Abstract
An evolutionary reconstruction technique (ERT) was developed for three-dimensional (3D) reconstruction of luminescent objects, in particular turbulent flames for the first time. The computed tomography (CT) algorithm is comprised of a genetic algorithm (GA) and a ray-tracing software. To guide the reconstruction process, a mask is introduced. It uses a Metropolis algorithm (MA) to sample locations where specific genetic operators can be applied. Based on an extensive parameter study, performed on several types of phantoms, the ability of our algorithm for 3D reconstructions of fields with varying complexities is demonstrated. Furthermore, it was applied to three experiments, to reconstruct the instantaneous chemiluminescence field of a bunsen flame, a highly turbulent swirl flame and the turbulent Cambridge-Sandia stratified flame. Additionally, we show direct and quantitative comparison to an advanced computed tomography of chemiluminescence (CTC) method that is based on an algebraic reconstruction technique (ART). The results showed good agreement between CTC and ERT using both phantom data from flame simulations, and experimental data.
Highlights
In the last decades 3D computed tomography (CT) methods have seen widespread use in numerous areas of engineering and physical sciences research
The capability of the evolutionary reconstruction technique (ERT) to reconstruct complex structures was tested in more depth using three different flame phantoms that were generated by large eddy simulations (LES)
The results of the parameter study are not affected by the ray-tracing scheme, since we solely focused on the features of the genetic algorithm (GA)
Summary
In the last decades 3D computed tomography (CT) methods have seen widespread use in numerous areas of engineering and physical sciences research. Continuous and direct ray-tracing of the reconstruction domain during the evolutionary process will allow us in later applications to implement more complex measurement models. These can be, e.g., particle interaction, multi-phase flows or accounting for beam steering. A calibration free reconstruction method is feasible with this method by optimizing the cameras parameters simultaneously while reconstructing This is generally not possible for our CTC method [8,9,16,17], as the matrix to be inverted is formed in a one-time ray-tracing step. The capability of the ERT to reconstruct complex structures was tested in more depth using three different flame phantoms that were generated by large eddy simulations (LES). The camera setup was tested in previous experiments [16,17] and we compare the ERT results to ART-based reconstructions using a CTC method [8,9] that features an advanced camera model
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