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Catalytic Cracking Unit (catalytic + cracking_unit)
Selected AbstractsModeling heterogeneous downward dense gas-particle flowsAICHE JOURNAL, Issue 5 2010Regis Andreux Abstract A novel approach is proposed to model heterogeneous downward dense gas-particle flows. The homogeneous behavior of the flow is described by the mass and momentum transport equations of the gas and particulate phases solved using a mono-dimension finite volume method on staggered grids. The heterogeneous features of the flow are predicted simultaneously using the bubble-emulsion formalism. The gas compressibility is taken into consideration. The model is supplemented with a new correlation to account for the wall-particle frictional effects. The predictions are compared with the vertical profiles of pressure and the amount of gas that flows up and down two standpipes and a cyclone dipleg of an industrial fluid catalytic cracking unit and of a cold small-scale circulating fluidized bed. The trends are well predicted. The model gives further information and is thus an innovative starting point for downward dense gas-particle flow hydrodynamics investigation. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source] Identification and control of a riser-type FCC unitTHE CANADIAN JOURNAL OF CHEMICAL ENGINEERING, Issue 6 2001Abdul-Alghasim Alaradi Abstract This paper addresses the use of feedforward neural networks for the steady-state and dynamic identification and control of a riser type fluid catalytic cracking unit (FCCU). The results are compared with a conventional PI controller and a model predictive control (MPC) using a state space subspace identification algorithm. A back propagation algorithm with momentum term and adaptive learning rate is used for training the identification networks. The back propagation algorithm is also used for the neuro-control of the process. It is shown that for a noise-free system the adaptive neuro-controller and the MPC are capable of maintaining the riser temperature, the pressure difference between the reactor vessel and the regenerator, and the catalyst bed level in the reactor vessel, in the presence of set-point and disturbance changes. The MPC performs better than the neuro controller that in turn is superior to the conventional multi-loop diagonal PI controller. On examine dans cet article l'utilisation de réseaux neuronaux à anticipation pour la détermination et la régulation en régimes dynamique et permanent d'une unité de craquage catalytique de fluide de type colonne montante (FCCU). Un algorithme de rétro-propagation avec un terme de quantité de mouvement et une vitesse d'apprentissage adaptative est utilisé pour l'entraînement des réseaux d'identification. L'algorithme de rétro-propagation est également utilisé pour le controle neuronal du procédé. On montre que pour un système non bruité le contôleur neuronal adaptatif est capable de maintenir la température de colonne, la différence de pression entre le réacteur et le régénerateur ainsi que le niveau de lit de catalyseur dans le réacteur, en présence de changements dans les point de consigne et les perturbations. [source] Optimization of a model IV fluidized catalytic cracking unitTHE CANADIAN JOURNAL OF CHEMICAL ENGINEERING, Issue 4 2001Rein Luus Abstract Maximization of a profit function related to a fluidized catalytic cracking unit model was carried out by Luus-jaakola optimization procedure. A 7-dimensional search is carried out on a FCC unit described by 113 nonlinear algebraic equations and 9 differential equations. Despite the low sensitivity and the existence of several local optima, the global optimum was obtained with reasonable amount of computational effort. At the optimum, the profit function is 1% higher than when the air blowers are constrained to operate at their maximum capacity. On a réalisé par la méthode d'optimisation de Luus-jaakola la maximisation d'une fonction de profit relativement à un modèle d'unité de craquage catarytique fluidisé (FCC). Une recherche en sept dimensions est menée sur une unité FCC décrite par 113 équations algébriques non linéaires et 9 équations différentielles. Malgré la faible sensibilité et l'existence de plusieurs optimums locaux, l'optimum global a été atteint avec des efforts raisonnables en termes de calcul. À l'optimum, la fonction de profit est de 1% supérieure à celle obtenue lorsqu'on force les ventilateurs soufflants à fonctionner à leur capacité maximum. [source] FCCU simulation based on first principle and artificial neural network modelsASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 6 2009Maria Mihe Abstract A first principle model has been developed for the reactor,regenerator system based on construction and operating data from an industrial fluid catalytic cracking unit (FCCU). The first principle model takes into account the main FCCU subsystems: reactor riser, regenerator, stripper, catalyst circulation lines, air blower, wet gas compressor and main fractionator. A five-lump kinetic scheme has been considered for the reactions taking place in the reactor riser. Subsequently, an artificial neural network (ANN) model has been built for the complex FCCU system. The dynamic simulator, based on the previously developed first principle model, served as the source of reliable data for ANN design, training and testing. The ANN developed model was successfully trained and tested. Comparison between first principle and neural network based model leads to a very good match between the two models. Results show the substantial reduction of the computation time featured by the ANN model compared to the first principle model, demonstrating its potential use for real-time implementation in model-based control algorithms. Copyright © 2009 Curtin University of Technology and John Wiley & Sons, Ltd. [source] | ||||||||||