In this work, a turbulent diffusion flame burning a methane-hydrogen mixture (1:1 by volume) under MILD combustion conditions and different co-flow compositions is investigated. The visible flame region extracted from flame images is compared with flame regions obtained from numerical simulations using several variables as potential flame markers. Quantitative metrics are employed to assess the level of agreement between numerically identified flame regions and flame photographs. The results indicate that the spatial distribution of the ground-state CH radical mass fraction provides the most accurate prediction of the visible flame envelope among the variables considered. Although ground-state CH does not emit in the visible range, its concentration peaks in the reaction zone where electronically excited species responsible for visible chemiluminescence are formed, leading to a strong spatial correlation with the observed luminous flame region. Other radicals, such as H , O and OH also exhibit a reasonable agreement with the flame region due to their presence in overlapping zones of intense chemical activity. In addition, reaction rates associated with key elementary reactions involving CH were examined and found to provide comparable flame-region predictions, with agreement levels exceeding 90 % . The present results demonstrate the capability of combining Computational Fluid Dynamics (CFD) and image-processing techniques to validate turbulent diffusion flame simulations through direct comparison of flame-region geometry and represent one of the first studies to systematically compare experimentally observed visible flame regions with numerical flame markers under MILD combustion conditions for methane/hydrogen flames. • CH radical best predicts the visible region in MILD CH 4 / H 2 turbulent flame. • Reactions 130, 132, and 133 rates show > 90 % precision as flame markers. • Temperature and specific heat capture the flame but with higher dispersion. • Novel validation compares experimental and numerical flame contours. • Image processing + CFD reinforces MILD flame structure understanding.
Ramos et al. (Mon,) studied this question.