Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash Mixtures
This study presents a comprehensive investigation into the cyclic shear behavior of sand–fly ash mixtures through experimental and data-driven modeling approaches. Cyclic direct shear tests were conducted on mixtures containing fly ash at 0%, 2.5%, 5%, 10%, 15%, and 20% by weight to examine the infl...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/1/353 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549382192726016 |
|---|---|
| author | Özgür Yıldız Ali Fırat Çabalar |
| author_facet | Özgür Yıldız Ali Fırat Çabalar |
| author_sort | Özgür Yıldız |
| collection | DOAJ |
| description | This study presents a comprehensive investigation into the cyclic shear behavior of sand–fly ash mixtures through experimental and data-driven modeling approaches. Cyclic direct shear tests were conducted on mixtures containing fly ash at 0%, 2.5%, 5%, 10%, 15%, and 20% by weight to examine the influence of fly ash content on the shear behavior under cyclic loading conditions. The tests were carried out under a constant stress of 100 kPa to simulate field-relevant stress conditions. Results revealed that the fly ash content initially reduces shear strength at lower additive contents, but shear strength increases and reaches a maximum at 20% fly ash content. The findings highlight the trade-offs in mechanical behavior associated with varying fly ash proportions. To enhance the understanding of cyclic shear behavior, a Nonlinear Autoregressive Model with External Input (NARX) model was employed. Using data from the loading cycles as input, the NARX model was trained to predict the final shear response under cyclic conditions. The model demonstrated exceptional predictive performance, achieving a coefficient of determination (R<sup>2</sup>) of 0.99, showcasing its robustness in forecasting the cyclic shear performance based on the composition of the mixtures. The insights derived from this research underscore the potential of incorporating fly ash in sand mixtures for soil stabilization in geotechnical engineering. Furthermore, the integration of advanced machine learning techniques such as NARX models offers a powerful tool for predicting the behavior of soil mixtures, facilitating more effective and data-driven decision-making in geotechnical applications. Evidently, this study not only advances the understanding of cyclic shear behavior in fly ash–sand mixtures but also provides a framework for employing data-driven methodologies to address complex geotechnical challenges. |
| format | Article |
| id | doaj-art-d2c0689436104beebdbcf5f3d138bef8 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-d2c0689436104beebdbcf5f3d138bef82025-01-10T13:15:16ZengMDPI AGApplied Sciences2076-34172025-01-0115135310.3390/app15010353Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash MixturesÖzgür Yıldız0Ali Fırat Çabalar1School of Architecture, Technology and Engineering, University of Brighton, Brighton BN2 4AT, UKDepartment of Civil Engineering, University of Gaziantep, 27310 Gaziantep, TurkeyThis study presents a comprehensive investigation into the cyclic shear behavior of sand–fly ash mixtures through experimental and data-driven modeling approaches. Cyclic direct shear tests were conducted on mixtures containing fly ash at 0%, 2.5%, 5%, 10%, 15%, and 20% by weight to examine the influence of fly ash content on the shear behavior under cyclic loading conditions. The tests were carried out under a constant stress of 100 kPa to simulate field-relevant stress conditions. Results revealed that the fly ash content initially reduces shear strength at lower additive contents, but shear strength increases and reaches a maximum at 20% fly ash content. The findings highlight the trade-offs in mechanical behavior associated with varying fly ash proportions. To enhance the understanding of cyclic shear behavior, a Nonlinear Autoregressive Model with External Input (NARX) model was employed. Using data from the loading cycles as input, the NARX model was trained to predict the final shear response under cyclic conditions. The model demonstrated exceptional predictive performance, achieving a coefficient of determination (R<sup>2</sup>) of 0.99, showcasing its robustness in forecasting the cyclic shear performance based on the composition of the mixtures. The insights derived from this research underscore the potential of incorporating fly ash in sand mixtures for soil stabilization in geotechnical engineering. Furthermore, the integration of advanced machine learning techniques such as NARX models offers a powerful tool for predicting the behavior of soil mixtures, facilitating more effective and data-driven decision-making in geotechnical applications. Evidently, this study not only advances the understanding of cyclic shear behavior in fly ash–sand mixtures but also provides a framework for employing data-driven methodologies to address complex geotechnical challenges.https://www.mdpi.com/2076-3417/15/1/353cyclic shear behaviorsandfly ashNARX model |
| spellingShingle | Özgür Yıldız Ali Fırat Çabalar Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash Mixtures Applied Sciences cyclic shear behavior sand fly ash NARX model |
| title | Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash Mixtures |
| title_full | Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash Mixtures |
| title_fullStr | Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash Mixtures |
| title_full_unstemmed | Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash Mixtures |
| title_short | Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash Mixtures |
| title_sort | predictive modeling and experimental analysis of cyclic shear behavior in sand fly ash mixtures |
| topic | cyclic shear behavior sand fly ash NARX model |
| url | https://www.mdpi.com/2076-3417/15/1/353 |
| work_keys_str_mv | AT ozguryıldız predictivemodelingandexperimentalanalysisofcyclicshearbehaviorinsandflyashmixtures AT alifıratcabalar predictivemodelingandexperimentalanalysisofcyclicshearbehaviorinsandflyashmixtures |