Preliminary Study on Improvement of Surface Characteristics of Stellite21 Deposited Layer by Powder Feeding Type of Direct Energy Deposition Process Using Plasma Electron Beam

2016 ◽  
Vol 33 (11) ◽  
pp. 951-959 ◽  
Author(s):  
Dong-In Kim ◽  
Ho-Jin Lee ◽  
Dong-Gyu Ahn ◽  
Jin-Seok Kim ◽  
Eun Goo Kang
Keyword(s):  
Electron Beam ◽  
Energy Deposition ◽  
Surface Characteristics ◽  
Deposition Process ◽  
Plasma Electron ◽  
Direct Energy Deposition ◽  
Feeding Type ◽  
Direct Energy ◽  
Preliminary Study ◽  
Powder Feeding

Multi-physics modeling of direct energy deposition process of thin-walled structures: defect analysis

2021 ◽  
Vol 67 (4) ◽  
pp. 1229-1242
Author(s):  
Shuhao Wang ◽  
Lida Zhu ◽  
Yichao Dun ◽  
Zhichao Yang ◽  
Jerry Ying Hsi Fuh ◽  
...  
Keyword(s):  
Energy Deposition ◽  
Deposition Process ◽  
Defect Analysis ◽  
Direct Energy Deposition ◽  
Thin Walled Structures ◽  
Direct Energy ◽  
Thin Walled ◽  
Physics Modeling

Direct energy deposition metamodeling using a meshless method

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Boussad Abbes ◽  
Tahar Anedaf ◽  
Fazilay Abbes ◽  
Yuming Li
Keyword(s):  
Surrogate Model ◽  
Manufacturing Process ◽  
Laser Power ◽  
Energy Deposition ◽  
Feeding Rate ◽  
Maximum Temperature ◽  
Direct Energy Deposition ◽  
Content Type ◽  
Direct Energy ◽  
Powder Feeding

Purpose Direct energy deposition (DED) is an additive manufacturing process that allows to produce metal parts with complex shapes. DED process depends on several parameters, including laser power, deposition rate and powder feeding rate. It is important to control the manufacturing process to study the influence of the operating parameters on the final characteristics of these parts and to optimize them. Computational modeling helps engineers to address these challenges. This paper aims to establish a framework for the development, verification and application of meshless methods and surrogate models to the DED process. Design/methodology/approach Finite pointset method (FPM) is used to solve conservation equations involved in the DED process. A surrogate model is then established for the DED process using design of experiments with powder feeding rate, laser power and scanning speed as input parameters. The surrogate model is constructed using neutral networks (NN) approximations for the prediction of maximum temperature, clad angle and dilution. Findings The simulations of thin wall built of Ti-6Al-4V titanium alloy clearly demonstrated that FPM simulation is successful in predicting temperature distribution for different process conditions and compare favorably with experimental results from the literature. A methodology has been developed for obtaining a surrogate model for DED process. Originality/value This methodology shows how to achieve realistic simulations of DED process and how to construct a surrogate model for further use in optimization loop.

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