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    A dynamic non-isothermal model for a hydrocracking reactor: model development by the method of continuous lumping and application to an industrial unit
    (Elsevier Sci Ltd, 2012) Çakal, Berna; Gökçe, Dila; Kuzu, Emre; N/A; Department of Chemical and Biological Engineering; Şıldır, Hasan; Arkun, Yaman; Phd Student; Faculty Member; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; College of Engineering; 242076; 108526
    Hydrocracking is an important refinery process which is carried out in catalytic reactors to convert heavy petroleum fractions into valuable products. Because of the large number of species and complex reactions involved, modeling of hydrocracking is a challenging task. In this paper a dynamic, non-isothermal reactor model has been constructed using the method of continuous lumping which treats the complex reactive mixture as a continuum. In doing so concentrations are characterized in terms of reactivity which is a monotonic function of the true boiling point of the mixture. The material and energy balances are developed in the form of integro-differential equations. The significant modeling parameters are identified and estimated using data from an industrial reactor. Steady-state and dynamic predictions of the model outputs such as reactor temperature, product yields and hydrogen consumption are shown to be in good agreement with plant data.
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    Plant-wide hierarchical optimization and control of an industrial hydrocracking process
    (Elsevier Sci Ltd, 2013) Çakal, Berna; Gökçe, Dila; Kuzu, Emre; N/A; Department of Chemical and Biological Engineering; Şıldır, Hasan; Arkun, Yaman; PhD Student; Faculty Member; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; College of Engineering; 242076; 108526
    Hydrocracking is a crucial refinery process in which heavy hydrocarbons are converted to more valuable, low-molecular weight products. Hydrocracking plants operate with large throughputs and varying feedstocks. In addition the product specifications change due to varying economic and market conditions. In such a dynamic operating environment, the potential gains of real-time optimization (RTO) and control are quite high. At the same time, real-time optimization of hydrocracking plants is a challenging task. A complex network of reactions, which are difficult to characterize, takes place in the hydrocracker. The reactor effluent affects the operation of the fractionator downstream and the properties of the final products. In this paper, a lumped first-principles reactor model and an empirical fractionation model are used to predict the product distribution and properties on-line. Both models have been built and validated using industrial data. A cascaded model predictive control (MPC) structure is developed in order to operate both the reactor and fractionation column at maximum profit. In this cascade structure, reactor and fractionation units are controlled by local decentralized MPC controllers whose set-points are manipulated by a supervisory MPC controller. The coordinating action of the supervisory MPC controller accomplishes the transition between different optimum operating conditions and helps to reject disturbances without violating any constraints. Simulations illustrate the applicability of the proposed method on the industrial process.