Simulation of behavioural modification effects in suspension waste pipe flows.

In nuclear facilities around the UK, waste suspension flows transport legacy radioactive material between, e.g., historic ponds and interim storage facilities as part of decontamination processes. The waste treatment programme relies heavily on the retrieval of legacy sludges, often performed using circular cross-section pipelines which transport solid-liquid suspensions over significant distances. Presently, these systems suffer from lack of design data, which can potentially result in problems such as blockages and poor mass-transfer conditions. As such, these processes are performed using conservative process conditions as correcting issues downstream is extremely expensive and time consuming. These operations generally use high flow rates to avoid the potential for aggregate build-ups and blockages. However, this process leads to increased turbulence levels within the flow which increases wall deposition and particle-particle collision rates, and the need to process more waste material. In order to perform POCO operations successfully, it is crucial that these types of flows are understood and, as a result, better controlled. This project will investigate the application of behavioural modification techniques to suspension waste pipe flows.


First principle mathematical modelling techniques have been developed at Leeds to predict particle-laden flows with extreme accuracy. The use of Lagrangian particle tracking (LPT) coupled to direct numerical simulation provides a high accuracy predictive capability for studying waste transport systems. They also show great promise in generating knowledge surrounding the development and application of behavioural modification techniques in flows. For instance, the addition of polymer additives to slurries can help obtain desired flow conditions such as reduced agglomeration and/or deposition rates. Alternatively, to enhance downstream sedimentation, the addition of flocculation agents can also be employed.


With all these methods, however, there remain uncertainties of the long-term behaviour of both the fluid and particle phase, and work needs to be performed to generate understanding. This project will study these techniques for a range of simulated multiphase pipe flows with relevance to nuclear waste transport, such as empty pipes and pipes with bends and deposited beds. To predict potential issues and develop knowledge surrounding these flows, properties such as particle dispersion, flow rate, turbulence modulation and collision rates will be investigated to determine the way in which the modifications techniques affect the bulk properties of the system.


A further complication is that particles present in nuclear slurry flows are distributed widely in terms of diameter and shape. Sizes generally range between 1µm to 1mm, with previous studies exhibiting a range of different particle-fluid and particle-particle interaction mechanisms depending on size. Moreover, the particles are not necessarily spherical, with morphologies ranging from needle-like to disc-like, and other complex shapes. Advances in LPT techniques allow for methods of predicting both polydispersed and ellipsoidal particles, and calculations will be performed as part of the project to investigate their influences on the resulting flow dynamics and aggregation properties.


Finally, to study the addition of polymer additives at a more fundamental level, this project will use an established immersed boundaries method (IBM) to simulate binary or low-particle number interactions. The effect of polymer structurants on the particle-scale dynamics will be investigated to feed back to LPT agglomeration and collision models, improving their accuracy. This work will be supported by another PhD and a PDRA, which will complement the present study by providing both experimental data for validation purposes as well as knowledge from IBM simulations to aid in the development of LPT modelling.

Academic Lead: Mike Fairweather
Researcher: Bisrat Wolde
Location: University of Leeds