Modeling, Simulation, and Design

Modeling, Simulation, and Design of Chemical and Biological Systems 

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In this case study we will model, simulate and design an industrial-scale BioDeNOx process. Rigorous rate-based models of the absorption and reaction units will be presented, taking into account the kinetics of chemical and biochemical reactions, as well as the rate of gas-liquid mass transfer. After transformation in dimensionless form, the mathematical model will be solved numerically. Because of the steep profiles around the gas/liquid interface and of the relatively large number of chemical species involved, the numerical solution is computationally expensive. For this reason we will derive a simplified model, which will be used to size the units. Critical design and operating parameters will be identified... 

The Center for Nanophase Materials Sciences at Oak Ridge National Laboratory (http //www.cnms.ornl.gov/) will concentrate on synthesis, characterization, theory/ modeling/simulation, and design of nanoscale materials. The NSF also funds several related facilities, such as the Cornell Uni-... 

S. Haussener, C. Xiang, J.M. Spurgeon, S. Ardo, N.S. Lewis, A.Z. Weber, Modeling, simulation, and design criteria for photoelectrochemical water splitting systems. Energy Environ. Sci. 5, 9922-9935 (2012)... 

Maroulis ZB, Saravacos GD, 2002. Modeling, simulation and design of drying processes. Keynote Lecture at the 13th International Drying Symposium, IDS 2002, Beijing, China. 

OntoCAPE specifies a conceptualisation of process modeling, simulation, and design. A skeleton ontology has been developed in which the major categories of COGents concepts... 

In many respects, the solutions to equations 12.7.38 and 12.7.47 do not provide sufficient additional information to warrant their use in design calculations. It has been clearly demonstrated that for the fluid velocities used in industrial practice, the influence of axial dispersion of both heat and mass on the conversion achieved is negligible provided that the packing depth is in excess of 100 pellet diameters (109). Such shallow beds are only employed as the first stage of multibed adiabatic reactors. There is some question as to whether or not such short beds can be adequately described by an effective transport model. Thus for most preliminary design calculations, the simplified one-dimensional model discussed earlier is preferred. The discrepancies between model simulations and actual reactor behavior are not resolved by the inclusion of longitudinal dispersion terms. Their effects are small compared to the influence of radial gradients in temperature and composition. Consequently, for more accurate simulations, we employ a two-dimensional model (Section 12.7.2.2). 

But how do we decide how to control this plant We will spend most of our time in this book exploring this important design and operating problem. AH our studies of mathematical modeling, simulation, and control theory are aimed at undeistanding the dynamics of processes and control systems so that we can develop and design better, more easily controlled plants that operate more efficiently and more safely. 

Mathematical models derived from mass-conservation equations under unsteady-state conditions allow the calculation of the extracted mass at different bed locations, as a function of time. Semi-batch operation for the high-pressure gas is usually employed, so a fixed bed of solids is bathed with a flow of fluid. Mass-transfer models allow one to predict the effects of the following variables fluid velocity, pressure, temperature, gravity, particle size, degree of crushing, and bed-length. Therefore, they are extremely useful in simulation and design. 

This section introduces some of the basic concepts of system theory in relation to modeling. Our presentation is rather brief since our aim is to integrate known models for chemical/biological processes with numerical techniques to solve these models for simulation and design purposes, rather than to give a broad introduction to either system theory or modeling itself. For references on modeling, see the Resources appendix. 

We have introduced many practical software based numerical procedures to solve physico-chemical models for simulation and design purposes. Therefore, we hope that our readers now feel comfortable and ready to handle more complex industrial problems from the modeling stage through the numerical solution and model validation stages on her/his own. 

In this paper, the advective control model for groundwater plume capture design is described, algorithmic requirements to accommodate unconfined aquifer simulation are presented, and two- and three- dimensional example problems are used to demonstrate the optimization model capabilities and design implications. The model is applicable for designing long-term plume containment systems and as such assumes steady-state flow and time-invariant pumping. 

Nestorov, I. A. Sensitivity analysis of pharmacokinetic and pharmacodynamic models in clinical trial simulation and design. In Kimko, H. C., Duffull, S. B eds. Simulation for designing clinical trials. A pharmacokinetic-pharmacodynamic modeling perspective. (Drugs and the pharmaceutical sciences, volume 127) Marcel Dekker, New York, 2003. 

In the steady state simulation and design, the state variables are the flowrates and the pressure drops or terminal pressures for each branch of the net. Each of the branches between two nodepoints are described by a mathematical model of the hydrodynamics relating the pressure drop to the fluid flow between the nodes. The material balance sums up the flow into and out of a node no is... 

Notice that in the synthesized netlist, the first input of the AND2 module instance Sl l is open. During the simulation of module AOI22 NetList, the open input takes the value z whereas the unassigned value of C in module AOI22u takes on a default value of x. The fact that different values are used for C during the design model simulation and the synthesized... 

At present there is no systematic work on simulation and design of packed bed nonadiabatic reactors of industrial size where a deactivation process occurs. The purpose of this work is to analyze the operation of a nonadiabatic deactivating catalyst bed and to develop simple techniques for simulation. Based on hydrogenation of benzene,full-scale reactor behavior is calcu lated for a number of different operational conditions. Radial transport processes are incorporated in the model, and it is shown that the two-dimensional model is necessary in some cases. 

Simulation, Modeling, and Design Feasibility Because reaction and separation phenomena are closely coupled in a reactive distillation process, simulation and design are significantly more complex than those of sequential reaction and separation processes. In spite of the complexity, however, most commercial computer process modeling packages offer reliable and flexible routines for simulating steady-state reactive distillation columns, with either equilibrium or kinetically controlled reaction models... 

The simulation flow diagram and optimization sequences of the process units for different products were examined. A relational data bases which including input component data base and process parameters data base as well as simulation results data base were developed. In this paper knowledge based process simulation and design of the starch plant were developed. The relational data bases system was linking with simulation models and simulation interface. The obtained results in this paper can be applied in the others domain. 

The PSA process steps again followed those of the Poly-bed process except that the order of steps (c) and (d) were interchanged. The solid line represents the results of the nonisothermal model simulations and the points are experimental data from a bench-scale unit. Both figures show that the model simulations are in fair to good agreement with experimental data but the accuracy demanded by industrial designs may still be lacking. 

Two different approaches have evolved for the simulation and design of multicomponent distillation columns. The conventional approach is through the use of an equilibrium stage model together with methods for estimating the tray efficiency. This approach is discussed in Chapter 13. An alternative approach based on direct use of matrix models of multicomponent mass transfer is developed in Chapter 14. This nonequilibrium stage model is also applicable, with only minor modification, to gas absorption and liquid-liquid extraction and to operations in trayed or packed columns. 

In this section we present a number of examples designed to demonstrate the use of the models presented in the preceding section as a condenser simulation and design tool. Four example problems, taken from the literature on multicomponent condensation, are used as a basis for illustrating the features of the model and calculation procedure. As was the case in Chapter 14, it is not practical to present illustrative examples of the condensation model that are as detailed as the examples in prior sections. Only a summary of the problem specifications and a selection of results is provided here. The discussion that follows is based on a paper by Taylor et al. (1986). 

Krishnamurthy, R. and Taylor, R., Absorber Simulation and Design Using a Nonequilibrium Stage Model, Can. J. Chem. Eng., 64, 96-105 (1986). 

The requirements of a process design or research engineer who wishes to use rigorous multicomponent mass transfer models for the simulation and design of process equipment. 

Chapter 12 presents models of mass transfer on distillation trays. This material is used to develop procedures for the estimation of point and tray efficiencies in multicomponent distillation in Chapter 13. Chapter 14 uses the material of Chapter 12 in quite a different way in an alternative approach to the simulation and design of distillation and absorption columns that has been termed the nonequilibrium stage model. This model is applicable to liquid-liquid extraction with very little modification. Chapter 15 considers the design of mixed vapor condensers. 

A more detailed description of the simulation and design tasks can be found in Subsect. 5.4.2 (subproject A3). For the possibilities of experience-based support for extruder design, refer also to the FZExplorer tool in Subsect. 3.1.5. Here, we will concentrate on structuring the domain model for annotation of the videos resulting from simulation. 

Both Bayer and InfraServ Knapsack carry out similar projects in their design departments. A project can include conceptual process design as well as basic and detail engineering. For the modeling, simulation, and optimization of chemical processes, several tools like CHEMCAD [592] or Aspen Plus [516] are used. In addition, laboratory experiments may be required to determine reaction parameters or other physicochemical data. A project can also include the planning, construction, operation, and analysis of a pilot plant. Depending on the customer s demands, not all of these project phases are executed. 

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