Deep hydrodesulfurization is an important process because of increasing environmental regulations. Reasonably accurate kinetics and deactivation models are important for predicting the catalyst life and reactor operational adjustments. Gas oil contains various sulfur compounds known by its boiling point, each with different reaction rates. Therefore, single-lumped kinetics is not accurate for all sulfur constituents. Hence, four-to six-lump models, grouping sulfur compounds according to their boiling points, are proposed and coupled with a catalyst deactivation model to predict the time-on-stream reactor performance. The multilump kinetic rate constants were obtained from fitting of operating data. The multilump models show predictions that are more accurate than those of the single-lump model, and the six-lump model gives the most accuracy. The obtained deactivation parameter was applied to present the long-term operational adjustment curve for the operating temperature as a function of time-on-stream to achieve the specified sulfur removal. Such curves are useful in hydrodesulfurization operational planning.

Optimization of biodiesel production requires fundamentals-based kinetic and reactor models. A liquid–liquid reactor requires reaction rate model including mass-transfer effects. Earlier studies have not analyzed such an effect in detail and thus cannot be used for scale-up and design. This work develops a two-scale model for design and scale-up. The intrinsic rate constant, fit from experimental data, is approximately 300 times larger than the apparent one. The model results for microchannel and stirred-batch reactors agree well with the experimental data and indicate that the former requires approximately 720 times shorter residence time than the latter. Scaling-up of an agitated-batch reactor to industrial scale by keeping tip speed constant provides lower performance due to inadequate power. In contrast, scaling-up with constant power/volume provides higher performance due to oversupply power. The two-scale model is used to adjust agitation speed for achieving performance similarity during scale-up. The corresponding power lies in between the two above-mentioned values.

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