Abstract
Process simulation represents an important tool for plant design and optimization, either applied to well established or to newly developed processes. Suitable thermodynamic packages should be selected in order to properly describe the behavior of reactors and unit operations and to precisely define phase equilibria. Moreover, a detailed and representative kinetic scheme should be available to predict correctly the dependence of the process on its main variables. This review points out some models and methods for kinetic analysis specifically applied to the simulation of catalytic processes, as a basis for process design and optimization. Attention is paid also to microkinetic modelling and to the methods based on first principles, to elucidate mechanisms and independently calculate thermodynamic and kinetic parameters. Different case studies support the discussion. At first, we have selected two basic examples from the industrial chemistry practice, e.g., ammonia and methanol synthesis, which may be described through a relatively simple reaction pathway and the relative available kinetic scheme. Then, a more complex reaction network is deeply discussed to define the conversion of bioethanol into syngas/hydrogen or into building blocks, such as ethylene. In this case, lumped kinetic schemes completely fail the description of process behavior. Thus, in this case, more detailed—e.g., microkinetic—schemes should be available to implement into the simulator. However, the correct definition of all the kinetic data when complex microkinetic mechanisms are used, often leads to unreliable, highly correlated parameters. In such cases, greater effort to independently estimate some relevant kinetic/thermodynamic data through Density Functional Theory (DFT)/ab initio methods may be helpful to improve process description.
Highlights
How to Implement Kinetic Models into Process SimulatorsThe implementation of kinetic models into process simulators is a scientific and industrial field in continuous growth
NH3 adsorption terms, in order to consider the inhibiting effect of hydrogen on catalyst performance [8]. This is a major difference between Ru-based catalysts, which are inhibited by hydrogen, and the commercial Fe-based ones, which are inhibited by the product, ammonia, and substantially unaffected by the reactants
Starting from a first-principle thermodynamic analysis and energy; (2) only chemicals are considered originated from ethanol Steam reforming (SR) plus water gas shift (WGS); (3) from Dry Reforming (DR), with full conversion of ethanol into
Summary
The implementation of kinetic models into process simulators is a scientific and industrial field in continuous growth. Plug-flow (PFR, in case filled with catalyst) and continuous stirred tank (CSTR) reactors are the most flexible options, which allow a full description of the process under variable conditions and proper sizing of the reactor To perform these calculations, a suitable reaction set and the relative kinetic model and thermodynamic data must be defined. Microkinetic modelling allows the simulator to reliably follow the system performance; Again, if the amount of parameters to be determined in a microkinetic scheme becomes too high, high correlation among them is usually observed and predictions reliability is newly at risk Especially in such cases, the possibility of independently determining some of the required kinetic parameters through ab initio methods is a powerful tool to cope with this issue.
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