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Final design: Extrapolation from scale-up rules, flow modeling, safety, risk and runaway analysis, dynamic modeling.Scale-up simulations: Pilot-scale design, scale-up parameters and design space exploration.Preliminary configuration: Analysis of vessel configuration, internals, baffles and coils.Engineering with idealized models: Analysis of plug flow or continuous stirred tank reactors (CSTR), volume sizing, overall heat transfer.Reactor selection: Analysis of flow regime, heat release, residence time distribution (RTD), liquid hourly space velocity (LHSV), as well as gas hourly space velocity (GHSV).Lab scale: Analysis of kinetics, catalysis, thermodynamics, material properties and toxicity.Conceptualization: Analysis of new chemistry and the business case.In reactor design, the process of taking the discovery of a new chemical with novel properties from lab to commercial production involves many steps ( Fig.
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Most crucial are the underlying transport processes-fluid flow, heat transfer, mass transfer and reactions-which is where CFD simulation can add substantial value.
#CHEMICAL PROCESS SIMULATION FREE SERIES#
Reactor design includes several key facets: Phase, or state of the reactants and products (solid, gas, liquid or aqueous/dissolved in water) reaction type (single, multiple, parallel series or polymerization) whether a catalyst is involved flow distribution and mixing transport of the species and mode of operation (i.e., batch, semi-batch or continuous). Chemical kinetics-the study of rates of chemical processes-is founded on the experimental study of how different conditions influence the speed of a chemical reaction, its mechanism and transition states, and the development of mathematical models of the reaction’s characteristics. Essential aspects of chemical reactor design.įrom the standpoint of computational fluid dynamics (CFD), reaction engineering is the application of transport phenomenon and chemical kinetics knowledge to industrial systems.
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Instead of thinking about it… we did it.” “Many are convinced that the life sciences industries will evolve towards more digitally designed processes associating experiments, user’s know-how and mechanistic modeling.