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A numerical investigation of high-resolution multispectral absorption tomography for flow thermometry


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Authors

Cai, W 
Kaminski, CF 

Abstract

Multispectral absorption tomography (MAT) is now a well-established technique that can be applied for the simultaneous imaging of temperature, species concentration, and pressure of reactive flows. However, only intermediate spatial resolution, on order of 15×15 grid points, has so far been achievable in previous demonstrations. The aim of the present work is to provide a numerical validation of our MAT algorithm for thermometry of combusting flows, but with greatly improved spatial resolution to motivate its experimental realization in practical environments. We demonstrate a grid resolution that is comparable to that of classical absorption tomography (CAT) containing 80×80 elements from only two orthogonal projections, which is impractical to realize with CAT but especially desirable for applications where optical access is limited. This is achieved using the smoothness assumption, which holds true under most combustion conditions. The study shows that better spatial resolution can be obtained through a simple increase in the spatial sampling frequency for the two available projections, as the smoothness condition becomes more reliable on smaller spatial scales. Our work also demonstrates the first application of MAT for full volumetric reconstructions. The studies thus provide robust guidelines for the implementation of MAT over large spatial scales and lay solid foundations for its development and application in complex technical combustion scenarios, where spatial resolution is crucial to investigate the interaction of flow phenomena with chemical reactions.

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Keywords

40 Engineering, 4002 Automotive Engineering, Bioengineering

Journal Title

Applied Physics B: Lasers and Optics

Conference Name

Journal ISSN

0946-2171
1432-0649

Volume Title

119

Publisher

Springer Science and Business Media LLC
Sponsorship
Engineering and Physical Sciences Research Council (EP/L015889/1)
European Commission (330840)
This work was funded by the European Commission under Grant No. ASHTCSC 330840 and was partly performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service. Clemens F. Kaminski also wishes to acknowledge EPSRC for funding (grant EP/L015889/1).