Composition-independent mean temperature measurements in laminar diffusion flames using spectral lineshape information

Temperature is an important thermochemical property in combusting flows that holds the key to uncovering pollutant formation, flame extinction, and heat release. In a practical combustion environment, the local composition is typically unknown, which hinders the effectiveness of many traditional non-intrusive thermometry techniques. This study aims to offset this limitation by developing a laser-based thermometry technique that does not require prior knowledge of the local composition. Two methods for obtaining temperature are demonstrated in this work, both of which make use of the spectral line broadening of an absorbing species (krypton) seeded into the flow. In the first method, the local Doppler broadening is extracted from an excitation scan to yield the corresponding temperature, while the second method utilizes compositional scaling information of the collisional broadening and collisional shift to determine the temperature. Both methods are demonstrated by measuring the radial temperature profile of a steady laminar CH4/N2 diffusion flame with an air co-flow. The accuracy of the temperature measurements obtained using both methods are evaluated using corresponding temperature profiles determined from computational simulations.