Experimental Study on the Impact of Soil Type Variations on Compressive Strength and Settlement Characteristics of Spread Footing Foundations
This research investigates the influence of soil type variations on the compressive strength and settlement behavior of spread footing foundations. Soil properties such as moisture content, dry density, void ratio, cohesion, and internal friction angle play a crucial role in determining how foundat...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
College of Engineering of Afe Babalola University, Ado-Ekiti (ABUAD), Ekiti State, Nigeria
2025-05-01
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| Series: | ABUAD Journal of Engineering Research and Development |
| Subjects: | |
| Online Access: | https://journals.abuad.edu.ng/index.php/ajerd/article/view/1292 |
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| Summary: | This research investigates the influence of soil type variations on the compressive strength and settlement behavior of spread footing foundations. Soil properties such as moisture content, dry density, void ratio, cohesion, and internal friction angle play a crucial role in determining how foundations respond to applied loads. Variations in these properties can lead to uneven settlements and structural instability, posing significant challenges in construction. The study aims to provide a comprehensive understanding of these interactions to enhance foundation design and prevent structural failures. We applied machine learning techniques for data analysis and visualized patterns using Power BI, enabling a detailed exploration of the relationships between soil characteristics, compressive strength, and settlement behavior. The results showed that soil cohesion and internal friction angle had the most significant impact on compressive strength, while moisture content and void ratio were key contributors to settlement behavior. The optimized model achieved high accuracy of 82% in classifying settlement levels, reinforcing the dataset's reliability. This research highlights the importance of thorough soil testing and data-driven modeling in foundation design. We recommend integrating predictive models into geotechnical practice to support safer, more resilient structures, especially in areas with diverse soil profiles. The findings provide a valuable tool for engineers to make informed decisions, reducing the risk of foundation failure and enhancing the long-term stability of infrastructure.
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| ISSN: | 2756-6811 2645-2685 |