Abstract
The computed tomography of chemiluminescence (CTC) can be used to reconstruct a three-dimensional (3D) flame chemiluminescence field to obtain information about the spatial characteristics of the flame. However, additional information is needed to solve the ill-posed inverse problem of the CTC due to the constraints such as economy of CTC system and the number of views. In this study, a PR-SART algorithm is proposed for 3D flame reconstruction by combining the flame outer contour pre-reconstruction model with the simultaneous algebraic reconstruction technique (SART). The influence of the number of pre-reconstruction iterations is analyzed in numerical studies. The reconstruction performance of the SART algorithm is compared with the PR-SART algorithm for two flame structures under various numbers of views and noise conditions. Finally, an OH* chemiluminescence imaging system consisting of 8 ultraviolet (UV) cameras is developed, and evaluated through use of reconstructing the 3D structure of low-swirl flames. Numerical and experimental studies indicate that the proposed algorithm and CTC system are effectively capable of removing the reconstruction error in the flame-free region, improving the reconstruction quality, and reducing the computational cost.
Published Version
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