Buckling Analysis of Thin-Walled Structures Based on Trace Theory: A Simple and Efficient Approach for Mechanical Characterization of GFRP MembersSource: Journal of Composites for Construction:;2024:;Volume ( 028 ):;issue: 006::page 04024057-1DOI: 10.1061/JCCOF2.CCENG-4816Publisher: American Society of Civil Engineers
Abstract: For unidirectional laminates, four properties are required for mechanical characterization regarding the laminae elastic response: the longitudinal elastic modulus, the transverse elastic modulus, the in-plane shear modulus, and the in-plane Poisson's ratio. Two approaches are usually followed to obtain these properties: an experimental program, which is costly and time-consuming, or micromechanical modeling, which is associated with many uncertainties. The trace theory has been widely explored for carbon fiber-reinforced polymers as an alternative option, where only one independent property is necessary and the others are obtained using a normalized relation with the trace of the stiffness matrix. Considering the wide application of glass fiber-reinforced polymers (GFRPs) in civil structures, an extension of the trace theory was developed by combining micromechanics and machine learning. First, a data set was generated using the asymptotic homogenization for the usual properties ranges of glass fibers and polymeric matrices. Next, the decision trees algorithm was implemented to evaluate the normalized properties variation according to the trace. Based on the results of the training procedure, linear equations were obtained for the normalized properties. The proposed equations were validated by comparing the estimations of the normalized properties with a set of 17 experimental data compiled from the literature, indicating that the average errors range between 3% and 13%. Once the proposed equations were validated, the novel theory was applied to analyze the buckling load of thin-walled structures, where square and channel profiles with different stacking sequences were evaluated. Only the longitudinal elastic modulus was used as input, while the other properties were computed using the trace relations. The properties computed analytically were applied in a finite-element model to calculate the buckling loads, resulting in average errors of this hybrid approach smaller than 10% for both profiles.
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| contributor author | Lucas L. Vignoli | |
| contributor author | Janaina Gomide | |
| contributor author | Laura E. A. S. Santana | |
| contributor author | Arthur Adeodato | |
| date accessioned | 2025-04-20T10:11:40Z | |
| date available | 2025-04-20T10:11:40Z | |
| date copyright | 9/24/2024 12:00:00 AM | |
| date issued | 2024 | |
| identifier other | JCCOF2.CCENG-4816.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4304183 | |
| description abstract | For unidirectional laminates, four properties are required for mechanical characterization regarding the laminae elastic response: the longitudinal elastic modulus, the transverse elastic modulus, the in-plane shear modulus, and the in-plane Poisson's ratio. Two approaches are usually followed to obtain these properties: an experimental program, which is costly and time-consuming, or micromechanical modeling, which is associated with many uncertainties. The trace theory has been widely explored for carbon fiber-reinforced polymers as an alternative option, where only one independent property is necessary and the others are obtained using a normalized relation with the trace of the stiffness matrix. Considering the wide application of glass fiber-reinforced polymers (GFRPs) in civil structures, an extension of the trace theory was developed by combining micromechanics and machine learning. First, a data set was generated using the asymptotic homogenization for the usual properties ranges of glass fibers and polymeric matrices. Next, the decision trees algorithm was implemented to evaluate the normalized properties variation according to the trace. Based on the results of the training procedure, linear equations were obtained for the normalized properties. The proposed equations were validated by comparing the estimations of the normalized properties with a set of 17 experimental data compiled from the literature, indicating that the average errors range between 3% and 13%. Once the proposed equations were validated, the novel theory was applied to analyze the buckling load of thin-walled structures, where square and channel profiles with different stacking sequences were evaluated. Only the longitudinal elastic modulus was used as input, while the other properties were computed using the trace relations. The properties computed analytically were applied in a finite-element model to calculate the buckling loads, resulting in average errors of this hybrid approach smaller than 10% for both profiles. | |
| publisher | American Society of Civil Engineers | |
| title | Buckling Analysis of Thin-Walled Structures Based on Trace Theory: A Simple and Efficient Approach for Mechanical Characterization of GFRP Members | |
| type | Journal Article | |
| journal volume | 28 | |
| journal issue | 6 | |
| journal title | Journal of Composites for Construction | |
| identifier doi | 10.1061/JCCOF2.CCENG-4816 | |
| journal fristpage | 04024057-1 | |
| journal lastpage | 04024057-12 | |
| page | 12 | |
| tree | Journal of Composites for Construction:;2024:;Volume ( 028 ):;issue: 006 | |
| contenttype | Fulltext |