Use this URL to cite or link to this record in EThOS:
Title: A generalised LES series approach for the modelling of premixed and non-premixed combustion
Author: Zeng, Weilin
ISNI:       0000 0004 7964 9215
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2019
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
The research in this work aims to derive and develop an innovative series combustion sub-grid model into a robust and reliable modelling technique in the context of LES for turbulent flames. This method is a mathematical approach, and capable of predicting both premixed and non-premixed combustion regimes. The model also has the correct limiting behaviour, approaching DNS as the filter size approaches Kolmogorov scales. In the first part of the research, the mathematical derivation of the series model is addressed and the simulation features are described. Relevant aspects about the numerical implementation are unfolded, and the potential error sources are identified. In the second part of the work, the applications to full scale test cases are presented: i) a series of non-premixed piloted methane jet flames (Sandia Flames D and F), ii) a premixed methane piloted Bunsen jet flame and iii) a bluff-body stabilised propane premixed flame. The investigated cases involve both premixed and non-premixed combustion regimes and display complex phenomena encountered in practical combustors (flame anchoring, recirculation zones and shear layers). Subsidiary non-reacting simulations are performed for the third case to guarantee a sufficient grid resolution for the turbulent flow field. The findings of this work demonstrate that the series model is an efficient and robust technique to predict turbulent premixed and nonpremixed combustion regimes and the combustion dynamics in the context of large eddy simulation. Due to the features of no extra parameters and correct limiting behaviours, the model can be easily incorporated into other established LES programming framework.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available