Characterisation of physical and mechanical properties of seven particulate materials proposed as traction enhancers.
Sadaf MaramizonouzSadegh NadimiWilliam SkipperRoger LewisPublished in: Scientific data (2023)
Particulate materials are utilised in many applications to manipulate the friction between surfaces. This dataset provides the characteristics of particulates used as rail sand in the train's wheel/rail interface (via an on-board system) to facilitate the train's acceleration and deceleration. Seven materials are studied including Austrian rail sand, standard Great British rail sand, waste glass beads, recycled crushed glass, non-coated alumina, coated alumina, and dolomite. The main objective of this research is to provide a physical and mechanical characterisation of these granular materials in terms of their density, bulk behaviour, particle size, particle shape, hardness, reduced modulus, and mineralogical properties. In particular, three-dimensional raw and post-processed micro-computed tomography images of more than 1200 particles are shared. The results provide a detailed dataset which can be used in ongoing and future experimental and numerical investigations studying the role of particulates in the wheel/rail interface.
Keyphrases
- drinking water
- computed tomography
- mental health
- physical activity
- magnetic resonance imaging
- deep learning
- high speed
- positron emission tomography
- machine learning
- mass spectrometry
- current status
- convolutional neural network
- staphylococcus aureus
- magnetic resonance
- optical coherence tomography
- pet ct
- high resolution