Perumal Kajendran
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Perumal Kajendran has a total of 1 co-authors. Here are the top co-authors by number of shared publications:
- Narayanan Pannirselvam
Department of Civil Engineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, India
3 shared publications
Latest Publications
- Open Access
- 1 January 2025
- Published by FapUNIFESP (SciELO) in Matéria (Rio de Janeiro)
- Vol. 30, e20240793
Machine learning-based prediction of ultimate load in pultruded glass fibre column under axial compression
This experimental study investigates the axial compression effect of rectangular pultruded glass fiber-reinforced polymer (P-GFRP) tubular column sections, examining the impact of width-to-thickness ratio (B/t), aspect ratio (H/B), and column height on their structural performance. A total of 27 GFRP columns were subjected to axial compression tests to evaluate their ultimate load and initial stiffness. The columns exhibited a uniform failure pattern, characterized by crushing, mid-section fractures, and longitudinal splitting at the corners. The results revealed a negative correlation between the ultimate load and the aspect ratio, as well as the width-to-thickness ratio. This study utilized advanced machine learning algorithms, namely Response Surface Methodology (RSM) and Artificial Neural Network (ANN), to develop predictive models for the ultimate load of GFRP columns. The RSM model achieved an R2 value of 0.8347, demonstrating good accuracy in predicting ultimate load. The ANN model outperformed the RSM model, with an R criterion exceeding 0.68807 across training, testing, and validation phases, showing a stronger correlation between experimental and predicted outcomes. This research establishes a framework for forecasting the mechanical properties of column sections.
- 1 January 2025
- Published by FapUNIFESP (SciELO) in Matéria (Rio de Janeiro)
- Vol. 30, e20240793
Open AccessMachine learning-based prediction of ultimate load in pultruded glass fibre column under axial compression
This experimental study investigates the axial compression effect of rectangular pultruded glass fiber-reinforced polymer (P-GFRP) tubular column sections, examining the impact of width-to-thickness ratio (B/t), aspect ratio (H/B), and column height on their structural performance. A total of 27 GFRP columns were subjected to axial compression tests to evaluate their ultimate load and initial stiffness. The columns exhibited a uniform failure pattern, characterized by crushing, mid-section fractures, and longitudinal splitting at the corners. The results revealed a negative correlation between the ultimate load and the aspect ratio, as well as the width-to-thickness ratio. This study utilized advanced machine learning algorithms, namely Response Surface Methodology (RSM) and Artificial Neural Network (ANN), to develop predictive models for the ultimate load of GFRP columns. The RSM model achieved an R2 value of 0.8347, demonstrating good accuracy in predicting ultimate load. The ANN model outperformed the RSM model, with an R criterion exceeding 0.68807 across training, testing, and validation phases, showing a stronger correlation between experimental and predicted outcomes. This research establishes a framework for forecasting the mechanical properties of column sections.
- 13 May 2024
- Published by IOP Publishing in Engineering Research Express
- Vol. 6 (2) , 025110
Experimental and finite element investigation on bolted connection in monolithic 3-dimensional cuff with pultruded box section
This article presents a concise and practical research study on the application of pultruded GFRP (Glass Fiber Reinforced Polymer) hollow sections in structural engineering. Experimental and computational investigations are conducted on the utilization of GFRP cuff components for joining tubular pultruded fiber-reinforced polymer (PFRP) beams and columns. Both adhesive bonding and bolted connections are explored for connecting PFRP box sections of beam-column interfaces. The study investigates twelve series of beam-to-column connections under monotonic loading conditions, varying cuff geometry. A finite element model is developed to represent the pultruded fiber-reinforced polymer box sections, columns, and cuff sections. The model’s accuracy in depicting frame stiffness and cuff damage patterns, considering different thicknesses and lengths of GFRP cuff connections, is validated against experimental test frame behavior. This research fills a gap in scientific inquiry regarding GFRP hollow profiles, providing valuable insights for structural engineering applications.
- 13 May 2024
- Published by IOP Publishing in Engineering Research Express
- Vol. 6 (2) , 025110
Experimental and finite element investigation on bolted connection in monolithic 3-dimensional cuff with pultruded box section
This article presents a concise and practical research study on the application of pultruded GFRP (Glass Fiber Reinforced Polymer) hollow sections in structural engineering. Experimental and computational investigations are conducted on the utilization of GFRP cuff components for joining tubular pultruded fiber-reinforced polymer (PFRP) beams and columns. Both adhesive bonding and bolted connections are explored for connecting PFRP box sections of beam-column interfaces. The study investigates twelve series of beam-to-column connections under monotonic loading conditions, varying cuff geometry. A finite element model is developed to represent the pultruded fiber-reinforced polymer box sections, columns, and cuff sections. The model’s accuracy in depicting frame stiffness and cuff damage patterns, considering different thicknesses and lengths of GFRP cuff connections, is validated against experimental test frame behavior. This research fills a gap in scientific inquiry regarding GFRP hollow profiles, providing valuable insights for structural engineering applications.