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Optimization of detector positioning in the radioactive particle tracking technique. | LitMetric

Optimization of detector positioning in the radioactive particle tracking technique.

Appl Radiat Isot

Department of Chemical Engineering, Ecole Polytechnique de Montreal, PO Box 6079, Stn. CV, Montreal, QC, Canada H3C 3A7. Electronic address:

Published: July 2014


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Article Abstract

The radioactive particle tracking (RPT) technique is a non-intrusive experimental velocimetry and tomography technique extensively applied to the study of hydrodynamics in a great variety of systems. In this technique, arrays of scintillation detector are used to track the motion of a single radioactive tracer particle emitting isotropic γ-rays. This work describes and applies an optimization strategy developed to find an optimal set of positions for the scintillation detectors used in the RPT technique. This strategy employs the overall resolution of the detectors as the objective function and a mesh adaptive direct search (MADS) algorithm to solve the optimization problem. More precisely, NOMAD, a C++ implementation of the MADS algorithm is used. First, the optimization strategy is validated using simple cases with known optimal detector configurations. Next, it is applied to a three-dimensional axisymmetric system (i.e. a vertical cylinder, which could represent a fluidized bed, bubble column, riser or else). The results obtained using the optimization strategy are in agreement with what was previously recommended by Roy et al. (2002) for a similar system. Finally, the optimization strategy is used for a system consisting of a partially filled cylindrical tumbler. The application of insights gained by the optimization strategy is shown to lead to a significant reduction in the error made when reconstructing the position of a tracer particle. The results of this work show that the optimization strategy developed is sensitive to both the type of objective function used and the experimental conditions. The limitations and drawbacks of the optimization strategy are also discussed.

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http://dx.doi.org/10.1016/j.apradiso.2014.02.019DOI Listing

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