Abstract
Timber connection is one of the important aspects that need to be evaluated in construction and manufacturing. The end product produced from these sectors depends on the strength of the timber connection especially in building constructions. A lot of laboratory experiments to measure the strength of timber connection were done before proceeding with the transformation process of a product. However, these experiments require high cost and time-consuming. In addressing these issues, there is an alternative mean that can be applied to predict the strength of timber connection to overcome those problems. This paper addresses on the employment of particle swarm optimization (PSO) in a simulated timber connection for tensile test with and without glass fiber-reinforced polymer (GFRP). Data from laboratory experiment of tensile test of tropical timber were used. The PSO potentially can adapt the behavior of the timber and predict the maximum weight that can be supported by the timber connection. The findings are acceptable which obtained 99.39 % accuracy for GFRP joints and 95.34 % accuracy for non-GFRP joint. By using population size of 20, it has shown that PSO provides good results and has capability to predict the timber joint strength. Results show that by combining the glass fiber-reinforced polymer (GFRP) sheet, the timber joint gives better strength than timber joint without GFRP. Thus, the outcome of PSO application would encourage the engineer or related construction fields to predict the timber joint strength with various fiber-reinforced polymer or other composite material.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Malaysian Investment Development Authority (MIDA).(n.d). Industries in Malaysia, from http://www.mida.gov.my
Teng, L. J. (2013). Timber industry needs restructuring: MTIB, The Sun.
Hassan, R., Ibrahim, A., Ahmad, Z., & Yusoff, M. (2014). Dowel-bearing strength properties of two tropical hardwoods. In InCIEC 2013 (pp. 27–36). Springer Singapore.
Yusoff, M., Roslan, I. I., Alisibramulisi, A., & Hassan, R. (2015). Computational Approach for Timber and Composite Material Connection Using Particle Swarm Optimization. In InCIEC 2014 (pp. 1141–1152). Springer Singapore.
Yusoff, M., Shalji, S. M., & Hassan, R. (2014). Particle swarm optimization for single shear timber joint simulation. In InCIEC 2013 (pp. 117–126). Springer Singapore.
Asif, R., Siril, Y., & Mark, D. (2014). Simulation and Optimization Techniques for Sawmill Yard Operations—A Literature Review. Journal of Intelligent Learning Systems and Applications, 06, 21–21. doi: 10.4236/jilsa.2014.61003
Favilla, S. (2010). Tensile Testing Laboratory. https://stephanfavilla.files.wordpress.com/2011/03/tensile-testing-laboratory.pdf, retrieved 4 September 2015.
Shafenzi, S. (2013). Tensile Behaviour of Bolted Timber Composite Connection for Merpauh (SG4). (Bachelor of Engineering (Hons) Civil), Universiti Teknologi MARA.
Hassan, R., Ibrahim, A., & Ahmad, Z. (2012, 23–26 Sept. 2012). Experimental performance of mortice and tenon joint strengthened with glass fibre reinforced polymer under tensile load. Paper presented at the Business, Engineering and Industrial Applications (ISBEIA), 2012 IEEE Symposium.
Judd, J., Fonseca, F., Walker, C., & Thorley, P. (2012). Tensile Strength of Varied-Angle Mortise and Tenon Connections in Timber Frames. Journal of Structural Engineering, 138(5), 636–644. doi: doi:10.1061/(ASCE)ST.1943-541X.0000468
Kennedy, J., & Eberhart, R. (1995). Particle Swarm Optimization. In In Proceeding of the IEEE International Conference on Neural Networks (Vol. 4, pp. 1942–1948). Perth, WA, Australia.
Kennedy, J., & Eberhart, R. C. (1997). A Discrete Binary Version of the Particle Swarm Algorithm. In Proceeding of the IEEE International Conference on Systems, Man, and Cybernetics (Vol. 5, pp. 4104–4108). Orlando, FL, USA.
Bhattacharya, I., & Samanta, S. (2010). Parameter Selection and Performance Study in Particle Swarm Optimization. AIP Conference Proceedings, 1298(1), 564–570. doi: 10.1063/1.3516367
Yusoff, M., Ariffin, J., & Mohamed, A. (2015). DPSO based on a min-max approach and clamping strategy for the evacuation vehicle assignment problem. Neurocomputing, 148(0), 30–38. doi: http://dx.doi.org/10.1016/j.neucom.2012.12.083
Acknowledgements
The authors would like to thank Faculty of Computer and Mathematical Sciences, Faculty of Civil Engineering, University Teknologi MARA and Institute for Infrastructure Engineering and Sustainable Management (IIESM) in establishing this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this paper
Cite this paper
Yusoff, M., Othman, D.F., Hassan, R., Alisibramulisi, A. (2016). Particle Swarm Optimization Application for Timber Connection with Glass Fiber-Reinforced Polymer (GFRP) and Non-GFRP. In: Yusoff, M., Hamid, N., Arshad, M., Arshad, A., Ridzuan, A., Awang, H. (eds) InCIEC 2015. Springer, Singapore. https://doi.org/10.1007/978-981-10-0155-0_10
Download citation
DOI: https://doi.org/10.1007/978-981-10-0155-0_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0154-3
Online ISBN: 978-981-10-0155-0
eBook Packages: EngineeringEngineering (R0)