On a WP basis, the main results achieved in the first reporting period can be summarized as follows:
WP2 - Fuel flexible combustion systems
A first test campaign at ambient pressure was carried out at ETH to investigate LEAF combustor for fuel-flex operations with jet A-1/H2, and transition of jet A-1 to 100% H2. Figure 2 shows time-averaged OH* chemiluminescence images showing LEAF topology or L_CC = 60 mm and P_th = 10 kW (left); L_CC = 60 mm and P_th = 35 kW (middle); L_CC = 80 mm and P_th = 35 kW (right). ϕ_global = 0.8 ± 0.01 and ALR-4 are constant for three cases. OH* intensity normalised between 0 and 1.
A new dual-fuel version of the CHAIR burner concept was developed by KIT and UNIFI. A preliminary experiemntal validation was carried out at KIT at ambient pressure, ranging from 100% jetA up to 100% H2. Figure 3 reports time-averaged OH* chemiluminescence images of flame for varying H2/Jet-A1 fuel splits under different configurations: (a, b, e) Config 1, (c, f) Config 2, and (d, g) Config 3., relative pressure drop = 3%, air inlet temperature = 673 K, thermal power=31 kW.
A chemical kinetics scheme has been developed by UNINA starting from literature data. The kinetic mechanism includes the oxidation of a few representative hydrocarbons, which are important components of aviation fuel surrogates. The reaction mechanism is intended to well-represent the individual components as well as a multi-component surrogate for jet fuel made up of these fuel components. The full mechanism also includes reactions for pollutant formation: gaseous and condensed phase compounds, and NOx formation reaction pathways.
UCAM and UNIFI had worked to dual-fuel versions of the CMC and DTFM turbulent combustion models for LES investigations. Models are under validation on the well known Cambridge Swirl flame operated with heptane and hydrogen
WP3 - Electric-fields assisted combustion and fuel preparation
A test rig to investigate plasma assisted combustion on the CHAIR concept is under final development and commissioning at UNILE.
Reactive molecular dynamics (MD) simulations have been used by IC to investigate the effects of an electric field on the reaction dynamics of a fuel representing SAF. Results are detailed in the first journal article published within FFLECS project (
https://doi.org/10.1063/5.0264365(s’ouvre dans une nouvelle fenêtre))
KIT/EBI is involved in the modelling of the atomization process in electro-sprayers within SPH code. First investigations confirmed that the electric charge of the liquid will significantly affect surface tension and may even lead to zero effective surface tension for large droplets thus improving the atomization process. IC has carried out an investigation by the means of CFD calculations (OpenFOAM) to verify the chance of controlling the trajectory of charged fuel droplets in a number of configurations relevant for aviation applications. Also in this case results have been reported in a journal paper (
https://doi.org/10.1016/j.ijmultiphaseflow.2025.105289(s’ouvre dans une nouvelle fenêtre)).
WP4 - Integration and emission prediction
With the contribution of all the partners, a set of reference engine cycle thermodynamic conditions has been selected for the investigation of the developed combustion concepts up to full-scale conditions. A small engine cycle (typical turbopropo engine) and a classical high pressure turbofan engine cycle were defined.
Task 4.1.2 has seen the consolidation of the conceptual design of CHAIR and LEAF combustion technologies and related plasma assisted operations. Full details are reported in Deliverable D4.2.
UNINA is currently collaborating with KIT and ETH to use two sensors, one for temperature measurements and the other for particulate matter (PM) measurements, to enable active combustion control.
KIT teams is developing a machine-learning-based digital twin to control flame instabilities in low-emission combustors. As part of this effort, time series data from ion probe sensors are being collected by project partners at KIT/EBI to characterize flame behavior and predict lean blowout (LBO) events.
