A study of the multi-environment conditional probability-density model for turbulent non-premixed combustion

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Smith, Sean
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Rodney O. Fox
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Chemical and Biological Engineering

The function of the Department of Chemical and Biological Engineering has been to prepare students for the study and application of chemistry in industry. This focus has included preparation for employment in various industries as well as the development, design, and operation of equipment and processes within industry.Through the CBE Department, Iowa State University is nationally recognized for its initiatives in bioinformatics, biomaterials, bioproducts, metabolic/tissue engineering, multiphase computational fluid dynamics, advanced polymeric materials and nanostructured materials.

The Department of Chemical Engineering was founded in 1913 under the Department of Physics and Illuminating Engineering. From 1915 to 1931 it was jointly administered by the Divisions of Industrial Science and Engineering, and from 1931 onward it has been under the Division/College of Engineering. In 1928 it merged with Mining Engineering, and from 1973–1979 it merged with Nuclear Engineering. It became Chemical and Biological Engineering in 2005.

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1913 - present

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  • Department of Chemical Engineering (1913–1928)
  • Department of Chemical and Mining Engineering (1928–1957)
  • Department of Chemical Engineering (1957–1973, 1979–2005)
    • Department of Chemical and Biological Engineering (2005–present)

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The multi-environment conditional probability density function (MECPDF) model is a mathematical description of the turbulent mixing of two streams of chemical reactants along with the complex sequence of chemical reactions that follow. The processes of mixing and chemical reactions can be intricately connected and complex, particularly when the rates of both processes are nearly equal. Furthermore mixing has the potential to completely determine the outcome of the chemical reactions. Mixing will have the strongest effect on chemical reactions when there are multiple reactions with competing pathways that proceed at different rates. As multiple reactions with competing pathways progress, with interaction of mixing, the resulting dynamics are very non-linear and as a result have eluded accurate mathematical description, except in the extreme case of using the world's largest computers to simulate all of the length scales of a turbulent flow. It is proposed that the MECPDF model provides a sufficiently accurate description of these dynamics with a model that is computationally practical for engineering work. The primary objectives of this thesis will be to describe the MECPDF model and to demonstrate its use and effectiveness.

Tue Jan 01 00:00:00 UTC 2008