Multi-Resolution SPH Simulation of a Laser Powder Bed Fusion Additive Manufacturing Process

Afrasiabi, Mohamadreza; Lüthi, C.; Bambach, Markus; Wegener, Konrad

doi:10.3390/app11072962

Cited by 44 publications

(18 citation statements)

References 52 publications

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“…Figure 9 presents the remelting depth as a function of laser power and scanning speed as calculated by the heat conduction model. The depth of the melt pool rises nearly linearly with increased laser power P and reduced scanning speed v , which is similar to the findings of Afrasiabi et al [ 20 ]. The results confirm that once the heat source provides sufficient energy to melt the material, an increase of the line energy

generally leads to larger melt pool dimensions.…”

Section: Resultssupporting

confidence: 89%

Laser Remelting Process Simulation and Optimization for Additive Manufacturing of Nickel-Based Super Alloys

et al. 2021

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Nickel-based super alloys are popular for applications in the energy and aerospace industries due to their excellent corrosion and high-temperature resistance. Direct metal deposition (DMD) of nickel alloys has reached technology readiness for several applications, especially for the repair of turbomachinery components. However, issues related to part quality and defect formation during the DMD process still persist. Laser remelting can effectively prevent and repair defects during metal additive manufacturing (AM); however, very few studies have focused on numerical modeling and experimental process parameter optimization in this context. Therefore, the aim of this study is to investigate the effect of determining the remelting process parameters via numerical simulation and experimental analyses in order to optimize an industrial process chain for part repair by DMD. A heat conduction model analyzed 360 different process conditions, and the predicted melt geometry was compared with observations from a fluid flow model and experimental single tracks for selected reference conditions. Subsequently, the remelting process was applied to a demonstrator repair case. The results show that the models can well predict the melt pool shape and that the optimized remelting process increases the bonding quality between base and DMD materials. Therefore, DMD part fabrication and repair processes can benefit from the remelting step developed here.

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generally leads to larger melt pool dimensions.…”

Section: Resultssupporting

confidence: 89%

Laser Remelting Process Simulation and Optimization for Additive Manufacturing of Nickel-Based Super Alloys

et al. 2021

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“…They highlighted in their paper that SPH, contrary to the Eulerian numerical approaches used in previous studies (King et al , 2015a, Khairallah et al , 2016), can trivially track the motion of a specific material point at any time over the length of a simulation. Intending to speed up the simulation, Afrasiabi et al (2021) introduced spatial adaptivity to the SPH framework of Russell et al (2018) and achieved a significant enhancement in the computational performance of their code. A graphical summary of these results is shown in Figure 16, suggesting that the extension of particle-based PBF models from mono-material to multimaterial is straightforward and needs to be considered an immediate future work.…”

Section: Simulation Of Multimaterials Powder Bed Fusion Techniquesmentioning

confidence: 99%

Multimaterial powder bed fusion techniques

Mehrpouya

Tuma

Vaneker

et al. 2022

RPJ

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Purpose This study aims to provide a comprehensive overview of the current state of the art in powder bed fusion (PBF) techniques for additive manufacturing of multiple materials. It reviews the emerging technologies in PBF multimaterial printing and summarizes the latest simulation approaches for modeling them. The topic of “multimaterial PBF techniques” is still very new, undeveloped, and of interest to academia and industry on many levels. Design/methodology/approach This is a review paper. The study approach was to carefully search for and investigate notable works and peer-reviewed publications concerning multimaterial three-dimensional printing using PBF techniques. The current methodologies, as well as their advantages and disadvantages, are cross-compared through a systematic review. Findings The results show that the development of multimaterial PBF techniques is still in its infancy as many fundamental “research” questions have yet to be addressed before production. Experimentation has many limitations and is costly; therefore, modeling and simulation can be very helpful and is, of course, possible; however, it is heavily dependent on the material data and computational power, so it needs further development in future studies. Originality/value This work investigates the multimaterial PBF techniques and discusses the novel printing methods with practical examples. Our literature survey revealed that the number of accounts on the predictive modeling of stresses and optimizing laser scan strategies in multimaterial PBF is low with a (very) limited range of applications. To facilitate future developments in this direction, the key information of the simulation efforts and the state-of-the-art computational models of multimaterial PBF are provided.

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“…To accelerate the simulations, model order reduction and proper orthogonal decomposition can be applied [ 66 ], however the computational time is still unacceptable for practical purposes. Research into adaptive refinement strategies for particle based simulations has just started and requires further investigations [ 67 ].…”

Section: Numerical Simulation and Machine Learning Of Metal Ammentioning

confidence: 99%

Digitisation of metal AM for part microstructure and property control

et al. 2022

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Metal additive manufacturing, which uses a layer-by-layer approach to fabricate parts, has many potential advantages over conventional techniques, including the ability to produced complex geometries, fast new design part production, personalised production, have lower cost and produce less material waste. While these advantages make AM an attractive option for industry, determining process parameters which result in specific properties, such as the level of porosity and tensile strength, can be a long and costly endeavour. In this review, the state-of-the-art in the control of part properties in AM is examined, including the effect of microstructure on part properties. The simulation of microstructure formation via numerical simulation and machine learning is examined which can provide process quality control and has the potential to aid in rapid process optimisation via closed loop control. In-situ monitoring of the AM process, is also discussed as a route to enable first time right production in the AM process, along with the hybrid approach of AM fabrication with post-processing steps such as shock peening, heat treatment and rolling. At the end of the paper, an outlook is presented with a view towards potential avenues for further research required in the field of metal AM.

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Multi-Resolution SPH Simulation of a Laser Powder Bed Fusion Additive Manufacturing Process

Cited by 44 publications

References 52 publications

Laser Remelting Process Simulation and Optimization for Additive Manufacturing of Nickel-Based Super Alloys

Laser Remelting Process Simulation and Optimization for Additive Manufacturing of Nickel-Based Super Alloys

Multimaterial powder bed fusion techniques

Digitisation of metal AM for part microstructure and property control

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