Solving Practical Catalytic Reactor Performance Issues by Intelligent Use of Reactor Modeling and Experimental Tools

Chemical reactions and the reactors where they are implemented are an integral component of any process technology. The crude product streams generated by reactors ultimately determine key economic factors that notably contribute to process capital and manufacturing costs, such as materials of construction, complexity of downstream separation and product purification unit processes, the composition and magnitude of recycle streams, and handling of by-product streams. Since most practical reaction systems employ either a solid heterogeneous or an organometallic complex, the profitability of process technology is critically dependent upon the atom efficiency achieved by a particular catalyst-reactor package. To optimize reactor performance, process engineers often attempt to identify process conditions that lead to a maximum in the space-time yield of the desired product or the targeted product distribution by process optimization techniques.

The complex interaction between reaction kinetics, hydrodynamics, and transport effects in commercial-scale reactors creates notable challenges for process engineers whose mission includes reactor debottlenecking and ongoing efforts toward greater capital productivity within the given process parameter space. Since it is not often practical to use the commercial-scale reactor as a pilot plant to validate proposed process improvements, other cost-effective approaches are required. The intelligent application of reactor modeling techniques and data derived from experimental measurements provide a synergistic combination for process reactor optimization.

This presentation will provide an overview of how process engineers can utilize experimental data derived from well-characterized laboratory or pilot-scale reactors, along with process reactor models, as a starting basis for solving practical reactor performance issues, advancing process improvements, and for process optimization. Since most practical processes involve multiphase gas-solid catalyzed or gas-liquid-solid catalyzed reactions, these classes of reactions will be used for illustrative purposes. The selection of appropriate small-scale reactors that will produce meaningful catalyst performance data and various operational options will be summarized. The importance of implementing process automation, robust analytical methods, and statistical-designed experimental protocols for efficient kinetic data collection will be highlighted through several practical example applications. The discrimination of reaction kinetic models and an overview of reactor-scale process models that properly account for transport-kinetic interactions will also be described. The implementation of reactor models using various modern software tools will be reviewed. The use of tracer experiments in commercial-scale reactors as a means of identifying the fluid flow patterns and fluid distribution patterns, or as a means of diagnosing reactor performance issues and guiding reactor model development, will be shown through two practical examples. Final thoughts on developing a platform of experimental and modeling tools to support business objectives using this methodology will be provided through practical industrial examples derived from the speaker’s industrial and consulting experience.