Research Article
Modified Pervious Concrete Pavement with Lime Mortar and Recycled Plastic Fibers for Urban Infrastructure in Bangladesh
Issue:
Volume 13, Issue 4, August 2025
Pages:
185-196
Received:
8 June 2025
Accepted:
23 June 2025
Published:
16 July 2025
Abstract: This study evaluates the mechanical and permeability performance of a Modified Pervious Concrete Pavement (MPCP) developed for urban infrastructure in Bangladesh. The MPCP incorporates lime mortar, selected for its binding properties, and recycled plastic bottle fibers, introduced to enhance tensile strength, crack resistance, and durability. A series of mix designs were developed and tested to assess the effects of varying proportions of lime mortar and plastic fibers on the structural and hydraulic characteristics of the pavement. Among the tested configurations, the A5 mix (cement: lime mortar: aggregate = 1:0.25:3) demonstrated an effective balance between strength and porosity. It achieved a 28-day compressive strength of 18.445 MPa and a porosity of 17.01%, meeting functional criteria for pervious pavement applications. Additionally, the A5 mix exhibited a high infiltration rate of 483.362 mm/hour, supporting its suitability for stormwater management in flood-prone areas. The experimental findings indicate that the integration of lime mortar and recycled plastic fibers can improve both mechanical and permeability characteristics of pervious concrete without compromising its fundamental design properties. The use of locally sourced and waste-derived materials further supports resource-efficient construction practices. This study provides a framework for the development of structurally sound and hydraulically functional pervious pavement systems tailored to the environmental and infrastructural context of Bangladesh.
Abstract: This study evaluates the mechanical and permeability performance of a Modified Pervious Concrete Pavement (MPCP) developed for urban infrastructure in Bangladesh. The MPCP incorporates lime mortar, selected for its binding properties, and recycled plastic bottle fibers, introduced to enhance tensile strength, crack resistance, and durability. A ser...
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Research Article
Automated Multi-Class Concrete Crack Detection and Severity Classification Using CNN-Based Deep Learning
Wisam Bukaita
,
Kalyan Naik Vankudothu*,
Junaid Khan
Issue:
Volume 13, Issue 4, August 2025
Pages:
197-210
Received:
17 June 2025
Accepted:
1 July 2025
Published:
22 July 2025
DOI:
10.11648/j.ajce.20251304.12
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Abstract: Structural integrity is essential to sustainable infrastructure development, particularly in concrete structures. These are prone to deterioration from environmental exposure, mechanical stress, and corrosion. Conventional inspection techniques such as manual surveys and non-destructive testing (NDT)—are labor-intensive, time-consuming, and often limited by human accuracy, making them unsuitable for large-scale deployment. This research proposes an automated system using a custom Convolutional Neural Network (CNN) architecture tailored for concrete defect detection and severity classification. The model was built with four convolutional blocks (32–256 filters), max-pooling layers, batch normalization, and a final dense layer, totaling approximately 129,000 parameters. It was trained on a custom-labeled dataset of 21,000 images (20,000 crack images and 1,000 corrosion images), collected from publicly available repositories and manually classified into seven categories: No Cracks, Hairline Cracks, Small Cracks, Moderate Cracks, Large Cracks, Very Large Cracks, and Cracks Due to Corrosion. Data augmentation techniques were used to address class imbalance and improve generalization. Experimental results showed 94.7% classification accuracy, 93.5% precision, 92.8% recall, and a 93.1% F1 score. The system processes ~25 images/sec on an NVIDIA RTX 3060 GPU, making it suitable for real-time applications. This system represents a scalable, high-performance approach to infrastructure health monitoring, contributing to safer and more effective structural maintenance.
Abstract: Structural integrity is essential to sustainable infrastructure development, particularly in concrete structures. These are prone to deterioration from environmental exposure, mechanical stress, and corrosion. Conventional inspection techniques such as manual surveys and non-destructive testing (NDT)—are labor-intensive, time-consuming, and often l...
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