An integrated computational framework for high energy beam welding

对高能制造过程进行建模需要一个多步骤的方法。电子束(EBW)和激光(LBW)焊接的目的是为了高效和精密制造。这些焊接技术被证明是对不同金属最有效的。本研究旨在建立一个框架，其中热流体流动(TFF)模型集成在晶体塑性有限元方法(CPFE)中，以模拟EBW和LBW过程。该框架将有助于理解低相变温度(LTT)合金填充材料的化学成分、马氏体相变和制造参数之间的相互作用。相场断裂(PFF)模拟将用于了解微裂纹在焊接接头特定位置形成的概率取决于制造参数，如束流功率和扫描速度。在后续阶段，这些模拟将用于优化梁参数和材料的化学成分，以增加焊接接头的强度。以下几点是对本研究目的的总结：1.估计和分析来自焊接线的微米级残余应力的形成。2.马氏体相变作用及其与焊缝化学成分分布的关系。3.采用TFF和CPFE相结合的方法对该过程进行数值模拟。4.参数模型，用于了解和优化材料成分、扫描速度、束流功率和填料类型，以提高强度和延展性。该项目将有助于了解母材和填充丝的制造参数和合金成分对最终部件的机械和断裂性能的综合影响。这对电子束焊接特别重要，它经常在没有填充物的情况下使用，而它的使用有望显著改善焊接接头。开发的计算工具将有助于优化EBW和LBW工艺，并通过找到使残余应力最小的制造条件来生产寿命更长的焊接接头。寿命更长的金属部件可以降低更换成本，并减少制造新部件所需的排放。提高车辆安全性和电厂发电可靠性。由于其预测能力，计算方法可以显示高能束技术在尚未应用的领域的潜力。这一点特别重要，因为设备的成本很高。易于使用的计算工具将消除昂贵的实验试验和错误程序的需要。该计算工具的应用将不仅限于电子束焊接，还将用于激光粉末-床层融合，这是一种广泛使用的AM技术。发现新合金和评估相应焊接方法之间的时间将会缩短。

Modelling high-energy manufacturing processes requires a multi-step approach. Electron (EBW) and laser beam (LBW) welding are utilized for the purpose of high efficiency and precision manufacturing. These welding techniques are proven to be the most efficient on dissimilar metals. This research aims to create a framework where thermal fluid flow (TFF) models are integrated along the crystal plasticity finite element method (CPFEM) to simulate EBW and LBW processes. The framework will help understand the interplay between the chemical composition of low transformation temperature (LTT) alloy fillers, martensitic transformation, and manufacturing parameters. Phase field fracture (PFF) simulations will be used to understand the probability that microcrack forms at a specific location in the welded joint depending on the manufacturing parameters, such as the beam power and scanning speed. In later stages, these simulations will be used to optimize the beam parameters and the chemical composition of the materials to increase the strength of the welded joint. Following points represent a summary of the aims of this research: 1. Estimation and analysis of the formation of residual stresses at the micrometer length scale from the welding line. 2. Role of martensitic transformation and its relationship to the chemical composition profile along the welding line. 3. Integration of TFF and grain growth CPFEM to model the process. 4. A parametric model to understand and optimize the material composition, scanning speed, beam power and type of filler for an improved strength and ductility. This project will help understand the combined effect of manufacturing parameters and alloy composition of the parent metal and filler wire on the mechanical and fracture properties of the final components. This is particularly important for EBW, which has often been used without filler, while its usage is expected to improve the welded joints substantially. The computational tool developed will help to optimize the EBW and LBW processes and to produce welded joints with an increased lifetime by finding the manufacturing conditions that minimize residual stress. Metallic components that can last longer can reduce the replacement cost and reduce the emissions necessary to fabricate new components. The safety of vehicles and reliability of power plants for energy generation will be improved. Because of their prediction capabilities, computational methods can show the potential of the high energy beam technology in sectors in which it has not already been applied. This is particularly important because of the substantial cost of the equipment. Easy-to-use computational tools will eliminate the need for expensive experimental trial and error procedures.The application of the computational tool will not be limited to EBW but will also be useful for laser powder-bed fusion, a widely used AM technique. The time between discovering new alloys and evaluating the corresponding welding methods will be shortened.