Influence of Corrugated Web Geometry on Mechanical Properties of I-beam: Laboratory Tests

This paper presents the results of experimental investigations performed on beams with corrugated webs. The aim of the research was to determine the effect of the geometric parameters of the sinusoidal web on the behavior of I-beams subjected to four-point bending. Special attention was paid to the effects of web thickness and wave geometry on the deflection of beams. The obtained failure modes of particular test samples are presented. Reference has also been made to the determined standard load capacities based on Annex D of the EC3 standard. In order to compare the performance of beams with corrugated webs, the results for beams with flat webs of the same thickness of web sheets are also presented.

Determining the Shear Capacity of Steel Beams with Corrugated Webs by Using Optimised Regression Learner Techniques

The use of corrugated webs increases web shear stability and eliminates the need for transverse stiffeners in steel beams. Optimised regression learner techniques (ORLTs) are rarely used for calculating shear capacity in steel beam research. This study proposes a new approach for calculating the maximum shear capacity of steel beams with trapezoidal corrugated webs (SBCWs) by using ORLTs. A new shear model is proposed using ORLTs in accordance with plate buckling theory and previously developed formulas for predicting the shear strength of SBCWs. The proposed ORLT models are implemented using the regression learner toolbox of MATLAB software (2020b). The available data of more than 125 test results from different specimens prepared by previous researchers are used to create the model. In this study, web geometry and relevant web steel grades determine the shear capacity of SBCWs. Four regression methods are adopted. Results are compared with those of an artificial neural network model. The model output factor represents the ratio of the web vertical shear stress to the normalised shear stress. Shear capacity can be estimated on the basis of the resulting factor from the model. The proposed model is verified using two methods. In the first method, a series of tests are performed by the authors. In the second method, the results of the model are compared with the shear values obtained experimentally by other researchers. On the basis of the test results of previous studies and the current work, the proposed model provides an acceptable degree of accuracy for predicting the shear capacity of SBCWs. The results obtained using Gaussian process regression are the most appropriate because its recoded mean square error is 0.07%. The proposed model can predict the shear capacity of SBCWs with an acceptable percentage of error. The recoded percentage of error is less than 5% for 93% of the total specimens. By contrast, the maximum differential obtained is ±10%, which is recorded for 3 out of 125 specimens.