Monte Carlo ModuleComputational modelling in chemical engineering is becoming more and more a field in its own right, due mainly to the rapidly increasing power of computers but also because of the progress being made in developing numerical algorithms necessary to solve sophisticated models. Moreover, industry is highly interested because of the significantly lower costs of computer simulations compared to experimental studies. Important ingredients for the field include accurate physical and chemical models in mathematical form, numerical values for the parameters that occur in these models either taken from carefully selected experiments or from first-principles calculations, fast computers, efficient and powerful numerical methods and, most importantly, competent engineers who are aware of the limitations of the models, parameters and numerical methods.
Needless to say, the whole field of computational engineering is far too rich to be taught in a single course. At the Department of Chemical Engineering at the University of Cambridge we focus on teaching stochastic (or Monte Carlo) methods to students of chemical engineering. Monte Carlo methods have been shown to be highly efficient in many applications and can be found in various areas in the process and chemical industry, such as polymer synthesis, crystallisation, liquid-liquid extraction, etc. They are also useful when it comes to simulating turbulent flames, their emissions and aerosol transport in the atmosphere.
|Screen Shot of web module|
To support the lectures in the course on "Stochastic Modelling in Chemical Engineering", Markus Kraft and Sebastian Mosbach have developed a web module. The central aim of the web module is to enable students without knowledge of a programming language to gain hands-on experience testing a Monte Carlo algorithm. For this purpose, two sets of reactions in a batch reactor are studied, one of which is the Belousov-Zhabotinsky reaction system, which shows oscillating behaviour.