Influence of Computational Grid and Deposit Volume on Residual Stress and Distortion Prediction Accuracy for Additive Manufacturing Modeling

Desmaison, Olivier; Pires, Pierre-Adrien; Levesque, George; Peralta, Alonso; Sundarraj, Suresh; Makinde, A.; Jagdale, Vijay; Megahed, Mustafa

doi:10.1007/978-3-319-57864-4_34

Cited by 12 publications

(4 citation statements)

References 7 publications

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“…The balance between accuracy and speed of computation is in line with studies reported in Ref. 22. The remaining discrepancy is expected to reflect the accuracy of the material behavior model used.…”

Section: Materials Consolidationsupporting

confidence: 83%

Numerical and Experimental Study of Ti6Al4V Components Manufactured Using Powder Bed Fusion Additive Manufacturing

Zielinski

Mindt

Düchting

et al. 2017

JOM

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Section: Materials Consolidationsupporting

confidence: 83%

Numerical and Experimental Study of Ti6Al4V Components Manufactured Using Powder Bed Fusion Additive Manufacturing

Zielinski

Mindt

Düchting

et al. 2017

JOM

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“…Using a mechanical analysis, the applied load will be equivalent to the thermal strain supplied by the process (due to the thermal contraction/expansion). Previous works were able to successfully estimate the workpiece distortion (and, consequently, the residual stresses) using similar approaches, validating the numerical results by experimental measurements [25]. Fig.…”

Section: Residual Stresses In Additive Manufacturingsupporting

confidence: 79%

Fatigue Behavior of Metallic Components Obtained by Topology Optimization for Additive Manufacturing

Fiorentin

Oliveira

Pereira

et al. 2020

Frattura Ed Integrità Strutturale

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The main goal of the present research is to propose an integrated methodology to address the fatigue performance of topology optimized components, produced by additive manufacturing. The main steps of the component design will be presented, specially the methods and parameters applied to the topology optimization and the post-smoothing process. The SIMP method was applied in order to obtain a lighter component and a suitable stiffness for the desired application. In addition, since residual stresses are intrinsic to every metallic additive manufacturing process, the influence of those stresses will be also analyzed. The Laser Powder Bed Fusion was numerically simulated aiming at evaluating the residual stresses the workpiece during the manufacturing process and to investigate how they could influence the fatigue behavior of the optimized component. The effect of the built orientation of the workpiece on the residual stresses at some selected potential critical points are evaluated. The final design solution presented a stiffness/volume ratio nearly 6 times higher when compared to the initial geometry. By choosing the built orientation, it is possible impact favorably in the fatigue life of the component.

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“…We study the influence of the powder bed characteristics (particle size distribution and spatial arrangement) on the SLM process using high fidelity models recently developed and validated [2][3][4][5]. Since the spatial arrangement of the particles in the powder bed cannot be manipulated or easily measured in a production 3D printer, the study of the impact of those parameters on the SLM process is investigated by comparing the melting behaviour of a BCC arrangement of powder particles with that of a powder bed obtained by modelling the racking process [6].…”

Section: Introductionmentioning

confidence: 99%

Influence of Powder Bed Characteristics on Material Quality in Additive Manufacturing

Zielinski

Vervoort

Mindt

et al. 2017

Berg Huettenmaenn Monatsh

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Abstract:In powder bed based Additive Manufacturing (AM) processes like Selective Laser Melting (SLM) or Electron Beam Melting (EBM), the spatial distribution of the individual powder particles is typically unknown. Nevertheless, the distribution of particles in the heat affected zone defines the thermophysical properties of the region being processed by the heat source and therefore plays a crucial role in heat transfer processes. In this work, the spatial distribution of individual particles and their influence on the AM process is numerically investigated. Two powder bed configurations are compared: One powder bed is generated using the discrete element method (DEM) to model the coating process; the second powder bed is arranged in the BCC structure. The melting and solidification of both configurations are modelled. The predicted melt pool dimensions are compared with experimentally determined values. The results indicate that modelling the coating process is necessary to ensure accurate modelling of the heat source powder bed interaction as well as an accurate prediction of the melt pool characteristics. Keywords

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Influence of Computational Grid and Deposit Volume on Residual Stress and Distortion Prediction Accuracy for Additive Manufacturing Modeling

Cited by 12 publications

References 7 publications

Numerical and Experimental Study of Ti6Al4V Components Manufactured Using Powder Bed Fusion Additive Manufacturing

Numerical and Experimental Study of Ti6Al4V Components Manufactured Using Powder Bed Fusion Additive Manufacturing

Fatigue Behavior of Metallic Components Obtained by Topology Optimization for Additive Manufacturing

Influence of Powder Bed Characteristics on Material Quality in Additive Manufacturing

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