(208d) New Developments in Positron Emission Particle Tracking and Their Applications in Food, Pharmaceuticals and Plastic Recycling | AIChE

(208d) New Developments in Positron Emission Particle Tracking and Their Applications in Food, Pharmaceuticals and Plastic Recycling

Authors 

Windows-Yule, K. - Presenter, University of Birmingham
Positron emission particle tracking (PEPT) is a non-invasive imaging technique capable of providing detailed, high-resolution, three-dimensional data even from the interior of large, dense, optically opaque systems (1). Though the technique has existed for more than 3 decades, recent years have seen an upsurge in new developments and improved capabilities. These include: the development of novel, machine-learning based algorithms (2) capable of, for the first time, of resolving particle collisions; a detailed and accurate simulation model of the Birmingham positron camera used in hundreds of previous experiments (3); the development and inauguration of a new “SuperPEPT” detector system offering micron-scale spatial resolution and sub-millisecond temporal resolution; the development of a first set of benchmarking tests allowing PEPT algorithms developed around the world to be rigorously tested and quantitatively compared; and the hybridisation of PEPT with DEM simulations and genetic algorithms to autonomously characterise particles and powders. This talk will provide a flying overview of these new developments, and the manners in which they have been applied to a diverse range of chemical engineering problems from refining the measurement of just-suspended speeds in stirred-tank systems (4) to the imaging and optimisation of mixing processes within novel fluidised-bed-based waste-plastic recycling methodologies (5, 6).

REFERENCES

  1. Windows-Yule C, Seville J, Ingram A, Parker D. Positron Emission Particle Tracking of Granular Flows. Annual Review of Chemical and Biomolecular Engineering. 2020;11.
  2. NicuÅŸan A, Windows-Yule C. Positron emission particle tracking using machine learning. Review of Scientific Instruments. 2020;91(1):013329.
  3. Herald M, Wheldon T, Windows-Yule C. Monte Carlo model validation of a detector system used for Positron Emission Particle Tracking. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2021;993:165073.
  4. Windows-Yule CR, Hart-Villamil R, Ridout T, Kokalova T, Nogueira-Filho JC. Positron Emission Particle Tracking for Liquid‐Solid Mixing in Stirred Tanks. Chemical Engineering & Technology. 2020;43(10):1939-50.
  5. Windows-Yule C, Moore A, Wellard C, Werner D, Parker D, Seville J. Particle distributions in binary gas-fluidised beds: Shape matters–But not much. Chemical Engineering Science. 2020;216:115440.
  6. Windows-Yule C, Gibson S, Werner D, Parker D, Kokalova T, Seville J. Effect of distributor design on particle distribution in a binary fluidised bed. Powder Technology. 2020;367:1-9.