[This article belongs to Volume - 56, Issue - 01, 2024]
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-27-05-2024-55

Title : MECHANICAL BEHAVIOUR OF RC COLUMNS USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNIQUES
Srinivasa C H1, Manjunatha H2, Dr Jayesh Juremalani3, Dr. Chetan S. Deshpande4, K. Vallarasu5, Ujjval Jayantibhai Solanki6

Abstract :

In this paper, a creative strategy is advanced for assessing the unique mechanical ways of behaving of supported concrete (RC) section individuals by applying the irregular woodland calculation. First, the proposed method's implementation and the creation of dynamic modified coefficient (DMC) predictive models were elaborated. Then, because of the absence of dynamic stacking tests on RC segment individuals, a mathematical model of RC sections considering the unique change on flexural, shear and bond-slip ways of behaving was created on the OpenSees stage, and the model exactness and the viability were confirmed with the accessible experimental outcomes. In addition, the effects of dynamic modification and the deformation sub-element were investigated by comparing the simulated results of the hysteretic curve using numerical models of varying complexity. Moreover, a mathematical trial information base was laid out to get the preparation information for fostering the DMC prescient models of basic mechanical conduct boundaries, including the yielding bearing limit, extreme bearing limit and uprooting pliability. At last, the consequences of component significance for various info boundaries were contemplated, and the model exactness was assessed utilizing the test set and accessible exploratory information. It was uncovered that the prescient models created utilizing the irregular woods calculation can be utilized to appraise the powerful mechanical ways of behaving of RC section individuals dependably.