UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

A new digital twin for enzymatic hydrolysis processes applied to model-based process design

Appl, Christian Bernhard; (2023) A new digital twin for enzymatic hydrolysis processes applied to model-based process design. Doctoral thesis (Ph.D), UCL (University College London). Green open access

[thumbnail of 2023_PhD_Thesis_Report_Christian_Appl.pdf]
Preview
Text
2023_PhD_Thesis_Report_Christian_Appl.pdf - Accepted Version

Download (3MB) | Preview

Abstract

Renewable raw materials containing starch and proteins are split into their main components using enzymatic hydrolysis processes. However, even small changes in temperature, pH or pressure may strongly affect the enzyme activity and stability. At the same time, natural fluctuations may lead to changes in the substrate composition. These mutually influencing factors place enormous demands on the design and control of enzymatic hydrolysis processes. Individual enzymatic hydrolysis processes have already been modelled, but models for the hydrolysis of potato starch by α-amylase and glucoamylase and the proteolysis of organic sunflower seed meal by endopeptidase and exopeptidase in a stirred tank reactor, or even digital twins, are unavailable. Therefore, a new mechanistic model for the combined starch hydrolysis and proteolysis was developed. Sigmoidal and double sigmoidal functions were implemented to map the temperature and pH-dependent enzyme activity. The model can simulate the enzymatic hydrolysis processes with an agreement of more than 90%. The new model was integrated into an existing digital twin of a 20 L stirred tank reactor to create a new stand-alone digital twin for enzymatic hydrolysis processes. Applying the new digital twin core model, a model-based process design strategy based on the open-loop-feedback-optimal and model-based design of experiment strategies was established. By applying the new strategy, the amount of α-amylase and glucoamylase required for starch hydrolysis could be reduced by more than 30%. In addition, the required amount of endopeptidase and exopeptidase for proteolysis could be reduced by more than 50%. Compared to the classic design of experiments approach, the number of experiments required for process optimisation could be reduced by more than 50%. The strategies resulting from this work can soon be used for the optimisation of the industrial organic nutrient media production from regenerative substrates for the cultivation of microorganisms such as Saccharomyces cerevisiae.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: A new digital twin for enzymatic hydrolysis processes applied to model-based process design
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2023. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
Keywords: Enzyme Technology, Digital Twin Technology, Modelling, Model-Based Process Design
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Biochemical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10175809
Downloads since deposit
146Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item