In this study, we first report the development of a robust and efficient finite volume based adsorption process simulator, essential for rigorous optimization of a transient cyclic operation without resorting to any model reduction. We present a detailed algorithm for the common boundary conditions encountered in nonisothermal and nonisobaric adsorption process simulations. A comprehensive comparison of the high-resolution total variation diminishing (TVD) schemes, namely, van Leer and Superbee, with the weighted essentially nonoscillatory (WENO) finite volume scheme is performed, and trade-off plots are presented to identify the numerical scheme most suitable for attaining speed and accuracy at the same time. The simulator is then used to perform rigorous optimization of a four-step process for postcombustion CO2 capture from dry flue gas on zeolite 13X. The aim is to identify operating conditions at which the purity and recovery demands are met and to calculate corresponding energy consumption and process productivity. The purity–recovery and energy–productivity Paretos are generated using multiobjective optimization. It is shown that, for a strict vacuum swing adsorption (VSA) process, an evacuation pressure of 0.02 bar is required to satisfy regulatory demands of attaining a CO2 purity and recovery of 90%. It is also quantitatively shown that pressurizing the flue gas is detrimental to the energy consumption of process, although offering improvement in productivity.

Crystallization is a major separation process in the pharmaceutical industry. Most crystallizations are performed batchwise, but there is great incentive for converting them to continuous operations. This paper investigates the modeling, simulation, and optimization of a special antisolvent plug-flow crystallizer: the multisegmented, multiaddition plug-flow crystallizer (MSMA-PFC). The MSMA-PFC accepts multiple antisolvent flows along its length, permitting finer control of supersaturation. A steady-state population balance equation was applied for tracking the crystal size distribution, and a mass balance equation was used to track the depletion of dissolved solute (flufenamic acid). A multiobjective optimization framework was applied to determine the antisolvent flow rates into each segment that simultaneously maximize the average crystal size, and minimize the coefficient of variation. The set of coupled differential equations was solved, depending on circumstance, with either the method-of-moments (MOM), or the high-resolution finite-volume (FV) method. The significant nonconvexity in the objective functions motivated the use of the nondominated sorting genetic algorithm (NSGA-II) to calculate the Pareto frontiers for the two competing objectives. It was found that the optimal antisolvent profile provides better product crystals, compared to the cases with equal additions of antisolvent in 1−4 injection points by keeping the total amount of antisolvent the same. The sensitivity of the Pareto frontier to variation in the growth and nucleation kinetic parameters was investigated. In addition, a novel simultaneous design and control (SDC) approach was proposed, based on the optimization of the full crystallizer design, over not only antisolvent profile, but also the number of injections and total crystallizer length, providing the best crystallization design that can allow optimal product performance in conjunction with the multiaddition control approach.

This work presents a systematic study for obtaining the optimal temperature profile in a continuous plug flow crystallizer (PFC). The proposed PFC consists of multiple segments where the temperature of each segment can be controlled individually. An optimization problem is formulated for a target crystal size distribution (without fines) with the temperature of the segments as decision variables. The results indicate that for the crystallization kinetics considered, dissolution steps are necessary for the reduction of fines due to nucleation. A systematic study on the form of growth and dissolution kinetics suggested that the key factor that determines whether the dissolution steps will be successful in reducing fines, without compromising the final size of the crystals from seed, is the size dependence of the growth and dissolution kinetics. Best fines removal is achieved when the larger crystals grow faster than the smaller ones and the smaller crystals dissolve faster than the larger ones. © 2013 American Institute of Chemical Engineers AIChE J, 59: 4582–4594, 2013

Encrustation, also known as fouling or scale formation, on the wall of plug flow crystallizers (PFC) can cause major operational and economic problems in pharmaceutical industries. These include increased energy requirements due to increment of thermal resistance and pressure drop, and clogging of the crystals due to reduction of flow area. In this work, a mathematical model for predicting the dynamic behavior of a PFC undergoing encrustation is presented. This model describes the formation of encrust layer by considering various mechanisms such as rate of solute transport from bulk to the wall, integration and removal due to shear stress induced by fluid turbulence. A population balance model for describing the crystallization process in the PFC is also coupled with the encrustation model in order to obtain the appropriate concentration profile in the PFC as well as product crystal size distribution (CSD). Based on this model, a mitigation strategy is proposed that relies on injection of pure solvent to dissolve the encrust layer.

. Multiimpurity adsorption model for modeling crystal purity and shape evolution during crystallization processes in impure media.Crystal Growth and Design, 16(2), pp. 555-568.Additional Information:•