Batch Time (batch + time)

Distribution by Scientific Domains

Selected Abstracts

Preferential crystallization: Multi-objective optimization framework

AICHE JOURNAL, Issue 2 2009
Shrikant A. Bhat
Abstract A four objective optimization framework for preferential crystallization of D-L threonine solution is presented. The objectives are maximization of average crystal size and productivity, and minimization of batch time and the coefficient of variation at the desired purity while respecting design and operating constraints. The cooling rate, enantiomeric excess of the preferred enantiomer, and the mass of seeds are used as the decision variables. The optimization problem is solved by using adaptation of the nondominated sorting genetic algorithm. The results obtained clearly distinguish different regimes of interest during preferential crystallization. The multi-objective analysis presented in this study is generic and gives a simplified picture in terms of three zones of operations obtained because of relative importance of nucleation and growth. Such analysis is of great importance in providing better insight for design and decision making, and improving the performance of the preferential crystallization that is considered as a promising future alternative to chromatographic separation of enantiomers. 2009 American Institute of Chemical Engineers AIChE J, 2009 [source]

Optimization of Fed-Batch Saccharomyces cerevisiae Fermentation Using Dynamic Flux Balance Models

Jared L. Hjersted
We developed a dynamic flux balance model for fed-batch Saccharomyces cerevisiae fermentation that couples a detailed steady-state description of primary carbon metabolism with dynamic mass balances on key extracellular species. Model-based dynamic optimization is performed to determine fed-batch operating policies that maximize ethanol productivity and/or ethanol yield on glucose. The initial volume and glucose concentrations, the feed flow rate and dissolved oxygen concentration profiles, and the final batch time are treated as decision variables in the dynamic optimization problem. Optimal solutions are generated to analyze the tradeoff between maximal productivity and yield objectives. We find that for both cases the prediction of a microaerobic region is significant. The optimization results are sensitive to network model parameters for the growth associated maintenance and P/O ratio. The results of our computational study motivate continued development of dynamic flux balance models and further exploration of their application to productivity optimization in biochemical reactors. [source]

Catalytic Liquid Phase Oxidation of Toluene to Benzoic Acid

A. Gizli
Abstract The production of benzoic acid from toluene in the liquid phase with pure oxygen was studied. Investigations have been carried out with a view to determining the most suitable reaction conditions with respect to operating variables including oxygen flow rate, reaction temperature, batch time and catalyst loading. In a series of batch experiments carried out at 4,atm, the optimum values of mole ratio of oxygen to toluene, temperature, reaction time, and catalyst loading were found to be 2, 157,C, 2,h and 0.57,g/L, respectively. In addition, a kinetic study was carried out by taking into consideration the optimum reaction conditions. The model dependent on the formation of benzyl radical was found to be feasible for describing the catalytic oxidation of toluene to benzoic acid in the liquid phase. The activation energy was determined as 40,kJ/mol. [source]

Nonlinear model predictive control for the polymorphic transformation of L -glutamic acid crystals

AICHE JOURNAL, Issue 10 2009
Martin Wijaya Hermanto
Abstract Polymorphism, a phenomenon where a substance can have more than one crystal forms, has recently become a major interest to the food, speciality chemical, and pharmaceutical industries. The different physical properties for polymorphs such as solubility, morphology, and dissolution rate may jeopardize operability or product quality, resulting in significant effort in controlling crystallization processes to ensure consistent production of the desired polymorph. Here, a nonlinear model predictive control (NMPC) strategy is developed for the polymorphic transformation of L -glutamic acid from the metastable ,-form to the stable ,-form crystals. The robustness of the proposed NMPC strategy to parameter perturbations is compared with temperature control (T-control), concentration control (C-control), and quadratic matrix control with successive linearization (SL-QDMC). Simulation studies show that T-control is the least robust, whereas C-control performs very robustly but long batch times may be required. SL-QDMC performs rather poorly even when there is no plant-model mismatch due to the high process nonlinearity, rendering successive linearization inaccurate. The NMPC strategy shows good overall robustness for two different control objectives, which were both within 7% of their optimal values, while satisfying all constraints on manipulated and state variables within the specified batch time. 2009 American Institute of Chemical Engineers AIChE J, 2009 [source]