Session: 04-12-02: Design of Materials and Discovery of Constitutive Models Linking Process-Structure-Property-Performance Relationships

Paper Number: 164017

Investigation of Process-Structure-Property Relationships for Additively Manufactured Al-Si-Mg Alloy via Integrated Finite-Element Modeling and Crystal Plasticity 

In this work, a computational framework was developed to investigate the relationship between Process-Structure-Property relationship for additively manufactured (AM) Al–Si–Mg alloy. Specifically, molten pool geometries were obtained through large amount of thermal simulations under different major process parameters including laser beam power, scanning speed, and hatch spacing. The molten pool dimensions were then used as the input to an analytical model to calculate the lack-of-fusion porosity. Statistically representative volume element (RVE) with respect to the size distribution of grains and pores as well as their shapes (i.e. columnar or equiaxed) were reconstructed via ImageJ and Dream.3D. Finally, a fast Fourier transform-based elasto-viscoplastic (EVP-FFT) model is employed to investigate the microstructural effects on the micromechanical behavior and properties for the (AM) Al-Si-Mg alloy. Porosity was found to degrade mechanical properties significantly. In addition, Anisotropic behavior of the columnar structure with 7.5% porosity value was confirmed. Moreover, the nature of probability density function of grain size in terms of lognormal and normal was found to have nontrivial effect on mechanical properties. The proposed framework was generally applicable to predict the process-structure-property relationship for additive manufacturing of a variety of alloy systems such as nickel-based superalloys.

             Additive manufacturing, including selective laser melting (SLM), selective laser sintering (SLS), directed energy deposition (DED), etc., is a process that joins materials to create a 3D component [1]. This manufacturing fashion bring about several advantages compared to the conventional subtractive manufacturing, in which the component of wanted geometry is, on the contrary, machined out of solid block of materials. Among them the major one is its great potential for fabricating component with complex geometry. A complicate component can be fabricated directly from the 3D computer aided design (CAD) model. Other advantages include the low waste and energy cost. For example, it adds material layer by layer so that usually what is required gets used. In this way, additive manufacturing can reduce material costs and waste by as much as 90 percent. A good understanding of process-microstructure-property can greatly help achieve product improvement though optimizing process conditions, thus enable us to make better use of AM. Specifically, use selective laser beam melting (SLBM) (one type of powder-bed fusion AM) of Al-Si-Mg alloy as an example, in this work we will utilize an integrated multi-scale multi-physics model to investigate the relationship among process-microstructure-property for process optimization.

      In this work, an integrated multi-physics model is developed. The proposed framework provides systematical insights into process-microstructure-property relationship during AM of Al-Si-Mg alloy. The porosity formation was  predicted based on thermal simulation results of FEM model, which yield molten pool dimension information for predicting the lack-of-fusion porosity. Dream.3D was utilized to reconstruct synthetic microstructures with different volume fraction of porosity. The computationally efficient EVP-FFT model was employed to fully investigated the crystal plasticity and predicts accurately micromechanical behavior.

Presenting Author: Yucheng Liu South Dakota State University

Presenting Author Biography: Dr. Yucheng Liu (PhD, PE, FASME, FSAE) is the Department Head of Mechanical Engineering (ME) Department at South Dakota State University (SDSU) and holds the Duane Sander Professor of Entrepreneurial Engineering in the Jerome J. Lohr College of Engineering at SDSU. Prior to joining SDSU in 2021, Dr. Liu was a faculty member in the Mechanical Engineering Department at Mississippi State University (MSU), where he served as Graduate Coordinator (2016 – 2021) and held the Jack Hatcher Chair in Engineering Entrepreneurship in the Bagley College of Engineering (2018 – 2021). Prior to MSU, Dr. Liu was an Assistant Professor at the University of Louisiana at Lafayette (UL Lafayette). Dr. Liu earned his PhD degree from the University of Louisville in 2005 and a bachelor’s degree from Hefei University of Technology in 1997, both in Mechanical Engineering. His research spans multiscale material modeling and simulation, high-strain-rate material performance, vehicle systems design, and renewable energy technologies. His current research focus is on understanding the process-structure-property-performance relationships of structural materials through advanced multiscale theoretical frameworks and integrated computational, experimental, AI, and machine learning methods. To date, Dr. Liu has authored over 260 peer reviewed publications, including 146 peer reviewed journal articles, holds 2 patents, and has over 3,500 citations with an H-index of 30. Ranked among the top 2% of researchers globally and top 1% in mechanical engineering by ResearchGate, he has secured and managed over $15.5 million in extramural funding across 40 grants from various private, state, and federal agencies. He has also served on review panels for many NSF, DOD, NASA, and DOE programs. Since becoming a faculty member in 2009, Dr. Liu has received numerous awards, including the Junior Faculty Researcher of the Year of the College of Engineering at UL Lafayette in 2013, the Outstanding Senior Faculty Research Award from the ME Department in 2016, MSU and BCOE Faculty Research Award in 2018, and the BCOE Service Award in 2021. Dr. Liu was named to the Jack Hatcher Chair in Engineering Entrepreneurship in 2018 and promoted to Full Professor in 2019. Dr. Liu’s professional honors include being named an ASME Fellow (2017), SAE Fellow (2019), ASEE Distinguished Member (2024), and recipient of the SAE Forest R. McFarland Award (2020). He is a registered Professional Engineer in Ohio and a member of AAAS.

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