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Search Results for Mohamad Alyounis

Article
Impact of Abutment Scour on Al-Nuhairat Bridge in Basrah Governorate

Abdulsattar A. Alhasan, Mohamad Alyounis, Mohammed H. Al-Tofan

Pages: 32-37

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Abstract

This study examined the impact of abutment scour around the concrete Al-Nuhairat Bridge, constructed over the Tigris River in Basrah Governorate. Local scour at bridge abutments is considered a contributing factor to bridge collapse. The study included an analysis of hydraulic variables and their interaction with the soil geological formation, which forms a supporting component in strengthening the abutments. The study also demonstrated the impact of these variables on the scour depth using the Hydraulic Toolbox software. The results were then discussed, clarifying the extent of erosion's impact on the undermining of abutment foundations and its repercussions on the safety and stability of bridges. The study also provided recommendations to mitigate its impact, preserve the sustainability of bridge operations, and take the necessary precautions when preparation future bridge designs, particularly in Basrah Governorate.

Article
A Comprehensive Review of Column-Based Ground Improvement Techniques: Mechanisms, Design, and Field Applications

Ahmed D. Aziz, Mohamad J. Alyounis

Pages: 14-20

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Abstract

This paper offers a comprehensive review of column-based ground improvement techniques, focusing on their fundamental mechanisms, design principles, construction methods, and field applications. It highlights stone columns and deep soil mixing (DSM) as the most widely used and effective solutions for enhancing the performance of weak and compressible soils. The core principles, including stress redistribution, increased shear strength, and accelerated consolidation, are discussed in detail. The review synthesizes key design parameters such as column geometry, area replacement ratio, and the role of geosynthetic reinforcement and load transfer platforms. It also examines the practical application of these methods through various case studies on embankments, tank foundations, and excavation supports. A dedicated section explores the pivotal role of numerical modeling, especially the finite element method (FEM), and emerging AI-driven approaches like Physics-Informed Neural Networks (PINNs) and surrogate modeling, which are shown to improve predictive accuracy and optimize the design process. Furthermore, the paper addresses critical challenges and limitations, including material variability, installation uncertainties, environmental impacts, and the need for enhanced quality control and long-term monitoring. It concludes by outlining future trends and innovations, such as the adoption of sustainable materials and the integration of machine learning for predictive design and real-time monitoring. This synthesis provides a structured overview of current best practices and offers valuable insights into the future direction of this vital area of geotechnical engineering.

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Civil Engineering Science and Technology Journal

College of Engineering, University of Basrah

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