50 citations · 61 across the 5 of their papers we have counts for
6 papers
Towards scientific machine learning for granular material simulations -- challenges and opportunities
Marc Fransen, Andreas Fürst, Deepak Tunuguntla +21
Micro-scale mechanisms, such as inter-particle and particle-fluid interactions, govern the behaviour of granular systems. While particle-scale simulations provide detailed insights…
Shape matters: Competing mechanisms of particle shape segregation
D. Hernández-Delfin, D. R. Tunuguntla, T. Weinhart +2
It is well-known that granular mixtures that differ in size or shape segregate when sheared. In the past, two mechanisms have been proposed to describe this effect, and it is uncle…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Surface flow profiles for dry and wet granular materials by Particle Tracking Velocimetry; the effect of wall roughness
Sudeshna Roy, Bert J. Scheper, Harmen Polman +4
Two-dimensional Particle Tracking Velocimetry (PTV) is a promising technique to study the behaviour of granular flows. The aim is to experimentally determine the free surface width…
Granular flow over inclined channels with linear contraction
D. R. Tunuguntla, T. Weinhart, A. R. Thornton +1
We consider dry granular flow down an inclined chute with a localised contraction theoretically and numerically. The flow regimes are predicted through a novel extended one-dimensi…
From discrete elements to continuum fields: Extension to bidisperse systems
Deepak R. Tunuguntla, Anthony R. Thornton, Thomas Weinhart
To develop, calibrate and/or validate continuum models from experimental or numerical data, micro-macro transition methods are required. These methods are used to obtain the contin…