A comprehensive statistical evaluation of shear and peel stresses in adhesively bonded joints

Year 2024, Volume: 5 Issue: 2, 47 - 60, 31.12.2024

Bertan Beylergil

Abstract

This study presents a detailed analysis of shear and peel stresses in adhesively bonded single lap joints using the Goland and Reissner analytical model. The investigation evaluates the effects of key parameters, including adhesive thickness, adhesive material, adherend material, and overlap length on stress distribution. A General Linear Model (GLM) and Analysis of Variance (ANOVA) are used to assess the significance of each factor. Results show that adhesive thickness contributes 36.55% to shear stress variation, followed by adhesive material (31.08%) and adherend material (25.83%). For peel stress, adhesive thickness accounts for 38.01% of the variation. A second-order polynomial regression model is employed to capture non-linear relationships between the input parameters and stress outcomes. The predicted shear stress of 8.676 MPa closely matches the actual value of 8.64 MPa, with a relative error of 0.42%, while the predicted peel stress of 10.9901 MPa aligns with the actual value of 11.04 MPa, with a relative error of 0.45%. The analysis highlights that thinner adhesive layers lead to higher stress concentrations, while thicker layers distribute stress more effectively. The choice of adhesive material and adherend material also significantly impacts stress levels. The study concludes that optimizing adhesive thickness, material selection, and overlap length is essential for improving the performance and reliability of adhesively bonded joints. The polynomial regression model successfully captures the non-linear stress behavior, offering a robust tool for predicting joint performance.

Keywords

Adhesively bonded joints, Shear stress, Peel stress, Goland and Reissner model, Polynomial regression

Ethical Statement

There are no ethical issues with the publication of this manuscript.

Supporting Institution

TÜBİTAK

Project Number

218M710

Thanks

The authors gratefully acknowledge financial support from the Scientific and Technological Research Council of Turkey (TÜBİTAK) with project number 218M710.

References

• REFERENCES
• [1] Yildirim, C., Ulus, H., Beylergil, B., Al-Nadhari, A., Topal, S., & Yildiz, M. (2023). Effect of atmospheric plasma treatment on Mode-I and Mode-II fracture toughness properties of adhesively bonded carbon fiber/PEKK composite joints. Engineering Fracture Mechanics, 289, Article 109463. [CrossRef]
• [2] Topal, S., Al-Nadhari, A., Yildirim, C., Beylergil, B., Kan, C., Unal, S., & Yildiz, M. (2023). Multiscale nano- integration in the scarf-bonded patches for enhancing the performance of the repaired secondary load- bearing aircraft composite structures. Carbon, 204, 112¬¬–125. [CrossRef]
• [3] Arenas, J. M., Narbón, J. J., & Alía, C. (2010). Optimum adhesive thickness in structural adhesive joints using statistical techniques based on Weibull distribution. International Journal of Adhesion and Adhesives, 30(2), 160–165. [CrossRef]
• [4] da Silva, L. F. M., Critchlow, G. W., & Figueiredo, M. A. V. (2008). Parametric study of adhesively bonded single lap joints by the Taguchi method. Journal of Adhesion Science and Technology, 22(13), 1477–1494. [CrossRef]
• [5] Lasprilla-Botero, J., Álvarez-Láinez, M., Acosta, D. A., & Martín-Martínez, J. M. (2017). Water-based adhesive formulations for rubber to metal bonding developed by statistical design of experiments. International Journal of Adhesion and Adhesives, 73, 58–65. [CrossRef]
• [6] Genty, S., Sauvage, J. B., Tingaut, P., & Aufray, M. (2017). Experimental and statistical study of three adherence tests for an epoxy-amine/aluminum alloy system: Pull-Off, Single Lap Joint, and Three-Point Bending tests. International Journal of Adhesion and Adhesives, 79, 50–58. [CrossRef]
• [7] Mishra, P. K., Padhee, N., Panda, S. K., Kumar, E. K., & Panda, S. K. (2024). Free vibration frequency prediction to design optimum adhesively bonded composite double lap joint. Journal of Vibration Engineering & Technologies, 12, 5571–5584.
• [8] Zhao, L., Shan, M., Liu, F., & Zhang, J. (2017). A probabilistic model for strength analysis of composite double- lap single-bolt joints. Composite Structures, 161, 419–427.
• [9] da Silva, L. F. M., Carbas, R. J. C., Critchlow, G. W., Figueiredo, M. A. V., & Brown, K. (2009). Effect of material, geometry, surface treatment and environment on the shear strength of single lap joints. International Journal of Adhesion and Adhesives, 29(6), 621–632. [CrossRef]
• [10] Vieira, A. J. A., Campilho, R. D. S. G., & Madani, K. (2024). Statistical analysis of adhesive rod-tube joints under tensile stress for structural applications. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 46, Article 574. [CrossRef]
• [11] Zhang, H., Zhang, L., Song, Z., & Zhu, P. (2023). Hierarchical uncertainty quantification of hybrid (riveted/bonded) single lap aluminum-CFRP joints with structural multiscale characteristic. Composite Structures, 324, Article 117561. [CrossRef]
• [12] Haddou, Y. M., Salem, M., Amiri, A., Amiri, R., & Abid, S. (2023). Numerical analysis and optimization of adhesively-bonded single lap joints by adherend notching using a full factorial design of experiment. International Journal of Adhesion and Adhesives, 126, Article 103482. [CrossRef]
• [13] Rangaswamy, H., Sogalad, I., Basavarajappa, S., Acharya, S., & Patel, G. C. (2020). Experimental analysis and prediction of strength of adhesive-bonded single-lap composite joints: Taguchi and artificial neural network approaches. SN Applied Sciences, 2, Article 1055. [CrossRef]
• [14] Choudhury, M. R., & Debnath, K. (2020). Experimental analysis of tensile and compressive failure load in single-lap adhesive joint of green composites. International Journal of Adhesion and Adhesives, 99, Article 102557. [CrossRef]
• [15] Gajewski, J., Golewski, P., & Sadowski, T. (2021). The use of neural networks in the analysis of dual adhesive single lap joints subjected to uniaxial tensile test. Materials, 14(2), Article 419. [CrossRef]
• [16] Chen, Y., Li, M., Yang, X., & Luo, W. (2020). Damage and failure characteristics of CFRP/aluminum single lap joints designed for lightweight applications. Thin-Walled Structures, 153, Article 106802. [CrossRef]
• [17] Silva, G. C., Beber, V. C., & Pitz, D. B. (2021). Machine learning and finite element analysis: An integrated approach for fatigue lifetime prediction of adhesively bonded joints. Fatigue & Fracture of Engineering Materials & Structures, 44(12), 3334–3348. [CrossRef]
• [18] Bellini, C., Parodo, G., & Sorrentino, L. (2020). Effect of operating temperature on aged single lap bonded joints. Defence Technology, 16, 283–289.
• [19] Tenreiro, A. F. G., Lopes, A. M., & da Silva, L. F. M. (2023). Damage metrics for void detection in adhesive single-lap joints. Mathematics, 11(4127), 1–43. [CrossRef]
• [20] Park, S.-M., Roy, R., Kweon, J.-H., & Nam, Y. (2020). Strength and failure modes of surface-treated CFRP secondary bonded single-lap joints in static and fatigue tensile loading regimes. Composites Part A, 134, Article
• [21] Jensen, R. E., DeSchepper, D. C., & Flanagan, D. P. (2019). Multivariate analysis of high throughput adhesively bonded single lap joints. International Journal of Adhesion and Adhesives, 89, 1–10. [CrossRef]
• [22] Quispe Rodríguez, R., Portilho de Paiva, W., Sollero, P., & Bertoni Rodrigues, M. R., & Lima de Albuquerque, É. (2012). Failure criteria for adhesively bonded joints. International Journal of Adhesion and Adhesives, 37, 26–36. [CrossRef]
• [23] Goland, M., & Reissner, E. (1944). The stresses in cemented joints. Journal of Applied Mechanics, 11, A17–A27.
• [24] da Silva, L. F. M., Costa, M., Viana, G., & Campilho, R. (2017). Analytical modelling for the single-lap joint. In R. Campilho (Ed.), Strength Prediction of Adhesively-Bonded Joints (pp. 8–46). CRC Press. [CrossRef]