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.

This work reports an optimized tomography method, termed Direct-Mapping Cross-Interfaces Computed Tomography (DMCICT), with enhanced calculation efficiency and accuracy for three-dimensional (3D) reconstruction in confined space. Confined-space tomography methods are designed to correct the image distortion on recorded target images caused by light refraction through optical walls, such as optical engine cylinders. However, past confined-space tomography methods have shortcomings in reconstruction accuracy and time efficiency, since they usually involve time-consuming iterations or numerical interpolation during calculating the mapping relationship from 3D measurement domain to 2D imaging planes. There, DMCICT is developed in this work to directly calculating the mapping relationship by performing reverse ray-tracings originated from imaging planes, then decide the intersection volumes with discretized measurement domain. Numerical and experimental validations of DMCICT are respectively performed based on multiple simulated phantoms and a two-branch laminar flame contained inside an optical cylinder. Compared to past confined-space reconstructions, DMCICT can reduce more than 50% of the computational time in majority of tested cases, while the reconstruction accuracy is also significantly enhanced. Moreover, DMCICT demonstrates the robustness under different spatial resolution conditions and presents solid endurance on measurement errors.

This work reports an optimized tomography method, termed Direct-Mapping Cross-Interfaces Computed Tomography (DMCICT), with enhanced calculation e ciency and accuracy for three-dimensional (3D) reconstruction in con ned space. Con ned-space tomography methods are designed to correct the image distortion on recorded target images caused by light refraction through optical walls, such as optical engine cylinders. However, past con ned-space tomography methods have shortcomings in reconstruction accuracy and time e ciency, since they usually involve time-consuming iterations or numerical interpolation during calculating the mapping relationship from 3D measurement domain to 2D imaging planes. There, DMCICT is developed in this work to directly calculating the mapping relationship by performing reverse ray-tracings originated from imaging planes, then decide the intersection volumes with discretized measurement domain. Numerical and experimental validations of DMCICT are respectively performed based on multiple simulated phantoms and a two-branch laminar ame contained inside an optical cylinder. Compared to past con ned-space reconstructions, DMCICT can reduce more than 50% of the computational time in majority of tested cases, while the reconstruction accuracy is also signi cantly enhanced. Moreover, DMCICT demonstrates the robustness under different spatial resolution conditions and presents solid endurance on measurement errors.