年間 6 号発行
ISSN 印刷: 2152-5080
ISSN オンライン: 2152-5099
Indexed in
A NEW INVERSE METHOD FOR THE UNCERTAINTY QUANTIFICATION OF SPATIALLY VARYING RANDOM MATERIAL PROPERTIES
要約
In this paper, a new inverse uncertainty quantification method was proposed to identify statistical parameters associated with spatially varying material properties and to reconstruct their heterogeneous distributions from limited experimental measurements. The proposed method parameterizes statistical models of random fields with analytic co-variance functions and spectral decomposition into Karhunen-Loeve random variables. The statistical model parameters are identified by an experimental-numerical inverse analysis method, which is expected to significantly reduce time and cost required for quantification of material uncertainties.
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Jeong SungWoo, Lim Hyung-Jun, Zhu Fei-Yan, Park Chanwook, Kim Yeonghwan, Yun Gunjin, Nano-Micro Multiscale Modeling for Graphene-Reinforced Nanocomposites, 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2018. Crossref
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Webbe Kerekes Tomas, Lim Hyoungjun, Joe Woong Yeol, Yun Gun Jin, Characterization of process–deformation/damage property relationship of fused deposition modeling (FDM) 3D-printed specimens, Additive Manufacturing, 25, 2019. Crossref
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Lim Hyoungjun, Choi Hoil, Lee Min Jung, Yun Gun Jin, Elasto-plastic damage modeling and characterization of 3D needle-punched Cf/SiCm composite materials, Ceramics International, 46, 10, 2020. Crossref
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Choi Ho-il, Park Chanwook, Lim Hyoung Jun, Yun Gun Jin, A Nano-Micro–Macro Multiscale Modeling for Carbon Fiber-Reinforced Graphene/Epoxy Nanocomposites, Multiscale Science and Engineering, 3, 1, 2021. Crossref