Ryan Leeming

Biography:

During Ryan’s course, the projects he has worked on built a strong interest for environmental applications of chemical engineering, particularly that in the field of air quality. However, Ryan became highly interested in a product development module in his final year, leading to his application to the CP3 CDT. Ryan believes it will be an excellent place to explore the potential adjustments that can be made to the production of particulate-based products that would be more beneficial to the environment.

PhD: Model predictive control of industrial crystallisation processes

Improved optimisation and control of crystallisation processes are crucial for manufacturing high precision solid active ingredients with required properties, e.g. narrow crystal size distribution, high crystal purity and optimum crystal morphology, in a number of process industries including agrochemical and pharmaceutical. Advanced first principles model-based process optimisation and control is a powerful tool which can be applied in a cost-effective way to optimise process operating conditions and develop an accurate control algorithm to meet product specifications at different scale of operations from laboratory to manufacturing.

This research focuses on the development of a first principle Model Predictive Control (MPC) algorithm using an integrated experimental and modelling approach. Initially, this will require development of a mechanistic crystallisation process model based on a 1D population balance model using the gCRYSTAL software (Process Systems Enterprise Ltd.) to simulate industry representative crystallisation processes and optimise the process parameters using data to be obtained from experiments. This model will be integrated with an advanced MPC algorithm PharmaMV (Perceptive Engineering), which provides the multivariate control and monitoring platform for the online laboratory and pilot-scale crystallisation processes. The control system will be applied to crystallisation processes in order to achieve target product crystals size and shape distributions.

Research Project(s) during degree:

• MEng research project: Modelling of solvent stripping column in a post-combustion CO2 capture process, with Dr Tariq Mahmud and Professor Peter Heggs, Chemical & Process Engineering
  Ryan developed an algebraic model using Microsoft Excel that produced profiles of CO2 compositions and temperatures of the liquid and gas streams along the height of a stripping column. Experimental data from previous modelling experiments Ryan found during his research was applied and the results were compared to investigate whether different mass and heat transfer theories would improve the accuracy. Ryan selected heat transfer as his presentation focus and proposed a list of changes that should be investigated if the project is developed further.

Industrial experience/placements:

• Jul-Aug 2017: Research Summer Placement, University of Leeds
  During his eight-week placement in the School of Earth and Environment presented by the NERC, Ryan used IDL software to develop a model for the polluting gases emitted by Drax power station. The model produced plots of the surface concentrations of pollutants under different weather conditions. Ryan expanded upon the original scope of the project by averaging each plot per month and displaying them on a to-scale map with Drax at the centre, allowing me to see how surrounding urban areas were affected by pollution. In addition to a detailed report on his work, Ryan gave a presentation to professionals in the School about his findings.

Masters research project in year 1 of CDT:

• ‘Modelling behaviour of faceted crystals’ with Dr Xiadong Jia, Chemical & Process Engineering