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"Discrete element modelling of the effects of particle angularity on th" by Jing Chen, Buddhima Indraratna et al.

Railroad ballast exhibits distinct morphological characteristics represented by shape irregularity, corner angularity, and surface texture. Upon repeated train loading, the morphology of ballast undergoes inevitable degradation, particularly in terms of its corner sharpness, which can affect track performance and even pose a substantial threat to operational safety. These aspects have rarely been captured insightfully in most DEM studies on ballast. In contrast, this study examines the influence of particle angularity on the deformation and degradation behaviour of railway ballast upon repeated loading using the discrete element method (DEM). The angularity of ballast particles is captured and quantified using the CT scanning technology in conjunction with an image-based processing strategy, after which the irregularly shaped particles are reconstructed in the DEM. In this numerical procedure, aggregates with varying angularities are created by incorporating a particle degradation subr ....

Ballast Degradation , Discrete Element Method , Ermanent Deformation , Hakedown Behaviour , Hape Angularity ,

40 Years of Dry Processing and Bulk Solids Handling: Challenges, Changes, and Successes

Bulk solids science has advanced significantly over the past half a century, yet there is much more to explore and develop. ....

United States , Mars Rover , Andrew Jenike , Eric Maynard , Jenike Johanson , Herman Purutyan , Santa Monica , Ronald Reagan , Jenike Johanson Inc , National Fire Protection Association , Procter Gamble , Us Department Of Energy , International Powder Bulk Solids Conference , Bulk Solids , Space Shuttle , Internet Protocol , Computer Aided Design , Statistical Process Control , Six Sigma , Brand Study , Global Financial Crisis , Stock Keeping Units , Didion Milling , International Powder , Bulk Solids Conference , Discrete Element Method ,

New AI-Powered Design for Mixing and Blending

The new design is applicable to a wide range of equipment across many industries. ....

United Kingdom , Leonard Nicusan , Dominik Werner , Leanard Nicuson , Jack Sykes , University Of Birmingham Enterprise United Kingdom , School Of Chemical Engineering , Birmingham Enterprise , Chief Executive Officer Dominik Werner , Chief Technology Officer Leonard Nicusan , Chief Operating Officer Jack Sykes , Chief Scientific Officer , Kit Windows Yule , Highly Autonomous Rapid Prototyping , Particulate Processes , Discrete Element Method , Positron Emission Particle Tracking ,

New AI-Powered Design for Mixing and Blending

The new design is applicable to a diverse range of equipment, across many industries. ....

United Kingdom , Leonard Nicusan , Jack Sykes , Dominik Werner , Leanard Nicuson , School Of Chemical Engineering , University Of Birmingham Enterprise United Kingdom , Birmingham Enterprise , Chief Executive Officer Dominik Werner , Chief Technology Officer Leonard Nicusan , Chief Operating Officer Jack Sykes , Chief Scientific Officer , Kit Windows Yule , Highly Autonomous Rapid Prototyping , Particulate Processes , Discrete Element Method , Positron Emission Particle Tracking ,

AI-powered design for industrial processing equipment

University of Birmingham Enterprise has launched an AI-powered product to optimise process equipment that mixes, blends, stores or stirs granular materials. ....

Dominik Werner , Jack Sykes , Leonard Nicusan , Birmingham School Of Chemical Engineering , University Of Birmingham , University Of Birmingham Enterprise , Birmingham Enterprise , Chief Executive Officer Dominik Werner , Chief Technology Officer Leonard Nicusan , Chief Operating Officer Jack Sykes , Chief Scientific Officer Dr Kit Windows Yule , Highly Autonomous Rapid Prototyping , Particulate Processes , Discrete Element Method , Ai Powered Design , Industrial Processing Equipment , University Of Birmingham Enterprise ,