Optimizing beam performance: ANSYS simulation and ANN-based analysis of CFRP strengthening with various opening shapes

Abstract

In modern construction, pipes and ducts are necessary for computer networking, electrical systems, air conditioning, water distribution, sewage management, and critical services. These conduits, which typically have diameters between a few millimeters and half a meter, can weaken the beam strength, increase deflection, encourage cracking, and decrease stiffness, all of which can compromise the structural integrity of buildings. One creative and affordable way to overcome these obstacles is to retrofit concrete structures with CFRP sheets. This technology has many advantages, including a favourable strength‒weight ratio, resistance to corrosion, remarkable fatigue durability, simple installation, and minimal impact on existing structural parts. The current research examines the performance of reinforced cement concrete (RCC) beams featuring various openings—rectangular, rounded rectangular, elliptical, and circular—in the shear zone. This study assesses the performance of three different CFRP reinforcement procedures via ANSYS software. It considers three different wrapping methods compared with a control beam and an opening without wrapping. The analysis focuses on finite element analysis (FEA) to observe stress variations under applied loads, enabling comparisons of different beam deflections. According to the analytical data, using CFRP reinforcement around apertures—both internally and externally—significantly increases the load-carrying capacity, which is nearly identical to that of the control beam—especially for circular holes where there is a more equal distribution of stress. Additionally, the generation of beam deflection data through ANSYS FEA simulations is explored, which is followed by training an artificial neural network (ANN) model in MATLAB and Python. The resulting ANN model serves as a rapid and accurate alternative to traditional FEA in structural analysis by effectively predicting beam deflections across various scenarios. This research contributes valuable insights into improving structural resilience in contemporary construction practices, particularly regarding the integration of essential services.