Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets

Abstract

The data and complementary information presented here are related to the research in the article of “https://doi.org/10.1016/j.cej.2018.01.027; Chem. Eng. J., 342, 41–51 (2018)”, where sets of in-silico data are constructed to show a novel method for parameter estimation in biodiesel production from triglycerides (Heynderickx et al., 2018) [1]. In this paper, the method for the used error superposition is explained and in order to ensure a ready reproduction by the reader, this work presents the basic steps for superposition of a normally distributed error via a simple Excel® datasheet file.

Activity Coefficients for Liquid Organic Reactions: Towards a Better Understanding of True Kinetics with the Synthesis of Jasmin Aldehyde as Showcase

“…Kinetic parameters are given in Table 6, containing ballpark values for the kinetic coefficients, based on existing literature for aldol condensation reactions [31,32,33,34]. Superposition of artificial Gaussian error is implemented at 10%, according to an earlier described procedure [40,41]. Error is implemented on calculated data every hour, giving 8 data points per response.…”