Ductility Estimation of Concrete Beams Longitudinally Reinforced with Hybrid FRP-Steel Bars

An experimental study was carried out to evaluate the ductility of reinforced concrete beams longitudinally reinforced with hybrid FRP-Steel bars. The specimens were fourteen reinforced concrete beams with and without hybrid reinforcement. The test variables were bars position, the ratio of longitudinal reinforcement, and the type of FRP bars. The beams were loaded up to failure using a four-point bending test. The performance of the tested beams was observed using the load-deflection curve obtained from the test. Numerical analysis using the fiber element model was used to examine the growth of neutral axis depth due to the effect of test variables. The neutral axis curves were then used to further estimate the neutral axis angle and neutral axis displacement index. The test results show that the position of the reinforcement greatly influences the flexural behavior of the beam with hybrid reinforcement. It was observed from the test that the flexural capacity of beams with hybrid reinforcement is 4% to 50% higher than that of the beams with conventional steel bars depending on bars position and the ratio of longitudinal reinforcement. The ductility decreases as the hybrid reinforcement ratio (Af/As) increases. This study also showed that a numerical model developed can predict the flexural behavior of beams with hybrid reinforcement with reasonable accuracy.

Experimental analysis of composite materials leaf spring used in automotive

product modifications or replacement of old products with new and improved material items. Vehicle suspension systems are another area where these developments are carried out on a regular basis. More efforts are being made to improve the user's comfort. Appropriate combination of comfort riding attributes and economics in leaf spring production becomes an evident requirement. Many changes have been made to the suspension system throughout time in order to enhance it. Some of the most recent suspension system innovations include the invention of the parabolic leaf spring and the usage of composite materials for these springs. The implementation of composite materials by replacing steel in conventional leaf springs of a suspension system. Composite material having a lot of good properties like simple fabrication, low weight and low cost to performance .The purpose of this study is to investigate the structural properties of a hybrid leaf spring consisting of 95% Epoxy, 5% carbon, 5% glass fiber, and 5% hybrid carbon-glass fiber composite. The various specimens were produced using the manual layup method, specimen were subjected to tensile, hardness, and fatigue tests, with all data reported and compared. The experimental results showed an increase in Hardness, Tensile, and fatigue life when the reinforcing fibers are applied. The best results of the mechanical test obtained when hybrid reinforcement was applied.

Analysis of the Mechanical and Preforming Behaviors of Carbon-Kevlar Hybrid Woven Reinforcement

Carbon-Kevlar hybrid reinforcement is increasingly used in the domains that have both strength and anti-impact requirements. However, the research on the preforming behaviors of hybrid reinforcement is very limited. This paper aims to investigate the mechanical and preforming behaviors of carbon-Kevlar hybrid reinforcement. The results show that carbon-Kevlar hybrid woven reinforcement presents a unique “double-peak” tensile behavior, which is significantly different from that of single fiber type reinforcement, and the in-plane shear deformation demonstrates its large in-plane shear deformability. Both the tensile and in-plane shear behaviors present insensitivity to loading rate. In the preforming process, yarn slippage and out-of-plane yarn buckling are the two primary types of defects. Locations of these defects are closely related to the punch shape and the initial yarn direction. These defects cannot be alleviated or removed by just increasing the blank holder pressure. In the multi-layer preforming, the compaction between the plies and the friction between yarns simultaneously affect the quality of final preforms. The defect location of multi-layer preforms is the same as that of single-layer, while its defect range is much wider. The results found in this paper could provide useful guidance for the engineering application and preforming modeling of hybrid woven reinforcement.

Transistor Sizing using Hybrid Reinforcement Learning and Graph Convolution Neural Network Algorithm

Transistor sizing is one the developing field in VLSI. Many researches have been conducted to achieve automatic transistor sizing which is a complex task due to its large design area and communication gap between different node and topology. In this paper, automatic transistor sizing is implemented using a combinational methods of Graph Convolutional Neural Network (GCN) and Reinforcement Learning (RL). In the graphical structure the transistor are represented as apexes and the wires are represented as boundaries. Reinforcement learning techniques acts a communication bridge between every node and topology of all circuit. This brings proper communication and understanding among the circuit design. Thus the Figure of Merit (FOM) is increased and the experimental results are compared with different topologies. It is proved that the circuit with prior knowledge about the system, performs well.

Influence of Heat Treatment on the Corrosion Behaviour of Aluminium Silver Nano Particle/Calcium Carbonate Composite

Corrosion is one of the leading sources of material failure and deterioration in society. Scholars have proposed different techniques to mitigate corrosion. This research study explores and validates one of these techniques. An Aluminium metal matrix (AMC) was produced using the stir casting method with various weight percentages of AgNp and CaCO3 reinforcements. Heat treatment was performed on the samples to enhance the metallurgical and corrosion properties of the materials. The corrosion rate of the AMC samples was tested in different corrosive media (neutral and acidic) with different concentrations using the weight loss analysis technique for several days. It was observed that the corrosion rate of the AMC relies on the nature of the electrolyte and the percentage concentration of this electrolyte. The heat treatment improves the corrosion resistance of the AMC samples. In addition, an increase in the % weight composition of the reinforcement (AgNp + CaCO3) results in a reduction in the corrosion rate of the AMC in both corrosive media. The optimal %weight composition was found to be 4% for the hybrid reinforcement of AgNp + CaCO3 and 6% for the CaCO3 reinforcement in both the untreated and heat-treated samples.