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The design of cantilever pile walls (CPWs) presents several common challenges. These challenges include soil variability, groundwater conditions, complex loading conditions, construction considerations, structural integrity, uncertainties in design parameters and construction and monitoring costs. Accordingly, this paper is to provide a detailed literature review on the design criteria of CPWs, specifically in cohesionless soil. This study aims to present a comprehensive overview of the current state of knowledge in this area.

The paper uses a literature review approach to gather information on the design criteria of CPWs in cohesionless soil. It covers various aspects such as excavation support systems (ESSs), deformation behavior, design criteria, lateral earth pressure calculation theories, load distribution methods and conventional design approaches.

The review identifies and discusses common challenges associated with the design of CPWs in cohesionless soil. It highlights the uncertainties in determining load distribution and the potential for excessive wall deformations. The paper presents various approaches and methodologies proposed by researchers to address these challenges.

The paper contributes to the field of geotechnical engineering by providing a valuable resource for geotechnical engineers and researchers involved in the design and analysis of CPWs in cohesionless soil. It offers insights into the design criteria, challenges and potential solutions specific to CPWs in cohesionless soil, filling a gap in the existing knowledge base. The paper draws attention to the limitations of existing analytical methods that neglect the serviceability limit state and assume rigid plastic soil behavior, highlighting the need for improved design approaches in this context.

The purpose of this article is to analyze the state-of-the art in a systematic way, identifying the main research groups and their related topics. The types of studies found are fundamental for understanding the application of artificial neural networks (ANNs) in cemented soils and the potential for using the technique, as well as the feasibility of extrapolation to new geotechnical or civil and environmental engineering segments.

This work is characterized as being bibliometric and systematic research of an exploratory perspective of state-of-the-art. It also persuades the qualitative and quantitative data analysis of cemented soil improvement, biocemented or microbially induced calcite precipitation (MICP) soil improvement by prediction/modeling by ANN. This study sought to compile and study the state of the art of the topic which possibilities to have a critical view about the theme. To do so, two main databases were analyzed: Scopus and Web of Science. Systematic review techniques, as well as bibliometric indicators, were implemented.

This paper connected the network between the achievements of the researches and illustrated the main application of ANNs in soil improvement prediction, specifically on cemented-based soils and biocemented soils (e.g. MICP technique). Also, as a bibliometric and systematic review, this work could achieve the key points in the absence of researches involving soil-ANN, and it provided the understanding of the lack of exploratory studies to be approached in the near future.

Because of the research topic the article suggested other applications of ANNs in geotechnical engineering, such as other tests not related to geomechanical resistance such as unconfined compression test test and triaxial test.

This article systematically and critically presents some interesting points in the direction of future research, such as the non-approach to the use of ANNs in biocementation processes, such as MICP.

Regarding the social environment, the paper brings approaches on methods that somehow mitigate the computational use, or elements necessary for geotechnical improvement of the soil, thereby optimizing the same consequently.

Neural networks have been studied for a long time in engineering, but the current computational power has increased the implementation for several engineering applications. Besides that, soil cementation is a widespread technique and its prediction modes often require high computational strength, such parameters can be mitigated with the use of ANNs, because artificial intelligence seeks learning from the implementation of the data set, reducing computational cost and increasing accuracy.

This study aims to optimize the design of reinforced concrete retaining walls to achieve the lowest possible cost while maintaining structural stability and compliance with standards.

The Rao1 algorithm was employed to optimize the design, considering seven independent variables related to geometry and four variables related to the reinforcement ratio. Geotechnical and structural analyses were performed using the Coulomb theory for static loads and the Mononobe–Okabe theory for dynamic loads. Cost calculations included concrete volume and reinforcement quantities across varying horizontal and vertical acceleration coefficients in four scenarios.

The optimization process revealed that the Rao1 algorithm consistently identified design variables near the lower regulatory limits, achieving the same cost across all scenarios. The results demonstrate that the Rao1 algorithm is an effective tool for optimizing the design of self-supporting reinforced concrete retaining walls, ensuring both cost efficiency and compliance with structural requirements.

In this study, the aim was to achieve an optimal, cost-effective design for retaining walls composed of a two-stage stem structure. Unlike conventional designs that utilize single-tier retaining walls, this study emphasizes the use of a two-stage stem configuration. It was noted that the Rao1 algorithm has not been previously applied to two-stage stem retaining walls in the literature. By applying the Rao1 algorithm, it was observed that a design meeting both minimum cost and required criteria was successfully achieved. Therefore, it was concluded that the Rao1 algorithm could be a valuable tool for retaining wall design. This study differs from other works in the literature both in terms of the two-stage stem-retaining wall design and the algorithm used.

The purpose of this paper is to provide a cost-effective foundation technique for the design of foundations of transmission towers, heavily loaded structures, etc.

Experimental model tests are conducted in a model test tank to find out the effect of length and diameter of geogrid encased granular pile anchors, the relative density of sand and the angle of inclination of the pile from the vertical on uplift behavior of granular pile anchors.

The uplift capacity of the geogrid encased granular pile anchor increased with increasing length and diameter of granular pile anchor. Further, increasing the relative density of surrounding soil increased uplift capacity of geogrid encased granular pile anchor system. Moreover, increasing the angle of inclination of loading also increased uplift capacity of whole system. Thus, the proposed system can be effectively used in field for further applications.

The paper is helpful for the engineers looking for cost-effective foundation techniques for heavily loaded structures.

This paper aims to develop a unified framework for modelling triaxial deviator stress – axial strain and volumetric strain – axial strain behaviour of granular soils with the ability to predict the entire stress paths, incrementally, point by point, in deviator stress versus axial strain and volumetric strain versus axial strain spaces using an evolutionary-based technique based on a comprehensive set of data directly measured from triaxial tests without pre-processing. In total, 177 triaxial test results acquired from literature were used to develop and validate the models. Models aimed to not only be capable of capturing and generalising the complicated behaviour of soils but also explicitly remain consistent with expert knowledge available for such behaviour.

Evolutionary polynomial regression (EPR) was used to develop models to predict stress – axial strain and volumetric strain – axial strain behaviour of granular soils. EPR integrates numerical and symbolic regression to perform EPR. The strategy uses polynomial structures to take advantage of favourable mathematical properties. EPR is a two-stage technique for constructing symbolic models. It initially implements evolutionary search for exponents of polynomial expressions using a genetic algorithm (GA) engine to find the best form of function structure; second, it performs a least squares regression to find adjustable parameters, for each combination of inputs (terms in the polynomial structure).

EPR-based models were capable of generalising the training to predict the behaviour of granular soils under conditions that have not been previously seen by EPR in the training stage. It was shown that the proposed EPR models outperformed ANN and provided closer predictions to the experimental data cases. The entire stress paths for the shearing behaviour of granular soils using developed model predictions were created with very good accuracy despite error accumulation. Parametric study results revealed the consistency of developed model predictions, considering roles of various contributing parameters, with physical and engineering understandings of the shearing behaviour of granular soils.

In this paper, an evolutionary-based data-mining method was implemented to develop a novel unified framework to model the complicated stress-strain behaviour of saturated granular soils. The proposed methodology overcomes the drawbacks of artificial neural network-based models with black box nature by developing accurate, explicit, structured and user-friendly polynomial models and enabling the expert user to obtain a clear understanding of the system.

The purpose of this study is to investigate the effect of presence of buried flexible pipe on the bearing capacity of shallow footing. First, a model study is performed where shallow footing model is tested for its load settlement behavior, with and without the existence of buried PVC pipe lying vertically below the base of the footing.

The experimental set-up consisted of a steel box filled with sand at two different relative density values [RD = 50 per cent (medium dense) and RD = 80 per cent (dense sand)] and vertical load was applied on the model footing through hydraulic jack and reaction frame arrangement connected with a proving ring. Test results are verified numerically using commercially available finite element code PLAXIS 2D. With due verification, a parametric study has been conducted, numerically, by varying the range of input parameters, such as unit weight, angle of internal friction, diameter of buried conduit and the Elastic modulus of the soil to assess the pre cent reduction in the capacity of the foundation soil because of the presence of underlying buried flexible pipe.

Results show that for each footing, there exists a critical depth below which the presence of the buried conduit has negligible influence on the footing performance. When the conduit is located above the critical depth, the bearing capacity of the footing varies with various factors, such as geotechnical parameters of soil and location and diameter of the buried conduit.

It is an original paper performed to assess the presence of buried flexible pipe on the bearing capacity of the shallow footing.

The purpose of this paper is to study the distribution of active earth pressure in retaining walls with narrow cohesion less backfill considering arching effects.

To this end, the approach of principal stresses rotation was used to consider the arching effects.

According to the presented formulation, the active soil pressure distribution is nonlinear with zero value at the wall base. The proposed formulation implies that by increasing the frictional forces at both sides of the backfill, the arching effect is increased and so, the lateral earth pressure on the retaining wall is decreased. Also, by narrowing the backfill space, the lateral earth pressure is extremely decreased.

A comprehensive analytical solution for the active earth pressure of narrow backfills is presented, such that the effects of the surcharge and the characteristics of the stable back surface are considered. The magnitude and height of the application of lateral active force are also derived.

The purpose of this study is the reduction of computational time demand of discrete element based modeling.

The methodology is the systematic changing of particle size and micromechanical parameters to reduce computational time requirements.

In some cases, the computational demand of discrete simulations can be reduced to about 95 per cent.

Based on the results and demonstrated methodology, the enormous computational time demand of discrete element-based modeling can be reduced significantly.

The purpose of this paper is to develop new constitutive models to predict the soil deformation moduli using multi expression programming (MEP). The soil deformation parameters formulated are secant (Es) and reloading (Er) moduli.

MEP is a new branch of classical genetic programming. The models obtained using this method are developed upon a series of plate load tests conducted on different soil types. The best models are selected after developing and controlling several models with different combinations of the influencing parameters. The validation of the models is verified using several statistical criteria. For more verification, sensitivity and parametric analyses are carried out.

The results indicate that the proposed models give precise estimations of the soil deformation moduli. The Es prediction model provides considerably better results than the model developed for Er. The Es formulation outperforms several empirical models found in the literature. The validation phases confirm the efficiency of the models for their general application to the soil moduli estimation. In general, the derived models are suitable for fine‐grained soils.

These equations may be used by designers to check the general validity of the laboratory and field test results or to control the solutions developed by more in‐depth deterministic analyses.

This paper aims to artificially generate seismic accelerograms compatible with the response spectrum imposed as a function of the given environmental parameters such as magnitude, epicentral distance and type of soil. This study is necessary for the non-linear dynamic analysis of structures in regions where real seismic records are not available.

First, a stochastic iterative method is used to estimate the spectral densities of acceleration power from the respective target response spectra. Thereafter, based on the superposition of seismic waves, a subsequent iterative procedure, which implicitly takes into account the non-stationary character of temporal intensity content of strong ground motions, is developed to synthesize, from these power spectral density, the corresponding acceleration time histories. The phase contents of the ground acceleration samples, thus obtained, are generated using a probability density function of phase derivatives with characteristic parameters estimated from seismological considerations. When based on seismic codes spectrum compatible criteria, this procedure can be used to generate strong ground motions for structural design.

The results found show that the forms of acceleration of the target and the simulated signals have similar characteristics in terms of strong motion durations, the peak ground acceleration values, corresponding time of occurrence and also, the corresponding cumulative energy functions follow practically the same pattern of variations.

The aim of this study is to generate seismic accelerograms compatible with regulatory spectra by the composition of the three acceleration duration segments based on environmental parameters (magnitude, epicentral distance and type of soil) and which subsequently serves to control the time envelope of the generated signals, and therefore the random generation of phase derivatives, which has not been previously treated.