journal article·2024-02Open access

Material and process invariant scaling laws to predict porosity of dense and lattice structures in laser powder bed fusion

Alexander Großmann, Manuel Rexer, Matthias Greiner, Guillaume Meyer, Jan Mölleney, Leonie Kohn, Vincenzo Abbatiello, Peter F. Pelz, Christian Mittelstedt

Materials & Design· Volume 238

Abstract

Scaling laws represent an efficient way to describe complex physical phenomena efficiently and reliably by simplified relative quantities, which are holistic in the sense that they are invariant to changes in scale and therefore often universal. During part manufacturing in laser powder bed fusion additive manufacturing several such complex physical phenomena arise leading to unstable melt pool behavior and part porosity. Correlating processing parameters with melt pool quantities and eventually part properties such as porosity computationally efficiently can enable real-time build failure detection and process adaption leading to zero scrap rates in additive manufacturing. The efficient and reliable process-property correlation for dense materials is an ongoing field of research, whereas architected cellular and lattice structures, which are becoming more and more relevant in the context of additive manufacturing are rarely considered in this regard. In this contribution, a dimensionless number and the corresponding scaling law are derived to describe the correlation between porosity and process parameters for components manufactured by laser powder bed fusion. The scaling law is tested and validated for the commonly used alloys Ti-6Al-4V and AlSi10Mg on both dense and lattice structures regarding its suitability to predict the type and amount of porosity in additively manufactured components. The objective of this work is to foster reliable and predictable part quality and enable quality-driven build rate optimization.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Additive Manufacturing Materials and Processes · Additive Manufacturing and 3D Printing Technologies · Manufacturing Process and Optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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