PhD Research Studentships

Physics-based Multi-scale Modelling of Multi-Material Additive Manufacturing

Supervisor: Chinnapat PANWISAWAS
Apply by:31 May 2024
Start in:September (Semester 1)

Description

Project Details

Additive manufacturing (AM) is emerging as a promising alternative for designing multi-material parts for complex geometries in engineering applications; especially in the biomedical sector. The challenge lies in process control, laser-matter interaction, melt pool dynamics and material behaviour [1-4].  The composition-process control is vital for predicting laser power-time-temperature processing window and final quality. A high-fidelity thermal-chemical-fluid modelling approach for accurate tracking of surface shape, thermo-capillary dynamics and vaporisation will be developed including multi-species formulations for multi-material simulation.

This project aims to develop the novel AM computational model for multi-material manufacturing in advanced materials for repair and biomedical application. This will involve;

  1. Digital materials design of composition-process relationship to optimise the chemistry and processing condition to obtain the high integrity parts.
  2. Development of microstructure-property relationship using thermal-chemical-fluid flow characteristic and the subsequent solidification, specifically to rationalise the variation of AM microstructures resulting from powder-heat source reaction – porosity, mass loss rate and interface mixing.
  3. Validation of models using high-speed in situ X-ray synchrotron radiography or high-speed photography to capture the thermal-fluid flow during AM. This includes tracking microstructural features emerging at the multi-material interface and between individual powder particles of same metal. Post-AM investigation of the microstructures using electron microscopy.

Essential skills for the post include, but are not limited to:

  • Computational fluid dynamics using volume-of-fluid (VOF) method;
  • Phase-field and/or cellular automata finite element calculation;
  • Crystal plasticity finite element calculation;
  • Reduced-order or data-driven modelling; and
  • Proficiency in programming languages, e.g. Python, C/C++, and/or MATLAB.

Utilising both computational and experimental data, the PhD student will be trained to have skills in computational additive manufacturing, data analytics and materials design.

The successful PhD candidate will have full access to the SEMS’ advanced microscopy centre as well as mechanical testing facilities. The candidate may also collaborate with project partners, including the University of Oxford, University College London and Imperial College London and the Science and Technology Facility Council (STFC). The developed computational model will be validated experimentally and then used to predict scatter in processing, microstructure and property in AM, specifically for repair and biomedical application.

References

[1] C. Panwisawas, et al. (2020) Metal 3D printing as a disruptive technology for superalloys. Nature Communications 11:2327. DOI: 10.1038/s41467-020-16188-7

[2] J. Shinjo and C. Panwisawas (2021) Digital materials design by thermal-fluid science for multi-metal additive manufacturing. Acta Materialia 210:116825. DOI: 10.1016/j.actamat.2021.116825

[3] J. Shinjo and C. Panwisawas (2022) Chemical species mixing during direct energy deposition of bimetallic systems using titanium and dissimilar refractory metals for repair and biomedical applications. Additive Manufacturing 51:102654. DOI: 10.1016/j.addma.2022.102654

[4] J. Shinjo, A. Kutsukake, A.S. Arote, S. Ueki, Y.T. Tang, R.C. Reed, C. Panwisawas (2023) Physics-based thermal-chemical-fluid-microstructure modelling of in-situ alloying using additive manufacturing: Composition-microstructure control. Additive Manufacturing, 64:103428. DOI: 10.1016/j.addma.2023.103428

Funding

Funded by: Queen Mary Research
UK students only.

Eligibility

  • The minimum requirement for this studentship opportunity is a good honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of 6.0 in Writing and 5.5 in all sections (Reading, Listening, Speaking).
  • Candidates are expected to start in September (Semester 1).
  • SEMS and Principal-funded studentships: this studentship arrangement covers home tuition fees and provides an annual stipend for up to three years (currently set at the 2023/24 stipend rate of £20,622 pa)
  • Note that Queen Mary Research Studentships cover home-rated tuition fees only (See: www.welfare.qmul.ac.uk/money/feestatus/ for details)
  • Overseas applicants would be required to meet the difference between home and international tuition fees

Contact

For informal enquiries about this opportunity, please contact Chinnapat PANWISAWAS.

Apply

Start an application for this studentship and for entry onto the PhD Materials Science full-time programme (Semester 1 / September start):

Apply Now »

Please be sure to quote the reference "SEMS-PHD-595" to associate your application with this studentship opportunity.

Related website:https://www.sems.qmul.ac.uk/staff/c.panwisawas
Keywords:Artificial Intelligence, Data Science, Fluid Mechanics, Manufacturing, Mechanical Engineering, Solid Mechanics, Ceramics, Metallurgy, Mathematical Modelling, Computational Physics