Abstract
In the design of lattice structures fabricated by additive manufacturing, a multiscale modeling process is usually required to effectively account for fine scale uncertainties. The validation of the multiscale model predictions, on the other hand, is a challenging task. In this research, two prediction assessment approaches, namely the area validation metric and the Kolmogorov-Smirnov test, are presented in a systematic validation pyramid approach with u-pooling method to address this issue. The use of these two approaches are evaluated in terms of being an unbiased decision criterion for the prediction assessment and validation of the multiscale models. The fine scale material and geometry uncertainties are propagated onto homogenized properties using a stochastic upscaling method at each scale of interest. The homogenized model predictions are validated using the experimental data obtained for the lattice structure example fabricated by material extrusion process. The results indicate that the presented approach is capable of effectively validate the predictions of the multiscale models under uncertainty.
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Recommended by Associate Editor Hyung Wook Park
Recep M. Gorguluarslan received his B.S. degree in Mechanical Engineering from TOBB University of Economics and Technology in 2010. He then received his M.S. degree in 2015 and Ph.D. degree in 2016 from Mechanical Engineering at Georgia Institute of Technology. He is currently an Assistant Professor in the Department of Mechanical Engineering of TOBB University of Economics and Technology in Ankara, Turkey. His research interests include design for additive manufacturing, optimization, lattice structures, uncertainty quantification, and multiscale modeling.
Seung-Kyum Choi is an Associate Professor in School of Mechanical Engineering at Georgia Institute of Technology. Dr. Choi's research interests include structural reliability, probabilistic mechanics, statistical approaches to design of structural systems, multidisciplinary design optimization, and information engineering for complex engineered systems. He served as Invited Guest Editors for Journal of Engineering Design and Journal of Electronic Materials. He also served as a Chair and Session Organizer at national conferences of AIAA, SDM, MDO, NDA and ASME/IDETC, in addition to being an invited member of the AIAA Non-Deterministic Technical Committee. Since 2017, Dr. Choi is currently appointed the Director of Center for Additive Manufacturing Systems (CAMS), where he has responsibilities for developing research and educational programs in additive manufacturing.
Hae-Jin Choi is a Professor in the School of Mechanical Engineering, Chung-Ang University (CAU) in Seoul, Korea. Before joining in CAU, he was an Assistant Professor in Nanyang Technological University in Singapore. He served as a Postdoctoral Fellow in the GWW School of Mechanical Engineering, Georgia Institute of Technology (Georgia Tech). He holds Ph.D. (2005) and M.S. (2001) in Mechanical Engineering from Georgia Tech. His research focuses on strategic product design, management of uncertainty, integrated materials and products design, multiscale simulation-based design, and distributed collaborative product realization
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Gorguluarslan, R.M., Grandhi, R.V., Choi, HJ. et al. Prediction assessment and validation of multiscale models for additively manufactured lattice structures under uncertainty. J Mech Sci Technol 33, 1365–1379 (2019). https://doi.org/10.1007/s12206-019-0238-9
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DOI: https://doi.org/10.1007/s12206-019-0238-9