Computed tomography in resolving flame topology with internal optical blockage involved

Area of Science:

• Optical Engineering
• Image Reconstruction
• Computational Imaging

Background:

• Computed tomography (CT) algorithms struggle with internal optical blockage (IOB), where opaque objects obstruct light paths.
• IOB disrupts line-of-sight intensity integration, leading to inaccurate reconstructions in optical field analysis.
• Existing CT methods require modifications to handle projections affected by internal obstructions.

Purpose of the Study:

• To develop and optimize a CT algorithm capable of reconstructing optical fields in the presence of internal optical blockage (IOB).
• To address the limitations of standard CT algorithms when internal opaque components interfere with light transmission.
• To provide guidance on sensor arrangement for practical CT applications with IOB.

Main Methods:

• Modification of a CT algorithm to account for known positions of internal optical blockage (IOB).
• Classification of voxels into 'effective voxels' participating in the CT process based on sensor, IOB, and signal geometry.
• Iterative reconstruction of effective voxels using projections from sensors with direct observation lines.
• Analysis of IOB impact on reconstruction accuracy across various sensor configurations.

Main Results:

• Successful reconstruction of optical fields despite the presence of internal optical blockage (IOB).
• Demonstration that the modified algorithm accurately identifies and reconstructs effective voxels.
• Validation of the algorithm and sensor strategy through numerical simulations and experimental testing with a laminar flame.

Conclusions:

• The modified CT algorithm effectively resolves optical fields with internal optical blockage (IOB).
• The proposed voxel classification and iterative reconstruction approach overcomes line-of-sight integration issues caused by IOB.
• The study offers practical insights into sensor arrangement for optimizing CT reconstruction accuracy in IOB scenarios.