Application of Uncertainty and Sensitivity Analysis to a Kinetic Model for Enzymatic Biodiesel Production

Jason Anthony Price, Mathias Nordblad, John Woodley, Jakob Kjøbsted Huusom

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Abstract

This paper demonstrates the added benefits of using uncertainty and sensitivity analysis in the kinetics of enzymatic biodiesel production. For this study, a kinetic model by Fedosov and co-workers is used. For the uncertainty analysis the Monte Carlo procedure was used to statistically quantify the variability in the model outputs due to uncertainties in the parameter estimates; showing the model is most reliable in the start (first 5 hours) of the reaction. To understand which input parameters are responsible for the output uncertainty, two global sensitivity methods (Standardized Regression Coefficients, and Morris screening) were used. The results from both sensitivity analyses identified that only 10 of the 32 parameters are influential to the model outputs. The model was then simplified by removing the non-influential parameters. A parity plot of the simplified model vs. the full model gave a R2 value of over 0.95 for all the model outputs.
Original languageEnglish
Title of host publicationProceedings of 12th IFAC Symposium on Computer Applications in Biotechnology
PublisherElsevier
Publication date2014
Pages161-168
ISBN (Print)9781632662910
DOIs
Publication statusPublished - 2014
EventCAB 2013 : 12th IFAC Symposium on Computer Applications in Biotechnology - Mumbai, India
Duration: 16 Dec 201318 Dec 2013

Conference

ConferenceCAB 2013
CountryIndia
CityMumbai
Period16/12/201318/12/2013

Keywords

  • Modelling
  • Sensitivity Analysis
  • Monte-Carlo Simulations
  • Enzymatic Biodiesel

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