CAREER: A Predictive Modeling and Simulation-Based Certification Framework for Additive Manufacturing of Metals

这一学院早期职业发展(CALEAR)计划研究项目将专注于得出一种高效的基于科学的策略--将预测建模和模拟与最佳实验选择相结合--由严格的不确定性量化方法驱动，以加速基于粉末床融合的金属添加剂制造的认证。基于粉末床熔融的添加剂制造技术是金属零件制造中用途最广、商业化程度最高的添加剂制造技术之一。它允许高度的设计自由度，开发新的材料结构，并以合理的成本制造定制产品。粉末床熔化需要使用高功率能量束来熔化粉末颗粒，并将它们一层又一层地融合在一起，形成所需的形状。颗粒经历的复杂热历史通常会导致在所制备的材料中形成更多的缺陷、显著的应力和变形以及裂纹。这项研究项目将开发建模和计算能力，以分析基于粉末床熔融的添加剂制造过程，并了解工艺参数与材料微观结构中缺陷形成的基本关系，以制造更好的金属产品。这项研究还将通过建立响应和灵活的教育和推广计划来补充，该计划的基础是课程开发、添加剂制造工作室的培训演示以及通过机构STEM教育中心进行K-12和代表性不足的少数民族推广。研究的具体目标是发现基于粉末床熔融的金属添加剂制造的过程-组织-性能关系。公认的事实是，熔池动力学控制着印制金属微观组织中缺陷的形成，并决定着制件的宏观性能和性能。因此，该项目的研究目标包括：(I)开发基于高性能计算的数值求解器，用于强热力和流固耦合问题；(Ii)能够执行粉末床熔化过程的直接数值模拟；(Iii)基于模型的印刷金属的不确定性量化和认证。将回答以下基本问题：(1)在严格的热机械载荷条件下，粉末床层的热力学响应是什么；(2)工艺参数和粉末特性在预制材料微观结构演变中的作用是什么。主要的重点将是更好地了解粉末床熔化过程中缺陷形成和演化的物理学，包括：气孔率、未熔化颗粒、晶界和微裂纹。这个项目将使PI能够推进计算科学、力学和材料科学的知识基础，并建立他在先进制造领域的长期职业生涯。

This Faculty Early Career Development (CAREER) program research project will focus on deriving a highly effective science based strategy --combing predictive modeling and simulations with optimal experimental selection-- driven by a rigorous uncertainty quantification methodology for accelerated certification of powder bed fusion based additive manufacturing of metals. Powder bed fusion based additive manufacturing technology is one of the most versatile and commercialized advances of all additive manufacturing techniques for the fabrication of metallic components. It enables a high degree of design freedom, development of novel material structures, and manufacture of customized products at reasonable costs. Powder bed fusion requires the use of high power energy beams to melt the powder particles and fuse them together layer after layer to form the desired shape. The complex thermal history experienced by the particles usually causes the formation of more defects, significant stresses and distortion as well as cracks in the fabricated materials. This research project will develop modeling and computational capabilities for the analysis of powder bed fusion based additive manufacturing processes and to understand the fundamental relationship between the processing parameters and the defect formation in the materials microstructure, to fabricate better metallic products. The research will also be complemented by establishing a responsive and flexible educational and outreach program based on curriculum development, training demonstrations in an additive manufacturing studio, and K-12 and underrepresented minority outreach through an institutional STEM education center.The specific goal of the research is to discover the process-microstructure-property relationship for powder bed fusion based additive manufacturing of metals. It is an established fact that the melt pool dynamics governs the defect formation in the microstructure of printed metals and determines the fabricated part?s macroscopic properties and performance. Thus, the research objectives of this project include: (i) development of a high performance computing based numerical solver for strong thermomechanical and fluid-structure coupled problems; (ii) capability to perform direct numerical simulation of powder bed fusion processes; (iii) model-based uncertainty quantification and certification of printed metals. The following fundamental questions will be answered: (1) what is the thermodynamic response of the powder bed under severe thermomechanical loading conditions; (2) what are the roles of processing parameters and powder characteristics in the microstructure evolution of fabricated materials. The overarching focus will be on obtaining a better understanding of the physics of defect formation and evolution, including: porosity, unmelted particles, grain boundaries and micro-cracks, during the powder bed fusion processes. This project will allow the PI to advance the knowledge base in computational science, mechanics and material science, and establish his long-term career in advanced manufacturing.