|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||The studentship is open to both home and overseas applicants and will cover both the cost of tuition fee and a yearly stipend (at UKRI rate) over the course of the PhD programme.|
|Placed On:||30th March 2023|
|Closes:||16th April 2023|
Project Title: Computational modelling of melting plastic particle flows: fundamental physics, reactor design and topology optimisations
Melting particle flows (MPFs) are a key phenomenon of any modern polymer manufacturing and plastic recycling technologies, where plastic feedstocks undergo melting or thermal cracking, depending on the heating rates, to precious materials such as renewable polymers, synthesised fuels, etc.
The project creates a cross-school collaboration involving a leading polymer industry to create the currently nonexciting computational toolsets for predictive modelling of phase-changing multiphase dense particle flows. The tool will be used for topology design and optimisation of such devices, especially those in the renewable polymer manufacturing and plastic waste recycling.
The project establishes a collaboration between a leading industry partner and the University of Birmingham to develop the knowledge and technology for the design of low-cost and robust melting plastic particle devices that are used in renewable polymer manufacturing and modern recycling technologies. Global plastic productions currently exceed 300 million tons per year.
They are continuously increasing, with a more than 38% contribution from Low-Middle Income Countries, where plastic wastes are either simply abundant in the landfill or burned in open fields/underperformed incinerators .
The former (especially with increasingly warmer climates and prolonged solar radiation) is the source of particulate microplastic (PM) emissions. The latter is responsible for even worse air pollution by releasing highly toxic gases such as Mercury and Polychlorinated Biphenyls, Furan and Dioxins, etc., which can contaminate land, foods and water resources through secondary cycles. Therefore, a cost-efficient and technologically viable solution is required to address plastic waste emissions by developing renewable materials such as renewable polymers .
The ability to calculate the exchange rates between different phases and phase transitions in gas-liquid-solid particle flow systems, in a computationally affordable manner, is the key to success in such endeavours. To date, such predictive knowledge and tools do not exist.
This project addresses this issue by developing predictive computational toolsets for unsteady and three-dimensional numerical simulations for flow in dense melting particle flows. We use a fully resolved particle-particle and particle-fluid simulations approach (including the phase-chaining particles with substantial deformation and topology change due to melting and agglomeration) to fill the gaps in experimentally unresolved data.
Results, along with the experimental data, will be used to develop new sub-models for engineering calculations. The sub-models will be implanted in our in-house LES and URANS solvers for engineering modelling.
Using the existing experimental test rig at UoB's unique Positron Emission Particle Tracking facility, the exchange rates of mass, momentum and heat at various particle loads, sizes and topologies are quantified. Using our in-house DNS code, the particle-particle and particle-fluid interactions are investigated in unprecedented detail. Results, along with experimental data, are interpreted, and sub-models for engineering calculations are developed.
The scope of validity of each model is discussed and involving model constants are determined by comparing the results with those from existing models. Results are further processed, new engineering calculations are proposed, and our in-house LES/URANS-DEM solvers are updated accordingly. The solver is used to quantify the role of device topology and particle feedstock size/shape distributions on the melting/conversion rates of the device. A new computational-based design and optimisation procedure is proposed.
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