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Blob-enhanced reconstruction technique

Castrillo, G., Cafiero, G., Discetti, S. and Astarita, T. (2016) Blob-enhanced reconstruction technique Measurement Science and Technology, 27 (9), 094011.

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Abstract

A method to enhance the quality of the tomographic reconstruction and, consequently, the 3D velocity measurement accuracy, is presented. The technique is based on integrating information on the objects to be reconstructed within the algebraic reconstruction process. A first guess intensity distribution is produced with a standard algebraic method, then the distribution is rebuilt as a sum of Gaussian blobs, based on location, intensity and size of agglomerates of light intensity surrounding local maxima. The blobs substitution regularizes the particle shape allowing a reduction of the particles discretization errors and of their elongation in the depth direction. The performances of the blob-enhanced reconstruction technique (BERT) are assessed with a 3D synthetic experiment. The results have been compared with those obtained by applying the standard camera simultaneous multiplicative reconstruction technique (CSMART) to the same volume. Several blob-enhanced reconstruction processes, both substituting the blobs at the end of the CSMART algorithm and during the iterations (i.e. using the blob-enhanced reconstruction as predictor for the following iterations), have been tested. The results confirm the enhancement in the velocity measurements accuracy, demonstrating a reduction of the bias error due to the ghost particles. The improvement is more remarkable at the largest tested seeding densities. Additionally, using the blobs distributions as a predictor enables further improvement of the convergence of the reconstruction algorithm, with the improvement being more considerable when substituting the blobs more than once during the process. The BERT process is also applied to multi resolution (MR) CSMART reconstructions, permitting simultaneously to achieve remarkable improvements in the flow field measurements and to benefit from the reduction in computational time due to the MR approach. Finally, BERT is also tested on experimental data, obtaining an increase of the signal-to-noise ratio in the reconstructed flow field and a higher value of the correlation factor in the velocity measurements with respect to the volume to which the particles are not replaced.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
NameEmailORCID
Castrillo, G.
Cafiero, G.g.cafiero@surrey.ac.uk
Discetti, S.
Astarita, T.
Date : 11 August 2016
DOI : 10.1088/0957-0233/27/9/094011
Uncontrolled Keywords : 3D velocimetry; Tomo-PIV accuracy; Tomographic PIV; Tomographic reconstruction; Algebra; Flow fields; Signal to noise ratio; Tomography; Velocity; Algebraic reconstruction; Flow field measurement; Integrating information; Reconstruction algorithms; Reconstruction techniques; Tomo-PIV accuracy; Tomographic; Velocity measurement
Depositing User : Clive Harris
Date Deposited : 12 May 2020 20:34
Last Modified : 12 May 2020 20:34
URI: http://epubs.surrey.ac.uk/id/eprint/856388

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