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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 24 Documents
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Search results for , issue "Vol. 11 No. 7 (2025): July" : 24 Documents clear
Experimental and Bearing Capacity Research on Prestressed Shape Memory Alloy Strips Confined Concrete Column Xu, Lidan; Mu, Guangtao; Zhao, Jitao; Zhu, Miaomiao; Chen, Ming; Yan, Yutong; Shi, Mingfang
Civil Engineering Journal Vol. 11 No. 7 (2025): July
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-07-01

Abstract

The prestressed shape memory alloy (SMA) strips confined columns are a novel reinforcement method, which not only exerts active confinement stress on the core concrete but also avoids the common stress hysteresis problem in reinforcement. This paper performed axial compression tests on eight sets of concrete columns with varying SMA strip width, net spacing, and pre-strain, and the impacts of these variables regarding the failure pattern, bearing capacity, and deformability of the specimens were investigated. A calculation model for the bearing capacity of SMA strips actively confined to concrete columns was established and contrasted with the prediction performance of the BP neural network. The results indicate that compared to the unconfined column, SMA strip-confined columns exhibit obvious ductile failure under compression, with the highest increase of bearing capacity and deformability reaching up to 20.27% and 24.96%, respectively. The confinement effect becomes better and better with the increasing strip width or the decreasing strip net spacing. When the strip pre-strain gradually increases, the bearing capacity of confined columns gradually improves, while the deformability first enhances and then weakens. The experimental data of other scholars is used to verify that the calculation results accord with the experimental results well, and the prediction precision of the proposed calculation model exceeds that of the BP neural network. Meanwhile, it is confirmed that the BP neural network exhibits a high fitting level in bearing capacity prediction (R2training=0.990 and R2test=0.965), offering a novel approach for predicting the bearing capacity of structures.
Prediction the Dynamic Modulus of Hot Asphalt Mix Using Genetic Algorithms and Neural Network Modeling Hanandeh, Shadi M.; Aneke, Frank I.; Alajlan, Zaid; Al khateeb, Shadi; Alkharabsheh, Ruba A.
Civil Engineering Journal Vol. 11 No. 7 (2025): July
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-07-08

Abstract

The dynamic modulus is a fundamental characteristic of asphalt concrete and expresses the stiffness properties of a hot mix asphalt mixture as a function of temperature and loading rate. This study used artificial neural network modeling and genetic algorithms to evaluate the asphalt concrete dynamic modulus. The experimental database was collected from LTPP DATA that used in the ANN and genetic algorithm development and modeling. The output for the two models was the asphalt concrete dynamic modulus. Moreover, mathematical models were employed to predict the dynamic modulus of asphalt concrete with different parameters. Following the establishment of the model designs, the deficiencies and strengths of the proposed models are evaluated using determination coefficient (R2) values. The evaluation was performed by comparing the dynamic modulus of asphalt concrete predicted from four models with the dynamic modulus obtained from the experimental testing. Notably, the neural network models achieved precise calculations for models 1 and 2, with R2 values of 0.96 and 0.93, respectively. The genetic algorithm models achieved R2 values of 0.73 for model 1 and 0.64 for model 2. The two models, the genetic algorithm model and the artificial neural network model, contributed to the generation of two new empirical equations.
Enhancing Durability in Recycled Concrete: Investigating Chloride Permeability with Recycled Aggregates and Plastic Waste Jantarachot, Krissana; Prayongphan, Somchai; Yodsudjai, Wanchai; Thepjunthra, Wiphada; Trakolkul, Chokchai; Thongchart, Siranya
Civil Engineering Journal Vol. 11 No. 7 (2025): July
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-07-020

Abstract

This study investigates the effects of substituting fine aggregates with recycled plastic in recycled concrete, focusing on chloride penetration, compressive strength, workability, and porosity. Recycled plastic was incorporated at 10% (A10) and 20% (A20) by volume, and properties were evaluated across six mix designs. The control mix without plastic (Mix A) achieved the highest 28-day compressive strength (400 KSC), while A10 and A20 showed reduced strengths of 320 and 255 KSC, respectively. The addition of plastic increased mix porosity, resulting in reduced strength and workability due to diminished cement bonding and lubrication. Chloride ingress was assessed under cyclic wetting–drying exposure using a 3.5% NaCl solution. Results revealed progressive surface chloride accumulation over time. Notably, Mix A showed a 137.96% increase in chloride content at a 0–2 cm depth after 280 days, with Mix A20 exhibiting even higher surface concentrations. Chloride content consistently decreased beyond a 4 cm depth, indicating limited long-term penetration into inner layers. These findings highlight the importance of porosity control in mitigating chloride transport in recycled concrete. A clear relationship between plastic content, increased porosity, and enhanced chloride diffusion was observed. While 10% plastic substitution demonstrated acceptable performance, higher levels significantly compromised durability. The study recommends limiting plastic waste incorporation to 10% by volume and maintaining a concrete cover of at least 8–10 cm over reinforcement to enhance resistance against chloride-induced corrosion. These findings support the controlled reuse of plastic waste in sustainable concrete development, particularly for non-structural or low-exposure applications. Optimizing mix design and incorporating supplementary cementitious materials are suggested to improve long-term durability.
Modeling of Geomechanical Processes from Open Pit to Underground Mining with Complex Morphology Bekbergenov, Dossanbay; Jangulova, Gulnar; Zeinullin, Abdikarim; Zhanakova, Raissa; Shagirova, Karlygash; Atalykova, Nazym; Kurmanbayev, Olzhas
Civil Engineering Journal Vol. 11 No. 7 (2025): July
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-07-013

Abstract

The relevance of this study is the need to optimize the transition from open-pit to underground mining in mines with complex deposit morphologies, such as the Akzhal Mine. This is essential to ensure the safety of mining operations and to prevent adverse manifestations of rock pressure and mass cave-ins when changing the type of mining. This study aimed to develop a geomechanical basis for selecting an optimal mining system for the transition from open-pit to underground mining. Particular attention is paid to rock mass stability and its behavior during mining operations, which makes it possible to optimize the parameters of the mining system by considering the characteristics of a mine with a complex deposit morphology. This study used methods to assess the strength of the rock mass, including the concept of the geological structure of the natural environment, the methodology of determining the structural weakening coefficient, and the determination of the rock mass deformation modulus using the fracturing ratio and stability of the rock mass coefficient with an analytical functional relationship of geo-structural factors. The study results made it possible to systematize the rock mass by stability categories and proposed recommendations for the safe operation of deposits during the transition to underground mining, on the choice of mining system, and on the design of its elements. The novelty of this study lies in an integrated approach for predicting the behavior of rock mass and selecting the optimal mining system, which makes it possible to improve the safety and efficiency of production under difficult geological conditions.

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