Numerical simulation on metallic additive manufacturing

In this work, a preliminary numerical assessment on the application of an additive manufactured hybrid metal/composite shock absorber panels to a military seat ejection system, has been carried out. The innovative character of the shock absorber concept investigated is that the absorbing system has a thickness of only 6 mm and is composed of a pyramid-shaped lattice core that, due to its small size, can only be achieved by additive manufacturing. The mechanical behaviour of these shock absorber panels has been examined by measuring their ability to absorb and dissipate the energy generated during the ejection phase into plastic deformations, thus reducing the loads acting on pilots. In this paper the effectiveness of a system composed of five hybrid shock absorbers, with very thin thickness in order to be easily integrated between the seat and the aircraft floor, has been numerically studied by assessing their ability to absorb the energy generated during the primary ejection phase. To accomplish this, a numerical simulation of the explosion has been performed and the energy absorbed by the shock-absorbing mechanism has been assessed. The performed analysis demonstrated that the panels can absorb more than 60% of the energy generated during the explosion event while increasing the total mass of the pilot-seat system by just 0.8%.

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Numerical simulation of the influence of the idle time on residual stress of walls deposited by wire + arc additive manufacturing

Rio Oil and Gas Expo and Conference ◽

10.48072/2525-7579.rog.2020.412 ◽

2020 ◽

Vol 20 (2020) ◽

pp. 412-413

Author(s):

Francisco Werley Cipriano Farias ◽

Augusto Veríssimo Passos ◽

Victor Hugo Pereira Moraes E Oliveira ◽

João da Cruz Payão Filho ◽

Diego Russo Juliano ◽

...

Keyword(s):

Numerical Simulation ◽

Residual Stress ◽

Additive Manufacturing ◽

Idle Time ◽

Wire Arc Additive Manufacturing

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Uncertainty Quantification in Metallic Additive Manufacturing Through Data-Driven Modelling Based on Multi-Scale Multi-Physics Models and Limited Experiment Data

Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation ◽

10.1115/msec2020-8379 ◽

2020 ◽

Author(s):

Zhuo Wang ◽

Chen Jiang ◽

Mark F. Horstemeyer ◽

Zhen Hu ◽

Lei Chen

Keyword(s):

Temperature Field ◽

Additive Manufacturing ◽

Uncertainty Quantification ◽

Surrogate Modeling ◽

Data Driven ◽

Modeling Framework ◽

High Quality ◽

Experimental Calibration ◽

Multi Scale ◽

Metallic Additive

Abstract One of significant challenges in the metallic additive manufacturing (AM) is the presence of many sources of uncertainty that leads to variability in microstructure and properties of AM parts. Consequently, it is extremely challenging to repeat the manufacturing of a high-quality product in mass production. A trial-and-error approach usually needs to be employed to attain a product with high quality. To achieve a comprehensive uncertainty quantification (UQ) study of AM processes, we present a physics-informed data-driven modeling framework, in which multi-level data-driven surrogate models are constructed based on extensive computational data obtained by multi-scale multi-physical AM models. It starts with computationally inexpensive metamodels, followed by experimental calibration of as-built metamodels and then efficient UQ analysis of AM process. For illustration purpose, this study specifically uses the thermal level of AM process as an example, by choosing the temperature field and melt pool as quantity of interest. We have clearly showed the surrogate modeling in the presence of high-dimensional response (e.g. temperature field) during AM process, and illustrated the parameter calibration and model correction of an as-built surrogate model for reliable uncertainty quantification. The experimental calibration especially takes advantage of the high-quality AM benchmark data from National Institute of Standards and Technology (NIST). This study demonstrates the potential of the proposed data-driven UQ framework for efficiently investigating uncertainty propagation from process parameters to material microstructures, and then to macro-level mechanical properties through a combination of advanced AM multi-physics simulations, data-driven surrogate modeling and experimental calibration.

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Numerical Simulation of Wire+arc Additive Manufacturing Process by GMAW Weld Pool Model

JOURNAL OF THE JAPAN WELDING SOCIETY ◽

10.2207/jjws.90.98 ◽

2021 ◽

Vol 90 (2) ◽

pp. 98-101

Author(s):

Yosuke OGINO

Keyword(s):

Numerical Simulation ◽

Additive Manufacturing ◽

Weld Pool ◽

Manufacturing Process ◽

Pool Model ◽

Wire Arc Additive Manufacturing

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Analysis of the Difference in Forming Precision of Different Non-metallic Additive Manufacturing Antennas

Lecture Notes in Electrical Engineering - Proceedings of the Seventh Asia International Symposium on Mechatronics ◽

10.1007/978-981-32-9437-0_98 ◽

2019 ◽

pp. 952-961

Author(s):

Jinwen Zhou ◽

Xingyu Chen

Keyword(s):

Additive Manufacturing ◽

Forming Precision ◽

Metallic Additive ◽

The Difference

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An Overview of Additive Manufacturing Technologies—A Review to Technical Synthesis in Numerical Study of Selective Laser Melting

Materials ◽

10.3390/ma13173895 ◽

2020 ◽

Vol 13 (17) ◽

pp. 3895 ◽

Cited By ~ 2

Author(s):

Abbas Razavykia ◽

Eugenio Brusa ◽

Cristiana Delprete ◽

Reza Yavari

Keyword(s):

Numerical Simulation ◽

Additive Manufacturing ◽

Selective Laser Melting ◽

Powder Bed Fusion ◽

Laser Melting ◽

Powder Bed ◽

Part Quality ◽

Melt Pool ◽

Wide Range ◽

Am Processes

Additive Manufacturing (AM) processes enable their deployment in broad applications from aerospace to art, design, and architecture. Part quality and performance are the main concerns during AM processes execution that the achievement of adequate characteristics can be guaranteed, considering a wide range of influencing factors, such as process parameters, material, environment, measurement, and operators training. Investigating the effects of not only the influential AM processes variables but also their interactions and coupled impacts are essential to process optimization which requires huge efforts to be made. Therefore, numerical simulation can be an effective tool that facilities the evaluation of the AM processes principles. Selective Laser Melting (SLM) is a widespread Powder Bed Fusion (PBF) AM process that due to its superior advantages, such as capability to print complex and highly customized components, which leads to an increasing attention paid by industries and academia. Temperature distribution and melt pool dynamics have paramount importance to be well simulated and correlated by part quality in terms of surface finish, induced residual stress and microstructure evolution during SLM. Summarizing numerical simulations of SLM in this survey is pointed out as one important research perspective as well as exploring the contribution of adopted approaches and practices. This review survey has been organized to give an overview of AM processes such as extrusion, photopolymerization, material jetting, laminated object manufacturing, and powder bed fusion. And in particular is targeted to discuss the conducted numerical simulation of SLM to illustrate a uniform picture of existing nonproprietary approaches to predict the heat transfer, melt pool behavior, microstructure and residual stresses analysis.

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