Additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (B)
This Final Year Project (FYP) systematically investigates the optimization of process parameters within the Directed Energy Deposition (DED) technique of Additive Manufacturing (AM), focusing on the impacts of wall boundary conditions such as the Coefficient of Restitution (COR) and wall roughness....
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2024
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sg-ntu-dr.10356-1773422024-06-01T16:50:44Z Additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (B) Chua, Wei Bin Li Hua School of Mechanical and Aerospace Engineering LiHua@ntu.edu.sg Engineering Additive manufacturing Direct energy deposition Nozzle Computational fluid dynamics Simulation Coefficient of restitution Wall roughness This Final Year Project (FYP) systematically investigates the optimization of process parameters within the Directed Energy Deposition (DED) technique of Additive Manufacturing (AM), focusing on the impacts of wall boundary conditions such as the Coefficient of Restitution (COR) and wall roughness. Utilizing advanced Computational Fluid Dynamics (CFD) simulations, this study aims to enhance the accuracy and reliability of modeling DED processes, which are critical for high-quality manufacturing. Extensive simulations were conducted using various meshing strategies to ascertain their influence on simulation fidelity. The findings indicate that polyhedral meshing significantly improves simulation accuracy due to its superior handling of complex geometries and computational efficiency. Additionally, the research established that while the COR significantly affects particle behaviour within the nozzle, influencing energy dissipation and particle dispersion, wall roughness does not exhibit a notable impact on the DED outcomes. Bachelor's degree 2024-05-27T09:07:52Z 2024-05-27T09:07:52Z 2024 Final Year Project (FYP) Chua, W. B. (2024). Additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (B). Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/177342 https://hdl.handle.net/10356/177342 en B146 application/pdf Nanyang Technological University |
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Engineering Additive manufacturing Direct energy deposition Nozzle Computational fluid dynamics Simulation Coefficient of restitution Wall roughness Chua, Wei Bin Additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (B) |
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This Final Year Project (FYP) systematically investigates the optimization of process parameters within the Directed Energy Deposition (DED) technique of Additive Manufacturing (AM), focusing on the impacts of wall boundary conditions such as the Coefficient of Restitution (COR) and wall roughness. Utilizing advanced Computational Fluid Dynamics (CFD) simulations, this study aims to enhance the accuracy and reliability of modeling DED processes, which are critical for high-quality manufacturing.
Extensive simulations were conducted using various meshing strategies to ascertain their influence on simulation fidelity. The findings indicate that polyhedral meshing significantly improves simulation accuracy due to its superior handling of complex geometries and computational efficiency. Additionally, the research established that while the COR significantly affects particle behaviour within the nozzle, influencing energy dissipation and particle dispersion, wall roughness does not exhibit a notable impact on the DED outcomes. |
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Li Hua |
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Li Hua Chua, Wei Bin |
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Final Year Project |
author |
Chua, Wei Bin |
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Chua, Wei Bin |
title |
Additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (B) |
title_short |
Additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (B) |
title_full |
Additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (B) |
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Additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (B) |
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Additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (B) |
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additive manufacturing: direct-energy-deposition process parameters optimisation via simulation (b) |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/177342 |
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1800916253968171008 |