Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/33731
Title: Mechanistic modelling of separating dispersions in pipes using model-based design of experiments techniques
Authors: Evripidou, Nikola 
Galvanin, Federico 
Angeli, Panagiota 
Major Field of Science: Engineering and Technology
Field Category: Chemical Engineering
Keywords: Mechanistic modelling;Liquid-liquid separation;Parametric sensitivity analysis;Model-based design of experiments
Issue Date: Feb-2024
Source: Chemical Engineering Science, 2024, vol. 284
Volume: 284
Journal: Chemical Engineering Science 
Abstract: This work presents a parametric study on a mechanistic model for separating liquid–liquid dispersions in pipes. The model considers drop-settling, drop-interface coalescence and drop-drop coalescence, predicting the evolution of four characteristic layers during separation. Parameter estimation, parametric sensitivity analysis (PSA), and model-based design of experiments (MBDoE) techniques are employed to acquire precise parameter estimates and propose optimal experimental conditions, thereby enhancing the accuracy of existing models. Experimental data from literature using oil-in-water dispersions are used for parameter estimation. PSA reveals regions of high sensitivity of the model outputs to uncertain parameters, which are corresponding to favourable sampling locations. Manipulating the mixture velocity, the dispersed phase fraction, and the layer heights at the inlet influences these sensitive regions. Clustered measurements around highly sensitive regions in the pipe enhance the information content they provide. MBDoE demonstrates that either of the A-, D-, or E-optimal experimental design criteria improves the expected parameter precision.
URI: https://hdl.handle.net/20.500.14279/33731
ISSN: 00092509
DOI: 10.1016/j.ces.2023.119504
Type: Article
Affiliation : University College London 
Funding: Chevron Corporation University College London UK Engineering and Physical Sciences Research Council (EPSRC) Programme Grant PREMIERE (EP/T000414/1)
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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