Analysis of stiffness and flexural strength of a reinforced concrete beam using an invented reinforcement system

Nariman, Nazim Abdul; Hušek, Martin; Mohammad, Ilham Ibrahim; Ahmed, Kaywan Othman; Dilshad, Diyako; Khidr, Ibrahim

doi:10.1007/s11709-021-0706-z

Cited by 2 publications

(1 citation statement)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a previous study, Nariman et al [14] experimentally and numerically investigated the flexural strength and stiffness of an invented reinforced concrete beam with a new reinforcement system comprising additional steel bracings and steel plates, arranged to auto-balance the compression and tension forces developed in the member due to an increasing applied load in a three-point flexure test. The newly invented reinforcement system increased the flexural strength and the stiffness of the member to 300% compared with an ordinary reinforced concrete beam.…”

Section: Introductionmentioning

confidence: 99%

Optimum Design of Flexural Strength and Stiffness for Reinforced Concrete Beams Using Machine Learning

et al. 2021

View full text Add to dashboard Cite

In this paper, an optimization approach was presented for the flexural strength and stiffness design of reinforced concrete beams. Surrogate modeling based on machine learning was applied to predict the responses of the structural system in three-point flexure tests. Three design input variables, the area of steel bars in the compression zone, the area of steel bars in the tension zone, and the area of steel bars in the shear zone, were adopted for the dataset and arranged by the Box-Behnken design method. The dataset was composed of thirteen specimens of reinforced concrete beams. The specimens were tested under three-points flexure loading at the age of 28 days and both the failure load and the maximum deflection values were recorded. Compression and tension tests were conducted to obtain the concrete data for the analysis and numerical modeling. Afterward, finite element modeling was performed for all the specimens using the ATENA program to verify the experimental tests. Subsequently, the surrogate models for the flexural strength and the stiffness were constructed. Finally, optimization was conducted, supporting the factorial method for the predicted responses. The adopted approach proved to be an excellent tool to optimize the design of reinforced concrete beams for flexure and stiffness. In addition, experimental and numerical results were in very good agreement in terms of both the failure type and the cracking pattern.

show abstract

Section: Introductionmentioning

confidence: 99%