Modeling of melt pool dynamics during powder-bed laser metal additive manufacturing

近年来，增材制造（AM）技术因其适应性和多功能性吸引了许多行业的关注。增材制造正在改变工程设计和制造的思想流派，新的“为设计而制造”范式正在形成，并将被“为制造而设计”的方法所取代。尽管增材制造技术具有无可争议的特点，但金属增材制造的广泛采用一直受到与所生产零件的验证和认证相关的问题的阻碍，这主要是由于增材制造工艺对环境和材料干扰的依赖性。可以显着简化增材制造工艺和增材制造组件认证的工具之一是彻底的增材制造建模，无需大量实验试错即可获得最佳工艺参数。 该研究项目的主要目标是开发一个高保真度有限元模型，以确定超级合金（镍基合金）粉末床激光金属增材制造过程中的熔池动力学和形状。西门子加拿大公司正在进行一个增材制造工艺模拟项目，该项目需要熔珠的精确特征才能有效地确定热图、残余应力和变形。这项研究的成果将帮助西门子调整其建模代码，而通过该项目生成的数据将被输入到当前的过程模拟中，以提高其精度和可靠性。 拟议的研究将分4个阶段进行。 (1) 将GPU添加到当前的计算设置中； (2) 模型开发； (3)利用现有的实验数据进行模型验证； 4) 从西门子应用模型中提取数据。 该成果将加强西门子正在采取的增材制造认证战略，从而提高生产力和产品质量。这可以使加拿大成为这一发展的起源地。

Additive manufacturing (AM) technologies have attracted many industries in the recent years due to their adaptability and versatility. AM is changing the school of thought in engineering design and manufacturing such that a new "manufacture for design" paradigm is forming to be replaced with the "design for manufacturing" approach. Regardless of undisputable features of AM technologies, the wide adoption of metal AM has been hurdled by the issues associated with the validation and certification of the produced parts, mainly due to the dependencies of the AM processes to environmental and material disturbances. One of the tools that can significantly ease the certification of AM processes and AM-made components is a thorough modeling of AM to obtain optimum process parameters without massive experimental trial-and-error. The main objective of this research project is to develop a high fidelity finite element model to determine the melt pool dynamics and shape during the powder-bed laser metal AM of supper-alloy (nickel-based alloy). Siemens Canada has an ongoing AM process simulation project which requires the precise features of melting bead to be able to effectively determine the thermal maps, residual stresses and distortion. The outcome of this research will help Siemens to adjust its modeling codes while the data generated through this project will be fed to the current process simulation to improve its precision and reliability. The proposed research will be carried out in 4 stages. (1) Adding GPUs to the current computing setup; (2) Model development; (3) Model validation using available experimental data; and, 4) Data extraction from the model for the Siemens application. The outcome will enhance the AM certification path forward strategies that are being taken by Siemens, thus promoting productivity and products quality. This can put Canada on the map as the origin of this development.