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

Philippe M Heynderickx; Raf Roelant

doi:10.1016/j.dib.2018.05.073

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

Data Brief. 2018 May 18:19:601-610. doi: 10.1016/j.dib.2018.05.073. eCollection 2018 Aug.

Authors

Philippe M Heynderickx^{1

2}, Raf Roelant³

Affiliations

¹ Center for Environmental and Energy Research (CEER) - Engineering of Materials via Catalysis and Characterization, Ghent University Global Campus, 119 Songdomunhwa-Ro, Yeonsu-Gu, Incheon 406-840, South Korea.
² Department of Green Chemistry and Technology (BW24), Faculty of Bioscience Engineering, Ghent University, 753 Coupure Links, Ghent B-9000, Belgium.
³ Process Design Center, Catharinastraat 21F, 4811 XD Breda, The Netherlands.

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.