Rights statement: This is the author’s version of a work that was accepted for publication in Composite Structures. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Composite Structures, 373, 4-5, 2021 DOI: 10.1016/S0370-1573(02)00269-7
Accepted author manuscript, 13.8 MB, PDF document
Available under license: CC BY-NC-ND
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Understanding mixed mode ratio of adhesively bonded joints using genetic programming (GP)
AU - Liu, Yiding
AU - Gu, Zewen
AU - Hughes, Darren J.
AU - Ye, Jianqiao
AU - Hou, Xiaonan
N1 - This is the author’s version of a work that was accepted for publication in Composite Structures. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Composite Structures, 373, 4-5, 2021 DOI: 10.1016/S0370-1573(02)00269-7
PY - 2021/2/15
Y1 - 2021/2/15
N2 - Adhesively bonding has been increasingly used for numerous industrial applications to meet the high demand for lightweight and safer structures. Debonding of adhesively bonded joints is a typical mixed mode failure process. It is highly depended on the interactional effects of material properties and geometric definitions of the constituents, which is very complicated. The existing studies in identifying fracture modes of joints based on either experiments or finite element analysis are often prohibitively time and computational expensive. This paper proposed an innovate method by combining Finite Element Analysis (FEA), Latin Hypercube Sampling (LHS) and Genetic Programming (GP) to understand the effect of the physical attributes on the fracture modes of adhesively single lap joints. A dataset of 150 adhesive joint samples has been generated using LHS, including different combinations of adherend and adhesive’s material properties and thicknesses. The mixed mode ratios of the 150 samples are calculated using Strain Energy Release Rate (SERR) outputs embedded in Linear Elastic Fracture Mechanics (LEFM), which has been validated by experimental tests. Finally, a GP model is developed and trained to provide an extracted explicit expression used for evaluating the early-state failure modes of the adhesively bonded joints against the design variables.
AB - Adhesively bonding has been increasingly used for numerous industrial applications to meet the high demand for lightweight and safer structures. Debonding of adhesively bonded joints is a typical mixed mode failure process. It is highly depended on the interactional effects of material properties and geometric definitions of the constituents, which is very complicated. The existing studies in identifying fracture modes of joints based on either experiments or finite element analysis are often prohibitively time and computational expensive. This paper proposed an innovate method by combining Finite Element Analysis (FEA), Latin Hypercube Sampling (LHS) and Genetic Programming (GP) to understand the effect of the physical attributes on the fracture modes of adhesively single lap joints. A dataset of 150 adhesive joint samples has been generated using LHS, including different combinations of adherend and adhesive’s material properties and thicknesses. The mixed mode ratios of the 150 samples are calculated using Strain Energy Release Rate (SERR) outputs embedded in Linear Elastic Fracture Mechanics (LEFM), which has been validated by experimental tests. Finally, a GP model is developed and trained to provide an extracted explicit expression used for evaluating the early-state failure modes of the adhesively bonded joints against the design variables.
KW - Adhesively bonded joints
KW - Mixed mode ratio
KW - Finite element analysis
KW - Latin Hypercube Sampling
KW - Genetic Programming
KW - Strain Energy Release Rate
U2 - 10.1016/j.compstruct.2020.113389
DO - 10.1016/j.compstruct.2020.113389
M3 - Journal article
VL - 258
JO - Composite Structures
JF - Composite Structures
SN - 0263-8223
M1 - 113389
ER -