Showing papers in "Canadian Journal of Chemical Engineering in 2007"

Petroleum residue upgrading via delayed coking: A review

Abstract: World petroleum residue processing capacity has reached about 725 million metric tons per annum (MMTPA). The high demand for transportation fuels and the ever-rising heavy nature of crude oil have resulted in a renewed interest in the bottom-of-the-barrel processing using various conversion processes. Delayed coking, known for processing virtually any refinery stream (which not only poses a serious threat to environment, but also involves a disposal cost) has garnered tremendous importance in the current refining scenario. Needle coke obtained from delayed coking process is a highly sought-after product, which is used in electric arc furnaces (in the form of graphite electrodes) in steel making applications. In the present communication, the published literature has been extensively analyzed and a state-of-the-art review has been written that includes: (1) importance and place of delayed coking as a residue upgrading process in the current refining scenario; (2) coking mechanism and kinetics; (3) design aspects; (4) feedstocks suitable for the production of needle coke; (5) characteristics of needle coke; (6) factors affecting needle coke quality and quantity; and (7) future market for needle coke. An attempt has been made to get the above-mentioned aspects together in a coherent theme so that the information is available at a glance and could be of significant use for researchers and practising refiners.

Non‐Linear Model Predictive Control: A Personal Retrospective

Abstract: An overview of non-linear model predictive control (NMPC) is presented, with an extreme bias towards the author’s experiences and published results. Challenges include multiple solutions (from non-convex optimization problems), and divergence of the model and plant outputs when the constant additive output disturbance (the approach of dynamic matrix control, DMC) is used. Experiences with the use of fundamental models, multiple linear models (MMPC), and neural networks are reviewed. Ongoing work in unmeasured disturbance estimation, prediction and rejection is also discussed. On presente un apercu general du controle predictif par modeles non lineaires (NMPC), en mettant l’accent en particulier sur les experiences des auteurs et les resultats publies. Les defi s incluent des solutions multiples (a partir des problemes d’optimisation non convexes), ainsi que la divergence entre les sorties de modele et d’installation lorsque la perturbation de sortie additive constante (la methode du controle de matrice dynamique, DMC) est utilisee. Les experiences avec les modeles fondamentaux, les modeles lineaires multiples (MMPC) et les reseaux neuronaux sont examinees. Le travail actuellement mene sur l’estimation, la prediction et le rejet des perturbations non mesurees est egalement examine.