Session: 20-07 Combustion & Heat Transfer

Paper Number: 81963

81963 - Towards Fast Prediction of Flame Stability and Emissions of mGT Combustion Chambers: a Chemical Reactor Network Approach 

Hydrogen as energy carrier, in combination with low-NOx micro gas turbines, is receiving increasing attention, since it can represent an attractive solution for a low-carbon, highly efficient and decentralized energy restitution system. However, accomodating Hydrogen-enriched fuel blends in already existing combustion technologies is not an easy task, due to the increased reactivity of this fuel and the higher associated NOx emission. In this framework, reliable numerical models are needed to assist the industry towards the re-design of existing combustion assets. In particular, predicting thermal efficiency and pollutant emissions is of crucial importance for assessing the performances of a given system, since energy production facilities will have to cope with more and more stringent regulations. In this framework, Computational Fluid Dynamics (CFD) has been widely used to model complex turbulent reactive flows in gas turbines applications, given their ability to reproduce the entire flow-field in typical industrial configurations. However, the computational cost associated with those simulations is significant, thus providing complex and time-consuming design exploration processes. For this reason, alternative, physics-based modeling tools, such as Chemical Reactor Networks (CRN), can represent an appealing solution for fast and reliable predictions of overall combustion efficiency and pollutants emissions. In particular, since CRN are based on the concept of zonal modeling, the combustor is divided into a few compartments, and each block is modeled as a canonical 0-D or 1-D chemical reactor (perfectly-stirred reactor or plug-flow reactor). With this flow simplification, it is possible to solve conservation of energy, mass and chemical species only in a reduced number of blocks, dramatically reducing the computational requirements with respect to CFD. Moreover, detailed kinetic mechanisms can be easiliy handled with this tool without compromising the computational efficiency. Detailed chemistry is crucial for reliable pollutants predictions, especially for NOx and CO, since the formation of those chemical species follows complex chemical pathways. The use of Chemical Reactor Networks [WDP1] is quite frequent in literature, especially for performing parametric studies for gas turbines applications. The design of an equivalent CRN for a given combustor is based on the manual observation of the main flow-field features, which can be obtained from experiments or CFD data. The aim of this paper is to employ already-existing simulations from a well-known test case, namely a Turbec T-100 combustion chamber, to build an equivalent CRN model of the combustor, which can effectively reproduce the available numerical data, in order to provide a preliminary validation of the model. Afterwords, the schematic CRN model will be employed to assess the main combustion features of Hydrogen-enriched natural gas fuel blends. In particular, the model will be used to quantify the emissions according to the fuel composition and it will also be employed to quantify the risk of undesired combustion phenomena, such as flashback, which are likely to occur when Hydrogen is added, due to its high burning velocity. At the end, an attempt to identify safe operability limit of the combustor will be made, and with the help of CRN possible dilution strategies to stabilize the combustion process, such as water dilution or exhaust gas recirculation, will also be explored. The motivation of this work is to show how reduced-order and computationally-efficient numerical models can be effectively employed to speed up the mGT combustor design process, providing a useful instrument to rapidly assess the main combustion features, able to deal with a huge variety of fuel compositions and operating conditions.

Presenting Author: Matteo Savarese Universite Libre de Bruxelles

Presenting Author Biography: Matteo Savarese got his Master degree in Chemical Engineering at Università di Pisa, Italy in 2020. For his master thesis he carried out a combined experimental and numerical campaign on a Flameless combustion furnace at the facility located at Université Libre de Bruxelles, Belgium. During this exchange program, he started focusing on the numerical modeling of the combustion of e-fuels mixtures in non-conventional combustion regimes, with a particular interest in developing model-based control systems. After this experience, he started his joint PhD in 2020 at Université Libre de Bruxelles with prof. Alessandro Parente and Université de Mons with prof. Ward De Paepe. His work is focused on the development of reduced-order, physics-based combustion modeling tools, suited for faster and reliable pollutants and thermal performances predictions of advanced combustion systems. In particular, he combines CFD simulations with data post-processing to develop Reactor Networks models of combustion assets.

Authors:

Matteo Savarese Universite Libre de Bruxelles
Jérémy Bompas Université de Mons
Ward De Paepe Universite de Mons
Alessandro Parente Université Libre de Bruxelles