Predictive approaches to the impact of environmental conditions on the durability of clayey soils stabilized with mineral additives.
| dc.contributor.author | TOUALBIA, YOUSSOUF | |
| dc.date.accessioned | 2026-03-12T09:10:44Z | |
| dc.date.available | 2026-03-12T09:10:44Z | |
| dc.date.issued | 2025 | |
| dc.description | THESIS Submitted for the DOCTORAL DEGREE Field: Civil Engineering Specialty: Geotechnical Engineering | en_US |
| dc.description.abstract | This doctoral thesis addresses a critical issue in geotechnical engineering: the impact of environmental conditions, particularly freeze–thaw cycles, on the effectiveness and long-term durability of stabilized clayey soils treated with mineral additives such as lime and fly ash. Numerous published experimental studies have demonstrated an initial improvement in unconfined compressive strength (UCS) following stabilization, but also a progressive deterioration of mechanical performance under repeated freeze–thaw exposure. However, experimental assessment remains challenging, due to the difficulty in realistically reproducing climatic conditions, precisely controlling curing parameters, and managing result variability. These limitations justify the adoption of predictive modeling approaches. In this context, two modeling approaches: a statistical regression and an ANN, were developed using literature-based experimental databases for soils stabilized with lime and fly ash. These models effectively simulate the evolution of UCS in stabilized soils subjected to environmental cycles. Parametric studies were also conducted to capture the influence of several key factors, such as the number of freeze–thaw cycles, water content, additive content, and curing duration. Results show that ANN models offer superior predictive performance and better capture of nonlinear relationships between input variables and soil strength response. By integrating diverse experimental data and leveraging the power of artificial intelligence, this work contributes to a better understanding of the long-term behavior of stabilized soils under harsh climatic conditions and provides reliable tools to support resilient geotechnical design in environmentally sensitive regions. Keywords: stabilized clayey soils; freeze–thaw cycles; mineral additives; statistical model; artificial neural network (ANN); unconfined compressive strength (UCS) | en_US |
| dc.identifier.uri | http://dspace.univ-chlef.dz/handle/123456789/2412 | |
| dc.publisher | Ali MAKHLOUF / Billal SARI-AHMED | en_US |
| dc.subject | abilized clayey soils | en_US |
| dc.subject | freeze–thaw cycles | en_US |
| dc.subject | mineral additives | en_US |
| dc.title | Predictive approaches to the impact of environmental conditions on the durability of clayey soils stabilized with mineral additives. | en_US |
| dc.type | Thesis | en_US |