Finding optimum mixing condition in an anaerobic digester using computational fluid dynamics approach for sustainable production of chemicals and materials

Chemicals such as pharmaceuticals, fertilizers and reagents are ubiquitous in our modern society which are mainly produced from fossil fuels, e.g., petroleum and natural gas. In contrast, production of the essential chemicals from biomass by anaerobic digestion offers us a sustainable approach which also contributes to the reduction of CO2 in the atmosphere. In this approach, organic waste such as food residue, animal manure is converted to useful chemicals in an anaerobic digester (i.e., in the absence of oxygen) by the microorganisms. The conversion of the biomass to useful chemicals is largely affected by the mass and heat transfers among enzymes, microorganisms and substrate in the digester. Thus, adequate mixing is required to accelerate mass and heat transfers and therefore the reaction kinetics. Optimum mixing will also contribute to substantially reduce the size of the reactor reducing the footprint of the system.
This project will investigate mixing in anaerobic digesters using advanced techniques such as mesoscale and particle-resolved simulations that have never been used before to simulate anaerobic digesters. This study will be aimed at identifying the optimum mixing conditions (e.g., impeller type, size, speed and location) in anaerobic digesters to maximise interaction of the various microbial communities and maximise the degradation of the waste and the conversion to products. Anaerobic digester can be treated as a multiphase reactor. Ideally one would like to increase solid concentration in the reactor to reduce the reactor size. However, high solid content will result in high viscosity leading to poor mass and heat transfers. Thus, one of the objectives of this study would be to find the optimum solid loading.
In regards to the numerical simulation, the major challenge is the dynamic information exchange or the coupling between the solid and fluid phases in the digester. An Eulerian-Lagrangian approach will be used for this purpose. In this approach, the fluid phase is treated as a continuum while the particles are tracked individually or as clusters through the fluid by considering various forces acting on the particles. The mesoscopic simulation technique such as lattice Boltzmann method (LBM) will be used in an Eulerian grid to solve the fluid flow. If the resolution of the Eulerian grid is sufficiently high so that it allows the calculation of the flow around particles by applying the no-slip condition on the particle surface, it is known the particle-resolved simulation. This particle-resolved technique can be computationally forbidding for industrial scale due to its computational expenses. In contrast, the particle-unresolved simulation allows the use of coarser grid where the flow around the particles is not resolved. This simulation technique, however, requires the use of closure relations for hydrodynamic forces and torques on the particles as a function of local flow conditions (e.g., Reynolds number and Stokes number). In this project, both the particle-resolved and particle-unresolved techniques will be explored depending on the computational cost of the process. Finally, reaction kinetics describing the biomass conversion will coupled with the mixing model. This study will provide theoretical support for design, optimization and scale-up of anaerobic digesters for sustainable production of chemicals and materials.

Selection will be made on the basis of academic merit. The successful candidate should have, or expect to have, an Honours Degree at 2.1 or above (or equivalent) in Chemical Engineering, Mechanical Engineering, Applied Mathematics, Applied Physics or related areas.

Knowledge of numerical methods, fluid dynamics and computer programming would be advantageous

APPLICATION PROCEDURE:
Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php
• Apply for the Degree of Doctor of Philosophy in Chemical Engineering
• State the name of the lead supervisor as the Name of Proposed Supervisor
• State ‘Leverhulme CDT in Sustainable Production of Chemicals and Materials’ as the Intended Source of Funding
• State the exact project title on the application form