###Optimal design and operation of energy-efficient and sustainable distillation processes
Project ID: 2228bd1119 (You will need this ID for your application)
Research Theme: Manufacturing The Future
UCL Lead department: Chemical Engineering
Lead Supervisor: Eva Sorensen
Project Summary:
The world is currently facing significant challenges related to sustainability, human health and availability of food and water. Chemical process industries play a critical role in addressing these challenges, particularly those related to decarbonisation, the reduction of CO2 emissions and the use of renewable energy. Distillation has been the separation workhorse for these industries for over a century and is by far the most important separation method currently used, accounting for over 90% of all separations in the chemical and refining industries. And distillation will continue to be the dominant separation method for the foreseeable future. However, considerable effort is needed to make the process more energy efficient, to move beyond heating sources using traditional fossil fuels and to switch towards renewable energy sources.
The project will be of interest to anyone with a desire to contribute to making the chemical process industries more sustainable, particularly related to energy reduction, energy integration and the use of renewable energy sources. You will apply advanced mathematical modelling and optimisation techniques to consider novel methods of process intensification applied to distillation, including novel column designs and operation, while also considering controllability and operational flexibility under uncertainty. You will be working within the Sargent Centre for Process Systems Engineering at UCL.
We are seeking a candidate with an interest in becoming an expert in process intensification applied to the chemical process industries and a desire to contribute to a more sustainable and energy-efficient society. The successful applicant must hold a minimum 2:1 MEng/MSc or equivalent degree in Chemical Engineering, or other areas pertinent to the project. An understanding of process systems engineering methodologies is required and prior experience within mathematical modelling, optimisation and/or control is desirable although not essential.