A discrete source model of powder bed fusion additive manufacturing thermal history
Significant attention has been focused on modeling of metallic additive manufacturing (AM) processes, with the initial aim of predicting local thermal history, and ultimately structure and properties. Existing models range greatly in physical complexity and computational cost, and the implications o...
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| Vydáno v: | Additive manufacturing Ročník 25; s. 485 - 498 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.01.2019
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| Témata: | |
| ISSN: | 2214-8604, 2214-7810 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Significant attention has been focused on modeling of metallic additive manufacturing (AM) processes, with the initial aim of predicting local thermal history, and ultimately structure and properties. Existing models range greatly in physical complexity and computational cost, and the implications of various simplifying assumption often go unassessed. In the present work, we first formulate a fast acting Discrete Source Model (DSM) capable of handling the complex processing often encountered in metal powder bed fusion AM. We then assess implications of the source representation, details of the numeric implementation, as well as effects of boundary conditions and thermophysical parameters. We verify the DSM implementation against simple numerical thermal predictions, calibrate it with single track deposit experiments, validate outputs against multitrack deposits, and finally quantify the scaling performance. The DSM is an effective means of quickly generating an estimate of the local thermal history induced by complex scan strategies when combined with arbitrary component geometry. While a number of approximations limit its quantitative accuracy, the inexpensive nature and ability to treat complex processing plans suggests it will be useful for screening and identification of regions experiencing anomalous thermal history. Such a capability is necessary to direct usage of higher fidelity, more expensive models and experimental resources. |
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| ISSN: | 2214-8604 2214-7810 |
| DOI: | 10.1016/j.addma.2018.12.004 |