Data Quality and Assessment, Validation Methods and Error Propagation through the Simulation Software: Report from the Round-Table Discussion at the 10th World Congress of Chemical Engineering in Barcelona (October 1-5, 2017)

Published

September 7, 2018

Author(s)

Paul M. Mathias, Ana Soto, Ljudmila Fele-Zilnik, Jean-Charles de Hemptinne, Ala Bazyleva, Jens Abildskov

Abstract

The issues of data quality and propagation of data uncertainties into process design and plant uncertainties are of great current interest, and hence two Working Parties of the European Federation of Chemical Engineers (EFCE) organized a Round Table Discussion on the topic as part of the World Congress of Chemical Engineering (WCCE10) in Barcelona, in October 2017. The discussion was guided by industrial and academic experts, with the audience as a key part of the discussion, trying to find some answers on the three questions, namely data acquisition and evaluation of experimental uncertainties, tools for data reconciliation to improve their quality, and impact of data uncertainties on the process at the end. Several concrete stories are presented that demonstrate the importance of considering data quality and all possible contributions to the uncertainty of process design. Difficulties in association with the data quality at different levels are discussed, namely at the level of the experimentalists, model developers, and vendors of the simulation software, as well as from the perspective of the process engineers. The importance of knowing all uncertainties that contribute to the uncertainty of a measured value was pointed out. These contributions include uncertainties of the equipment, procedure, sensors, purity of the materials, and of the variables. Not only experimental data, but also process simulators have uncertainties. Once a model is selected, its parameters must be determined, and their uncertainties estimated. However, which property/data range has the most effect on the process should not be overlooked. Vendors of the simulation tools expect their software to be applied in a responsible way by the users, either being a researcher or a process engineer. The prerequisite for simulation packages to be used efficiently is a certain level of knowledge, the foundation of which is the fundamentals of thermodynamics. Paths for improvements were proposed.

Citation

Chemical Engineering Research & Design

Volume

137

Pub Type

Journals

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DOI Link

Keywords

data quality and assessment, uncertainties, data reconciliation, error propagation, process simulation

Citation

Mathias, P. , Soto, A. , Fele-Zilnik, L. , de Hemptinne, J. , Bazyleva, A. and Abildskov, J. (2018), Data Quality and Assessment, Validation Methods and Error Propagation through the Simulation Software: Report from the Round-Table Discussion at the 10th World Congress of Chemical Engineering in Barcelona (October 1-5, 2017), Chemical Engineering Research & Design, [online], https://doi.org/10.1016/j.cherd.2018.08.010 (Accessed April 25, 2024)