An integrated computational framework for high energy beam welding

建模高能制造过程需要一个多步骤的方法。电子焊接和激光焊接是实现高效率和精密制造的重要手段。这些焊接技术被证明是对异种金属最有效的。本研究旨在建立一个框架，将热流体流动（TFF）模型与晶体塑性有限元法（CPFEM）相结合，以模拟EBW和LBW过程。该框架将有助于了解低相变温度（LTT）合金填料的化学成分、马氏体相变和制造参数之间的相互作用。相场断裂（PFF）模拟将用于了解在焊接接头特定位置形成微裂纹的概率，这取决于制造参数，如光束功率和扫描速度。在后期阶段，这些模拟将用于优化梁参数和材料的化学成分，以提高焊接接头的强度。以下几点概括了本研究的目的：焊缝在微米长度尺度上残余应力形成的估计与分析。2. 马氏体相变的作用及其与焊缝化学成分分布的关系。3. 结合TFF和晶粒生长CPFEM对这一过程进行建模。4. 一个参数化模型，以了解和优化材料组成，扫描速度，光束功率和填料类型，以提高强度和延性。该项目将有助于了解制造参数以及母材和填充丝的合金成分对最终部件的力学和断裂性能的综合影响。这对于通常不使用填料的EBW尤其重要，而它的使用有望大大改善焊接接头。开发的计算工具将有助于优化EBW和LBW工艺，并通过找到最小化残余应力的制造条件来生产具有延长寿命的焊接接头。金属部件寿命更长，可以降低更换成本，减少制造新部件所需的排放。提高车辆安全性和发电厂发电可靠性。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。由于设备的巨大成本，这一点尤为重要。易于使用的计算工具将消除昂贵的实验试错过程的需要。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融合，这是一种广泛使用的增材制造技术。从发现新合金到评估相应的焊接方法之间的时间将缩短。

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.