MANUFACTURING NOVEL HEAT TRANSFER DEVICES BY SELECTIVE LASER MELTING

Equipment ◽  
2006 ◽  
Author(s):  
S. Tsopanos ◽  
M. Wong ◽  
I. Owen ◽  
C. J. Sutcliffe
2007 ◽  
Vol 254 (4) ◽  
pp. 975-979 ◽  
Author(s):  
A.V. Gusarov ◽  
I. Yadroitsev ◽  
Ph. Bertrand ◽  
I. Smurov

Author(s):  
Mohammad Masoomi ◽  
Xiang Gao ◽  
Scott M. Thompson ◽  
Nima Shamsaei ◽  
Linkan Bian ◽  
...  

Selective Laser Melting (SLM), a laser powder-bed fusion (PBF-L) additive manufacturing method, utilizes a laser to selectively fuse adjacent metal powders. The powders are aligned in a bed that moves vertically to allow for layer-by-layer part construction-Process-related heat transfer and thermal gradients have a strong influence on the microstructural features, and subsequent mechanical properties, of the parts fabricated via SLM. In order to understand and control the heat transfer inherent to SLM, and to ensure high quality parts with targeted microstructures and mechanical properties, comprehensive knowledge of the related energy and mass transport during manufacturing is required. In this study, the transient temperature distribution within and around parts being fabricated via SLM is numerically simulated and the results are provided to aid in quantify the SLM heat transfer. In order to verify simulation output, and to estimate actual thermal gradients and heat transfer, experiments were separately conducted within a SLM machine using a substrate with embedded thermocouples. The experiments focused on characterizing heat fluxes during initial deposition on an initially-cold substrate and during the fabrication of a thin-walled structure built via stainless steel 17-4 powders. Results indicate that it is important to model heat transfer thorough powder bed as well as substrate.


2019 ◽  
Vol 3 (3) ◽  
pp. 62 ◽  
Author(s):  
Fyrillas ◽  
Ioannou ◽  
Papadakis ◽  
Rebholz ◽  
Doumanidis

In this paper we introduce an analytical approach for predicting the melting radius during powder melting in selective laser melting (SLM) with minimum computation duration. The purpose of this work is to evaluate the suggested analytical expression in determining the melt pool geometry for SLM processes, by considering heat transfer and phase change effects with density variation and cylindrical symmetry. This allows for rendering first findings of the melt pool numerical prediction during SLM using a quasi-real-time calculation, which will contribute significantly in the process design and control, especially when applying novel powders. We consider the heat transfer problem associated with a heat source of power Q' (W/m) per unit length, activated along the span of a semi-infinite fusible material. As soon as the line heat source is activated, melting commences along the line of the heat source and propagates cylindrically outwards. The temperature field is also cylindrically symmetric. At small times (i.e., neglecting gravity and Marangoni effects), when the density of the solid material is less than that of the molten material (i.e., in the case of metallic powders), an annulus is created of which the outer interface separates the molten material from the solid. In this work we include the effect of convection on the melting process, which is shown to be relatively important. We also justify that the assumption of constant but different properties between the two material phases (liquid and solid) does not introduce significant errors in the calculations. A more important result; however, is that, if we assume constant energy input per unit length, there is an optimum power of the heat source that would result to a maximum amount of molten material when the heat source is deactivated. The model described above can be suitably applied in the case of selective laser melting (SLM) when one considers the heat energy transferred to the metallic powder bed during scanning. Using a characteristic time and length for the process, we can model the energy transfer by the laser as a heat source per unit length. The model was applied in a set of five experimental data, and it was demonstrated that it has the potential to quantitatively describe the SLM process.


2007 ◽  
Vol 13 (5) ◽  
pp. 291-297 ◽  
Author(s):  
Matthew Wong ◽  
Sozon Tsopanos ◽  
Chris J. Sutcliffe ◽  
Ieuan Owen

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