plants. ( 2001 Elsevier Science Ltd. All rights reserved.

MODELING OF AN INDUSTRIAL WIPED FILM POLY(ETHYLENE TEREPHTHALATE) REACTOR

Multiobjective optimization of an industrial third-stage, wiped-film poly(ethylene terephthalate) reactor is carried out, using a pre-validated model. The two objective functions minimized are the acid and vinyl end group concentrations in the product. These are two of the undesirable side products produced in the reactor. The optimization problem incorporates an end-point constraint to produce polymer having a desired value of the degree of polymerization (DP). In addition, the concentration of the di-ethylene glycol end group in the product is constrained to lie within a certain range of values. The possible decision variables for the problem are the reactor pressure, temperature, catalyst concentration, residence time of the reaction mass in the reactor and the speed of rotation of the agitator. The nondominated sorting genetic algorithm (NSGA) is used to solve this multiobjective optimization problem. It is found that this algorithm is unable to converge to the correct solution(s) when two or more decision variables are used, and we need to run the code several times over (with different values of the computational variable, Sr, the seed for generating the random numbers) to obtain the solutions. In fact, this is an excellent test problem for future multiobjective optimization algorithms. It is found that when temperature is kept constant, Pareto optimal solutions are obtained, while, when the temperature is included as a decision variable, a global unique optimal point is obtained.

Parametric sensitivity in tubular polymerization reactors

An improved two-phase model has been developed for a wiped film (third stage) polyester reactor. The model accounts for all the important main and side reactions and incorporates the effect of vaporization of four low molecular weight volatile species. Industrial data under three different operating conditions are used to obtain best-fit (tuned) values of the model parameters. When these values are used unchanged in the model, the latter predicts industrial operation under a fourth set of operating condition. This indicates that the ‘tuned’ model accounts for all the physico-chemical phenomena present in the reactor. A sensitivity study reveals the importance of some parameters and suggests that these should be determined experimentally using more basic experimental studies rather than by tuning industrial data wherein several additional physical phenomena are present.

Electropolymerization of 9-vinylanthracene: kinetic study using thin-layer spectroelectrochemistry

Abstract A recent technique for studying the parametric sensitivity of chemical reactors is applied to tubular chain homopolymerization reactors. The sensitivities of the temperature maxima with respect to various parameters of the model are computed. Using conditions typically encountered for high-pressure polyethylene systems, it is found that the temperature sensitivities with respect to all the nine parameters have their maxima at approximately the same value of the feed initiator concentration, thus leading to a generalized sensitivity-based constraint for design. It is also found that, under usual conditions of operation, no significant design constraints on the feed temperature are indicated. Detailed sensitivity plots are presented, which could be used to obtain “safe” operating conditions. The effects of changing the most important parameters, the dimensionless heat of reaction and the dimensionless activation energy (ϵ), on the sensitivity envelope are also investigated. Our studies reveal that better estimates of ϵ than are available presently are required. Sensitivities of the number-average chain length maxima with respect to the same nine parameters are also computed. Under conditions where the steady-state hypothesis applies, estimates of these sensitivities can be obtained analytically. However, for the usual values of the parameters, and close to “sensitive” values of the feed initiator concentration, this hypothesis does not apply, and the chain length sensitivities need to be obtained numerically. In the absence of the gel effect, chain length sensitivities do not usually provide design constraints because of the very low monomer conversions encountered.

Simulation of an industrial nylon 6 tubular reactor

An in situ spectroelectrochemical technique has been employed to investigate the electropolymerization of 9-vinylanthracene. The propagation reaction as monitored from excimer emission of poly(9-vinylanthracene) followed pseudo-first-order kinetics. The dependence of the polymer yield and the propagation reaction rate constant on the monomer and initiator concentrations has been studied to elucidate the kinetics of the electropolymerization process. The energy of activation of the propagation reaction was 7.85 kcal mol−1.