CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition PhD

About the Project

We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research opportunity focuses on advancing the field of large-scale additive manufacturing, utilising metal wire as the feedstock and electric arc as the heat source. The project aims to enhance our understanding of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field, ultimately optimising the deposition process.

Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace, energy, and automotive. Among its variants, wire-arc directed energy deposition (WA-DED) is emerging as an increasingly compelling approach for building large-scale structural components. This process involves feeding a metal filler wire, either coaxially or off-axis, into an electric arc to create a molten pool that solidifies on a substrate, enabling the layer-by-layer construction of 3D objects. The temperature field generated by the interaction between the arc and the material plays a critical role in determining the microstructure, residual stress, and distortion of the built parts—all of which profoundly affect their mechanical properties and overall performance. Therefore, understanding the temperature field and developing effective thermal control techniques are vital to ensuring a high-quality WA-DED process.

Finite element analysis (FEA) is widely used to predict the temperature field during the WA-DED process. Traditional FEA models rely heavily on empirical heat source definitions, such as the double ellipsoidal model, to represent energy input. While effective in reproducing the temperature field for analysing residual stresses and distortions after experimental calibration, these models lack a direct correlation with process parameters, limiting their ability to predict temperature fields under varying process conditions. The transferred arc energy distribution becomes particularly complex in scenarios like parallel-pass deposition, thin-wall deposition, and off-centre or out-of-position deposition. Additionally, FEA models are focused on thermal conduction in solid medium and often overlook the impact of liquid metal convection within the molten pool. Although using an artificial compensation through calibration with experiments can improve the temperature prediction, the predictive accuracy is still limited. In contrast, computational fluid dynamics (CFD) models can capture the arc physics and molten pool dynamics, including arc energy transfer and liquid metal convection within the molten pool. However, these models are computationally intensive and impractical for widespread simulations of large-scale part deposition.

This project aims to develop a novel FEA-based approach that incorporates realistic energy input linked to arc physics and equivalently accounts for the effects of liquid metal convection on temperature predictions. This innovative FEA approach will be informed by small-scale, high-fidelity CFD simulations, providing detailed insights into transferred arc energy distribution, molten pool behaviour, and their relationship with process parameters. The key research objectives and activities include:

• Developing a CFD model to analyse arc physics and establish correlations between transferred energy distribution and deposition conditions (including WA-DED process parameters, underlying material geometry and process environment).
• Integrating process-dependent transferred arc energy distributions into an improved heat source model for FEA simulations.
• Creating an FEA-based method to approximate the CFD-revealed effects of liquid metal convection on molten pool temperature predictions.
• Designing and conducting instrumented WA-DED experiments to validate the developed models.
• Applying the CFD-informed FEA model to predict and control temperature fields for building parts with representative geometries in industrial applications.

This integrated modelling framework seeks to enhance the predictivity, accuracy and applicability of FEA for WA-DED, enabling more efficient design and control of large-scale additive manufacturing processes.

The student will be based at the Welding and Additive Manufacturing Centre (WAMC), a renowned hub for impactful research into advanced fusion-based processing and manufacturing methods. The Centre's contributions to industry are demonstrated through its extensive MSc and PhD research initiatives and its ongoing technology development programs in large-scale additive manufacturing. This project will be closely aligned with the ATI research program (I-Break: Wire-based DED Technology Maturation and Landing Gear Application) and other industrial research projects within WAMC. The student will become part of a diverse and dynamic research community at WAMC, fostering collaboration and innovation. Additionally, there will be opportunities to work with WAMC’s industrial partners, such as WAAM3D and members of WAAMMat, gaining valuable industry experience and exposure.

The student is expected to acquire the following (including but not limited to) knowledge and skills from the research in this project:

• Techniques, requirements, and applications of metal additive manufacturing
• Analysis of the temperature evolution, distribution and control in wire based additive manufacturing
• Calibration and validation experiments for modelling
• Computational fluid dynamics techniques
• Finite element analysis method
• Reviewing literature, planning and managing research, writing technical report / paper, presenting in meetings / conferences, teamwork, etc.

Entry requirements

Applicants should hold the equivalent of a first or second-class UK honours degree in a related discipline, such as mechanical, manufacturing, or materials engineering. International candidates must also meet the English language requirements set by Cranfield University. This project is ideal for individuals with a strong interest in modelling and manufacturing, along with a foundational understanding of arc physics, fluid flow, and heat transfer. Previous experience with thermal processes or additive manufacturing would be highly advantageous. The successful candidate should demonstrate self-motivation, proactivity, and good communication and teamwork skills.

Funding

Self-funded. The cost for running experiments and accessing to research facilities will be supported by the Welding and Additive Manufacturing Centre.

How to apply

Name: Dr Yongle Sun

Email: Yongle.Sun@cranfield.ac.uk

If you are eligible to apply for this studentship, please complete the online application form.