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Numerical Simulation and Experimental Characterization of Metal Additive Manufacturing

Submission Deadline: 31 December 2024 View: 149 Submit to Special Issue

Guest Editors

Prof. Wu-Gui Jiang, Nanchang Hangkong University, China
A.Prof. Lv Zhao, Huazhong University of Science and Technology, China  
Dr. Juan Guillermo Santos Macías, IMDEA Materials Institute, Spain


Summary

Metal-based additive manufacturing parts make up a significant and growing proportion of 3D printing, with increasingly diverse areas of application in the medical, aerospace, and automotive sectors.


Many factors, including materials and processes, and their expanding use as final or structural parts have contributed to this growth and have led to the need for specialized research in this field, which is of importance in many branches of engineering.


It is well known that several characteristics of printed parts, such as mechanical properties, depend on printing parameters. Therefore, analysis of the influence of manufacturing parameters on printed parts is a key factor in order to optimize the printing process as well as to predict and understand the material properties.


We encourage scientists and engineers to submit papers for inclusion in this Special Issue. There are no restrictions on the type of manufacture, Metal or field of application. Papers on theory, experiments, design, simulation, etc. will be considered for publication, and we expect that many will contain aspects of all of these.


A non-exhaustive list of possible items would be:

• Process parameters

• Experimental testing

• Constitutive models

• Numerical simulation

• Discrete element method

• Finite element analysis

• Computational fluid dynamics

• Phase field simulation

• Cellular automata simulation

• Molecular dynamics

• Machine learning

• Static and impact strength

• Fatigue and fracture


Keywords

• Additive manufacturing
• Numerical simulation
• Experimental testing
• Discrete element method
• Finite element analysis
• Computational fluid dynamics
• Phase field simulation
• Cellular automata simulation
• Molecular dynamics
• Machine learning

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