Computational framework to model the selective laser sintering process

Selective laser sintering (SLS) is one of the most well-regarded additive manufacturing (AM) sub-processes, whose popularity has been increasing among numerous critical and demanding industries due to its capabilities, mainly manufacturing parts with highly complex geometries and desirable mechanical properties, with potential to replace other, more expensive, conventional processes. However, due to its various underlying multi-physics phenomena, the intrinsic complexity of the SLS process often hampers its industrial implementation. Such limitation has motivated academic interest in obtaining better insights into the process to optimize it and attain the required standards. In that regard, the usual experimental optimization methods are time-consuming and expensive and can fail to provide the optimal configurations, leading researchers to resort to computational modeling to better understand the process. The main objective of the present work is to develop a computational model capable of simulating the SLS process for polymeric applications, within an open-source framework, at a particle-length scale to assess the main process parameters’ impact. Following previous developments, virgin and used polymer granules with different viscosities are implemented to better represent the actual process feedstock. The results obtained agree with the available experimental data, leading to a powerful tool to study, in greater detail, the SLS process and its physical parameters and material properties, contributing to its optimization.This work was funded by National Funds through FCT, The Portuguese Foundation for Science and Technology, References UID/CTM/50025/2019 and UIDB/04436/2020, project SIFA— Sistema Inteligente de Fabricação Aditiva (POCI-01-0247-FEDER-047108) and European Regional Development Fund through the Operational Competitiveness and Internationalization Programme (COMPETE 2020)

Computational modelling of the selective laser sintering process

Additive Manufacturing (AM) has increased in popularity in numerous important and demanding industries due to the capability of manufacturing parts with complex geometries and reduced wastage. As one of its most popular techniques, selective laser sintering (SLS) is sought after by several industries that aim to replace conventional and more expensive processes. However, the SLS process is intrinsically complex due to the various underlying multi-physics phenomena and more studies are needed to obtain more insights about it. This has resulted in many academical interests to optimize the process and allow it to achieve industrial standards. Most of these optimization attempts are performed through experimental methods that are time-consuming, expensive and do not always provide the optimal configurations. This has led researchers to resort to computational modelling, aiming at better understanding the process to anticipate and fix the defects. The main objective of the present work was to develop a computational model capable of simulating the SLS process for polymeric applications, within an open-source framework, at particle length scale. Since distinct approaches are required for accurately simulating each step of the SLS process, different numerical methods were employed to develop a tool capable of studying the impact, in a representative section of the powder bed, of the physical parameters that can be adjusted in the process. The developed work comprises several steps, starting with an extensive study of the theoretical aspects of the SLS process, which aimed at the acquaintance with the underlying phenomena, process unwind, its parameters and their influence, as well as evaluating the existing limitations and challenges. This step was then followed by a detailed analysis of the most common employed models to represent the major phenomena and of the accuracy level of the approaches, based on the employed simplifications. A set of computational tools was then assessed and their built-in models were selected, when possible, according to the precedent literature review. Lastly, various tests were carried to obtain an experimental qualitative validation of the used code, to assure that the undetaken approach was adequate to simulate the process. The achieved developments represent a significant advance towards the detailed SLS process simulation. With the use of open-source software (LIGGGHTS e OpenFOAM), several studies were performed on a realistic powder bed section and, despite the absence of enough and more detailed experimental data, the simulation results are in agreement with the ones used for comparison. Overall, the accomplished work allowed to conclude that the employed tools constitute a great potential to study, in detail, the SLS process and its parameters influence and, therefore, contribute to its optimization.This work was funded by National Funds through FCT - Portuguese Foundation for Science and Technology, Reference UID/CTM/50025/2019 and UIDB/04436/2020, and project SIFA - Sistema Inteligente de Fabricação Aditiva (POCI-01-0247-FEDER-047108). The authors also acknowledge the support of the computational clusters Search-ON2 (NORTE-07-0162-FEDER-000086) and Minho Advanced Computing Center (MACC

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Comportamento de bananeiras submetidas a diferentes níveis de sombreamento.

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