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Kenneth Williams

Researcher at University of Newcastle

Publications -  86
Citations -  800

Kenneth Williams is an academic researcher from University of Newcastle. The author has contributed to research in topics: Pressure drop & Slug flow. The author has an hindex of 13, co-authored 84 publications receiving 607 citations.

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Solids Friction Factors for Fluidized Dense-Phase Conveying

TL;DR: In this paper, a series of calculations were performed on experimental data in order to estimate solids friction factor for four types of material conveyed in the fluidized dense-phase flow regime.
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Predicting the mode of flow in pneumatic conveying systems—A review ☆

TL;DR: In this paper, a review of the commonly used and available techniques for predicting mode of flow is presented, where two types of predictive charts are defined: basic particle parameter based (e.g. particle size and density) and air-particle parameter based, and two general categories of modes of flow, two dense flows: fluidised dense phase and plug flow, and dilute phase only.
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On the challenges facing the handling of solid biomass feedstocks

TL;DR: In this article, the main feedstock attributes associated with a number of handling chain phases and the approach to obtain them are discussed and a framework for a holistic approach to the characterisation and design of biomass feedstock handling systems for further development and practical implementation is also proposed.
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CFD simulation methodology for gas-solid flow in bypass pneumatic conveying – A review.

TL;DR: In this article, a review of numerical models for simulation of gas-solid flow in bypass pneumatic conveying is presented and the experimental results for pressure drops based on a number of test cases are compared with numerical results obtained with different numerical models.
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Particle shape characterisation and its application to discrete element modelling

TL;DR: The objective of this research is to assess particle shape descriptors through a digital image segmentation technique, and to further implement particle shape parameters into generation of corresponding irregular shaped DEM particles.