The complex interactions between soil and additives such as lignin, glass powder, and rubber tires were investigated using principles of material and soil mechanics. Previous research has mainly focused on individual additives in clay soils. In contrast, this study investigates soil improvement with two different types of waste materials simultaneously. The improvement of soil properties by hybrid waste materials was evaluated using several laboratory tests, including the standard Proctor test, the unconfined compressive strength test, the California Bearing Ratio (CBR) test, and cyclic triaxial tests. The aim of this research is to identify key parameters for the design and construction of road pavements and to demonstrate that improving the subgrade with hybrid waste materials contributes significantly to the sustainability of road construction. The mechanical and physical properties were evaluated in detail to determine the optimal mixtures. The results show that the most effective mixture for the combination of waste glass powder and rubber tires contains 20% glass powder and 3% rubber tires, based on the dry weight of the soil. For the combination of waste glass powder and lignin, the optimum mixture consists of 15% glass powder and 15% lignin, based on the dry weight of the soil. These results provide valuable insights into the sustainable use of waste materials for soil stabilization in road construction projects.

This paper presents the design of geosynthetic reinforced flexible pavements and their modification by incorporating waste materials into bonded and unbonded layers of the pavement structure. The optimal design of flexible pavements was achieved by minimizing the construction cost of the pavement. The incorporation of waste materials into the pavement structure affects the material properties. Therefore, along with the traffic load, the effects of the material properties of the asphalt concrete, base layer, sub-base layer, and subgrade were analyzed in terms of pavement structure costs and CO₂ emissions of materials used in pavement construction. In addition, a comparison was made between pavements with and without geosynthetic reinforcement in terms of design, optimum construction cost, and CO₂ emissions. The use of geosynthetics is even more effective in pavement structures that contain waste materials in an unbound layer, both in terms of cost and CO₂ emissions. The minimum value of the California Bearing Ratio of the subgrade was determined at which the use of geosynthetic reinforcement for pavement structure with and without the inclusion of waste materials is economically and sustainably justified. The use of geosynthetics could result in a 15% reduction in pavement structure cost and a 9% reduction in CO₂ emissions due to the reduced thickness of unbound layers. In addition, reducing the CBR of the unbound layer from 100% to 30% due to the inclusion of waste materials implies a cost increase of up to 13%. While the present study is based on an empirical pavement design method in which pavement thickness is limited by the pavement thickness index, the same minimum thicknesses are obtained in the optimization process regardless of whether the objective function is the minimum construction cost or minimum CO₂ emissions.

The design of a gravity retaining wall should be simple to construct, quick to build and the best economic solution to a problem. This can be achieved by using advanced optimization methods. Since geotechnical engineers are not always able to determine the exact soil properties and other project data, an optimal design of a gravity retaining wall should also be determined for a wide range of input parameters. Therefore, a multiparametric analysis of an optimal designed gravity retaining wall was carried out. Optimum designs of gravity retaining walls were obtained for 567 combinations of different design parameters. Diagrams were developed to help engineers determine the optimum section of the wall, based on construction costs. An exhaustive search was carried out within the available parameters (project data). The parameters were ranked according to which had the most influence on the optimum cost of the gravity retaining wall and the utilization of multiple constraints. The most important parameter for the optimal cost of a gravity retaining wall is the height of the retained ground, followed by the shear angle of the soil, the soil–wall interaction coefficient, the slope angle and the variable surcharge load. The shear angle of the soil is most relevant to the bearing capacity and eccentricity condition, while the soil–wall interaction coefficient is most relevant to the sliding condition. Since European countries apply different load, material and resistance safety factors, the optimization model was developed in a general form, where different design approaches and unit prices could be applied. The case study provides an improved optimization model for selecting the optimal design of gravity walls, for engineers.

In this paper, a comparative analysis of the effects of groundwater, seepage and hydraulic heave on the optimal design of embedded retaining walls is carried out. The optimization model for an optimal retaining wall (ORW) minimizes the total length of the retaining wall considering design constraints. The model is extended to include the probability of failure as an additional constraint. This overcomes the limitations of the partial safety factor approach, which does not fully account for uncertainties in the soil. In contrast, the reliability-based design (RBD) approach integrates these uncertainties and enables an assessment of the impact of seepage and hydraulic heave on the reliability of the structure. A real-coded genetic algorithm was used to determine optimal designs for both optimization methods. The results of the case study show that the addition of seepage (groundwater flow) to the hydrostatic conditions has a modest effect on the embedment depth. The design based on partial safety factors, which takes seepage into account, leads to a slight increase in the embedment depth of 0.94% compared to a retaining wall design that only takes the hydrostatic conditions of the groundwater into account. When designing on the basis of probability failure, the percentage increase in embedment depth due to seepage is between 2.19% and 6.41%, depending on the target probability of failure. Furthermore, the hydraulic heave failure mechanism did not increase the required embedment depth of the retaining wall, which means that the failure mechanism of rotation near the base was decisive for the design.

The paper presents an optimal design for a gravity retaining wall based on a mixed-integer constrained optimization. To solve this optimization problem, a real coded genetic algorithm was applied. The gravity retaining wall optimization model (OPT-GRW) includes a cost function of the wall, which is limited by design and resistance constraints. The deterministic optimization model, based on partial safety factors, was extended by an optimization approach in which the cost objective function was constrained by a defined target probability of failure. The paper presents an example for determining the most cost-effective gravity retaining wall for given design parameters. The presented case study shows the optimization process based on Eurocode 7, which takes into account part of the uncertainty of the soil parameters. As the study progresses, the need for optimization based on the probability of failure becomes crucial, as several designs exist with the same probability of failure, but only one is optimal.