cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
,
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 23 Documents
 1   2   3 
Search results for , issue "Vol. 12 No. 2 (2026): February" : 23 Documents clear
From Corrosion to Collapse: Spatiotemporal Evolution of Local Stability in Anchored Anti-Dip Slopes Wang, Ding-Jian; Wang, Qian-Yun; Fan, Zhi-Qiang; Ouyang, Fang; Zhang, Ya-Hui
Civil Engineering Journal Vol. 12 No. 2 (2026): February
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2026-012-02-01

Abstract

The long-term stability of anchored anti-dip slopes in hydropower and mining projects is threatened by corrosion-induced degradation of rock bolt systems. Existing deterministic models relying on global safety factors fail to capture localized failure mechanisms and inherent geotechnical uncertainties. This study aims to develop a probabilistic framework for assessing the spatiotemporal stability evolution of such slopes under progressive bolt corrosion. A novel Factor of Local Safety (FoLS) is introduced to quantify stability at individual rock column levels, enabling spatially explicit assessment. This metric is integrated with a time-variant mechanical model for bolt capacity loss and Monte Carlo simulation for uncertainty propagation. Applied to a representative slope, the framework reveals complex degradation patterns: failure initiates in the extremely active toppling zone, progresses to the moderately active zone, and ultimately extends to the passive and shear sliding zones. Sensitivity analyses highlight the critical influence of bolt inclination, yield strength, bolt-rock bond strength, and grout water-cement ratio. Comparative anchorage scenarios demonstrate the superior long-term effectiveness of lower-bench reinforcement. The study provides a novel, spatially differentiated approach for the design, maintenance, and risk management of anchored anti-dip slopes, emphasizing the necessity of dynamic stability monitoring over time.
Optimization of Drilling and Blasting Parameters During the Drifting of Underground Mine Workings Almenov, Talgat; Zhanakova, Raissa; Shabaz, Din-Mukhammed; Orynbas, Arsen
Civil Engineering Journal Vol. 12 No. 2 (2026): February
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2026-012-02-014

Abstract

The study aims to scientifically substantiate optimal drilling-and-blasting (D&B) parameters for driving underground mine workings under complex geological and mining conditions at the Akzhal deposit. The work addresses the selection of explosive types and the rational depth, configuration, and design of cut boreholes, together with their blasting pattern (BP), to improve rock-mass stability, operational safety, and advance efficiency. The methodology combines an assessment of geological-technical conditions with a review of current blasting practice, mathematical and numerical modelling of blast-induced face breakage, and pilot-scale industrial trials supported by statistical analysis and techno-economic evaluation under routine production constraints and reporting. The results show that optimization of the BP increases the borehole utilization factor (BUF) from η = 0.85 to η = 0.98. The locally produced Granulite A6 is proven effective, reducing blasting costs by 1.5 times relative to AS-8 while preserving the required energy characteristics. Charge optimization improves excavation-contour quality, enhances fragmentation uniformity, and reduces overbreak; the most rational solution is a rhombic cut combined with Granulite A6. Scientific novelty lies in integrating geological-geomechanical analysis, 3D modelling in Micromine, and industrial validation. Practical relevance is confirmed by decreasing cycle costs from USD 538.85 to USD 489.38, improving BUF, and enhancing contour quality.
Hierarchical Learning-Based System Decomposition for Time-Dependent Structural System Reliability Assessment Yan, Bingchuan; Han, Bing; Xie, Huibing; Yu, Jiaping
Civil Engineering Journal Vol. 12 No. 2 (2026): February
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2026-012-02-05

Abstract

Time-dependent reliability assessment of structural systems is challenging when degradation and multiple interacting failure modes govern failure. Under these conditions, the system limit state function (LSF) may be highly nonlinear, non-smooth, and available only implicitly through high-fidelity analysis. This paper proposes a system decomposition and hierarchical learning (DHL) framework to construct an evaluable surrogate system LSF for degradation-driven, time-variant reliability analysis. The structural system is decomposed into dominant failure modes and their connectivity. Artificial neural networks are trained hierarchically to learn the decomposed relationships. Mode-level surrogates approximate the LSF of each failure mode. A system-level surrogate then integrates the mode-level performance quantities and time to capture mode interaction and mechanism switching. The resulting surrogate is combined with Monte Carlo simulation and the probability density evolution method to compute time-dependent failure probabilities and, when required, the evolution of the system performance probability density. Two benchmark problems—a highly nonlinear parallel system and a rigid–plastic portal frame with correlated collapse mechanisms under degrading capacities—are used to evaluate the approach. DHL improves system-level surrogate fidelity relative to direct system-level ANN learning, with mean reliability prediction errors below 3.1% and 1.23% in the two benchmarks, respectively, while remaining compatible with both sampling-based and density-evolution propagation schemes.

Page 3 of 3 | Total Record : 23

 1   2   3 

Filter by Year

2026 2026


Reset
Filter By Issues
All Issue Vol. 12 No. 2 (2026): February Vol. 12 No. 1 (2026): January Vol. 11 No. 12 (2025): December Vol. 11 No. 11 (2025): November Vol. 11 No. 10 (2025): October Vol. 11 No. 9 (2025): September Vol. 11 No. 8 (2025): August Vol. 11 No. 7 (2025): July Vol. 11 No. 6 (2025): June Vol. 11 No. 5 (2025): May Vol. 11 No. 3 (2025): March Vol 11, No 3 (2025): March Vol 11, No 2 (2025): February Vol. 11 No. 2 (2025): February Vol 11, No 1 (2025): January Vol 10, No 12 (2024): December Vol 10, No 11 (2024): November Vol. 10 No. 11 (2024): November Vol 10, No 10 (2024): October Vol 10, No 9 (2024): September Vol 10, No 8 (2024): August Vol. 10 No. 7 (2024): July Vol 10, No 7 (2024): July Vol 10, No 6 (2024): June Vol 10, No 5 (2024): May Vol. 10 No. 5 (2024): May Vol 10, No 4 (2024): April Vol 10, No 3 (2024): March Vol 10, No 2 (2024): February Vol 10, No 1 (2024): January Vol 10 (2024): Special Issue "Sustainable Infrastructure and Structural Engineering: Innovations in Vol 9, No 12 (2023): December Vol 9, No 11 (2023): November Vol 9, No 10 (2023): October Vol 9, No 9 (2023): September Vol 9, No 8 (2023): August Vol 9, No 7 (2023): July Vol 9, No 6 (2023): June Vol 9, No 5 (2023): May Vol 9, No 4 (2023): April Vol 9, No 3 (2023): March Vol 9, No 2 (2023): February Vol 9, No 1 (2023): January Vol 9 (2023): Special Issue "Innovative Strategies in Civil Engineering Grand Challenges" Vol 8, No 12 (2022): December Vol 8, No 11 (2022): November Vol 8, No 10 (2022): October Vol 8, No 9 (2022): September Vol 8, No 8 (2022): August Vol 8, No 7 (2022): July Vol 8, No 6 (2022): June Vol 8, No 5 (2022): May Vol 8, No 4 (2022): April Vol 8, No 3 (2022): March Vol 8, No 2 (2022): February Vol 8, No 1 (2022): January Vol 7, No 12 (2021): December Vol 7, No 11 (2021): November Vol 7, No 10 (2021): October Vol 7, No 9 (2021): September Vol 7, No 8 (2021): August Vol 7, No 7 (2021): July Vol 7, No 6 (2021): June Vol 7, No 5 (2021): May Vol 7, No 4 (2021): April Vol 7, No 3 (2021): March Vol 7, No 2 (2021): February Vol 7, No 1 (2021): January Vol 7 (2021): Special Issue "Innovative Strategies in Civil Engineering Grand Challenges" Vol 6, No 12 (2020): December Vol 6, No 11 (2020): November Vol 6, No 10 (2020): October Vol 6, No 9 (2020): September Vol 6, No 8 (2020): August Vol 6, No 7 (2020): July Vol 6, No 6 (2020): June Vol 6, No 5 (2020): May Vol 6, No 4 (2020): April Vol 6, No 3 (2020): March Vol 6, No 2 (2020): February Vol 6, No 1 (2020): January Vol 6 (2020): Special Issue "Emerging Materials in Civil Engineering" Vol 5, No 12 (2019): December Vol 5, No 11 (2019): November Vol 5, No 10 (2019): October Vol 5, No 9 (2019): September Vol 5, No 8 (2019): August Vol 5, No 7 (2019): July Vol 5, No 6 (2019): June Vol 5, No 6 (2019): June Vol 5, No 5 (2019): May Vol 5, No 4 (2019): April Vol 5, No 4 (2019): April Vol 5, No 3 (2019): March Vol 5, No 3 (2019): March Vol 5, No 2 (2019): February Vol 5, No 2 (2019): February Vol 5, No 1 (2019): January Vol 5, No 1 (2019): January Vol 4, No 12 (2018): December Vol 4, No 12 (2018): December Vol 4, No 11 (2018): November Vol 4, No 11 (2018): November Vol 4, No 10 (2018): October Vol 4, No 10 (2018): October Vol 4, No 9 (2018): September Vol 4, No 9 (2018): September Vol 4, No 8 (2018): August Vol 4, No 8 (2018): August Vol 4, No 7 (2018): July Vol 4, No 7 (2018): July Vol 4, No 6 (2018): June Vol 4, No 6 (2018): June Vol 4, No 5 (2018): May Vol 4, No 5 (2018): May Vol 4, No 4 (2018): April Vol 4, No 4 (2018): April Vol 4, No 3 (2018): March Vol 4, No 3 (2018): March Vol 4, No 2 (2018): February Vol 4, No 2 (2018): February Vol 4, No 1 (2018): January Vol 4, No 1 (2018): January Vol 3, No 12 (2017): December Vol 3, No 12 (2017): December Vol 3, No 11 (2017): November Vol 3, No 11 (2017): November Vol 3, No 10 (2017): October Vol 3, No 10 (2017): October Vol 3, No 9 (2017): September Vol 3, No 9 (2017): September Vol 3, No 8 (2017): August Vol 3, No 7 (2017): July Vol 3, No 7 (2017): July Vol 3, No 6 (2017): June Vol 3, No 5 (2017): May Vol 3, No 5 (2017): May Vol 3, No 4 (2017): April Vol 3, No 3 (2017): March Vol 3, No 2 (2017): February Vol 3, No 2 (2017): February Vol 3, No 1 (2017): January Vol 2, No 12 (2016): December Vol 2, No 12 (2016): December Vol 2, No 11 (2016): November Vol 2, No 11 (2016): November Vol 2, No 10 (2016): October Vol 2, No 9 (2016): September Vol 2, No 9 (2016): September Vol 2, No 8 (2016): August Vol 2, No 8 (2016): August Vol 2, No 7 (2016): July Vol 2, No 7 (2016): July Vol 2, No 6 (2016): June Vol 2, No 6 (2016): June Vol 2, No 5 (2016): May Vol 2, No 4 (2016): April Vol 2, No 3 (2016): March Vol 2, No 3 (2016): March Vol 2, No 2 (2016): February Vol 2, No 1 (2016): January Vol 1, No 2 (2015): December Vol 1, No 1 (2015): November More Issue