Novel coal gasification process: Improvement of syngas yield and reduction of emissions

This article is intended to propose and model an innovative process layout for coal gasification that improves the production of syngas and also reduces the sulfur and CO2emissions. The typical coal gasification process uses Sulfur Recovery Units to convert H2S to sulfur, but these have some disadvantage, e.g low sulfur price, coal charge with low sulfur flow rate, use of Tail Gas Treatment unit. Compared to the Claus process, this solution converts H2S and CO2into syngas (economically appealing), reduces emission of H2S and CO2and allows the use of coal charge with high sulfur flow rate, e.g. 9.5% mol/mol. The novel process takes advantage of a double amine wash, a thermal regenerative furnace and considers the recycle of the acid gases coming from the catalytic reactor to further promote the H2S conversion. In particular, the double amine wash is useful to purify the H2S stream to be sent to the thermal furnace from the syngas and CO2, in order to reduce the reactor inlet flow rate. The regenerative furnace is simulated using a large detailed kinetic scheme to appropriately describe the minor species (among them, pollutants like CS2 and COS). As a result, the recycle appears to substantially reduce the pollutant emissions. In addition, the conversion of the Claus process into the novel process doesn't require any change in the main equipment, just needing for a variation in the layout and the operating conditions

Exploiting C++ Polymorphism for Operational Optimization of Chemical Processes

Object-oriented programming is more and more spreading in engineering and scientific areas for some relevant benefits making it particularly appealing to write complex codes. Nevertheless, the use of such a programming philosophy still encounters large inertia in those areas characterized by a long programming experience and one of them is engineering. This is mainly due to a set of existing models and subroutines wrote in procedural (usually Fortran) language. The present paper is aimed at showing some benefits coming from object-oriented programming applied to the field of process optimization and specifically to the operational levels of supply chain management paradigm such as nonlinear model predictive control (NMPC). Polymorphism is exploited to provide a single solution for different NMPC techniques such as input blocking, offset blocking, and delta-blocking

Corporate Production Planning for Industrial Gas Supply Chains under Low-Demand Conditions

When the market demand significantly changes as within the ongoing worldwide economical crisis, many plants are forced to operate far from their nominal conditions. In this case, the plantwide optimization of production sites is a myopic approach that could unavoidably lead to plant inefficiencies and unconventional operation issues without preventing anyhow economical losses. A way to tackle low-demand conditions is to raise the decision-making process from the plantwide level to the corporate level by assigning a Boolean variable to each production site to manage its on/off status. By doing so, certain additional (social) constraints may become relevant. This work proposes a novel approach to the corporate production planning entirely based on MS VISUAL C++ and on specific algorithms belonging to BzzMath library. © 2011 Elsevier B.V

A Comprehensive and General Class for Solving Nonlinear Model Predictive Control and Dynamic Optimization

Nonlinear model predictive control (NMPC) and real-time dynamic optimization (RTDO) both based on a receding horizon methodology are fast spreading outside their common application field towards some scientific and industrial areas particularly far from their original cradle. Unfortunately, algorithms and numerical methods behind NMPC and RTDO are not a prerogative of these novel application fields with the result of having not so performing or furthermore ineffective solutions. From this perspective, the possibility to provide a generalized approach to solve NMPC and RTDO problems able to automatically select the best combination of algorithms could have the twofold aim of supporting an inexpert user in implementing these appealing methodologies and to favor their spreading in other scientific areas

Dynamic simulation of the lurgi-type reactor for methanol synthesis

The purpose of this work is to develop a reasonably detailed dynamic model of a Lurgi-type industrial methanol synthesis reactor so as to determine important simplifications, to identify application/operating model limits, and to preliminary check the feasibility for the Nonlinear Model Predictive Control (NMPC) methodology. To do so, a Partially Differential Equation (PDE) system is formulated and integrated to characterize the main phenomena occurring in this shell and tube boiler-reactor. The PDE numerical solution is performed via certain very performing algorithms (BzzMath library)

Generalized Classes for Lower Levels of Supply Chain Management: Object-Oriented Approach

A possible and promising approach to effectively tackle the distinct optimization levels of supply chain hierarchy is to combine the object-oriented programming with the parallel computing. From this perspective, the paper proposes a generalized framework to solve the lowest levels of supply chain management paradigm by means of the BzzMath library as numerical kernel (optimizers and differential solvers) and openMP directives for exploiting shared memory machines. Also, the object-oriented approach allows the implementation of more solvers to force the same generalized class to automatically select the best one among them according to the problem and the user has not to worry about what solver and which optimizer are preferable

Model Predictive Control of a CVD Reactor for Production of Polysilicon Rods

Production of polysilicon plays a key role in the development of hi-tech and renewable energy industry. Massive production is obtained by chemical vapor deposition (CVD) in semi-batch reactors, traditionally called Siemens reactors, where silicon rods are grown. Following recent increase in market demand for polysilicon, a fine process control on industrial processes for improving production yield and reducing energy consumption is required. In this work, a technique for a real-time model-based predictive control applied to a laboratory-scale Siemens reactor is presented; a lumped model is used for describing the CVD process. Discussion is based on numerical results

Online Feasibility And Effectiveness Of A Spatio-temporal Nonlinear Model Predictive Control: The Case Of Methanol Synthesis Reactor

This work provides the theoretical formulation, implementation directives and validation case for the extension of the nonlinear model predictive control from the time domain to the spatio-temporal domain. Effectiveness and online feasibility are demonstrated for industrial processes of distributed nature. The case of methanol synthesis (control of hot-spot temperature and axial position) is selected. © 2012 Elsevier B.V.30867871Bendersky, E., Christofides, P.D., Optimization of transport-reaction processes using nonlinear model reduction (2000) Chemical Engineering Science, 55, pp. 4349-4366Buzzi-Ferraris, G., Manenti, F., A Combination of Parallel Computing and Object-Oriented Programming to Improve Optimizer Robustness and Efficiency (2010) Computer Aided Chemical Engineering, 28, pp. 337-342Christofides, P.D., Daoutidis, P., Nonlinear control of diffusion-convection-reaction processes (1996) Computers & Chemical Engineering, 20, pp. S1071-S1076Flores-Tlacuahuac, A., Biegler, L.T., Saldivar-Guerra, E., Optimal grade transitions in the high-impact polystyrene polymerization process (2006) Ind. Eng. Chem. Res., 45, pp. 6175-6189Liu, J., de la Pena, D.M., Christofides, P.D., Distributed Model Predictive Control of Nonlinear Process Systems (2009) Aiche Journal, 55, pp. 1171-1184Lou, Y.M., Hu, G.S., Christofides, P.D., Model predictive control of nonlinear stochastic partial differential equations with application to a sputtering process (2008) Aiche Journal, 54, pp. 2065-2081Lurgi, G., (2009) Lurgi MegaMethanol®, , http://www.lurgi.comManenti, F., Considerations on Nonlinear Model Predictive Control Techniques (2011) Computers & Chemical Engineering, 35, pp. 2491-2509Manenti, F., Cieri, S., Restelli, M., Considerations on the steady-state modeling of methanol synthesis fixed-bed reactor (2011) Chemical Engineering Science, 66, pp. 152-162Manenti, F., Cieri, S., Restelli, M., Lima, N.M.N., Zuniga Linan, L., Dynamic Simulation of Lurgi-type Reactor for Methanol Synthesis (2011) Chem. Eng. Trans., 24, pp. 379-384Morari, M., Lee, J.H., Model predictive control: past, present and future (1999) Computers & Chemical Engineering, 23, pp. 667-682Ni, D., Christofides, P.D., Multivariable predictive control of thin film deposition using a stochastic PDE model (2005) Industrial & Engineering Chemistry Research, 44, pp. 2416-2427Palavajjhala, S., Motard, R.L., Joseph, B., Blocking and Condensing design for quadratic dynamic matrix control using wavelets (1994) Ind. Eng. Chem. Res., 33, pp. 1159-117

Experimental Campaign, Modeling, And Sensitivity Analysis For The Molecular Distillation Of Petroleum Residues 673.15k+

This research activity proposes a sensitivity analysis of the molecular distillation process by focusing the attention on the response of the overall distillate flow rate under several conditions of distillation temperature and feed flow rate. Specific equations to characterize physicochemical properties of petroleum residues have been formulated by means of ASTM-based experimental campaigns combined with specific optimization techniques.The steady state refining process simulator by Petrobras coupled with appropriate finite-difference methods is adopted for the simulation of a heated and extremely low-pressure falling film evaporator to separate a heavy residue 673.15. K+ of Gamma. +. Sigma crude oil. Numerical results are validated on the experimental points. © 2011.902243258Amin, M.B., Beg, S.A., Kinematic viscosity-temperature behavior of heavy TBP-fractions (455°C+) of Arabian crude oils (1993) Fuel Sci. Technol. Int., 11, pp. 1425-1439(2008), ASTM D 70. 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