Emerging Technologies and Engineering Journal

Shear Strengthening and Rehabilitation of Normal Reinforced Concrete Beams: A Review

2024-08-20T00:33:54-06:00

The structural integrity of reinforced concrete (RC) structures diminishes over time due to ageing, unexpected loads such as earthquakes, and corrosion-induced deterioration, necessitating rehabilitation or replacement. Insufficient shear capacity and lack of ductility in normal RC beams lead to extensive damage during earthquakes. Addressing shear deficiencies is critical as they are more hazardous and can lead to sudden failure. Shear strengthening of RC beams enhances their load-carrying capacity and prevents brittle shear failures. This paper reviews several methods of strengthening beams in shear, focusing on the Fiber Reinforced Polymers (FRP) method for strengthening beams in shear as ACI 440.2R fully covers the design procedure. To enhance the shear strength of a concrete beam using FRP, the shear force contribution by the composite should be estimated, and a suitable system should be selected, such as two-sided, three-sided wraps or a fully wrap system of the application. Then, the spacing between the FRP strips should be found. The beam would be properly strengthened for shear using FRP sheets.

Effect of Different Types and Ratio of Fibers on the Tensile Strength of Reinforced Foam Concrete: A Review

2024-09-05T00:34:53-06:00

Reducing the weight of buildings—particularly dead loads—is one effective way to lower construction costs. Foam concrete offers a viable alternative to conventional concrete for non-structural elements. This paper reviews the impact of incorporating polypropylene, natural fibers, steel fibers from waste tyres, and carbon fibers on the tensile strength of foamed concrete. According to the literature, the polypropylene content varied between 0.2% and 0.8%, with different target densities. Steel fibers extracted from scrap tyres ranged from 0.2% to 0.6%, while carbon fiber and Henequen fiber (natural fiber) were used separately or in combination with polymers in volumetric fractions ranging from 0.5% to 1.5%. The results presented in this paper indicate that tensile strength gradually increased as the volume of fibers increased up to a certain point, suggesting an optimal dosage for enhancing performance.

Modeling Signal Integrity in High-Frequency and Radio Frequency Circuits: A Comparison of Ohm's Law Variants

2024-08-22T01:47:40-06:00

High-frequency circuit performance is significantly impacted by impedance variations, particularly within the low-resistance regime. Traditional Ohm's Law-based modeling approaches often fail to accurately predict circuit behavior in these conditions, leading to design inaccuracies and potential system failures. The Standard Ohm's Law-based model's prediction of infinite current as resistance approaches zero is unrealistic and hinders its application in practical scenarios. Despite recognizing these limitations, existing models have not comprehensively addressed the complex impedance behavior observed in high-frequency circuits. This paper introduces a modified version of the Ohm's Law incorporating an exponential correction term to overcome these challenges. The accuracy of the Modified Ohm's Law was evaluated through simulated experiments across a wide frequency range (1kHz to 1GHz) using various electronic components. The findings demonstrate the superior performance of the modified model in predicting currents under low-resistance and high-current conditions compared to the Standard Ohm's Law model. By providing finite and accurate current values, the proposed model effectively mitigates the unrealistic infinite current predictions of the standard approach. The enhanced predictive capabilities of the Modified Ohm's Law hold significant implications for high-frequency circuit design and analysis. Its application can improve performance and reliability in power electronics, telecommunications, and other high-frequency systems. By incorporating non-linear impedance behavior, the model offers a more accurate representation of real-world circuit conditions. Future research should focus on refining the exponential term's parameters to optimize the model's accuracy across a broader range of applications. Additionally, real-time implementation and hardware validation are essential to assess the model's practical utility in complex circuit environments.

An Artificial Neural Network Model for Short-Term Traffic Flow Prediction in Two Lane Highway in Khulna Metropolitan City, Bangladesh

2024-06-15T10:22:43-06:00

Short-term traffic flow prediction is one of the most significant research topics in traffic engineering. It is instrumental in designing a more modern transport network to manage traffic signals and reduce congestion. Short-term traffic flow is a challenge that a third-world country like Bangladesh is all too familiar with. Like the other cities of Bangladesh, Khulna Metropolitan City is gradually becoming more aware of this situation. The Khulna-Jashore National Highway (N-7), which runs through the city and provides a linear shape, serves as the backbone of the Khulna Metropolitan City traffic flow. This study developed an Artificial Neural Network (ANN) model for the short-term Traffic Flow Prediction on Two-Lane Highway in Khulna Metropolitan City, Bangladesh. Data was collected from March 1, 2021, through June 30, 2021, during 600–900 hours and 1200–1500 hours. Good-quality electronic cameras recorded the vehicles at the full designated length. The regression graphs displayed the network outputs with targets for the training, validation, and test sets. The various speed level parameters for which the fit is reasonable for all data sets, with R values of 0.98426 in each case. The various traffic volume parameters for which the fit is reasonable for all data sets, with R values of 0.96758 in each case. The model's superiority is indicated by its low mean squared error values. This study demonstrated that the neural network has a good prediction effect on specific road traffic flow, which can achieve the goal of short-term prediction and has improved practicability through testing on real traffic data. This study provides an opportunity to provide a suitable alternative for short-term traffic flow forecasting in Khulna Metropolitan City with traffic flow conditions for two-lane undivided highways.

Utilization of Neem Seed Oil as Surfactant in the Production of Flexible and Rigid Polyurethane Foam

2024-06-01T07:32:59-06:00

Extraction and processing of polyether polyols derived from petrochemicals, commonly used as surfactants during polyurethane foam (PUF) production, contribute to carbon emissions and raises the issue of long-term sustainability given that petrochemicals are non-renewable resources. Here, 5 mg and 4 mg of neem seed oil are employed to form flexible and rigid PUF, classified purposefully based on their divergent usage. To find an environmentally friendly replacement, flexible PUF whose mass, volume, density, compression, tensile strength, cream time, foam rise and rising time are 0.0047 kg m³, 16.52 kg/m³, 8.10%, 39.28 kN/m², 60s, 10s and 60s is formed by mixing 1.25 kg polyol, 5mg silicon oil and 10g calcium carbonate (CaCO3). Likewise, by mixing 1.2 kg polyol, 4mg silicon oil and 8g CaCO3, a rigid PUF with 0.005kg, m³, 16.2 kg/m³, 8.15%, 40.72 kN/m², 50s, 15 cm and 58s key, physical and mechanical property as respectively listed under the flexible PUF formulation is produced. Both foams were produced using equal amounts of toluene diisocyanate, water, stannous octoate and methylene chloride, resulting in PUF that can be used in insulation, cushioning and construction support applications based on their characteristic height, density, tensile strength and compressive strength. As the surfactant, neem seed oil's potential in the synthesis of PUF cannot be overemphasized. The study of the kinetics of PUF production is limited and should trigger the adoption of biobased surfactants for industrial applications in the future.