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Chemical Engineering

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    A generalized novel group contribution kinetic modeling approach to linear alkene metathesis.
    (2023) Bansi, Nikhiel Isaiah.; Lokhat, David.
    Traditional modeling approaches for linear metathesis systems involve the use of complicated approaches – This paper proposes a generalized novel kinetic modeling technique, in which the substituent (alkyl) groups on the transition states are postulated to have a unique effect on the rate at which the controlling step (transition state dissociation) occurs. Metathesis involves the redistribution of the carbon-carbon double bond across constituents, to create longer chain hydrocarbons, which significantly enhances product value in an industrial context. This work proceeds by unpacking the mechanics of the 1-Hexene (linear) metathesis pathway and utilizes this as a basis for developing a group contribution kinetic modeling approach. The substituent (alkyl) groups present in the forming transition state complexes were used to define (identify) rate constants that would potentially control the rate of formation of the various transition state complexes. A key assumption in this work was that the largest externally attaching substituent, and the substituent existing in the metallacyclobutane complex, be selected as the groups that define the formation of the respective transition state complexes. These observations resulted in a system of 25 uniquely defined (identified) rate parameters that were derived based on the defining groups observed within the mechanisms and are sufficient to describe the metathesis system under investigation. Literature experimental data, at a range of temperatures (420℃ – 460℃) was readily available and was used for the purpose of fitting the identified rate parameters, by simultaneously solving the system of differential equations that result from this system. Given the system size (25 parameters), and complexity of the interactions in the system, evolutionary and swarm optimization techniques were found to be fit for this purpose. It was found that combination between a genetic algorithm (GA) and particle swarm optimization (PSO) approach yielded identified parameters that minimized the overall error of the prediction. Kinetic parameters were identified, and Arrhenius plots were developed – These allowed for the activation energies (𝐸𝑎) and pre-exponential factors (𝐴𝑜) to be determined for each parameter. This was tested using literature experimental datasets, and predictions were found to present with a modified fitness value between 1.968 and 50.55. This illustrates that the novel group contribution kinetic modeling approach was suitable to define the interactions in the system. Further research is required to generalize this result over other alkene metathesis systems; however, this work proves that the approach is viable. Extending this work to ring closing metathesis (RCM), is a future area of research that is of particular importance, as pharmaceutical intermediates result from these processes, and represents the unique opportunity to create a synergistic industrial landscape.
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    Online diagnosis of flow maldistribution in packed bed reactors.
    (2023) Maparanyanga, Tsitsi.; Lokhat, David.
    Massive adiabatic fixed bed reactors are common in the process industries for conversion of raw materials into valuable products. The unit usually consists of a vessel filled with catalyst particles through which the process gas flows. In general, the operation of this unit is akin to the ideal plug flow reactor, i.e. there are no radial gradients of concentration or temperature. During the normal operation of the unit, the catalyst particles can undergo attrition and dusting, resulting in regions of the bed that have different void fractions. These differences in bed voidage can result in non-uniform flow through the packed bed. When the process gas finds a path of least resistance it can flow through this path with little contact with the catalyst. This is referred to as channelling. Channelling leads to low conversion of reactants to product as there will be little contact with the catalyst. The maldistribution of flow through packed bed reactors can be determined by taking the unit offline and carrying out a residence time distribution test, for example a pulse of tracer is injected into the vessel inlet and the concentration of the tracer is measured at the exit. Although valuable information can be obtained from these measurements, it cannot be performed in most cases whilst the unit is online. Experimental work was done to determine if there is an appreciable difference in the pressure fluctuations of pressure vessels during correct and incorrect flow through packed beds and to assess if the effect of pressure fluctuations can be used to develop a method for diagnosing flow maldistribution in packed bed reactors online. Correct and incorrect flow through packed beds were achieved by using uniform and non-uniform packing arrangements, to induce non-uniform flow during the operation of the packed bed reactor. To develop a model for analysing flow maldistribution in packed bed reactors online, experiments were done using a small and large vessel. Rachsig rings were used as packing material in the laboratory packed bed reactor. The pressure fluctuations were converted to an analysable form using the Fast Fourier Transform, resulting in dominant frequency for the oscillations. The dominant frequency data could not give a distinguishable difference in the pressure fluctuations data. Experimental work done using various packings showed a significant difference in the measured amplitude as packing arrangement changes. Large(uniform) packing arrangement was seen to minimize pressure loss through the packed bed. The large packing also had the largest magnitude of pressure fluctuations. There was an inflection point in the amplitude vs flowrate data. The amplitude of pressure fluctuation first increased with an increase in gas flowrate up to a flowrate of 2 dm3/minute. From 2 dm3/minute to 2.33 dm3/minute there was an inflection point and the amplitude dropped. There was a further decrease in amplitude with a further increase in gas flowrate. The non-uniform packing had the highest amplitude below 2.33 dm3/minute but, after 2.33 dm3/minute the uniform packing had the largest amplitude followed by the large and small packing at the side while the large and small packing at the centre configuration had the least amplitude at high flowrates. This can be used online to check for particle breakage and the resulting maldistribution in flow in packed bed reactors. A model was developed to analyse pressure fluctuations in packed bed reactors. The model was developed using equations, found from literature, for non-ideal flow in packed beds. MATLAB software was used to solve and analyse the model. The pressure fluctuations obtained from experimental work agreed with the simulated data. The uniform packing had the highest amplitude while the nonuniform (large and small at the centre) had the least amplitude. The model was in agreement with experimental data, as it was seen that the amplitude of pressure fluctuations can be used for diagnosing flow maldistribution in packed bed reactors.