Computational modeling and statistical analysis of buckling characteristics of polysilicon reinforced fiber

Abstract The purpose of this study is to evaluate the effect of volume fraction of continuous carbon fiber and sample length on buckling characteristics of polysilicon. A statistical design of 12 samples were formulated with constant cross-section area of 2500 mm 2 using Design of Experiment software (DOE). The samples were sketched using ABAQUS 2019 software, and the total buckling force each sample was estimated. The estimated buckling forces were statically evaluated as a response using DOE. The estimated forces of 3.48776e07, 4.00652e07 and 5.78142e07 newton for the simulated samples of 100 mm in length and 0,15, and 25% volume fraction respectively, is an indication of positive effect of fiber volume fraction on the necessary force for buckling. In addition, similar tendency was found in other samples (the higher fiber volume fractions the higher buckling force). However, the estimated buckling force for each sample was negatively affected with length of the sample. The result indicated a value of 4.00652E+07, 5.00447E+06 and 1.80390E+06 newton at a constant fiber volume fraction and different length of 100, 300 and 500 mm respectively. The statistical analysis of the simulated buckling force showed a signification design, and the date of one factor effect is highly supported by the simulated buckling forces. The equation of a significant design can be used to estimate the buckling force at any fiber volume fraction and sample length.

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Publication Details

Journal
Materials Research Express
Published
2024-08-01
DOI
https://doi.org/10.1088/2053-1591/ad68d0
Citations
1
Primary Topic
Structural Behavior of Reinforced Concrete
Type
article
Field-Weighted Citation Impact
0.27
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article

Computational modeling and statistical analysis of buckling characteristics of polysilicon reinforced fiber

Waham Ashaier Laftah, Wan Aizan Wan Abdul Rahman
1 citations
Materials Research Express
Structural Behavior of Reinforced Concrete
0.27
article

Computational modeling and statistical analysis of buckling characteristics of polysilicon reinforced fiber

Waham Ashaier Laftah, Wan Aizan Wan Abdul Rahman
article en
1 citations

Abstract

Abstract The purpose of this study is to evaluate the effect of volume fraction of continuous carbon fiber and sample length on buckling characteristics of polysilicon. A statistical design of 12 samples were formulated with constant cross-section area of 2500 mm 2 using Design of Experiment software (DOE). The samples were sketched using ABAQUS 2019 software, and the total buckling force each sample was estimated. The estimated buckling forces were statically evaluated as a response using DOE. The estimated forces of 3.48776e07, 4.00652e07 and 5.78142e07 newton for the simulated samples of 100 mm in length and 0,15, and 25% volume fraction respectively, is an indication of positive effect of fiber volume fraction on the necessary force for buckling. In addition, similar tendency was found in other samples (the higher fiber volume fractions the higher buckling force). However, the estimated buckling force for each sample was negatively affected with length of the sample. The result indicated a value of 4.00652E+07, 5.00447E+06 and 1.80390E+06 newton at a constant fiber volume fraction and different length of 100, 300 and 500 mm respectively. The statistical analysis of the simulated buckling force showed a signification design, and the date of one factor effect is highly supported by the simulated buckling forces. The equation of a significant design can be used to estimate the buckling force at any fiber volume fraction and sample length.

Materials Research ExpressVol. 11(8)
University of Technology Malaysia (MY)
Sustainable cities and communities
Openalex Percentile: Top 45%
Structural Behavior of Reinforced Concrete
0.27
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Computational modeling and statistical analysis of buckling characteristics of polysilicon reinforced fiber — Waham Ashaier Laftah, Wan Aizan Wan Abdul Rahman · Materials Research Express (2024) | TGRS Research Map | TGRS