A crucial factor in the efficient design of concrete sustainable buildings is the compressive strength (Cs) of eco-friendly concrete. In this work, a hybrid model of Gradient Boosting Regression Tree (GBRT) with grid search cross-validation (GridSearchCV) optimization technique was used to predict the compressive strength, which allowed us to increase the precision of the prediction models. In addition, to build the proposed models, 164 experiments on eco-friendly concrete compressive strength were gathered for previous researches. The dataset included the water/binder ratio (W/B), curing time (age), the recycled aggregate percentage from the total aggregate in the mixture (RA%), ground granulated blast-furnace slag (GGBFS) material percentage from the total binder used in the mixture (GGBFS%), and superplasticizer (kg). The root mean square error (RMSE) and coefficient of determination (R²) between the observed and forecast strengths were used to evaluate the accuracy of the predictive models. The obtained results indicated that—when compared to the default GBRT model—the GridSearchCV approach can capture more hyperparameters for the GBRT prediction model. Furthermore, the robustness and generalization of the GSC-GBRT model produced notable results, with RMSE and R² values (for the testing phase) of 2.3214 and 0.9612, respectively. The outcomes proved that the suggested GSC-GBRT model is advantageous. Additionally, the significance and contribution of the input factors that affect the compressive strength were explained using the Shapley additive explanation (SHAP) approach.

Growing environmental pollution worldwide is mostly caused by the accumulation of different types of liquid and solid wastes. Therefore, policies in developed countries seek to support the concept of waste recycling due to its significant impact on the environmental footprint. Hot-mix asphalt mixtures (HMA) with reclaimed asphalt pavement (RAP) have shown great performance under rutting. However, incorporating a high percentage of RAP (>25%) is a challenging issue due to the increased stiffness of the resulting mixture. The stiffness problem is resolved by employing different types of commercial and noncommercial rejuvenators. In this study, three types of noncommercial rejuvenators (waste cooking oil (WCO), waste engine oil (WEO), and date seed oil (DSO)) were used, in addition to one type of commercial rejuvenator. Three percentages of RAP (20%, 40%, and 60%) were utilized. Mixing proportions for the noncommercial additives were set as 0–10% for mixtures with 20% RAP, 12.5–17.5% for mixtures with 40% RAP, and 17.5–20% for mixtures with 60% RAP. In addition, mixing proportions for the commercial additive were set as 0.5–1.0% for mixtures with 20% RAP, 1.0–1.5% for mixtures with 40% RAP, and 1.5–2.0% for mixtures with 60% RAP. The rutting performance of the generated mixtures was indicated first by using the rutting index (G*/sin δ) for the combined binders and then evaluated using the Hamburg wheel-track test. The results showed that the rejuvenated mixtures with the commercial additive at 20 and 60% RAP performed well compared to the control mixture, whereas the rejuvenated ones at 40% RAP performed well with noncommercial additives in comparison to the control mixture. Furthermore, the optimum percentages for each type of the used additives were obtained, depending on their respective performance, as 10%, 12.5%, and 17.5% of WCO, 10%, 12.5–17.5%, and 17.5% of WEO, <10%, 12.5%, and 17.5% of DSO, and 0.5–1.0%, 1.0%, and 1.5–2.0% of the commercial rejuvenator, corresponding to the three adopted percentages of RAP.

Geotextile reinforcement techniques have been widely used in paving works around the world and have proven to be effective in improving pavement performance. This study has focused on using different positions and numbers of geotextile reinforcement sheets between the layers of flexible pavement for rutting reduction. Fitting depth was measured in the field at seven constructed sections of the pavement of the road model. Each section has been strengthened with different reinforcement approaches. All road sections were subjected to a maximum load repetition of 10,000 cycles. The results indicate that using three layers of geotextile beneath each course of the designed road pavement sections (surface, binder, and base) reduced rutting by 96%. Traffic benefit ratio (TBR) has been employed in this study to reveal the behavior of geotextile reinforcement in increasing the service life of the road. TBR values are the load cycling ratio between the reinforced and unreinforced section for the exact recorded rut depth, it has been found to be minimally equal to 4 for the case of using one layer of reinforcement at interface I, and that value keeps growing up for other reinforcement cases.

Seepage from the earth dam’s body reduces the amount of water in the dam’s reservoir and threatens its stability. In this paper, the earth‐type Sattarkhan Dam on the Aharchai River has been investigated. In this regard, the SEEP/W model from the GeoStudio 2018 software suite was used for modeling. This study examines the effects of various lengths and positions of cutoff wall and horizontal drainage on seepage, uplift pressure, and exit gradient. Increasing the length of the cutoff wall reduces seepage in both sections, with a more significant effect on Section 2; it also decreases the uplift pressure and the exit gradient. Changing the position of the cutoff wall has a significant effect on seepage fluctuations in Section 1 but has no effect on seepage in Section 2; in positions 2 to 7, the uplift pressure values are nearly identical, and the exit gradient is most significant at position 1 and least at position 2. Increasing the horizontal drainage’s length increases seepage, reduces uplift pressure, and increases the exit gradient. The closer proximity of the horizontal drainage position to the dam’s core increases seepage and decreases uplift pressure and exit gradient. Finally, it is concluded that the construction of a cutoff wall and horizontal drainage with appropriate lengths and positions reduces risk and improves the stability of earth dams.