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Study on Shear Behavior of Reinforced Concrete Beams Confined with Reinforcing Meshes
No full textThis study reveals the results of a numerical simulation performed using the ABAQUS/CAE finite element program. The study aimed to provide a simulation model that can forecast the shear behavior of reinforced concrete beams confined with reinforcing meshes. Limited numerical studies have been conducted using geogrid or FRP mesh as shear reinforcement, with limited representation accuracy and limited material quality. The results were compared to published experimental findings in the literature. The finding of the finite element model and the experimental results were highly comparable; consequently, the model was determined to be valid. Following this, the domain of numerical analyses was broadened to include the investigation of many aspects, like the material of reinforcement mesh, the angle of inclination of mesh strip, and the number of mesh strips. The results show that the inclined strip beams gave ultimate loads greater than the beams with vertical strips, where the ultimate load for beams with inclined strips was higher than that for beams with vertical strips by 5.6, 2.5, and 9.4% for beams with geogrid, geotextile, and GFRP mesh, respectively. The smaller the strip width and the larger the number, the better. Beams with inclined strips (45°) gave higher ductility indexes than similar beams with vertical strips. Beams with six strips (width of 50 mm) gave higher ductility indexes than similar beams with four strips (width of 75 mm)
Predicting Speeding Behavior of Long-Haul Freight Truck Drivers Using Machine Learning Models
Get PDFThe behavior of long-haul truck drivers is shaped by the weak enforcement of working-hour rules, tight deadlines, and heavy workloads. Over-dimensioning and overloading practices further increase risks by forcing drivers to handle excessive loads and work for prolonged periods. This study predicts speeding behavior among long-haul freight truck drivers using statistical and machine learning models. Data was collected from 370 respondents at two weigh stations in South Sulawesi, Indonesia, covering eight socio-demographic, economic, and operational predictors. Three models were tested: Binary Logistic Regression (BLR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The dataset was balanced and split into 70% training and 30% testing, with performance assessed using accuracy, recall, F1-score, and AUROC. XGBoost delivered the best results, achieving 97.3% accuracy, 93.2% recall, a 96.4% F1-score, and a perfect AUROC of 1.000. RF also showed strong performance with 94.05% accuracy and an AUROC of 0.973, while BLR served as a relevant baseline despite weaker predictions. Key predictors of speeding violations were daily sleep duration, monthly income, and driving experience. This study demonstrates how machine learning can be effectively integrated alongside transportation data under imbalanced conditions, providing evidence-based insights to strengthen freight transport safety
Effect of the Stepped Spillway Geometry on the Flow Energy Dissipation
Get PDFIn this research, flume experiments were conducted on stepped weirs to investigate the effect of step shape on the energy dissipation of flow. Four configurations with a constant number of steps were considered, namely, horizontal steps, inclined steps, horizontal steps with rounded sills, and "Žinclined steps with rounded sills. The slopes of inclined steps were 13% and 23%, and the diameters of the rounded sills of the step ends were 10 and 15 cm. The majority of previous studies focused on energy dissipation in stepped weirs in horizontal and inclined steps. In this research, new step geometries were used, such as horizontal steps with rounded sills and inclined steps with rounded sills. Dimensional analysis was applied to correlate the different variables affecting the flow hydraulics. Flow rates in the range of 0.61-9.12 lit/sec were used with each step shape. Results showed that the inclined steps with rounded sills had the highest flow energy dissipation in comparison to the other types. Rounded sills at the end of steps had more effective energy dissipation than did the horizontal step. However, the 23% inclination slope with rounded sills of a 7.5 cm radius was the most effective in dissipating flow energy. Doi: 10.28991/CEJ-2024-010-01-09 Full Text: PD
Application of GIS Models in Determining the Suitable Site for a Solid Waste to Energy Plant in an Urban Area
Get PDFThis paper deals with the establishment of a solid waste-to-energy plant that significantly reduces the volume of solid waste and produces electricity at the same time. Thirteen criteria have been identified to locate the station based on environmental, economic, and social factors to avoid its negative impacts. These criteria were addressed by combining a Multi Criterion Decision Making (MCDM) method based on the GIS software. This study aims to establish a MCDM system based on the classical AHP and validated by the fuzzy AHP method. The findings revealed that using the classical AHP and fuzzy AHP methods, there was no significant difference in decision-making between the two methods. The importance of the criteria under study has been identified based on the judgments of experts; a questionnaire was designed and conducted electronically, which was collected with the help of a weighted overlay GIS model. This technique combines multiple reclassified data in ArcGIS 10.8 software to overlay criteria layers with different weights to create a composite map of suitability categories across the study area. The outcomes revealed that 96.76% of the study area is unsuitable for establishing the station, 1.36% is moderately suitable, and 0.04% is only very suitable for station site selection. Doi: 10.28991/CEJ-2024-010-01-011 Full Text: PD
Concrete Strength and Aggregate Properties: In-Depth Analysis of Four Sources
Get PDFIn the field of Reinforced Concrete Construction, concrete emerges as the predominant and extensively employed construction material. Concrete comprises a solid, chemically inert granular substance called coarse aggregate (CA) bonded with cement and water. Compared to fine aggregate or cement, CA has a larger volume of concrete. By examining the characteristics of the coarse aggregate using various laboratory testing processes, the coarse aggregate may be properly used in concrete. Bangladesh is experiencing significant growth in its infrastructure industry due to the construction of mega projects nationwide. For the building of RCC in Bangladesh, coarse aggregate is mainly procured from two sources in Bangladesh, and another is imported from China. This study aims to develop a clear understanding of aggregate and concrete strength quality for different coarse aggregates and track changes in the appearance of CA from multiple sources in China and Bangladesh. Coarse aggregates were collected from four prominent sources: Jaflong and Bholaganj (Bangladesh), Shandong, and Jiangsu (China). ACV (aggregate crushing value), gradation, voids, and unit weight; AIV (aggregate impact value), absorption, specific gravity, and resistance to abrasion-induced deterioration; and Los Angeles (LA) machines' impact tests have been conducted for all sources of CA. The concrete cylinder was made and tested for all sources of CA with the same ratio of cement, sand, and water to know the concrete strength for different CAs. Doi: 10.28991/CEJ-2024-010-04-016 Full Text: PD
Prediction of the Dynamic Properties of Concrete Using Artificial Neural Networks
Get PDFThis study explores how dynamic characteristics of concrete, such as dynamic shear modulus, dynamic modulus of elasticity, and dynamic Poisson's ratio, affect stability and performance in civil engineering applications. Traditional testing procedures, which include the time-consuming and costly process of mixing and casting specimens, are both time-consuming and costly. The primary objective of this research is to improve efficiency by using Artificial Neural Networks (ANNs) and regression analysis to predict the dynamic properties of concrete, providing a machine-learning-based alternative to traditional experimental methodologies. A set of 72 concrete specimens was methodically built and evaluated, with compressive strengths of 50 MPa, aspect ratios ranging from 1 to 2.5, and an average density of 2400 kg/m3. An input dataset and ANN targets were built using these samples. The ANN model, which used cutting-edge deep learning techniques, went through extensive training, validation, and testing, as well as statistical regression analysis. A comparison shows that the predicted dynamic modulus of elasticity and shear modulus using both ANN and regression approaches nearly match the experimental values, with a maximum error of 5%. Despite good forecasts for the dynamic Poisson's ratio, errors of up to 20% were detected on occasion, which were attributed to sample shape variations. Doi: 10.28991/CEJ-2024-010-01-016 Full Text: PD
Recycling of Eggshell Powder and Wheat Straw Ash as Cement Replacement Materials in Mortar
Get PDFCement is among the important contributors to carbon dioxide emissions in modern society. Researchers are studying solutions to reduce the cement content in concrete to minimize the negative impact on the environment. Among these solutions is replacing cement with other materials, such as waste, which also poses environmental damage and requires landfill areas for disposal. Among these wastes are eggshell powder ash (ESPA) and wheat straw ash (WSA), which were utilized as cement substitutes in green mortar production. Thirteen mixtures were cast, one as a reference without replacement and twelve others that included replacing ESPA and WSA (single and combined) with cement in 2%, 4%, 6%, and 8% proportions of cement's weight. The mechanical (compressive and flexural strength), microstructural (SEM), and thermogravimetric analysis (TG/DTA) properties of all mixtures were examined. The results showed a remarkable improvement in mechanical properties, and the best improvement was recorded for the (4%ESPA+4%WSA) mixture, which reached 73.3% in compressive strength and 56% in flexural strength, superior to the reference mixture. Furthermore, SEM analyses showed a dense and compact microstructure for the ESPA and WSA-based mortars. Therefore, the WSA and ESPA wastes can be recycled and utilized as a substitute for cement to produce an eco-friendly binder that significantly improves the microstructural and mechanical characteristics of mortar. In addition, combining the two materials also presents a viable option for creating a sustainable ternary blended binder (with cement) that boasts superior properties compared to using the WSA or ESPA individually. Doi: 10.28991/CEJ-2024-010-01-05 Full Text: PD
Vulnerability Index Assessment for Mapping Ground Movements Using the Microtremor Method as Geological Hazard Mitigation
Get PDFVarious geological disasters, such as landslides and ground movements, occur annually in Srimulyo Village, Malang District, with varying levels of damage. Ground movements can affect structures built above, causing sinking, cracking, and collapse. Research into landslides and ground movements triggered by vibrations is generally conducted using the microtremor method, which has proven effective. This study uses the microtremor method to map the soil condition that is potentially prone to movement or landslides based on the observed soil vulnerability index. Data was collected using a TDL 303s Digital Portable Seismograph instrument; the measurement points were established in the form of a grid distributed across the research area, with a recording duration of approximately 45 minutes at each point. The analysis technique utilizes the Horizontal Vertical Spectrum Ratio (HVSR) based on the Fast Fourier Transform (FFT) principle. The study's results found that the research location's seismic vulnerability index varies between 6.5 and 16.5. Areas with high seismic vulnerability index values, specifically those with Kg>11.5, are scattered on the west, south, and southeast sides of the research location. Based on field observations, these areas are dominated by relatively thick sediment layers, leading to lower dominant frequency values and higher amplification values; consequently, the seismic vulnerability index in the southern region is also high. Doi: 10.28991/CEJ-2024-010-05-017 Full Text: PD
Effect of Construction Manager's Political Skills on Relationship between Quality Management Practices and Inter-Organizational Project Success
Get PDFThis study aims to explore the impact of construction managers' political skills on the relationship between quality management practices and the success of inter-organizational construction projects in Pakistan. Objectively, it examines how project managers' political acumen influences the effectiveness of quality management strategies and, consequently, project success. Employing a survey-based methodology, the research encompasses a broad spectrum of professionals involved in various construction projects across Pakistan. Through this analysis, the study identifies key challenges to project success and assesses the correlation between managerial political skills and the effective implementation of quality management practices. The findings reveal a notable positive relationship between these elements, highlighting the critical role of skills such as communication, stakeholder management, and conflict resolution. Additionally, the research underscores the interconnected nature of managerial competencies and identifies key factors impacting project success through advanced statistical techniques like principal component analysis and median absolute deviation. Significantly, this research provides novel insights into the role of human factors in the Pakistani construction industry's project management, proposing actionable strategies for skill enhancement and offering a comprehensive overview of factors influencing project success. These findings not only show the current skills and practices landscape but also lay the groundwork for future research and strategy implementation to boost industry-wide success. Doi: 10.28991/CEJ-2024-010-01-019 Full Text: PD
Development of a Cross-Asset Model for the Maintenance of Road and Water Pipe Assets using AHP Method
Get PDFRoads and water pipe assets undergo various deterioration processes due to the high demand for their services. Maintenance of these assets is often planned as individual assets, and the interdependency among different assets is neglected. An integrated framework for cross-asset maintenance is required for optimum utilization of the available funds for asset maintenance. To date, there are very few studies focusing on the use of the analytical hierarchy process (AHP) for cross-asset maintenance of roads and water pipe assets. Therefore, this research aims to develop an integrated fund allocation model for the maintenance of road and water pipe assets. A model was developed using AHP analysis based on expert opinions captured through a questionnaire in order to obtain optimum maintenance fund allocation for the cross-assets, roads, and water pipes. Then, a case study corridor segment with the considered cross-assets was selected, and a trade-off analysis was conducted for the intervention alternatives considering different levels of service (LOS) of the asset elements. The results of the trade-off analysis can be used to identify the optimum intervention alternative that satisfies the budget requirement and results in the maximum benefit. Overall, asset managers can use the approach presented in the present study to develop a cross-asset fund allocation model when multiple assets are involved in maintenance. Doi: 10.28991/CEJ-2024-010-02-01 Full Text: PD