Chemical reactors dynamic simulation

Health, Safety, and Accident Management in the Chemical Process Industries, Ann Marie Flynn and Louis Theodore Plantwide Dynamic Simulators in Chemical Processing and Control, William L. Luyben Chemical Reactor Design, Peter Harriott Catalysis of Organic Reactions, edited by Dennis G. Morrell Lubricant Additives Chemistry and Applications, edited by Leslie R. Rudnick... 

Zuflerey, B. (2006) Scale-down Approach Chemical Process Optimisation Using Reaction Calorimetry for the Experimental Simulation of Industrial Reactors Dynamics, EPFL, n°3464, Lausanne. 

In the RSR approach the chemical reactor is the key unit, designed and simulated in terms of productivity, stability and flexibility. From the systemic viewpoint the key issue is the quality and dynamics of flows entering the reactor and less how they have been produced. Obviously, these flows include fresh reactants and recycle streams. The dynamics of flows must respect the overall material balance at steady state, as well as the process constraints. For this reason, the chemical-reactor analysis should be based on a kinetic model. 

The dynamic simulation file prepared in Aspen Plus is exported in Aspen Dynamics [10]. We select the flow-driven simulation mode. Aspen Dynamics files have already implemented the basic control loops for levels and pressures. Units with fast dynamics, such as the evaporator or some heat exchangers, may be handled as steady state. The implementation of control loops for the key operational units, chemical reactor and distillation columns, take into account some specific issues from the plantwide perspective, which are developed in detail in Luyben et al. [8]. 

From a simulation viewpoint units SO, S6 and S7 may be considered blackboxes. On the contrary, SI to S5 are simulated by rigorous distillation columns, as sieve trays. In the steady state all the reactors can be described by a stoichiometric approach, but kinetic models are useful for Rl, R2 and R4 in dynamic simulation [7, 8]. As shown before, the reaction network should be formulated so as to use a minimum of representative chemical species, but respecting the atomic balance. This approach is necessary because yield reactors can misrepresent the process. 

There have been many hybrid multiscale simulations published recently in other diverse areas. It appears that the first onion-type hybrid multiscale simulation that dynamically coupled a spatially distributed 2D KMC for a surface reaction with a deterministic, continuum ODE CSTR model for the fluid phase was presented in Vlachos et al. (1990). Extension to 2D KMC coupled with ID PDE flow model was described in Vlachos (1997) and for complex reaction networks studied using 2D KMC coupled with a CSTR ODEs model in Raimondeau and Vlachos (2002a, b, 2003). Other examples from catalytic applications include Tammaro et al. (1995), Kissel-Osterrieder et al. (1998), Qin et al. (1998), and Monine et al. (2004). For reviews, see Raimondeau and Vlachos (2002a) on surface-fluid interactions and chemical reactions, and Li et al. (2004) for chemical reactors. 

Takeuchi et al. 7 reported a membrane reactor as a reaction system that provides higher productivity and lower separation cost in chemical reaction processes. In this paper, packed bed catalytic membrane reactor with palladium membrane for SMR reaction has been discussed. The numerical model consists of a full set of partial differential equations derived from conservation of mass, momentum, heat, and chemical species, respectively, with chemical kinetics and appropriate boundary conditions for the problem. The solution of this system was obtained by computational fluid dynamics (CFD). To perform CFD calculations, a commercial solver FLUENT has been used, and the selective permeation through the membrane has been modeled by user-defined functions. The CFD simulation results exhibited the flow distribution in the reactor by inserting a membrane protection tube, in addition to the temperature and concentration distribution in the axial and radial directions in the reactor, as reported in the membrane reactor numerical simulation. On the basis of the simulation results, effects of the flow distribution, concentration polarization, and mass transfer in the packed bed have been evaluated to design a membrane reactor system. 

Mathematical models of tubular chemical reactor behaviour can be used to predict the dynamic variations in concentration, temperature and flow rate at various locations within the reactor. A complete tubular reactor model would however be extremely complex, involving variations in both radial and axial positions, as well as perhaps spatial variations within individual catalyst pellets. Models of such complexity are beyond the scope of this text, and variations only with respect to both time and axial position are treated here. Allowance for axial dispersion is however included, owing to its very large influence on reactor performance, and the fact that the modelling procedure using digital simulation is relatively straightforward. 

This gas-liquid modeling approach has been used performing dynamic simulations of two-phase bubble column reactor flows operating at low gas holdups [201, 202, 19]. A major limitation revealed in these simulations is that there is some difficulties in conserving mass for the dispersed phases, so this concept is not recommended for the purpose of simulating chemically reactive flows. 

It is further noticed that in the sense of preserving monotonicity of the solution a difference between the limiting processes of TVD and FCT schemes lies in that the TVD schemes usually are of one step, while the FCT is of two steps. FCT schemes are widely used for simulating time-dependent flows, but are less suited for steady-state calculations and therefore have had little influence in computational fluid dynamics applied to chemical reactor engineering. The TVD schemes, on the other hand, can be easily implemented into standard CFD codes by means of the deferred correction approach using flux limiters without enlarging the stencil. 

The job is not finished with steady state controllability analysis. Only dynamic simulation enables a reliable assessment of the control problem. The solution of the dynamic modelling depends on the dynamics of units involved in the control problem. Detailed models are necessary for the key units. The simplification of the steady-state plant simulation model to a tractable dynamic model, but still able to represent the relevant dynamics of the actual problem, is a practical alternative. Steady-state models can be used for fast units, as heat exchangers, or even chemical reactors with low inventory. 

A case of practical interest is a chemical reactor coupled with a separation section, from which the unconverted reactants are recovered and recycled. Let s consider the simplest situation, an irreversible reaction A—>B taking place in a CSTR coupled to a distillation column (Fig. 13.5). Here we present results obtained by steady state and dynamic simulation with ASPEN Plus and ASPEN Dynamics. The reader is encouraged to reproduce this example with his/her favourite simulator. The species A and B may be defined as standard components with adapted properties. In this case, we may take as basis the properties of n-propanol and iso-propanol, and assume ideal phase equilibrium. The relative volatility B/A increases at lower pressures, being approximately 1.8 at 0.5 atm. We consider the following data nominal throughput of 100 kmol/hr of pure A, reactor volume 2620 1, and reaction constant =10 s". For stand-alone operation the reaction time and conversion are r= 0.106 hr and = 0.36. 

In recent times, considerable progress has been made in describing complicated flow patterns in vessels, with flow simulations. These are combined with measurements of local flow velocities. This leads to much more accurate predictions of the effects of transport phenomena. It is expected that in the future computational fluid dynamics" will be applied generally to chemical reactors (Trambouze, 1993). Until now, practical applications for reactors are still quite limited. 

This review, which certainly cannot claim to have covered the whole spectrum of problems, shows that considerable progress has been made in the last decade in kinetic data analysis and parameter estimation. Specially designed reactors, dynamic analysis techniques, as well as computer aided experimentation are some of the highlights. But reaction analysis and reactor simulation for heterogeneously catalysed reactions are still a challenging task that needs the intelligent action of the chemical reaction engineer. 

Plantwide Dynamic Simulators in Chemical Processing and Control, William L. Luyben Chemicial Reactor Design, Peter Harriott Catalysis of Organic Reactions, edited by Dennis G. Morrell... 

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