Granular Materials
Granular materials, found ubiquitously in nature, exhibit distinctive properties due to their discrete nature. Energy systems such as solid oxide fuel cells, granular thermal energy storage systems, and fusion breeder beds consist of granular assemblies. The effective thermal conductivity of these assemblies is pivotal for ensuring their robust design and reliable operation. The thermo-mechanical response of granular assemblies is not only determined by the bulk properties of the particles but also strongly influenced by the micro-structural contact topographic parameters, resulting in complex behaviour. This intricate behaviour is comprehensively analyzed and understood through advanced tools such as discrete element methods and statistical analysis.Â
Our research endeavours explored various aspects of effective thermal conductivity (ETC) in granular assemblies, mainly focusing on pebble beds in energy systems such as solid oxide fuel cells and fusion reactors. The studies employed analytical models, machine learning techniques, and hierarchical approaches to estimate and predict ETC, offering valuable insights for designing and optimising these complex systems. The numerical codes developed in this project are available in a GitHub repository.
Some snapshots of the research
A resistor-network approach based thermal discrete element method (TDEM) framework to estimate the effective thermal conductivity of granular assemblies
Thermal analysis of large granular assemblies using a hierarchical approach coupling the macro-scale finite element method and micro-scale discrete element method through artificial neural networks
Dual phase pebble beds have been investigated to identify configurations that will enhance the ETC of the beds
