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INDONESIA
Civil Engineering Journal
Published by C.E.J Publishing Group
ISSN : 24763055     EISSN : 24763055     DOI : -
Core Subject : Engineering,
Civil Engineering, Building, Construction & Architecture
Civil Engineering Journal is a multidisciplinary, an open-access, internationally double-blind peer -reviewed journal concerned with all aspects of civil engineering, which include but are not necessarily restricted to: Building Materials and Structures, Coastal and Harbor Engineering, Constructions Technology, Constructions Management, Road and Bridge Engineering, Renovation of Buildings, Earthquake Engineering, Environmental Engineering, Geotechnical Engineering, Highway Engineering, Hydraulic and Hydraulic Structures, Structural Engineering, Surveying and Geo-Spatial Engineering, Transportation Engineering, Tunnel Engineering, Urban Engineering and Economy, Water Resources Engineering, Urban Drainage.
Arjuna Subject : -
Articles 20 Documents
 1   2 
Search results for , issue "Vol 10, No 9 (2024): September" : 20 Documents clear
The Challenges of Implementing Cognitive Computing in Small Construction Projects: A Data-Driven Perspective Alsehaimi, Abdullah; Alrasheed, Khaled A.; Hayat, Saleh; Nisar, Saad; Benjeddou, Omrane
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-011

Abstract

This study aims to identify and analyze the challenges of implementing cognitive computing in small construction projects, where decision-making, process optimization, and sustainability enhancements are crucial yet challenging. The research adopts a mixed-methods approach, integrating a thorough literature review, quantitative evaluation, and structural equation modeling (SEM) to explore the relationships between the identified barriers and the effective application of cognitive computing. The findings reveal significant hurdles, including complexity in customization (β = 0.327, t = 9.848, p < 0.001), data integrity and integration issues (β = 0.389, t = 14.534, p < 0.001), financial and cultural constraints (β = 0.295, t = 7.850, p < 0.001), and ethical and privacy concerns (β = 0.319, t = 8.963, p < 0.001). These barriers impede the seamless adoption of cognitive computing technologies. This research contributes novel insights into the specific challenges faced by small construction projects and provides practical recommendations to overcome these obstacles. By addressing these challenges, this study offers valuable guidance for stakeholders aiming to leverage cognitive computing to improve project outcomes in the construction industry. The novelty of this research lies in its focus on small-scale projects, a relatively underexplored area, and its comprehensive analysis of the multifaceted barriers that hinder the successful implementation of cognitive computing. Doi: 10.28991/CEJ-2024-010-09-011 Full Text: PDF
Analysis of Traffic Safety Factors and Their Impact Using Machine Learning Algorithms Sejdiu, Liridon; Tollazzi, Tomaz; Shala, Ferat; Demolli, Halil
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-06

Abstract

The safety of road traffic is facing increasing challenges from a range of factors, and this study aims to address this issue. The paper describes the development of a model that assesses both the quantitative and qualitative aspects of the current traffic situation and can also predict future trends based on monthly data on traffic accidents over a period of years. The dataset is composed of the number of accidents that occurred in the Pristina region over a 10-year period, and these are categorized based on the type of accident and safety factors, including human, vehicle, and road factors. By using machine learning algorithms, a model has been developed that determines the factor with the greatest impact on traffic safety. To create the model, the algorithms Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Random Trees (RT) were used. The model evaluates the contribution of human, road, and vehicle factors to traffic accidents, using machine learning algorithms and 36 types of traffic accidents to analyze the relevant statistics. The results indicate a very good fit of the model according to the MLR algorithm, and this model also identifies the road factor as the main influencer of the traffic safety level. Doi: 10.28991/CEJ-2024-010-09-06 Full Text: PDF
Modeling of the Full-Scale Secondary Sedimentation Basin Using the GPS-X Model Hasan, Safi A.; Nile, Basim K.; Faris, Ahmed M.
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-017

Abstract

The secondary sedimentation basin is being modeled in this study for the first time using the GPS-X model instead of the computational fluid dynamics (CFD) model. This study was conducted in the extended-aeration Al-Hur treatment plant that struggles with unstable sedimentation in its sedimentation tank. After collecting and entering the data into the GPS-X model, the model was calibrated and validated, and the results were statistically examined based on R and RMSE. To determine the efficiency of the sedimentation tank, the following scenarios were investigated: 1) testing the efficiency in removing pollutants; 2) conducting state point analysis (SPA); and 3) measuring the concentration of sludge in the layers of the sedimentation basin. Six factors were considered during the sensitivity analysis, namely sludge volume index (SIV), surface area, underflow rate (RAS), pumped flow (WAS), maximum settling velocity, and liquid temperature. The calibration and validation results were within the specified limits, and the secondary sedimentation basin demonstrated high efficiency in removing pollutants, with the analysis point (SPA) obtaining the highest MLSS concentration of 3000 mg/L. The sludge concentrations in the lower layers were 7000 mg/L, while those in the upper layer were 18 mg/L. These results suggest that a lower (100 ml/g) sludge volume index corresponds to a better sedimentation basin efficiency. Increasing the surface area of sedimentation basins can positively affect their efficiency, while increasing waste-activated sludge, maximum settling velocity, and liquid temperature may reduce pollutants and improve the sedimentation process. The GPS-X model is demonstrated as an excellent tool for understanding and predicting the work behavior of sedimentation basins, making this model particularly valuable for the management of sewage treatment plants. Doi: 10.28991/CEJ-2024-010-09-017 Full Text: PDF
Adaptive Seismic Upgrading of Isolated Bridges with C-Gapped Devices: Model Testing Ristic, Jelena; Ristic, Danilo; Behrami, Ragip; Hristovski, Viktor
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-01

Abstract

The seismic safety margins of seismically isolated bridges have not been thoroughly studied or comprehended due to a lack of actual on-site data observations. This study introduces a newly validated method for the efficient seismic protection of bridges that may be exposed to extremely strong, multidirectional near-source and critical far-source earthquakes. The isolated system was improved by incorporating innovative adaptive horizontal C-multigapped (HC-MG) energy dissipation devices to overcome the safety limitations associated with solely using isolated bridges under seismic loads. The newly developed adaptive C-gapped (ACG) bridge system was systematically validated through extensive experimental seismic tests on bridge models and additional analytical studies. The new ACG bridge system represents an advanced technical solution that integrates the benefits of seismic isolation and energy dissipation. The seismic isolation system for the large-scale ACG bridge prototype was designed using double spherical rolling seismic bearings (DSRSB). The seismic performance of the system was enhanced with adaptive HC-MG energy dissipation devices. The improved seismic performance of the system was demonstrated through extensive seismic shaking-table tests on the ACG bridge prototype, simulating selected seismic inputs characteristic of typical near- and far-source earthquakes. Doi: 10.28991/CEJ-2024-010-09-01 Full Text: PDF
Development of Pavement Deterioration Models Using Markov Chain Process Isradi, Muhammad; Rifai, Andri I.; Prasetijo, Joewono; Kinasih, Reni K.; Setiawan, Muhammad I.
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-012

Abstract

A common phenomenon in developing countries is that the function of the pavement in the road network will experience structural damage before the completion of life is reached, and the uncertainty of pavement damage is difficult to predict. Planning for maintenance treatment depends on the accuracy of predicting future pavement performance and observing current conditions. This study aims to apply the Markovian probability operational research process to develop a decision support system predicting future pavement conditions. Furthermore, it determines policies and effectiveness in managing and maintaining roads. A standard approach that can be used by observing the history of pavement damage from year to year is to estimate the transition probability as a Markovian-based performance prediction model. The results show that the application of the model is quite optimal, changes in pavement conditions after repair can be easily compared with an increase in good condition, reaching 92.8%. Routinely and consistently handling road deterioration will give favorable results regarding pavement condition value. This will ease in the management of the road network and the accomplishment of the optimal maintenance and repair policies. Doi: 10.28991/CEJ-2024-010-09-012 Full Text: PDF
Frictional Axial Resistance of Clamped Split Pocket Mechanism Steel Structural Joint: An Experimental Study Putra, Whelly T.; Setiawan, Angga F.; Saputra, Ashar; Satyarno, Iman; Pratama, Hamdi Y.
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-07

Abstract

The Clamped Split Pocket Mechanism (CSPM) prefabricated joint system was developed for a single-story steel instant house, designed to be compact and rapidly constructed without modifying the end of the beam and column element member. The CSPM bolted joint system was proposed as an optimal solution for post-disaster housing, especially after earthquakes. Despite its potential, the frictional tensile resistance behavior of the CSPM bolted joint system has not been previously studied, necessitating experimental investigation. This study examined the frictional tensile resistance behavior of the CSPM joint system by monitoring the effective friction coefficient under axial tension force. The experiments considered both the strong and weak axes of the joint and utilized two configuration types of specimens (L and T) with varying bolt pretensions of 2.5, 5, 7.5, and 10 kN. Results indicated that the effective friction coefficient of the CSPM bolted joint system ranged from 0.19 to 0.26, correlated to bolt pretension. Increased bolt pretension resulted in larger surface deformation of the split pocket, triggering a not uniform frictional tensile resistance across the steel surfaces of the split pocket joint. From this study, the achieved effective friction coefficients could guide the design of minimum pretension forces for clamps in prefabricated steel instant houses. Doi: 10.28991/CEJ-2024-010-09-07 Full Text: PDF
Artificial Intelligence Using FFNN Models for Computing Soil Complex Permittivity and Diesel Pollution Content Nimer, Hamsa; Ismail, Rabah; Rawashdeh, Adnan; Al-Mattarneh, Hashem; Khodier, Mohanad; Hatamleh, Randa; Abuaddous, Musab
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-018

Abstract

Soil pollution caused by hydrocarbons, such as diesel, poses significant risks to both human health and the ecosystem. The evaluation of soil pollution and various soil engineering applications often relies on the analysis of complex permittivity, encompassing parameters such as dielectric constant and dielectric loss. Various computational models, including theoretical physics-based models, mixture theory models, statistical empirical models, and artificial neural network (ANN) models, have been explored for computing soil complex permittivity and predicting water and pollutant content. Theoretical models require detailed data that is often unavailable, and thus have limited applicability. Mixture models tend to underestimate soil characteristics due to inaccuracies in permittivity estimation of soil phases. While empirical models are widely used, their applicability is restricted to specific soil types, datasets, and locations. ANN models offer promising predictions, accommodating nonlinear phenomena and allowing for missing information and variables. In this study, capacitive electromagnetic electrode sensors were utilized to determine the complex permittivity of soil contaminated with varying levels of diesel at different moisture levels. Theoretical mixture, empirical, and Feed Forward Neural Network (FFNN) models were employed to compute the permittivity of polluted soil based on its phases and to predict the level of diesel pollution. A comparison of these modeling approaches revealed that the FFNN model exhibited the best performance. The ANN model demonstrated superior performance metrics, including a high correlation coefficient and lower mean square error. Specifically, the correlation coefficients for the FFNN model were 0.9942 for training samples, 0.9967 for validation samples, and 0.9977 for test samples. Additionally, the ANN model yielded the lowest mean square error compared to the other three models. Doi: 10.28991/CEJ-2024-010-09-018 Full Text: PDF
Effectiveness of Different Configurations of Ferrocement Retrofitting for Seismic Protection of Confined Masonry: A Numerical Study Habieb, Ahmad B.; Hidayat, Muhammad R.; Sutrisno, Wahyuniarsih; Kandymov, Nurmurat; Milani, Gabriele
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-02

Abstract

A ferrocement layer, which consists of a wire mesh and cement mortar, is a popular retrofitting method for existing structural elements, particularly wall or slab panels. This paper presents a study on the effectiveness of different configurations of ferrocement for seismic retrofitting of confined masonry through finite element analysis. The masonry panel was modeled using expanded brick-unit elements, where the element was expanded in size by as much as half of the mortar thickness, and an interacting zero-thickness interface was applied to mimic the elastic-plastic and damage behavior during tension, shear, and compression. The concrete damage plasticity (CDP) model was used to model the confining reinforced concrete frame and overlay mortar in the ferrocement layer, and the reinforcing bars and wire mesh were modeled using elastic-plastic behavior. In the present numerical study, nine models were subjected to cyclic and pushover shear test simulations, considering the effects of the number of ferrocement layers and the wire mesh orientation. The volumetric ratio of the wire mesh to the masonry (ρwm) ranged from 0.48% to 1.92%, whereas the ratio of the mortar overlay to the masonry (ρmo) varies from 10.42% to 41.66%. Based on the increase in the lateral strength, the model with the largest volume of the ferrocement layer exhibited the largest increase in strength. However, the most cost-effective retrofitting configuration was presented by model DS-1-45, in which a single layer of ferrocement was applied on both sides of the wall using 45° of wire mesh orientation. The DS-1-45 model provided a lateral strength increase of more than 6 times compared to the original unreinforced model. Doi: 10.28991/CEJ-2024-010-09-02 Full Text: PDF
Effect of Climate Change on Wetland Areas in West Iraq Using Satellite Data and GIS Techniques Hassan, Waqed H.; Khazaal, Suhail T.; Al-Shammari, Musa H.
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-013

Abstract

Iraq is considered to amongst those countries in the Middle Eastern region that are most exposed to the effects of climate change, which will have notable effects on wet areas and lakes. Natural or industrial water resources must be paid particular attention due to their importance in preserving environmental and biological systems, in addition to their economic and social importance. As a result of the effects of climatic change, water resources in Iraq have seen a multitude of changes. The aim of this study is to determine changes in the wetland area around AL-Razzaza Lake, Karbala province, Iraq, during the years 2000, 2005, 2010, 2015, and 2023. Landsat 5 satellite data from 2000, 2005, and 2010, and Landsat 8 and 9 data for 2015 and 2023, respectively, were used in this analysis, which was conducted using NDWI as a free, open-source program (ArcMap 10.8) to detect these changes; NDWI is a natural water anisotropy index used to detect the surface area of bodies of water in satellite images. The results revealed a clear decrease throughout the study period, as the wetland area of the lake in 2000 was 1189.7 km2, which represents a decrease of 34.3% compared to the total area of the lake (1810 km2); it decreased by 52.7% in 2005 (855.5 km2) and continued to decrease for 2010, 2015, and 2023, by 79.2%, 80%, and 85%, (376.5 km2, 362.9 km2, and 270.4 km2, respectively). The wetland area of Al-Razzaza Lake decreased between 2000 and 2023 by 919.3 km2, that is, an average of 40 km2per year. It was found that the lake wetland area sharply declined over the study period due to a lack of water surface resources via the Euphrates River, as well as climatic changes and poor water resource management. It is anticipated that the lake will lose more than half its current wetland area by 2040 if the current decline continues. These results are considered important in terms of preparing a strategic plan to preserve water bodies and wet areas in Iraq, including Al-Razzaza Lake. Remote sensing and GIS technologies have played a major and essential role in detecting such changes. Doi: 10.28991/CEJ-2024-010-09-013 Full Text: PDF
Experimental Investigation on Pervious Recycled Aggregate Concrete Made of Waste Porcelain Khoshnaw, Ganjeena J.; Younis, Khaleel H.; Hamad, Waleed A.; Ismail, Ayser J.; Jukil, Glpa Ali Mahmood; Jirjees, Firas F.; Yaba, Hozan K.; Maruf, Shelan M.
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-08

Abstract

The current study examines the physical, mechanical, and durability of eco-efficient pervious concrete produced with partial and complete substitutions of natural aggregate (NA) by recycled aggregate (RA) waste from demolished concrete and porcelain. The experimental investigation assessed the workability (slump test), compressive strength, flexural strength, and tensile strength along with the concrete's water permeability, impact, and abrasion resistance. Seven mixes were examined; the first is a control mix with natural aggregate, and the other six are made with various RA ratios, including 30%, 70%, and 100%. The sand was also fully replaced by waste porcelain, even though the ratio of sand used in pervious concrete was low. The results revealed that using waste concrete and porcelain adversely affected the workability of fresh pervious concrete mixes, reducing it by approximately 14%. Furthermore, a decrease in the strength of pervious concrete was noticed, especially in the splitting tensile strength, where the reduction reached 32%. Moreover, the impact resistance of pervious concrete made with RA reduced by 29% compared to that made with NA; the same applies to durability, with an increase of 20% in weight loss. On the other hand, using both recycled concrete and recycled porcelain improved the permeability of the pervious concrete, which reached 30%. Pervious concrete made with waste concrete and porcelain can be an acceptable alternative to that made from natural aggregate due to its improved water permeability and positive environmental impact. However, further investigation is important to consider strength and durability enhancement. Doi: 10.28991/CEJ-2024-010-09-08 Full Text: PDF

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