High-Throughput Numerical Investigation of Process Parameter-Melt Pool Relationships in Electron Beam Powder Bed Fusion

Breuning C, Böhm J, Markl M, Körner C (2023)


Publication Type: Journal article

Publication year: 2023

Journal

Book Volume: 4

Pages Range: 336-350

Issue: 3

DOI: 10.3390/modelling4030019

Abstract

 The reliable and repeatable fabrication of complex geometries with predetermined homogeneous properties is still a major challenge in electron beam powder bed fusion (PBF-EB). Although previous research identified a variety of process parameter–property relationships, the underlying end-to-end approach, which directly relates process parameters to material properties, omits the underlying thermal conditions. Since the local properties are governed by the local thermal conditions of the melt pool, the end-to-end approach is insufficient to transfer predetermined properties to complex geometries and different processing conditions. This work utilizes high-throughput thermal simulation for the identification of fundamental relationships between process parameters, processing conditions, and the resulting melt pool geometry in the quasi-stationary state of line-based hatching strategies in PBF-EB. Through a comprehensive study of over 25,000 parameter combinations, including beam power, velocity, line offset, preheating temperature, and beam diameter, process parameter-melt pool relationships are established, processing boundaries are identified, and guidelines for the selection of process parameters to the achieve desired properties under different processing conditions are derived.

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How to cite

APA:

Breuning, C., Böhm, J., Markl, M., & Körner, C. (2023). High-Throughput Numerical Investigation of Process Parameter-Melt Pool Relationships in Electron Beam Powder Bed Fusion. Modelling, 4, 336-350. https://dx.doi.org/10.3390/modelling4030019

MLA:

Breuning, Christoph, et al. "High-Throughput Numerical Investigation of Process Parameter-Melt Pool Relationships in Electron Beam Powder Bed Fusion." Modelling 4 (2023): 336-350.

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