Dr L Mazzei
1 year ago
An Advanced Computational Modelling Framework for the Design and Optimization of Agitated Filter Dryers University College London in United Kingdom
Degree Level
PhD
Field of study
Mechanical Engineering
Funding
Fully Funded
Deadline
Expired
Country
United Kingdom
University
University College London

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Where to contact
Official Email
Keywords
Mechanical Engineering
Experimental Physics
Chemical Engineering
Materials Science
Catalysis
Fluid Mechanics
Industrial Engineering
Computational Fluid Dynamics
Process Engineering
Experimental Medicine
Process Control
Pharmaceutical Science
Pharmaceutical Engineering
Particle Technology
Multiphase Flow
Experimental Data
Population Balance
Particle Size
Reduced-order Model
Multiphysics Phenomena
Batch Rejection
Right-first-time Manufacturing
Agitated Filter Dryers
Pharmaceutical Ingredients
International Conferences
Peer-reviewed Journal Articles
Crystallization Process
Solid-liquid Mixing
About this position
Vacancy informationThe UCL Department of Chemical Engineering is one of the top research and teaching departments in the UK and has world-class standing. The department offers undergraduate and postgraduate programmes and has an extensive research portfolio across a wealth of areas, from the molecular scale to the scale of industrial plants. It hosts 32 academics whose research is collaborative, ground-breaking and focused on solving societal problems.The Chemical Engineering Department is seeking an enthusiastic and dedicated PhD student to research the design and optimization of agitated filter dryers via advanced computational fluid dynamics modelling. This project is in collaboration with AstraZeneca, a global pharmaceutical company with strong focus on research and development (R&D). The post-holder will have the opportunity to share ideas and results with the industrial partner and collaborate with its R&D team.Studentship descriptionParticle size distribution (PSD) is a critical quality attribute in the production of active pharmaceutical ingredients (APIs). Owing to particle attrition, breakage and/or agglomeration, in agitated filter dryers the PSD is prone to deviate from specifications. Failure to meet the required PSD can result in poor powder flowability, potentially leading to batch rejection. Because drying is a crucial final step in API manufacturing, controlling the PSD is critical. Batch rejection incurs significant costs and has substantial implications for sustainability. To address this challenge and enhance right-first-time manufacturing, this project aims to leverage modelling and simulation to understand more deeply the complex multiphysics phenomena occurring in agitated filter dryers. To characterize these unit operations, existing models are either too simplistic, lacking in detail, or too computationally expensive (e.g., discrete element methods). This project aims to model the isolation and drying of crystals from the mother liquor following the upstream crystallization process. The workflow involves constructing a detailed computational fluid dynamics (CFD) model for solid-liquid mixing. Subsequent stages will include incorporating population balance modelling (PBM) into the CFD model for describing the drying of the crystals. Additionally, the student will develop a reduced-order model (ROM) by combining data generated from the CFD/PBM simulations with experimental data provided by the industrial partner. This integrated approach aims to offer a more accurate representation of the complex phenomena involved, facilitating the effective control and optimization of agitated filter dryers.The post-holder will learn how to use multiphase CFD codes and post-process and interpret the results of the simulations, which will be validated against experimental data. The techniques and skills that the student will learn are transferable to technological problems relevant to several industrial sectors, e.g., healthcare and catalysis.The post-holder will present the research results at international conferences and in peer-reviewed journal articles of high international standing.Person specificationThe successful candidate must be a dedicated student who has completed a first-class degree at the MEng/MSc level in Chemical or Mechanical Engineering, Physics or a related discipline. Willingness to perform independently, yet within a collaborative environment, is a must. Demonstrable knowledge of research methods, multiphase flows, computational fluid dynamics and transport phenomena are desirable.EligibilityThe post is fully funded (stipend and UK fees) for 3.5 years. Overseas students may apply, provided they can independently cover the difference between UK and overseas tuition fees.Applications should be submitted through: https://evision.ucl.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RRDCENSING01&code2=0037 Please nominate Prof. Luca Mazzei as supervisor and include a statement of interest.For informal enquiries please contact Prof. Luca Mazzei at [email protected] .For further information on the MPhil/PhD course as well as the recruitment and selection process, please click on the link below:https://www.ucl.ac.uk/chemical-engineering/study/mphilphd
Funding details
Fully Funded
How to apply
? Interested candidates should contact the Chemical Engineering Department at UCL for more information.
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