Optimisation of flow chemistry: tools and algorithms

González Niño, Carlos (2020) Optimisation of flow chemistry: tools and algorithms. PhD thesis, University of Leeds.



Supervisors: Kapur, Nikil and Blacker, John and Bourne, Richard and Thompson, Harvey
Keywords: Flow chemistry, cross-validation, Machine Learning, Continuous oscillatory baffled reactor, surrogate modelling, fReactor, continuous stirred tank reactor, optimisation, residence time distribution, multi-objective optimisation
Awarding institution: University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Mechanical Engineering (Leeds)
Identification Number/EthosID: uk.bl.ethos.806854
Depositing User: Carlos González Niño
Date Deposited: 11 Jun 2020 15:48
Last Modified: 11 Jul 2020 09:53


Final eThesis - complete (pdf)

Filename: GonzalezNino_C_MechEng_PhD_2020.pdf

Description: Thesis - PDF format

Licence: Creative Commons Licence
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License



You do not need to contact us to get a copy of this thesis. Please use the 'Download' link(s) above to get a copy.
You can contact us about this thesis. If you need to make a general enquiry, please see the Contact us page.