PREDICTION OF ULTIMATE LOAD ON RCC BEAM UTILIZING ANN ALGORITHM

Authors

  • Praveen Kaurav, Research Scholar (Dept. of Civi lEngineering, Gyan Ganga Institute of Techanology & Science, Jabalpur M.P.)
  • Anubhav Rai Asst. Prof. (Dept. of Civi lEngineering, Gyan Ganga Institute of Techanology & Science, Jabalpur M.P.)
  • Dr. Preeti Rai associate prof. (Dept. of Computer science, Gyan Ganga Institute of Techanology & Science, Jabalpur M.P.)
  • Prof. Yogesh kumar Bajpi (Gyan Ganga Institute of Techanology & Science, Jabalpur M.P.)

Keywords:

concrete beam, ultimate load, parameters

Abstract

In this research work, shows an analytical study regarding RCC (reinforced cement concrete) beam comprised with FRP (fiber reinforced polymers) bars. ANN is used in order to estimate and predict the ultimate load of a RCC beam along with the prediction of the failure load associated in the beam. A total of 40 dataset of simply supported beams are considered in the study. The neural network has been trained using MATLAB tool as it contains different training networks and application of training algorithm can be done easily. The data are arranged in a format such that 6 input parameters cover the geometrical and loading properties of beams and the corresponding output is the ultimate failure load. Several input parameters are considered in the study such as the length (L) in the range (900-3000 mm), width (b) in the range (80-250 mm), depth (d) in the range of (150-300 mm), compressive strength of concrete (Fc) in between range (25-80 Mpa), tensile strength (fu) in the range of (3.5-1300 Mpa), elasticity modulus (Ef) in the range of (23000-45000 Mpa) for the RCC beam, and only the ultimate load (40-248kN) is calibrated as the output variable. The input parameters have been taken as per the reference from previous works in the literature. The complete dataset is taken in five parts and depending on the reference papers. Further mean values of the ultimate load is calculated from each part in order to identify the type of beams suitable for use to bear the ultimate load. The results depict significant improvement in percentage for each of the data set which has been calculated. The predicted values from the five datasets gives 15.57%, 7.38%, 10.33%, 16.04% and 5.86% improvement respectively compared to actual ultimate load values. The results showed that using ANN method successfully predicted the values for the ultimate load of the beam. Separate graphs for each of the datasets have been plotted depicting the comparison between the actual ultimate load and predicted ultimate load. The predicted results were more accurate in terms of predicting the failure load. Scope of future work has been also discussed later in this study.

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Published

30-06-2019

How to Cite

Praveen Kaurav, Anubhav Rai, Dr. Preeti Rai, & Prof. Yogesh kumar Bajpi. (2019). PREDICTION OF ULTIMATE LOAD ON RCC BEAM UTILIZING ANN ALGORITHM. International Journal for Research Publication and Seminar, 10(2), 72–83. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1259

Issue

Vol. 10 No. 2 (2019): APRIL-JUNE

Section

Original Research Article

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