Bending stiffness of bamboo-concrete composite (BCC) beams under short-term loads

Abstract

Bamboo-concrete composite (BCC) beams are newly-innovated products used for floor system which synergistically utilizes bamboo and concrete components. These composite beams at current technology belong to the beam characterized with partial composite action due to the existence of relative slip between bamboo segment and concrete slab. Existing investigations have demonstrated that the load bearing capacity of BCC beams depends on their bending stiffness; however, very limited prediction models are available to accurately estimate the bending stiffness of BCC beams. At present, the bending stiffness of BCC beams is predicted with the help of γ-method in Eurocode 5-Part 1-1, and available studies have demonstrated that this method overestimates the bending stiffness of BCC beams. To this end, this paper presents a novel explicit model characterized with mechanism and data mining to predict the bending stiffness of BCC beams under short-term loads. Three steps were performed to achieve the aforementioned research objective. The first step was to introduce the axial force transfer coefficient into the equilibrium equations of internal force for bamboo segment and concrete slab. Secondly, the bending stiffness of BCC beams was established by taking into account the effect of relative slip with the help of existing experimental results from the interfacial shear test and flexural test. Finally, the proposed model was validated by comparing with flexural performance results of BCC beams collected from available literature as well as those obtained from γ-method. The comparative results show that: i) the predicted bending stiffness of BCC beams is much closer to tested ones compared with γ-method; ii) the errors of proposed model predicting the bending stiffness for most BCC beams are within 10% of test results; however, nearly half of the predicted ones using γ-method have errors exceeding 10% of test results, both of which verify that the mechanism and data mining-dual driven model receives a better prediction for short-term bending stiffness of BCC beams.