Comparing Attic Method with the Existing Techniques for Linear Programming

The aim of the work is to compare the performances of the novel Attic method for linear programming (Buzzi-Ferraris, 2011) with the existing algorithms of the simplex and interior point families. Potentialities of the new method are demonstrated and quantified on the linear programming problem of thermal cracking refinery

Performance Assessment of Existing Methodologies for Chemical Process Dynamic Simulation

The chemical engineer has nowadays a wide choice of tools, numerical libraries, and programming languages to perform computations. Actually, it is possible to use several well established commercial packages, implement dedicated solvers into specific programming languages, or use existing numerical libraries. Also, it is possible to combine these possibilities to get either superior performances or more robustness, according to the problem features through the so-called mixed-language approach, which is increasingly spreading in the scientific communities. Since there is no full clarity on their benefits in handling numerical problems and their performances have not been yet compared in the literature, this paper is aimed at analyzing efficiency and robustness of some of the most widespread methodologies adopted for numerical computations: the conventional methods, the implementation of numerical libraries, the mixed-language, and the commercial tools. Specifically, the common case of differential systems is selected as comparison field

Modelling of a dynamic multiphase flash: the positive flash. Application to the calculation of ternary diagrams

A general and polyvalent model for the dynamic simulation of a vapor, liquid, liquid-liquid, vapor-liquid or vapor-liquid-liquid stage is proposed. This model is based on the -method introduced as a minimization problem by Han & Rangaiah (1998) for steady-state simulation. They suggested modifying the mole fraction summation such that the same set of governing equations becomes valid for all phase regions. Thanks to judicious additional switch equations, the -formulation is extended to dynamic simulation and the minimization problem is transformed into a set of differential algebraic equations (DAE). Validation of the model consists in testing its capacity to overcome phase number changes and to be able to solve several problems with the same set of equations: calculation of heterogeneous residue curves, azeotropic points and distillation boundaries in ternary diagrams

Assessment of control techniques for the dynamic optimization of (semi-)batch reactors

YesThis work investigates how batch reactors can be optimized to increase the yield of a desired product coupling two appealing techniques for process control and optimization: the nonlinear model predictive control (NMPC) and the dynamic real-time optimization (D-RTO). The overall optimization problem is formulated and applied to calculate the optimal operating parameters of a selected case study and the numerical results are compared to the traditional control/optimization techniques. It has been demonstrated in our previous work (Pahija et al, Selecting the best control methodology to improve the efficiency of discontinuous reactors, Computer Aided Chemical Engineering, 32, 805-810, 2013) that the control strategy can significantly affect optimization results and that the appropriate selection of the control methodology is crucial to obtain the real operational optimum (with some percent of improved yield). In this context, coupling NMPC and D-RTO seems to be the ideal way to improve the process yield. The results presented in this work have been obtained by using gPROMS® and MS C++ with algorithms of BzzMath library

A robust sustainable optimization & control strategy (RSOCS) for (fed-)batch processes towards the low-cost reduction of utilities consumption

YesThe need for the development of clean but still profitable processes and the study of low environmental impact and economically convenient management policies for them are two challenges for the years to come. This paper tries to give a first answer to the second of these needs, limited to the area of discontinuous productions. It deals with the development of a robust methodology for the profitable and clean management of (fed-)batch units under uncertainty, which can be referred to as a robust sustainability-oriented model-based optimization & control strategy. This procedure is specifically designed to ensure elevated process performances along with low-cost utilities usage reduction in real-time, simultaneously allowing for the effect of any external perturbation. In this way, conventional offline methods for process sustainable optimization can be easily overcome since the most suitable management policy, aimed at process sustainability, can be dynamically determined and applied in any operating condition. This leads to a significant step forward with respect to the nowadays options in terms of sustainable process management, that drives towards a cleaner and more energy-efficient future. The proposed theoretical framework is validated and tested on a case study based on the well-known fed-batch version of the Williams-Otto process to demonstrate its tangible benefits. The results achieved in this case study are promising and show that the framework is very effective in case of typical process operation while it is partially effective in case of unusual/unlikely critical process disturbances. Future works will go towards the removal of this weakness and further improvement in the algorithm robustness

Direct crude oil cracking for producing chemicals: Thermal cracking modeling

[EN] The direct cracking of crude oil is an interesting option for producing cheaply large amounts of petrochemicals. This may be carried out with catalyst and equipment similar to that of catalytic cracking, but at a temperature range between that of standard catalytic cracking and steam cracking. Thermal cracking will play a role in the conversion, but is rarely disclosed in experimental or modeling work. Thus, a crude oil and its fractions were thermally cracked and the products yields were modeled using a 9 lumps cracking scheme. It was found that heavy fraction cracks twice as fast as diesel fraction and ten times faster than gasoline fraction, with activation energies in the 140-200 kJ/mol range. Selectivity to ethylene, propylene and butenes were found similar in the operating range explored.The authors thank Saudi Aramco for its material and financial support. Financial support by the Spanish Government-MINECO through programs "Severo Ochoa" (SEV 2012-0267) and CTQ2015-70126-R and by the Generalitat Valenciana through the Prometeo program (PROMETEOII/2013/011) is also acknowledged.Corma Canós, A.; Sauvanaud, LL.; Mathieu, Y.; Al-Bogami, S.; Bourane, A.; Al-Ghrami, M. (2018). Direct crude oil cracking for producing chemicals: Thermal cracking modeling. Fuel. 211:726-736. https://doi.org/10.1016/j.fuel.2017.09.099S72673621

Optimal Design of a Trickle Bed Reactor for Light Fuel Oxidative Desulfurization based on Experiments and Modelling

YesIn this work, the performance of oxidative desulfurization (ODS) of dibenzothiophene (DBT) in light gas oil (LGO) is evaluated with a homemade manganese oxide (MnO2/γ-Al2O3) catalyst. The catalyst is prepared by Incipient Wetness Impregnation (IWI) method with air under moderate operating conditions. The effect of different reaction parameters such as reaction temperature, liquid hour space velocity and initial concentration of DBT are also investigated experimentally. Developing a detailed and a validated trickle bed reactor (TBR) process model that can be employed for design and optimization of the ODS process, it is important to develop kinetic models for the relevant reactions with high accuracy. Best kinetic model for the ODS process taking into account hydrodynamic factors (mainly, catalyst effectiveness factor, catalyst wetting efficiency and internal diffusion) and the physical properties affecting the oxidation process is developed utilizing data from pilot plant experiments. An optimization technique based upon the minimization of the sum of the squared error between the experimental and predicted composition of oxidation process is used to determine the best parameters of the kinetic models. The predicted product conversion showed very good agreement with the experimental data for a wide range of the operating condition with absolute average errors less than 5%