Aydogan Beytullah, Chou Kevin
Department of Industrial Engineering, J.B. Speed School of Engineering, University of Louisville, Louisville, KY 40292, USA.
Bayburt University, Bayburt 69000, Turkey.
Materials (Basel). 2024 Dec 5;17(23):5955. doi: 10.3390/ma17235955.
The simulation of additive manufacturing has become a prominent research area in the past decade. Process physics simulations are employed to replicate laser powder bed fusion (L-PBF) manufacturing processes, aiming to predict potential issues through simulated data. This study focuses on calculating surface roughness by utilizing 3D surface topology extracted from simulated data, as surface roughness significantly influences part quality. Accurately predicting surface roughness using a simulation remains a persistent challenge. To address this challenge, the L-PBF technique with two different cases (pre- and post-contouring) was simulated using two-step process physics simulations. The discrete element method was utilized to simulate powder spreading, followed by the Flow-3D melting simulation. Ten layers were simulated at three different linear energy density (LED) combinations for both cases, with samples positioned at a 30-degree angle to accommodate upskin and downskin effects. Furthermore, a three-dimensional representation of the melted region for each layer was generated using the thermal gradient output from the simulated data. All generated 3D layers were stacked and merged to consolidate a 3D representation of the overall sample. The surfaces (upskin, downskin, and side skins) were extracted from this merged sample. Subsequently, these surfaces were analyzed, and surface roughness (Sa values) was calculated using MATLAB. The obtained values were then compared with experimental results. The downskin surface roughness results from the simulation were found to be within the range of the experimental results. This alignment is attributed to the fact that the physics simulation primarily focuses on melt pool depth and width. These promising findings indicate the potential for accurately predicting surface roughness through simulation.
在过去十年中,增材制造模拟已成为一个突出的研究领域。过程物理模拟被用于复制激光粉末床熔融(L-PBF)制造过程,旨在通过模拟数据预测潜在问题。本研究重点是利用从模拟数据中提取的3D表面拓扑结构来计算表面粗糙度,因为表面粗糙度会显著影响零件质量。使用模拟准确预测表面粗糙度仍然是一个持续存在的挑战。为应对这一挑战,采用两步过程物理模拟对两种不同情况(轮廓处理前和轮廓处理后)的L-PBF技术进行了模拟。利用离散元方法模拟粉末铺展,随后进行Flow-3D熔凝模拟。两种情况下,在三种不同的线能量密度(LED)组合下模拟了十层,样品以30度角放置以适应上表面和下表面效应。此外,利用模拟数据输出的热梯度生成了每层熔融区域的三维表示。将所有生成的3D层堆叠并合并,以巩固整个样品的三维表示。从这个合并后的样品中提取表面(上表面、下表面和侧面)。随后,对这些表面进行分析,并使用MATLAB计算表面粗糙度(Sa值)。然后将获得的值与实验结果进行比较。发现模拟得到的下表面粗糙度结果在实验结果范围内。这种一致性归因于物理模拟主要关注熔池深度和宽度。这些有前景的发现表明通过模拟准确预测表面粗糙度具有潜力。