Limited View Tomography of Combustion Zones Using Tunable Diode Laser Absorption Spectroscopy: Simulation of an Algebraic Reconstruction Technique

Abstract

Temperature and concentration distributions of a simulated flame were reconstructed with the help of computer tomography and tunable diode laser absorption spectroscopy (TDLAS). Reconstructions were based on the simulated numerical values of temperature and concentration of a stationary flame. Integrated absorption measurements along the line-of-sight (LOS) across the flames due to absorption by water vapor (H2O) in the near infra-red (NIR) region, specifically the 6930–6940 cm−1 range, were simulated to obtain the projection values for tomography. Spectroscopic parameters for the absorptions transitions, such as line-strengths, transition wavenumbers, collisional broadening coefficients and coefficients for their temperature dependency were selected from the HITRAN 2004 database. Simulated LOS data are inverted using a multiplicative algebraic reconstruction technique (MART), which are known to outperform traditional filtered back projection methods for cases with limited numbers of views. Based on spatially resolved reconstructions of spectroscopic data, temperature and concentration distributions are calculated using the wavelength modulation spectroscopy with second harmonic detection (WMS-2f) technique. A parametric study based on the number of views, orientation of views and number of rays per view required by the ART is performed in order to assess requirements for an acceptable reconstruction.

A Study of Two Dimensional Tomography Reconstruction of Temperature and Gas Concentration in a Combustion Field Using TDLAS

“…Therefore, the set volume fractions of H 2 O C set in the measurement grids are assumed to be 0.17 ± 0.005 and 0.015 ± 0.005, correspondingly. It is known that the orientation of the view and the number of rays per view has a significant bearing on the quality of reconstruction [28,29]. Therefore, we assumed four different laser beams distributions to study the influence on the reconstruction in simulations.…”