A Step by Step Approach to the Modeling of Chemical Engineering Processes: Using Excel for Simulation (original) (raw)
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Chemical Process System Engineering
2016
Use of computational fluid dynamics to model chemical process system has received much attention in recent years. However, even with state-of-the-art computing, it is still difficult to perform simulations with many physical factors taken into accounts. Hence, translation of such models into computationally easy surrogate models is necessary for successful applications of such high fidelity models to process design optimization, scale-up and model predictive control. In this work, the methodology, statistical background and past applications to chemical processes of meta-model development were reviewed. The objective is to help interested researchers be familiarized with the work that has been carried out and problems that remain to be investigated.
Modelling and simulation in chemical engineering: Tools for process innovation
Computers & Chemical Engineering, 2005
The Chemical Engineering Science movement has served well in solving problems from micro to macro scales. Ultimately, as Professor R. Sargent pointed out, it would be better if translated in "Scientific Engineering". Examples of innovation as a combination of science (concept), technology and process/product will be presented. The first example is perfusion chromatography based on the concept of "diffusivity augmented by convection" and on the technology of fabrication of large-pore packings. The second example, Simulated Moving Bed (SMB), is based on a concept developed to overcome the difficulties in implementing True Moving Bed processes. Technological contributions come from adsorbent materials and rotary valve to simulate the solid movement. SMB is now a key technology for chiral separations. Modelling/Simulation tools provide sound basis for design/operation by using the concept of "separation volume". The third example is from the area of multifunctional reactors. The SMB technology is extended to the simultaneous reaction/separation.
Mathematical Model (Eykhoff, 1974) "a representation of the essential aspects of an existing system (or a system to be constructed) which represents knowledge of that system in a usable form" Everything should be made as simple as possible, but no simpler. General Modeling Principles • The model equations are at best an approximation to the real process. • Adage: "All models are wrong, but some are useful." • Modeling inherently involves a compromise between model accuracy and complexity on one hand, and the cost and effort required to develop the model, on the other hand. • Process modeling is both an art and a science. Creativity is required to make simplifying assumptions that result in an appropriate model. • Dynamic models of chemical processes consist of ordinary differential equations (ODE) and/or partial differential equations (PDE), plus related algebraic equations. 1. State the modeling objectives and the end use of the model. They determine the required levels of model detail and model accuracy. 2. Draw a schematic diagram of the process and label all process variables. 3. List all of the assumptions that are involved in developing the model. Try for parsimony; the model should be no more complicated than necessary to meet the modeling objectives. 4. Determine whether spatial variations of process variables are important. If so, a partial differential equation model will be required. 5. Write appropriate conservation equations (mass, component, energy, and so forth). 6. Introduce equilibrium relations and other algebraic equations (from thermodynamics, transport phenomena, chemical kinetics, equipment geometry, etc.). 7. Perform a degrees of freedom analysis (Section 2.3) to ensure that the model equations can be solved. 8. Simplify the model. It is often possible to arrange the equations so that the dependent variables (outputs) appear on the left side and the independent variables (inputs) appear on the right side. This model form is convenient for computer simulation and subsequent analysis. 9. Classify inputs as disturbance variables or as manipulated variables. Modeling Approaches • Physical/chemical (fundamental, global)
Chemical Product and Process Modeling, 2000
The papers in this issue of Chemical Product and Process Modelling are substantially those that arose from special sessions on ``process simulation and control" (organised by Brent R. Young) and ``mathematical modeling" (organised by Mark I. Nelson) at the 34th Australasian Chemical Engineering Conference (held between 17-20th September 2006, in Auckland, New Zealand). The papers in this special issue are available at: http://www.bepress.com/cppm/vol2/iss2\. The papers featured in this issue have been revised and extended from CHEMECA and re-reviewed before publication here.All the papers in this issue use mathematics. However, this special issue only features a small number of the presentations at CHEMECA that use mathematics. Mathematics finds many practical applications within chemical engineering and consequently presentations involving mathematics were featured in many special sessions throughout CHEMECA. Some of these presentations will appear in special issues elsewh...
Background: Process simulation has been extensively used in recent years to design, evaluate or optimize processes, systems and specific operations of the chemical industry and its related disciplines. Currently , CHEMCAD® constitute one of the most used process simulators because of the great number of chemical and petrochemical processes that can be simulated. Method: The simulation of the production process of styrene via catalytic dehydrogenation of ethyl-ben-zene is carried out by using the process simulator CHEMCAD® version 5.2.0, in order to determine the composition and mass flow-rate of each process involved in the production, as well as the main operating parameters of the equipment used. Two sensitivity studies were carried out: firstly, the influence of the temperature and pressure values applied at the LLV Separator on the amounts of ethyl-benzene and styrene to be obtained by the intermediate and top