Roberto Hart-Villamil , Jack Sykes , Andy Ingram , Christopher R.K. Windows-Yule , Santosh Kumar Gupta
{"title":"Positron Emission Projection Imaging: A technique for concentration field measurements in opaque industrial systems","authors":"Roberto Hart-Villamil , Jack Sykes , Andy Ingram , Christopher R.K. Windows-Yule , Santosh Kumar Gupta","doi":"10.1016/j.partic.2024.07.009","DOIUrl":null,"url":null,"abstract":"<div><p>A novel Positron Emission Projection Imaging (PEPI) algorithm designed to compute the plane-projected spatial distribution of radiolabelled materials without the need for collimation is introduced. By leveraging improved data efficiency, we have achieved a technique with enhanced spatial resolution and temporal resolution compared to previous PEPI algorithms. Validation of this algorithm was conducted using synthetic data generated from a digital twin of a PET scanner, demonstrating its accuracy for practical applications. The industrial advantage of this novel algorithm was applied in the imaging of laminar flow mixing within a ploughshare mixer, with the experimental results compared against those obtained from validated computational fluid dynamics (CFD) models. This comparison highlights an important use case for PEPI as a robust validation tool for CFD simulations, crucial for enhancing industrial processes. PEPI, which uses deeply penetrating gamma-photons, is now capable of imaging opaque fluids and solids in industrial casing. Future directions for this work include further algorithmic refinements and expanding its application across various industrial systems, establishing PEPI as a robust tool for in-depth industrial process analysis. The advancements presented here allow for optimized mixer design and enhanced process efficiency, extending the frontiers of tomographic imaging in industrial applications.</p></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"94 ","pages":"Pages 1-15"},"PeriodicalIF":4.1000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1674200124001366/pdfft?md5=ab95855890f4e5c876437bd7f12231ba&pid=1-s2.0-S1674200124001366-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Particuology","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1674200124001366","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0
Abstract
A novel Positron Emission Projection Imaging (PEPI) algorithm designed to compute the plane-projected spatial distribution of radiolabelled materials without the need for collimation is introduced. By leveraging improved data efficiency, we have achieved a technique with enhanced spatial resolution and temporal resolution compared to previous PEPI algorithms. Validation of this algorithm was conducted using synthetic data generated from a digital twin of a PET scanner, demonstrating its accuracy for practical applications. The industrial advantage of this novel algorithm was applied in the imaging of laminar flow mixing within a ploughshare mixer, with the experimental results compared against those obtained from validated computational fluid dynamics (CFD) models. This comparison highlights an important use case for PEPI as a robust validation tool for CFD simulations, crucial for enhancing industrial processes. PEPI, which uses deeply penetrating gamma-photons, is now capable of imaging opaque fluids and solids in industrial casing. Future directions for this work include further algorithmic refinements and expanding its application across various industrial systems, establishing PEPI as a robust tool for in-depth industrial process analysis. The advancements presented here allow for optimized mixer design and enhanced process efficiency, extending the frontiers of tomographic imaging in industrial applications.
期刊介绍:
The word ‘particuology’ was coined to parallel the discipline for the science and technology of particles.
Particuology is an interdisciplinary journal that publishes frontier research articles and critical reviews on the discovery, formulation and engineering of particulate materials, processes and systems. It especially welcomes contributions utilising advanced theoretical, modelling and measurement methods to enable the discovery and creation of new particulate materials, and the manufacturing of functional particulate-based products, such as sensors.
Papers are handled by Thematic Editors who oversee contributions from specific subject fields. These fields are classified into: Particle Synthesis and Modification; Particle Characterization and Measurement; Granular Systems and Bulk Solids Technology; Fluidization and Particle-Fluid Systems; Aerosols; and Applications of Particle Technology.
Key topics concerning the creation and processing of particulates include:
-Modelling and simulation of particle formation, collective behaviour of particles and systems for particle production over a broad spectrum of length scales
-Mining of experimental data for particle synthesis and surface properties to facilitate the creation of new materials and processes
-Particle design and preparation including controlled response and sensing functionalities in formation, delivery systems and biological systems, etc.
-Experimental and computational methods for visualization and analysis of particulate system.
These topics are broadly relevant to the production of materials, pharmaceuticals and food, and to the conversion of energy resources to fuels and protection of the environment.