Research Article
Statistical Analysis of Variation Indices of Different Support in a Steel Beam Girder
Olaitan Oluwasheun Akol,
John Wasiu,
Ibrahim Abdulrazaq Olayinka*
Issue:
Volume 14, Issue 5, October 2026
Pages:
304-311
Received:
9 June 2026
Accepted:
3 July 2026
Published:
22 August 2026
Abstract: The reliability and safety performance of steel beam girders are significantly influenced by the number of supports provided along their spans. This study presents a statistical analysis of the variation of reliability indices (β) of a steel beam girder subjected to bending, shear, and deflection limit states under different support conditions. Reliability indices were evaluated for girders having two, three, four, and five supports and compared with the target reliability index (βt = 4.0). The results show considerable variation in structural reliability with changes in support configuration. Shear reliability remained consistently high, ranging from 5.14 to 5.32, indicating adequate safety against shear failure. Bending reliability exhibited significant fluctuations, with indices ranging from 0.532 to 6.98, suggesting that support arrangement strongly affects bending performance. Deflection reliability increased progressively from 0.402 for two supports to 4.65 for five supports, indicating improved serviceability performance with increased support numbers. The study demonstrates that while increasing the number of supports generally enhances serviceability reliability, it does not necessarily guarantee improved bending reliability. Statistical evaluation revealed that girders with four supports achieved the most balanced performance, satisfying the target reliability requirement for all failure modes. The findings provide useful insights for the reliability-based design and optimization of steel girder support systems.
Abstract: The reliability and safety performance of steel beam girders are significantly influenced by the number of supports provided along their spans. This study presents a statistical analysis of the variation of reliability indices (β) of a steel beam girder subjected to bending, shear, and deflection limit states under different support conditions. Rel...
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Research Article
Microstructural Evaluation of Bagasse Ash Stabilized Sand-Bentonite Mixtures Using XRD SEM, and EDX Techniques
Amedu Lawal Makhu*,
Zekeri Jafaru,
Ahmed Alhassan,
Ifabiyi Stephen Olugbemniga
Issue:
Volume 14, Issue 5, October 2026
Pages:
312-323
Received:
16 July 2026
Accepted:
29 July 2026
Published:
11 September 2026
Abstract: The microstructure of compacted sand–bentonite mixtures (SBMs) modified with sugarcane bagasse ash (SBA) was investigated to evaluate the mechanisms responsible for improving their suitability as sustainable landfill liner materials. SBA was incorporated at replacement levels of 0%, 2.5%, 5%, 7.5%, 10%, and 12.5%, while the mixtures were characterized using Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), and X-ray Diffraction (XRD). XRD analysis of the control sand revealed quartz, kaolinite, and metahalloysite as the dominant mineral phases, with minor quantities of gibbsite and vermiculite. The mixture containing 10% bentonite and 12.5% SBA exhibited new diffraction peaks and peak broadening, indicating the formation of calcium silicate hydrate (C–S–H) and confirming the occurrence of pozzolanic reactions. SEM images demonstrated a progressive transformation from the loose, porous granular structure of the untreated sand to a dense, compact, and well-cemented matrix in the SBA-modified mixtures. EDX analysis of the optimum mixture recorded oxygen (61.40 wt%), silicon (17.37 wt%), aluminum (6.52 wt%), and iron (6.42 wt%), confirming the development of a silica–alumina-rich cementitious matrix. These microstructural modifications enhanced particle bonding, reduced pore spaces, and improved contaminant retention capacity. The findings demonstrate that SBA effectively induces pozzolanic reactions and pore refinement, making SBA-modified SBMs a sustainable and environmentally friendly material for engineered landfill liner systems.
Abstract: The microstructure of compacted sand–bentonite mixtures (SBMs) modified with sugarcane bagasse ash (SBA) was investigated to evaluate the mechanisms responsible for improving their suitability as sustainable landfill liner materials. SBA was incorporated at replacement levels of 0%, 2.5%, 5%, 7.5%, 10%, and 12.5%, while the mixtures were characteri...
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Research Article
Benchmarking YOLOv8 Variants for Automated Infrastructure Assessment
Nnanna Ekedebe*
Issue:
Volume 14, Issue 5, October 2026
Pages:
324-330
Received:
13 July 2026
Accepted:
24 July 2026
Published:
18 September 2026
DOI:
10.11648/j.ajce.20261405.13
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Abstract: Structural cracks in buildings and bridges pose a serious safety concern in Nigeria, with manual inspection methods being slow, subjective and impractical at scale. Undetected structural cracks can lead to building collapses, which have become a recurring and deadly problem in Nigeria's construction sector. This study benchmarks three YOLOv8 variants – nano, small and medium under identical training and evaluation conditions using a 500-image Building Crack Detection dataset sourced from Roboflow Universe, with models evaluated on mAP@50, mAP@50-95, Precision, Recall and Inference Speed. All three models were trained for 50 epochs under the same conditions to ensure a fair comparison across variants. All three models achieved a mAP@50 of at least 99.4% and 100% recall, with YOLOv8s and YOLOv8m both achieving the highest mAP@50-95 at 99.50% and YOLOv8n achieving the fastest inference speed at 3.1 ms per image. These results show that all three models were highly accurate and rarely missed a crack, with the main difference between them being how fast each one could process an image. YOLOv8n was identified as the most optimal model for Nigerian infrastructure deployment, demonstrating the best balance of accuracy and speed for resource-constrained settings. Although the larger models were slightly more precise, the accuracy gap was small enough that speed became the deciding factor for practical deployment. This study demonstrates the viability of automated crack detection using YOLOv8 and provides a foundation for affordable and scalable structural monitoring in Nigeria.
Abstract: Structural cracks in buildings and bridges pose a serious safety concern in Nigeria, with manual inspection methods being slow, subjective and impractical at scale. Undetected structural cracks can lead to building collapses, which have become a recurring and deadly problem in Nigeria's construction sector. This study benchmarks three YOLOv8 varian...
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