This dissertation includes two process modeling studies -- (1) predictive modeling of large-scale integrated refinery reaction and fractionation systems from plant data – hydrocracking process; and (2) integrated process modeling and product design of biodiesel manufacturing. \r\n1. Predictive Modeling of Large-Scale Integrated Refinery Reaction and Fractionation Systems from Plant Data -- Hydrocracking Processes: This work represents a workflow to develop, validate and apply a predictive model for rating and optimization of large-scale integrated refinery reaction and fractionation systems from plant data. We demonstrate the workflow with two commercial processes -- medium-pressure hydrocracking unit with a feed capacity of 1 million ton per year and high-pressure hydrocracking unit with a feed capacity of 2 million ton per year in the Asia Pacific. This work represents the detailed procedure for data acquisition to ensure accurate mass balances, and for implementing the workflow using Excel spreadsheets and a commercial software tool, Aspen HYSYS from Aspen Technology, Inc. The workflow includes special tools to facilitate an accurate transition from lumped kinetic components used in reactor modeling to the boiling point based pseudo-components required in the rigorous tray-by-tray distillation simulation. Two to three months of plant data are used to validate models' predictability. The resulting models accurately predict unit performance, product yields, and fuel properties from the corresponding operating conditions.\r\n2. Integrated Process Modeling and Product Design of Biodiesel Manufacturing: This work represents first a comprehensive review of published literature pertaining to developing an integrated process modeling and product design of biodiesel manufacturing, and identifies those deficient areas for further development. It also represents new modeling tools and a methodology for the integrated process modeling and product design of an entire biodiesel manufacturing train. We demonstrate the methodology by simulating an integrated process to predict reactor and \r\nseparator performance, stream conditions, and product qualities with different feedstocks. The results show that the methodology is effective not only for the rating and optimization of an existing biodiesel manufacturing, and but also for the design of a new process to produce biodiesel with specified fuel properties. / Ph. D.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/58043 |
| Date | 12 October 2011 |
| Creators | Chang, Ai-Fu |
| Contributors | Chemical Engineering, Liu, Y. A., Achenie, Luke E. K., Davis, Richey M., Durrill, Preston L. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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