Civil Engineering Journal
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2007 research outputs found
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Assessment of Urban Changes at the Residential Neighbourhood Level Based on Satellite Imageries
No full textOngoing urban expansion leads to the steady loss of green spaces. Residential units' gardens and green open spaces are a vital part of city life, contributing considerably to urban green infrastructure and ecological services. However, these areas are diverse, making it difficult to assess their changes over time to take advantage of their benefits and contribution to sustainable urban development. This study proposes a new methodology that combines survey data with high-resolution image analysis to construct maps and statistics of change in two residential neighbourhood areas in the Iraqi city of Baqubah. Three change detection techniques utilising very high-resolution multispectral Pléiades images were used to evaluate the changes: pixel value differencing, band index differencing, and categorical change detection. Then, a unique strategy employing geo-processing processes by the ModelBuilder tool was applied to the evaluation outcomes to assess the changes in a final manner. In addition to survey data that supported the final change detection outcomes, study validation was conducted through field verification, and the mean accuracy was 93%. The final results indicated that open or green spaces decreased over a period of seven years at rates of 24% and 14% of the total of both areas assessed. Policymakers and urban planners see such privately owned land as difficult to affect. However, reducing vegetative cover areas and turning them into impermeable surfaces may result in the areas becoming inefficient in the development of urban sustainability. Our developed method demonstrates the capability of utilising Very High Resolution (VHR) imagery with local survey data to accurately infer changes in urban vegetation within residential neighbourhood regions. Doi: 10.28991/CEJ-2025-011-01-05 Full Text: PD
Driver Drowsiness and Alcohol Detection for Automotive Safety Systems
No full textDriver drowsiness and alcohol impairment are major causes of traffic accidents, making road safety a main concern. This study highlights the importance of addressing these issues through improved driver monitoring technologies. A prototype combining MQ-3 alcohol sensors, and facial detection was created, integrating with IoT via a Raspberry Pi to monitor and alert on drowsiness and alcohol levels. The developments use the NTHU-DDD dataset, which supports a supervised learning approach to develop a reliable drowsiness detection model. The study explored various machine learning algorithms such as Logistic Regression, Support Vector Machine (SVM), Random Forest (RF), K-nearest neighbors (KNN), Gradient Boosting Classifier, and Gaussian Naive Bayes, with Random Forest and Gradient Boosting emerging as top performers, particularly suited to complex non-linear data. The system effectively used supervised learning techniques to differentiate drowsy and non-drowsy images and exhibited consistent accuracy in detecting drowsiness, especially when the driver’s face was centered. However, accuracy decreased when faces were tilted, highlighting areas for refinement. Moreover, the environmental tests on the MQ-3 sensor demonstrated its sensitivity to alcohol presence, even distinguishing the intensity based on beverage type and concentration. The findings underscore the efficacy of using sensor-based technologies in real-world conditions and provide a foundation for optimizing the system's detection capabilities across various scenarios
Shaking-Table Test on a Multi-Story Continuous Vibration-Control System Employing Pulley Amplification Mechanism
No full textThis study proposes an innovative passive vibration-control system, named the Pulley Damper Multi-story System (PDMAS), which incorporates pulley tackles installed at multiple stories in the successive stories to amplify inter-story displacement. This configuration significantly enhances the energy absorption efficiency of the linked dampers at the middle of the cable by utilizing the cumulatively amplified story displacements via a continuously stretched cable across the entire structure. The proposed system shows notable potential for controlling responses induced by higher vibration modes by customizing the wire installation layout. The aim of this study is to introduce PDMAS and to investigate its seismic-mitigation effectiveness. As a primary investigation of this new system, comparative experimental studies were conducted through shaking-table tests on nine specimens featuring various cable layouts optimized for the first and second structural vibration modes, with or without dampers, under harmonic waves, white-noise waves, and simulated seismic waves. The experimental results demonstrate that the PDMAS effectively accommodates the cumulative amplified story displacement across the structure to match theoretical damper values. Furthermore, the specimens employing PDMAS with a wire layout optimized for the first structural mode reduced both acceleration and displacement by nearly half compared to specimens without PDMAS. Doi: 10.28991/CEJ-2025-011-01-02 Full Text: PD
Sedimentation Characteristics and Sediment Transport in the Palu River Estuary
No full textSedimentation is the process through which materials transported by water flow settle within that water. Changes in current patterns, driven by tides and variations in current velocity, can influence sediment transport. This study aimed to identify sediment transport patterns and analyze the characteristics of suspended sediment and bed load in the Palu River estuary. We employed field investigations, two-dimensional (2D) numerical modeling, and data analysis to process the findings. The results indicated that the sediment characteristics in the Palu River estuary varied, with a predominance of sand and gravelly sand. Additionally, sediment transportation patterns were found to be primarily influenced by river flow discharge rather than tidal effects. The research findings are presented in a correlation equation that illustrates the relationship between dimensionless parameters: C = Ïs.(a.ψ)bwith coefficient values of a = 412.71 and b = (-0.545). The results of this correlation equation indicate that as the energy from water movement increases, sediment becomes more dispersed, leading to changes in the concentration of sediment particles. It can be concluded that various variables affect sediment transport due to hydrodynamic conditions. Doi: 10.28991/CEJ-2025-011-02-03 Full Text: PD
A Theoretical Pore Network Model for the Soil–Water Characteristic Curve and Hysteresis in Unsaturated Soils
No full textThis study presents a novel approach to modeling the soil–water characteristic curve in unsaturated soils, employing Monte Carlo simulations to capture the complex behavior of the pore network. The primary objective is to develop an alternative method to represent the hysteretic nature of the soil–water characteristic curve, which is critical for understanding unsaturated soil behavior in various engineering applications. The proposed approach conceptualizes soil as a network of interconnected pores, where each pore interacts with its nearest neighbors. Monte Carlo simulations are used to model the pore-filling distribution as a function of pressure differences during drying and wetting cycles. The model effectively reproduces the characteristic hysteresis curves associated with the hydraulic and mechanical processes in unsaturated soils. A key finding is that the simulated soil–water characteristic curve captures the impact of pore-scale interactions and reflects the complex hysteresis effects observed in experimental data. The novelty of this work lies in integrating pore network modeling with Monte Carlo simulations, addressing limitations of traditional models and offering a more accurate representation of unsaturated soil behavior. While the model has not yet undergone experimental validation, it provides valuable insights into the dynamics of soil moisture retention and serves as a foundation for future experimental testing and refinement of soil–water models. Doi: 10.28991/CEJ-2025-011-02-021 Full Text: PD
Downscaling GRACE Data for Improved Groundwater Forecasting Using Artificial Neural Networks
No full textThis study introduces a dual-phase approach utilizing Artificial Neural Networks (ANNs) to overcome the challenges of groundwater monitoring at regional scales. Traditional well-based methods provide limited spatial coverage, while GRACE satellite data, despite its value for large-scale hydrological analysis, suffers from low spatial resolution (~300 km), limiting its application for local-scale assessments. Existing downscaling methods such as geographically weighted regression and Random Forests are computationally intensive and often lack adaptability to complex groundwater systems. In this study, Phase 1 refines GRACE data using ANNs to achieve a 4í—4 km spatial resolution, addressing the resolution challenge for regional applications. Phase 2 integrates the downscaled GRACE data with groundwater well observations and climatic factors to predict groundwater levels with high accuracy (R² = 0.9885). This dual-phase framework demonstrates significant improvements over existing methods, providing an efficient and scalable solution for groundwater monitoring in hydrologically complex regions. The findings highlight the potential of machine learning to enhance groundwater resource management, particularly in addressing water scarcity and climate variability challenges. Doi: 10.28991/CEJ-2025-011-02-01 Full Text: PD
Modeling Tourist Transportation Mode Choice and Trip Chains Through Key Influencing Factors
No full textTo understand tourist behavior and the factors influencing it, a thorough analysis of transportation mode choice and trip chain is required, especially from the tourists' perspective. Therefore, this study aims to model transportation mode choice and trip chain in the Bira Peninsula, Bulukumba Regency, South Sulawesi. To achieve this, a quantitative method was employed with a sample size of 500 tourists. The study results show that independent variables significantly impact dependent variables, such as individual characteristics, movement characteristics, destination attributes, mode choice attributes, and trip chains. Several indicators showed a significant influence for transportation mode choice with a confidence level of over 85%. These indicators include age, income, origin location, destination location, number of visits, group size, flexibility, facilities, ease of access, activity type, cost, distance, time, and safety. Similarly, the analysis identified several key indicators affecting the trip chain, with a significance level above 85%. These indicators include age, income, origin, destination location, estimated arrival time, number of visits, flexibility, and destination attraction. Other indicators include facilities, ease of access, trip purpose, activity type, travel time, distance from the city center to the tourist destination, cost, distance, time, and safety. Two significant indicators found as differentiators from previous research are flexibility and type of activity. The study demonstrated high accuracy for the mode choice model and the trip chain model, with validity rates of 98.40% and 97.65%, respectively. The findings indicate that the model accurately captures the factors influencing transportation mode choice and trip chains, making it a valuable reference for future explorations to improve transportation systems' efficiency and comfort. Doi: 10.28991/CEJ-2025-011-02-017 Full Text: PD
Enhancing Construction Safety Evaluation Through a Standardized Rating Tool System
No full textIndonesia has achieved considerable advancements in infrastructure development over the past decade; yet, the incidence of work-related accidents in the construction sector continues to be elevated. Data indicates that the rising trend of infrastructure projects in Indonesia correlates with the annual increase in work-related accidents. This signifies that a construction safety issue persists. Despite the establishment of pertinent rules, the execution of the construction safety management system remains suboptimal. Noncompliance with safety rules is a primary contributor to construction accidents. Consequently, measurement is essential to evaluate the enforcement of construction safety regulations. Regrettably, the execution of safety performance metrics in building projects has been inadequate. It is executed customarily using non-standardized parameters, differing from one project to another. This project seeks to create a rating tool system for assessing construction safety performance and to analyze the relationship model between information systems and safety rating tools in relation to construction safety performance. This study employs both qualitative and quantitative methodologies. The initial phase involved the development of an information system for measuring construction safety performance, utilizing characteristics derived via expert validation. The second stage examined the impact of the system on construction safety performance. The findings indicated that the information system and safety rating tools positively impact construction safety performance. Furthermore, the Safety Rating Tools system standardizes the assessment of construction safety performance, rendering it more straightforward and efficient. The evaluation results aim to enhance compliance to safety standards to prevent building mishaps. Doi: 10.28991/CEJ-2025-011-04-016 Full Text: PD
Dynamic Analysis of MICP-Stabilized Soil and Liquefiable Soil With Varying Salinity Levels
No full textThis study investigates the liquefaction potential of soils at Yogyakarta International Airport (YIA), a high-risk seismic zone, and evaluates the efficiency of carbonate precipitation driven by microbial activity (MICP) stabilization under varying salinity situations. The purposes include understanding the dynamic response of natural and MICP-treated soils to seismic loads and assessing the role of salinity in soil behavior. Triaxial cyclic testing was conducted on remolded soil samples at a very loose density (Dr = 10%) to simulate field situations, using Bacillus Safensis. Microbes and a biocementing procedure enhanced with 35% fly ash. Salinity levels of 0%, 1%, 2%, and 3.4% were tested by curing for 28 days. The outcomes reveal that untreated soils liquefied inside of 4–6 cycles at ru = 0.8 for 0%, 2%, and 3.4% salinity. In contrast, 1% salinity delayed liquefaction to 14 cycles, thereby enhancing soil resistance. MICP-treated soils showed enhanced stiffness, decreased compressive strain, and extended resistance to liquefaction under dynamic loads. SEM and XRD analyses verified CaCO3deposition, particle bonding, and decreased pore space. The novelty lies in demonstrating the significant role of salinity in enhancing the MICP procedure and improving soil stability, providing a sustainable solution for mitigating liquefaction risks in saline coastal regions. Doi: 10.28991/CEJ-2025-011-04-010 Full Text: PD
The Role of Urban Structure in Enhancing the Sustainability of Cities: A Comparative Study
No full textThe topic of sustainable urban structure is a crucial area in urban planning, given its direct connection to land use patterns, their distribution and density, as well as their relationship with transportation network patterns. These factors play a vital role in achieving sustainability. The theoretical aspect of the research focused on modern literature and global experiences addressing sustainable urban structures, aiming to provide a clear definition and to identify critical indicators that influence the achievement of urban sustainability. The study identified seven key indicators: density, average distance to the center, hierarchical structure, spread index, land price, the location of the center relative to the city, and the street network pattern. These indicators are applicable and measurable for any city worldwide to assess the sustainability of its urban structure. The research conducted a comparative case study between the cities of Kut and Hillah. The urban structure of Kut is characterized by separation due to the presence of a river, whereas Hillah features a more connected structure, in addition to differences in density distribution, land use, and transportation network patterns. The indicators for both cities were measured using mathematical models, geographic information systems (GIS), and three-dimensional spatial representations. The study concluded that while the indicator results varied between the two cities, Kut achieved better outcomes than Hillah in four of the seven indicators. Doi: 10.28991/CEJ-2025-011-04-015 Full Text: PD