Session: 04-19 Combustor Design I
Paper Number: 128828
128828 - Optimisation of a Hydrogen-Fuelled Parametric Strut Injector Using an Automated Workflow CFD Method
In order to decarbonise aviation, alternative fuels are being considered as a replacement for kerosene. One of the most promising candidates is hydrogen, the combustion of which produces no carbon dioxide. The properties of gaseous injected hydrogen differ enormously from liquid kerosene and as such both the injection strategy and numerical tools need to be adapted. Although this presents several challenges, it also presents opportunities as new injection concepts can be imagined in design spaces inaccessible to kerosene injectors. This work reintroduces the strut injector concept, originally designed for supersonic combustion, in a revised form for subsonic gas turbine combustion. A strut injector for burning hydrogen has been optimised using an automated workflow system. The design process began with a parametric CAD (Computer Aided Design) model that allowed for several design parameters to be modified and various different designs to be generated from a given list of input values. In order to choose the optimal set of injectors to cover the design space, an optimised design of experiments (DOE) method was used to automatically choose the parameters that best spanned the design space. One hundred candidate designs were chosen and a script used to generate a series of stereolithography (STL) files for each design. The STL files were then uploaded to a supercomputer for CFD analysis. For each of the 100 designs, a 4-step process was followed to generate the required data, this included an automated mesh generation step, field initialisation step, mesh adaption step and finally an LES, all within the YALES2 numerical framework. These 400 simulations were run using an automatic workflow management process that limited the quantity of human intervention required and massively boosted productivity. In order to reduce the time required for post-processing and the amount of necessary data, the simulations relied heavily on an on-the-fly post-processing methodology which reduced the complex time-unsteady flow fields to a small number of quantified outputs of interest which measured the suitability of each design such as the pressure drop across the injector and the efficiency of the mixing process. At the conclusion of these simulations, automated scripts translated these outputs into a smaller set of parameters that could be used to compare each design and allow subsequent optimisation and surrogate modelling. Several surrogate modelling methods were attempted with mixed results however a simple classification methodology quickly identified the parameters of interest.
Presenting Author: Nicholas Treleaven Safran Tech
Presenting Author Biography: Nicholas is a research engineer at Safran Tech.
Authors:
Nicholas Treleaven Safran TechGuillaume J. J. Fournier Safran Tech
Julien Leparoux Safran Tech
Renaud Mercier Safran Tech
Optimisation of a Hydrogen-Fuelled Parametric Strut Injector Using an Automated Workflow CFD Method
Paper Type
Technical Paper Publication