Computed tomography in resolving flame topology with internal optical blockage involved

Abstract

This work reports the modification and optimization of a computed tomography (CT) algorithm to become capable of resolving an optical field with internal optical blockage (IOB) present. The IOB—practically, the opaque mechanical parts installed inside the measurement domain—prevents a portion of emitted light from transmitting to optical sensors. Such blockage disrupts the line-of-sight intensity integration on recorded projections and eventually leads to incorrect reconstructions. In the modified algorithm developed in this work, the positions of the obstacle are measured a priori, and then the discretized optical fields (i.e., voxels) are classified as those that participate in the CT process (named effective voxels) and those that are expelled, based on the relative positions of the imaging sensors, IOB, and light signal distribution. Finally, the effective voxels can be iteratively reconstructed by combining their projections on sensors that provide direct observation. Moreover, the impact of IOB on reconstruction accuracy is discussed under different sensor arrangements to provide hands-on guidance on sensor orientation selection in practical CT problems. The modified algorithm and sensor arrangement strategy are both numerically and experimentally validated by simulated phantoms and a two-branch premixed laminar flame in this work.

Volumetric flame reconstructions in an optical engine cylinder involving refraction and blockage

“…Admittedly, such processing could possibly deteriorate the reconstruction quality for some voxels whose projections are blocked on multiple CCDs. The shortage can be reduced by increasing the camera numbers and arranging cameras at optimized orientations [28].…”

“…Minor reconstruction error appearing in figure 4(f) may be caused by limited iteration numbers. Furthermore, to provide a quantitative evaluation of 3D reconstruction accuracy by different methods, the reconstruction error e R is calculated by averaging over all voxels following the same procedure in our previous publication [28]:…”

“…For example, to investigate the behavior of flame kernels close to the sparking plug during the ignition process of an optical engine, cutting off the sparking plug from the measurement domain would possibly remove the kernels as well. By understanding such limitations, past works modified the mapping relationship from the 3D target to 2D projections, and managed to simulate incomplete projections under light path blockage [26,28]. These projections can be directly combined to reconstruct the target.…”