In the thesis, a multiphysics loosely-coupled tool, called U-THERM3D, is assessed as a detailed investigation tool for high-fidelity prediction of combustion and near-wall processes in a LES CHT simulation framework, allowing a deep understanding of heat transfer modes influence with an affordable computational cost. The numerical analysis is carried out on a laboratory-scale combustor representative of a Rich-Quench-Lean concept, emphasizing the effect of radiative and wall heat losses on the highly sooting flame and the improvements in the wall temperature prediction with respect to a steady calculation. In addition, a novel approach based on the application of 2D boundary sources to simulate the injection of coolant from effusion cooling holes is presented to overcome the issues related to the discretization of the effusion perforation, employing Reduced-Order Model techniques from a Machine Learning framework. For this scope, an in-house external code is combined with the CFD package within the U-THERM3D framework. The numerical tool is firstly validated on simplified geometries in RANS and SBES calculations and then applied on a non-reactive single sector planar rig representative of a real combustor geometry to test the robustness of the proposed strategy in presence of a more complex flow field. Nevertheless, several improvable aspects are highlighted, pointing the way for further enhancements.
Development of advanced numerical tools for the prediction of wall temperature and heat fluxes for aeroengine combustors / Simone Paccati. - (2021).
Development of advanced numerical tools for the prediction of wall temperature and heat fluxes for aeroengine combustors
Simone Paccati
2021
Abstract
In the thesis, a multiphysics loosely-coupled tool, called U-THERM3D, is assessed as a detailed investigation tool for high-fidelity prediction of combustion and near-wall processes in a LES CHT simulation framework, allowing a deep understanding of heat transfer modes influence with an affordable computational cost. The numerical analysis is carried out on a laboratory-scale combustor representative of a Rich-Quench-Lean concept, emphasizing the effect of radiative and wall heat losses on the highly sooting flame and the improvements in the wall temperature prediction with respect to a steady calculation. In addition, a novel approach based on the application of 2D boundary sources to simulate the injection of coolant from effusion cooling holes is presented to overcome the issues related to the discretization of the effusion perforation, employing Reduced-Order Model techniques from a Machine Learning framework. For this scope, an in-house external code is combined with the CFD package within the U-THERM3D framework. The numerical tool is firstly validated on simplified geometries in RANS and SBES calculations and then applied on a non-reactive single sector planar rig representative of a real combustor geometry to test the robustness of the proposed strategy in presence of a more complex flow field. Nevertheless, several improvable aspects are highlighted, pointing the way for further enhancements.File | Dimensione | Formato | |
---|---|---|---|
Paccati_PhD_thesis_final.pdf
accesso aperto
Descrizione: Versione finale tesi di dottorato
Tipologia:
Tesi di dottorato
Licenza:
Open Access
Dimensione
33.58 MB
Formato
Adobe PDF
|
33.58 MB | Adobe PDF |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.