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The steam cracking process is a common technology for producing ethylene from naphtha. However, one of the major contaminants in the ethylene product stream is acetylene, which poisons catalysts used in downstream polymerization processes and must be converted to ethylene by selective catalytic hydrogenation in order to upgrade product quality and increase overall ethylene yield. The selective hydrogenation process is usually carried out in a multistage fixed-bed catalytic reactor with internal cooling between stages to ensure that the outlet concentration of acetylene does not exceed 1 ppm. Nevertheless, side reactions also occur, including total hydrogenation to ethane, which increases energy consumption at the recycle furnace and decreases overall plant productivity. Moreover, in a tail-end hydrogenation process, the catalyst surface often becomes covered by so-called green oil generated from acetylene oligomerization, which causes catalyst deactivation and lowers the selectivity to ethylene. A key challenge of the tail-end acetylene hydrogenation process is to maximize the selectivity to ethylene while maintaining a full conversion of acetylene and maximizing the run length between catalyst regenerations. In this work, a model of the tail-end three-stage fixed-bed catalytic selective hydrogenation reactor was developed and validated to accurately predict the reactor outlet composition and other important variables. To achieve the optimum operating policy, the model-based dynamic optimization was applied to maximize overall process economics through enhancement of selectivity to production of ethylene. Implementation of the optimal operating policy on a commercial acetylene hydrogenation reactor resulted in a 13% improvement of ethylene selectivity and 10% increase of overall process economics while simultaneously decreasing the rate of catalyst deactivation. This modeling and optimization approach should be applicable to other fixed-bed hydrogenation processes, such as hydrogenation of methyl acetylene and propadiene in propylene product stream.

The water-gas shift (WGS) is one of the major steps for H2 production from gaseous, liquid and solid hydrocarbons. It is used to produce hydrogen for ammonia synthesis, to adjust the hydrogen-to-carbon monoxide ratio of synthesis gas, to detoxify gases. The WGS reactor is widely used as a part of fuel processors which produce hydrogen-rich stream from hydrocarbon-based fuels in a multi-step process. The WGS unit is placed downstream the fuel reformer in order to increase overall efficiency of hydrogen production and to lower CO content in reformate. Fuel processors stand for considerable option for fuelling PEM fuel cells for both portable and stationary applications. Micro-structured reactors are used with benefits of process miniaturization, intensification and higher heat and mass transfer rates compared with conventional reactors. Micro-structured reactor systems are essential for processes where potential for considerable heat transfer exists as well as for kinetic studies of highly exothermic reactions at near-isothermal conditions. Modelling and simulation of a microchannel reactor for the WGS reaction is presented. The mathematical models concern a single reaction channel with porous layer of catalyst deposited on the metallic wall of the microstructure unit. Simplified one-phase and more sophisticated two-phase models, with separate mass and energy balances for gas and solid phase at different levels of complexity, were developed. The models were implemented into gPROMS process modelling software. The models were used for an estimation of parameters in a kinetic expression using experimental data obtained with a new WGS catalyst. The simulations provide detailed information about the composition and temperature distribution in gas phase and solid catalyst inside the channel.

Careful design of catalytic reactors can reduce both the cost and risk associated with new designs and can reduce ownership costs significantly through better performance during operation. Digital design techniques based on high-fidelity predictive models now afford a way of doing this rapidly and effectively. Such techniques make it possible to perform detailed design of multitubular reactors taking into account multiscale effects, from catalyst pore to industrial reactor, by combining high-fidelity models with model-targeted experimentation. Further benefits can be realized by implementation of the detailed model online for monitoring, forecasting, and optimization. This paper introduces the digital design approach for design, optimization, and online implementation of fixed-bed catalytic reactors, with examples taken from selected industrial cases.

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