Doctoral Dissertations

Keywords and Phrases

computational fluid dynamics; mathematical modelling; model validation


"Mathematical modelling of multiphase flow systems has been a major and persistent challenge over the last decades. Vast attempts to obtain predictive models can be found reported in literature, where major advances can be recognized in recent years, paired to enhancements in computer science and engineering. Notwithstanding, universally valid models with a mechanistic development are far from being achieved. The current status of modelling any multiphase flow system relies on the model order reduction of purely theoretical models. Such reductions and simplifications become the source of deviations in the predictions of the experimentally measured parameters and will constrain the applicability of the models. Hence, when modelling any multiphase flow system, there is a primal need of pairing mathematical modeling and experimental studies, in order to validate the models’ predictive quality, quantifying the deviations and providing a standpoint of the applicability and limitations of the models. In this sense, a successful multiphase flow system model should provide highly accurate local predictions, have a reduced number of possible sources of deviations (i.e., reducing the number of coupled sub-models, nor relying on vast simplifications), and have a high flexibility for being adapted or optimized to different conditions. In this work, it is sought to develop highly predictive, simplified and locally validated mathematical models by applying Computational Fluid Dynamics techniques, paired with other modelling and experimental techniques. Six cases of study are developed: i) Trickle Bed Reactors (TBR), ii) Packed Bed Reactors (PBR), iii) Fluidized Bed Reactors (FBR), iv) Spouted Bed Reactors (SBR), v) Heat transfer systems enhanced by nanofluids, vi) Bubble Column Reactors (BCR)"--Abstract, p. iv


Al-Dahhan, Muthanna H.

Committee Member(s)

Smith, Joseph D.
Forciniti, Daniel
Hosder, Serhat
Schlegel, Joshua P.


Chemical and Biochemical Engineering

Degree Name

Ph. D. in Chemical Engineering


Missouri University of Science and Technology

Publication Date

Fall 2022


xxii, 425 pages

Note about bibliography

Includes_bibliographical_references_(pages 409-424)


© 2022 Jose Sebastian Uribe Lopez, All Rights Reserved

Document Type

Dissertation - Open Access

File Type




Thesis Number

T 12207