Title: Part-scale Thermal Modeling of Laser Powder Bed Fusion Additive Manufacturing Abstract: In this project, a part-scale physics-based analytical thermal model will be developed to simulate the melting behavior in the laser powder bed fusion process (LPBF). In the modeling process, the influence of complex scan strategies, part boundary heat loss, process-dependent laser power absorptivity, preheating temperature, powder packing behavior, and powder bed material properties will all be considered. The temperature distribution during both the heating and cooling stages will be predicted. The molten pool dimensions and geometry will be estimated by comparing the temperature distribution with the melting point of the materials. Experimental validation will be conducted to validate the predictive accuracy of the developed thermal model. The calculation time of the proposed thermal model will be compared with that of finite element models so that to prove the high computational efficiency of the physics-based analytical model. The proposed part-scale thermal modeling method will help the researchers understand the underlying physics in LPBF and optimize the process conditions to avoid the defects formation during the melting process and thus increase the product quality. 1. Introduction: Laser powder bed fusion (LPBF) is a widely used technique for additive manufacturing of metallic materials. It can fabricate products with complex geometries directly from digital models, which is quite superior when compared with traditional manufacturing techniques, such as machining, casting, powder metallurgy, etc. However, it is still very challenging to ensure product quality in LPBF. There are some common process-induced defects in LPBF, such as lack-of-fusion porosity, keyhole-induced porosity, and balling phenomenon. All these defects will lead to bad product quality and have detrimental effects on the mechanical performance of the final products. The formations of these defects are closely related to the complex melting behavior during the printing process. Lack-of-fusion porosity is induced by the insufficient melting of the powder materials and incomplete overlapping of the molten pool in adjacent melting tracks and layers. Balling defect represents the phenomenon that a continuous melting track breaks into plenty of individual droplets due to instability and surface tension of the molten pool. Keyhole porosity is induced by the severe evaporation and instability of the deep vapor depression in the keyhole melting mode. Thus, it is very necessary to study the melting process and understand the underlying physics of the behavior of molten pool and vapor depression, so that to avoid the defects formation in the melting process and control the product quality in LPBF. 2. Intellectual merits Physics-based analytical modeling methods have explicit mathematical expressions, which means that the computational efficiency of this kind of method will be much higher than iteration-based numerical modeling methods such as finite element methods. Also, the development of physics-based analytical models does not rely on plenty of expensive experimental data, which means that analytical models can help researchers avoid conducting plenty of experiments and avoid purchasing high-cost metal 3D printers and testing equipment. In this project, a physics-based analytical thermal modeling method will be developed to simulate the complex melting behavior in LPBF. The effects of complex product geometry, complex scan strategies, process-dependent laser power absorption, preheating temperature, heat accumulation and cooling stages will all be considered in the modeling process. The time-dependent temperature distribution during the printing process will be predicted. The molten pool under different process conditions will be estimated. Experimental validations will be conducted to demonstrate the predictive accuracy of the proposed models. The calculation time of the developed analytical models will be compared with that of the finite-element-based numerical models so that to demonstrate the higher computational efficiency of analytical models. If the project succeeds, the proposed model will be the first ultra-fast physics-based part-scale thermal model to predict the melting process of LPBF, and it will become an efficient tool for process optimization of LPBF and will thus help the researchers control the product quality of LPBF. 3. Research plan: Task 1: A physics-based heat sink solution will be developed to consider the heat loss through product boundaries and the heat loss during cooling stages of LPBF. The heat sink solution will be combined with a previously developed heat input solution to predict the time-dependent temperature distribution during cooling stages. Task 2: A mathematical model will be developed to predict the powder packing behavior based on the information of powder size/shape distribution. The powder packing density will also be predicted using this model. Task 3: An analytical model will be developed to predict the powder bed material properties based on the information of solid properties and powder packing density. The powder material properties will be the inputs of the heat input and heat sink solutions. Task 4: The heat input and sink solutions will be improved to consider the influence of complex strategies on the heat accumulation during LPBF. The temperature distribution and molten pool under different process conditions will be predicted. The effects of different complex strategies will be compared. Task 5: Experimental validation will be conducted to demonstrate the accuracy of the above proposed modeling methods. Computational efficiency will be recorded and compared with numerical models.