Carbon-Fiber-reinforced Polymer as Confinement Reinforcement to Maximize Compressive Strength of Engineered Bamboo: An Artificial Neural Network Model

The type of infrastructure and selection of its materials is one of the principal factors that must be considered. Due to its usual large quantifications on projects, it directly affects the environment and communities where it belonged. And collectively, the future of our world. As a strong, versatile, durable, sustainable, and environmentally beneficial material, bamboo and its derivatives are frequently utilized since the early times; the Philippines is fortunate to have an abundance of it across the country. The mechanical properties of one of the local R&D-prioritized and market-prominent bamboo specie, the Bambusa blumeana, are remarkable and well-known to be an excellent material for many structural elements. But to fully utilize it, reinforcements may be required, just like with any other ligneous and organic materials. Extensions in its compression strength along the grain may be accomplished from its 50.83 MPa average strength by confinement-reinforcing it with the promising, adaptable, and strong Carbon-fiber-reinforced polymer (CFRP). The Artificial Neural Network (ANN) model involving CFRP's confinement reinforcement thickness, edges that constitutes the compression area, moisture content, temperature, and density of Laminated Veneer Bamboo (LVB) was established using the Levenberg-Marquardt (LM) algorithm as the training algorithm (TA) and hyperbolic tangent sigmoid as the transfer function (TF). The relationship of the variables to the composite section's ultimate compressive strength, was indirectly proportional, except for density, and was further checked the influence using Garson's algorithm (GA). In addition, the results were verified using additional physical experimentation and Finite Element (FE) simulations, while the ANN model was compared to other prediction modelling techniques, by which the FE simulation proved to be an effective complement to the physical testing and the ANN prediction model performed the best. The results also reconfirmed other literature on engineered bamboo studies; and the failure of the CFRP-LVB composite section was found to be a combination of isolated partial failures of the LVB core as the cross-sections become larger, while full crushing was observed on smaller cross-sections.