Prashant R. Gunjal

Experimental and computational study of liquid drop over flat and spherical surfaces

Flow of a liquid droplet over a flat plate and a spherical pellet was studied to improve understanding of wetting in trickle bed reactors. High speed imaging system and computational fluid dynamics (CFD) was used for this purpose. Experimental data is reported on dynamics of drop rest on a flat and a spherical surface. Micro-scale motion of liquid droplet on these surfaces was captured with a high-speed CCD camera. Images were analyzed to provide quantitative data of drop dynamics. Drop spread and recoiling velocities were reconstructed from the experimental data. CFD model based on the volume of fluid (VOF) method was used to simulate drop dynamics on flat and spherical surfaces. Surface tension and wall adhesion phenomenon were included in the computational model. Simulated drop dynamics was found to capture key qualitative features observed in the experiments. Numerical simulations with three-dimensional domains are essential for quantitative comparison with experimental data. The experimental results and computational model discussed in this paper would be useful for better understanding of wetting in trickle bed reactors.

Reactor Performance and Scale-Up

This chapter provides a methodology for the engineering of trickle bed reactors such as to enhance performance and scale up production. In engineering practice, the reactor engineering solution is composed of three main steps: analysis of transport and reaction rate parameters; identifying uncertainties associated with design parameters; and resolving process complexities and conflicting demands. In trickle bed reactors, interaction between reaction kinetics and hydrodynamics is often complex. Key practical aspects involving rate analysis including hysteresis and multiplicity, particle and bed properties (particle size/shape/orientation), distributor effects, liquid phase maldistribution, and mixing of phases along the length of the column are discussed. Issues related to selection of reactor aspect ratio and issues pertaining to scale-up and scale-down are also discussed. An overall methodology combining experiments and computational modeling is presented at the end. It is evident from the current state of the art that in spite of the considerable advances in the understanding of different phenomena occurring in trickle beds, it is futile to attempt a single comprehensive model for a trickle bed reactor incorporating all the processes. It is therefore recommended to use a suite of models comprising many “learning” and “design” models. These modeling efforts need to be complemented by appropriately designed experiments of three categories: learning, calibration, and validation. Such a composite approach based on the methodology discussed will be useful for the engineering of trickle bed reactors.

Reaction Engineering of Trickle Bed Reactors

This chapter discusses the fundamental issues relating to the understanding of the rate processes and performance of trickle bed reactors. It is useful to interpret the experimental data in laboratory or pilot plant reactors as well as the simulation of industrial-scale reactors. The mathematical models accounting for the contributions of reaction kinetics, external and intraparticle mass transfers, and axial and radial mixing for simple and complex reaction kinetics have been summarized. These require several design parameters, which can be predicted using the correlations. The models for a more detailed understanding of the complexities of hydrodynamics and flow behavior can be extended with CFD models. All the elements of developing reactor performance models that would capture relevant issues of scale-up and design are also provided. It is important to note, however, that while the basic rate and performance models are useful for the quantitative analysis of the rate controlling steps for a given process, several issues concerning differences in hydrodynamic and flow behavior at different scales (pilot and industrial) are not easy to assess from these models. Careful judgment of these factors using other approaches is needed to develop more general models which would not depend on the scale of operation.

Catalytic Reaction Engineering

Chemical reaction engineering has contributed remarkably in bringing laboratory-developed chemistry into commercial practice. Reaction engineering is useful for analysis of reactions, identifying rate-limiting steps, determining overall rates, selection of reactor configuration and design and scale-up of reactors. Reaction engineering also provides useful insights into catalytic cycles and provides clues for improving catalyst systems. It essentially includes all the activities necessary to evolve best possible hardware and operating protocol for the reactor to carry out the desired transformation of raw materials (or reactants) into value-added products. This chapter provides an overview of reaction engineering aspects of catalytic processes.

Flow Modeling of Trickle Beds

With the current level of understanding, it is more advantageous to use a hierarchy of models coupled with key experimental findings to achieve practical benefits. This chapter, therefore, discusses different modeling approaches, which allow better quantitative understanding of the processes occurring in trickle bed reactors. A “unit cell” approach, or considering an assembly of a few particles, is very useful for obtaining quantitative insights into the flow structures and transport processes occurring in packed beds. This approach can also be extended to gas-liquid flow through packed beds using VOF (volume of fluid) models. Information obtained from these models can be used for developing appropriate closures for macroscopic models. The Eulerian-Eulerian approach is recommended for the modeling of macroscale flow processes in fixed bed as well as trickle bed reactors. The realistic representation of the characteristics of the fixed bed (porosity distribution, degree of anisotropy, and so on) is crucial for carrying out simulations for engineering applications. Most of the current work relies on empirical information and pressure drop data to calibrate computational flow models of fixed and trickle bed reactors. Such calibrated computational flow models will be useful for understanding issues related to maldistribution, channeling, formation of hot spots, etc. To realize process intensification and performance enhancement, accurate knowledge of the underlying flowfield in chemical reactors is essential.

Hydrodynamics and Flow Regimes

This chapter presents and reviews available knowledge on hydrodynamics, flow regimes, and transport parameters in the trickle bed. Accurate estimation of hydrodynamic parameters is an indispensable step for the reactor design, performance evaluation, and scale-up studies. Hydrodynamics of trickle bed reactors is controlled by complex internal bed structure and associated interactions with the gas and liquid flows. The first step in estimating the hydrodynamic parameters is estimation of prevailing flow regimes under operating conditions. The correlations and discussion presented in flow regimes are useful for selection of criteria to evaluate the flow regime and its transition so that all further calculations will be based on the characteristics of that flow regime. Trickle bed reactors are often operated near the boundary of trickle and pulse flow regimes in practice. It is therefore important to be able to estimate the transition boundary between trickle and pulse regimes accurately. The methods and models presented in flow regime transition can be used to determine the transition boundary. Methods and correlations for estimating other key hydrodynamic parameters such as pressure drop, liquid holdup, mass and heat transfer coefficients, and axial dispersions are discussed in the estimation of key hydrodynamic parameters. It is important to note that the hydrodynamics of trickle beds is a complex function of interactions of particle properties, packing characteristics of the bed, properties of gas and liquid, and operating conditions. Therefore, literature data when correlated for particular parameters give considerably different values for the same operating parameters.

Applications and Recent Developments

This chapter focuses on the application of engineering to trickle beds as well as a brief review of recent developments and the path forward in trickle bed reactors. Trickle bed reactors are extensively used in chemical and associated industries such as the petroleum, petrochemical, oil and gas, mineral, and coal industries, pharmaceuticals, fine and specialty chemicals, biochemicals, and waste treatment. Applications may vary considerably from industry to industry. Trickle bed reactors offer several advantages such as simplicity in operation (without any moving part or catalyst separation unit), high catalyst loading per unit volume, and low capital and operating costs. It also has some inherent drawbacks such as poor external and intraparticle heat transfer rates, significant intraparticle diffusion limitations, and susceptibility to liquid maldistribution. Therefore, the design of reactors for a particular application often requires balance among different competing requirements. For example, reduction in operating cost (by reducing pressure drop) is possible by using larger-sized particles; however, larger particles lead to lower effectiveness factors because of intraparticle diffusion limitations. Trickle bed operation is simple at the expense of fewer degrees of freedom available to engineers for manipulating its performance. There is a limited scope to manipulate local conditions within the bed such as local hot spots (which may lead to sintering or runaway) and use of catalysts with rapid deactivation. In recent years, other variants of trickle bed reactors such as monolith reactors or microtrickle bed reactors have been evolved, which may minimize some of the inherent disadvantages of the trickle bed reactors while significantly improving their performance.