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EFFICIENT EARLY STAGE CHEMICAL PROCESS DESIGN

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2018, Master of Science, Miami University, Chemical, Paper and Biomedical Engineering.
Design of any chemical processes on a large scale such as distillation, extraction requires tremendous amount of data. Such data can be obtained either through literature review (if available), experiments, molecular, property prediction tools. Conducting experiments on a large scale for multicomponent mixtures at different variables can be quite expensive and time consuming, while molecular simulation is still computationally demanding even though it can provide accurate molecular level details. Property prediction tools are simple analytical model based on empirical relations or thermodynamics relations that can provide accurate estimates, which is why they are used throughout the industry. However, most commons property predictions tools provide no qualitative insight on a molecular level that could be extremely useful for process intensifications. Thus, this research is focused on a analytical model called MOSCED that has shown tremendous capability in providing accurate property predictions and qualitative molecular insights that could guide chemical process design during early stage.
Andrew Paluch (Committee Chair)
Catherine Almquist (Committee Member)
Shashi Lalvani (Committee Member)
84 p.

Recommended Citations

Citations

  • Dhakal, P. (2018). EFFICIENT EARLY STAGE CHEMICAL PROCESS DESIGN [Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1533323971644795

    APA Style (7th edition)

  • Dhakal, Pratik. EFFICIENT EARLY STAGE CHEMICAL PROCESS DESIGN . 2018. Miami University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=miami1533323971644795.

    MLA Style (8th edition)

  • Dhakal, Pratik. "EFFICIENT EARLY STAGE CHEMICAL PROCESS DESIGN ." Master's thesis, Miami University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=miami1533323971644795

    Chicago Manual of Style (17th edition)