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Several constitutive models are available in the literature to describe the mechanical behaviour of cement stabilized soils. However, difficulties in implementing such models within commercial finite element programs have hindered their application to solve related boundary value problems. Therefore, the aim of this study is to implement a constitutive model, which has the capability to simulate cement stabilized soil behaviour, into the finite element program ABAQUS through the user material subroutine UMAT.

After a detailed review of existing constitutive models for cement stabilized soils, a model based on the elasto‐plastic theory and the extended critical state concept with an associated flow rule is selected for the finite element implementation. A semi‐implicit integration method (cutting plane algorithm) with a continuum elasto‐plastic modulus and path dependent stress prediction strategy has been used in the implementation. The performance of the new finite element formulation of the constitutive model is verified by simulating triaxial test data using the finite element program with the new implementation and predictions from constitutive equations as well as experimental data.

The paper provides the implementation procedure of the constitutive model into ABAQUS but this method is useful for the implementation of any other constitutive model into ABAQUS or any other finite element program. Simulated results for the volumetric deformation of cement stabilized soils show that the cement stabilized soils do not obey the associated flow rule at high confining pressures. The parametric study shows that the influence of cementation increases the brittle nature and the bearing capacity of treated clay. In addition the results show that proposed finite element implementation has the ability to illustrate key features of the cement stabilized clay.

This paper presents an implementation of an elasto‐plastic constitutive model, based on the extended critical state concept, for cement stabilized soils into a finite element programme, which has been identified as an important and challenging topic in computational geomechanics. This implementation is useful in solving boundary value problems in geomechanics involving cement stabilized soils, incorporating key characteristics of these soils.

To investigate the effect of cement and cement by‐pass dust (CBPD) as a stabilizer on the geotechnical properties of oil‐contaminated soils resulting from leaking underground storage tanks, or soils surrounding petroleum refineries and crude oil wells.

Oil‐contaminated soil (untreated soil) and a soil treated by bio‐remediation (treated soil) as well as a natural soil were obtained from Northern Oman. These soils were stabilized with cement and cement by‐pass dust at 0, 5, 10, 15 and 20 percent, by dry weight of the soil, and cured for seven, 14 and 28 days. Compaction, compressive strength, direct shear, permeability and leaching tests were carried out on the stabilized soils.

The results indicate that cement and cement by‐pass dust improve the properties of oil‐contaminated soils. Traces of arsenic, barium, cadmium, chromium and lead were found in the oil soils, but none of them exceeded the EPA limits.

Reuse in construction applications provides a safe and useful solution for the problem of the disposal of oil‐contaminated soils.

The paper addresses an environmental problem facing many oil companies in disposing of or treating contaminated soil. The approach presented in the paper offers a beneficial, safe and economical solution to this problem.

This paper describes the effect of factors on the strength characteristics of cement treated clay from laboratory tests performed on cement mixed clay specimens. It is considered that several factors such as soil type, sample preparing method, quantity of binder, curing time, etc. can have an effect on strength characteristics of cement stabilized clay. A series of unconfined compression tests have been performed on samples prepared with different conditions. The results indicated that soil type, mixing method, curing time, dry weight ratio of cement to clay (Aw), and water‐clay to cement (wc/c) ratio were main factors which can have an influence on unconfined compressive strength, modulus of elasticity, and failure strain of cement stabilized clay. Unconfined compressive strength of soil‐cement samples prepared from dry mixing method was higher than those prepared from wet mixing method.

This study aims to investigate the optimum proportion of coconut fibre and cement suitable for rammed earth wall construction. Coconut fibres and cement can be easily incorporated into the soil mixture which adds strength and durability to the wall. This paper highlights the salient observations from a systematic investigation on the effect of coconut fibre on the performance of stabilized rammed earth blocks.

Stabilization of soil was done by adding Ordinary Portland Cement (2.5, 5.0, 7.5 and 10.0 per cent by weight of soil), whereas coconut fibre in length about 15 mm was added (0.2, 0.4, 0.6, 0.8 and 1.0 per cent by weight of soil) as reinforcement. Thirty types of mixes were created by adding different proportions of cement and fibre to locally available soil and compacting the mix at constant compaction energy in three layers with Proctor rammer.

Samples were tested for compressive strength and tensile strength, and failure patterns were analysed. The use of cement and fibre increases ultimate strengths significantly up to an optimum limit of 0.8 per cent fibre content, provides a secondary benefit of keeping material bound together after failure and increases residual strength. Benefits of fibre reinforcement includes both improved ductility in comparison with raw blocks and inhibition of crack propagation after its initial formation.

After analysing the results, it is recommended to use 0.8 per cent fibre and 5-10 per cent cement by weight of soil to achieve considerable strength. This research may add a value in the areas of green and sustainable housing, waste utilization, etc.

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 paper aims to investigate the behaviour of geosynthetic reinforced deep cement mixed (DCM) column-supported embankments constructed over soft soils.

Coupled consolidation analyses based on the finite element method are carried out assuming that the soil and DCM columns are fully saturated porous mediums. In the first part of the paper, a case study of an embankment constructed over a very soft soil deposit in Finland is presented. Two- and three-dimensional finite element models for the case study are developed including isolated and attached DCM columns beneath the embankment to capture the arching mechanism between DCM columns. The model simulations were carried out considering the actual staged construction procedure adopted in the field. Finite element predictions show good agreement with field data and confirm that the load transfer is mainly between attached columns beneath the embankment. Next, the significance of geosynthetic reinforcement on the load transfer mechanism is investigated. Finally, the influence of permeability of columns and soft soil on the performance of geosynthetic reinforcement column-supported embankments is studied.

Results demonstrate that the excess pore pressure dissipation rate is fast in DCM column-improved ground compared to the same case without any columns, although the same permeability is assigned to both DCM columns and surrounding soft soil. When DCM column permeability exceeds soil permeability, excess pore pressure dissipation rate shows a remarkable increase compared to that observed when the DCM column permeability is less than or equal to the permeability of surrounding soft soil. [ ]

This paper investigates the contribution of permeability and geosynthetic layer on the vertical load transfer mechanism of the embankment and modelling issues related to application of the embankment load and the properties of the cement-improved columns.

Explore the development trend of chemically-improved soil in railway engineering.

In this paper, the technical standards home and abroad were analyzed. Laboratory test, field test and monitoring were carried out.

The performance design system of the chemically-improved soil should be established.

On the basis of the performance design, the test methods and standards for various properties of chemically-improved soil should be established to evaluate the improvement effect and control the engineering quality.

The purpose of this study is to investigate the effect of various heat conditions on the durability of eggshell powder (ESP)–flyash (FA) geopolymer subjected to wetting–drying cycles.

In this study, two waste materials, ESP and FA, which are destined for landfills, were used as precursors to produce geopolymers in a sustainable manner. The mixture of Na₂SiO₃ and NaOH was used as a liquid alkaline activator in geopolymerization. The ESP and FA content were varied as 30, 50 and 70% and Na₂SiO₃/NaOH ratios were varied as 0.5, 1 and 2. Geopolymer samples were cured at three heat conditions: 25°C (ambient temperature), 50°C and 80°C for seven days prior to durability tests.

The results of this study revealed that the strength loss of the geopolymer decreases with an increase in curing temperature up to 50°C and then increases for higher temperature up to 80°C. Further, the strength loss of the geopolymer decreases with an increase in FA replacement and Na₂SiO₃/NaOH ratio. Geopolymer composites exhibited early strength development because of the inclusion of calcium-rich ESP. The weight loss of the ESP–FA geopolymer follows a similar pattern of strength loss. Geopolymer samples previously cured at optimum heat condition of 50°C for seven days exhibited higher durability.

The inclusion of calcium-rich ESP in FA-based geopolymer is novel research. As ESP–FA geopolymer composites show higher mechanical strength and higher durability compared to Indian standards, the potential use of this geopolymer can be in road subbases/subgrades.

The purpose of this paper is to identify the sustainability conditions of primary schools in Turkey within the scope of the life cycle assessment (LCA). It is aimed to develop optimum alternatives to reduce the environmental impact of primary schools and reach environmental sustainability targets of the sustainable development goals in Turkey.

From the construction project of 103 buildings located in Istanbul, 10 case buildings with various typical plans were chosen for analysis. The results regarding their life cycle energy and carbon emission for material production, operation and maintenance stages were calculated for a lifespan of 50 years. Results were evaluated and compared within the scope of environmental sustainability. Optimum alternatives for improving the environmental sustainability and performances of selected case buildings’ facades were developed, and the life cycle energy and carbon emission for proposed conditions were calculated. The obtained results were evaluated for current and proposed conditions.

Results showed that reinforced concrete material contributes the most to the life cycle-embodied energy and CO₂ emission of buildings. Cooling load increases the life cycle operational energy (LCOE) and CO₂ emission of buildings. Using high-performance glazing significantly reduces LCOE and CO₂ emission. Recycled and fiber-based materials have significant potential for reducing life cycle-embodied energy and CO₂ emission.

This study has been developed in response to achieving sustainable development targets on public buildings in Turkey. In this regard, external walls of primary schools were analyzed within the scope of LCA and recommendations were made to contribute to the policies and regulations requested by the Government of Turkey. This study proves that alternative and novel materials have great potential for achieving sustainable public buildings. The study answers to questions about reducing the environmental impact of primary school buildings by using LCA approach with a holistic point of view.

Reinforced lightweight soil (RLS) consisting of dredged soil, cement, air‐foam, and waste fishing net is considered to be an eco‐friendly backfilling material because it provides a means to recycle both dredged soil and waste fishing net. It may be difficult to find an optimum mixing ratio of RLS considering the design criteria and the construction's situation using the limited test results because the unconfined compressive strength is complicatedly influenced by various mixing ratios of admixtures. As a result, in order to expedite the field application of RLS, an appropriate prediction method is needed. The paper aims to address these issues.

In this study, an artificial neural network (ANN) model that was based on experimental test results performed on various mixing ratios, was developed to predict the unconfined compressive strength of RLS.

It was found that the unconfined compressive strength of RLS at a given mixing ratio could be reasonably estimated using the developed neural network model. In addition, sensitivity analysis was also conducted to evaluate the effect of mixing conditions on the compressive strength of RLS.

RLS is considered to be environmentally friendly because it provides a means to recycle both dredged soil and waste fishing net. The contractors could use the proposed ANN model as an alternative method to predict the strength of RLS with a specific mixing ratio.

This paper reveals that the developed ANN model can be served as a simple and reliable predictive tool for the strength of RLS without excessive laboratory tests for various admixture contents. An optimum admixture ratio of composed materials to get a designed strength could be easily found by using the proposed ANN model.