Modeling, simulation and control of a methanol synthesis fixed-bed reactor

Shahrokhi, Mohammad; Baghmisheh, Gholamreza

doi:10.1016/j.ces.2004.12.051

Cited by 78 publications

(43 citation statements)

References 13 publications

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“…Thus the sum of activation energy and enthalpies of adsorption or reaction may result in a negative value of this parameter. Nevertheless, the Vanden Bussche and Froment kinetic model is very often used for describing the experimental data both from laboratory and industry scale (Shahrokhi and Baghmisheh, 2005) and modelling of methanol synthesis (Petera et al, 2013).…”

Section: Resultsmentioning

confidence: 99%

Kinetic Characterisation of Catalysts for Methanol Synthesis

Ledakowicz¹,

Nowicki²,

Petera³

et al. 2013

Chemical and Process Engineering

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The results of activity studies of four catalysts in methanol synthesis have been presented. A standard industrial catalyst TMC-3/1 was compared with two methanol catalysts promoted by the addition of magnesium and one promoted by zirconium. The kinetic analysis of the experimental results shows that the Cu/Zn/Al/Mg/1 catalyst was the least active. Although TMC-3/1 and Cu/Zn/Al/Mg/2 catalysts were characterised by a higher activity, the most active catalyst system was Cu/Zn/Al/Zr. The activity calculated for zirconium doped catalyst under operating conditions was approximately 30% higher that of TMC-3/1catalyst. The experimental data were used to identify the rate equations of two types -one purely empirical power rate equation and the other one -the Vanden Bussche & Froment kinetic model of methanol synthesis. The Cu/ZnO/Al 2 O 3 catalyst modified with zirconium has the highest application potential in methanol synthesis.

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Section: Resultsmentioning

confidence: 99%

Kinetic Characterisation of Catalysts for Methanol Synthesis

Ledakowicz¹,

Nowicki²,

Petera³

et al. 2013

Chemical and Process Engineering

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“…Several authors reported the development of computational tools for the simulation of methanol synthesis reactors on an industrial scale [1][2][3][4][5][6][7][8][9][10][11][12][13]. Some of the research focuses on the analysis of the reactor operation, providing mathematical models for simulation and operational optimization [1][2][3][4][5][6][7][8]. To maximize the methanol yield, decision variables of the optimization problem are related to the temperature profile along the reactor, feed composition, or recycle ratio.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Methanol Yield from a Lurgi Reactor

et al. 2011

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Methanol is an important chemical with the potential to become an alternative fuel. An optimization study was performed for a Lurgi methanol synthesis reactor using the commercial process simulator Aspen Plus. The optimization routine is coupled with a steady-state model of the methanol synthesis reactor. Syngas inlet temperature, steam drum pressure, and cooling water volumetric flow rate were optimized so that methanol production in the reactor outlet was maximized. The methanol yield increased by 7.04 %.

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“…This model consists of mass and energy balance equations with the incorporation of intra-particle mass and heat transfers. The assumptions that govern these equations are: (1) only the axial temperature change is taken into account, (2) the radial temperature change is neglected due to the fact that the diameter of the reactor is small and adiabatic (no heat loss from the surface of the reactor); see [15], (3) momentum conservation equation has been disregarded in this model because the bed height is too small to create a significance amount of pressure drop, i.e., see [16], (4) is neglected. Equations (5) - (7) show the mass and energy balance equations for the PBTR system.…”

Section: Packed Bed Tubular Reactor Model With Inter-stage Coolingmentioning

confidence: 99%