In situ soot characterization in flames by coupling extinction, emission and light scattering at different wavelengths
Résumé
To optimize combustion systems and reduce their fine particle (soot) emissions, it is essential to improve models predicting the formation of these particles—models that still struggle to accurately forecast nucleation, surface growth, and oxidation processes. To validate and refine these models, comprehensive experimental characterizations of target academic flames are required. These characterizations have to include volume fraction, aggregate and primary spherule sizes, temperature, number density, and morphology. In this work, we focus on laminar diffusion flames. Optical techniques—such as extinction, natural or laser-induced emission, and angular and spectral scattering—offer the advantage of in situ measurements with unparalleled spatial resolution. However, these techniques require knowledge of the optical index of the particles, which evolves as the particles mature during formation. Therefore, advancing the simultaneous determination of both the quantities of interest and the optical properties is crucial. To achieve this, we propose combining extinction, thermal emission, and angular scattering measurements at multiple wavelengths. By inverting these data using a light-particle interaction model based on Rayleigh theory adapted for fractal aggregates (RDG-FA), we can retrieve all the desired quantities. We demonstrate that this inversion process is greatly facilitated by the use of Physics-Informed Neural Networks (PINNs). For the first time, we present spatial maps of the soot optical index within the studied flames, revealing the transition from an organic-rich phase to amorphous carbon and ultimately to a more graphitized form. We conclude this presentation by discussing the potential applications and future prospects of these results.
