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The study is carried out to analytically reconnoiter geotechnical index properties of subgrade soils as key variables that shape the cost profile of road infrastructure projects in a tropical geographic setting with starkly heterogenous ground conditions.

Using the Niger Delta region, as a point of reference, data on geotechnical index properties of subgrade soils at spatially dispersed locations for 61 completed highway projects are collated. Exploratory statistical tests were carried out to infer significant associations with final project costs before regression analysis. Regression analysis is principally deployed as an explanatory analytical tool, relevant to quantify the sensitivity of highway project costs to the individual and collective impact of geotechnical variables.

Several parameters of expansivity and compressibility exhibited significantly strong associations with the final costs recorded on the highway projects. The statistical analysis further established a cause-effect relationship, whereby small changes in the geotechnical properties of sub-grade soils at project locations, would result in disproportionately large changes in the cost of road construction.

The study findings provide insight into the sensitivity of road construction costs to geotechnical variables, which can serve as a useful input in financial risk analysis for development appraisal and the generation of location adjustment factors.

The study statistically demonstrates location-induced construction cost profiles, triggered in response to the spatial geotechnical variability and occurrence of problem subgrade soils in the humid tropics, which may be different from those traditionally established in studies of cold and temperate climate soils.

This paper presents physical and geotechnical characteristics of unstabilized (original) and stabilized peat soil samples from Sarawak, Malaysia. Peat soil is heterogeneous, with high compressibility, high water content, low specific gravity and has medium to low permeability. As a result, evaluation of physical and geotechnical properties are very important for any types of construction on it. Different physical and geotechnical properties e.g. organic content, loss on ignition, liquid limit, specific gravity, fiber content, compaction and Unconfined Compressive Strength (UCS) tests have been carried out on peat soil sample. Locally available fly ash (FA) from coal fired thermal power plant and commercially available quick lime (QL) were used as stabilizers. The amount of FA and QL added to the peat soil sample, is 5 to 25% and 2 to 8%; respectively, for curing periods of 7 to 120 days. The standard Proctor compaction test and UCS test were carried out on original and stabilized peat soil samples with the above mentioned percentages of stabilizer and results show that the UCS value increases significantly with the increase of FA and QL percentage and also with curing periods. But, with 15 to 20 % FA and 6 % QL added with peat soil, the UCS values slightly decreases up to 28 days and again increases after 120 days curing periods. Furthermore, liquid limit and specific gravity tests have been carried out with only for the FA stabilized peat soil samples, in order to comprehend their stabilized behavior.

This paper aims to present physical and geotechnical study in terms of experimental field and laboratory investigations of the subgrade soils in severely damaged and highly degraded road section with numerous potholes between Chencha to Ezo towns of Ethiopia needs to be addressed for a robust pavement.

Eighteen soil samples were collected from 18 km road stretch at a kilometer interval by considering variation and composition of soils along the road alignment. The field density with dry density, natural moisture content, consistency limit, compaction and California Bearing Ratio (CBR) were determined.

Soils were classified predominantly as silty-clay that replicates its expansive nature, characterized as bad to medium subgrade. The average optimum moisture content and maximum dry density are 17.18% and 1.83 g/cc, whereas the average CBR and swell as 8.40% and 1.49%, respectively. The investigated results indicated that the indispensable way for a stable and durable road subgrade in the existing silty clayey soil requires a capping layer. The results were uploaded into ArcGIS platform to create interactive maps for spatial distribution, composition and strength of the subgrade properties.

Experimental investigation of subgrade soils by scientific procedures and presenting important properties through integrated approach using ArcGIS Mapping for the road pavement design and construction purpose of under developed areas like Chencha-Ezo. ArcGIS-based mapping of all required and numerical subgrade properties with a single click using ArcGIS tool is the main significance and contribution of this study. To the best of the authors’ knowledge, this paper is original, and all the references are properly cited.

The purpose of this paper is to examine the feasibility of committee neural network (CNN) theory for the improvement of accuracy and consistency of the neural network model on the estimation of preconsolidation pressure from the field piezocone measurements.

In this study, CNN theory is introduced to improve the initial weight dependency of the neural network model on the prediction of preconsolidation pressure of soft clay from a piezocone test result. It was found that the proposed CNN model can improve the initial weight dependency of the NN model and provide a more consistent and precise inference result than existing NN models, as well as empirical and theoretical models.

It was found that the CNN overcomes the initial weight dependency of the single neural network model. Various committees of the single multilayer perceptrons (MLPs) were tested. It was found that if eight single MLPs, which have the same structure but have been trained with a different initial weight and bias, are accumulated in the committee with the same weighting factor, any variation on the prediction of the preconsolidation pressure from the piezocone test result can be simply and successfully eliminated.

In recent years, ANN has been found to be a powerful theory for analyzing complex relationships involving a multitude of variables, on many geotechnical applications. However, single MLP, when repeatedly trained on the same patterns, tends to reach different minima of the objective function each time and hence give a different set of neuron weights, because the solution is not unique for noisy data, as in most geotechnical problems. The authors observed that a committee neural network system is able to provide improved performance compared with a single optimal neural network.

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 statistical validity of geotechnical risk factors in accounting for cost overruns in highway projects. The study hypothesises that “latent pathogens” because of mismanaged geotechnical risk, which lay dormant in organisational practices of highway agencies, trigger cost overruns.

To test this hypothesis, cost and geotechnical data gathered for 61 completed highway projects, executed in the Niger Delta, recording unusually high cost overruns, along with qualitative data from 16 interviews with the project commissioners, were comprehensively analysed via regression modelling, to statistically explain recorded cost variance.

The results provide empirical evidence supporting a cause–effect relationship between the extent of cost overrun and key geotechnical factors. It is suggested that positive changes made in the geotechnical practices of the highway agencies will produce an expected exponential decrease in the level of cost overruns recorded in highway projects.

The study is limited to explaining the propagation of unusually high cost overruns in the geologic setting of the Niger Delta region of Nigeria. As such there is a need to test the generalisability of the theory presented.

The emergent view of geotechnical practice calls for further research, necessary to align geotechnical best practice into highway project delivery in the Niger Delta region.

The study used a robust methodological approach to understanding the propagation of cost overruns in highway projects, based on a characterisation of geotechnical intricacies, which is unprecedented in cost overrun research.

The purpose of this study was to investigate the likely causes of failure of some sections of road pavements in Ajaokuta, Northcentral Nigeria. This was achieved through a geotechnical assessment of subgrade soils in affected areas.

The methods entailed field and laboratory methods and statistical analysis. Subgrade soil samples were retrieved from a depth of 1,000 mm beneath the failed portions using a hang auger. The soils were analyzed for natural moisture content (NMC), Atterberg limit (liquid limit, plastic limit and linear shrinkage), grain size distribution, compaction and California bearing ratio (CBR), respectively.

The results of the geotechnical tests ranged from NMC (12.5%–19.4%), sand (84%–98%), fines (2%–16%), LL (16.0%–32.2%), PL (17%–27.5%), LS (2.7%–6.4%), PI (2.5%–18.4%), maximum dry density (1756 kg/m2–1961 kg/m2), optimum moisture content (13.2%–20.2%), unsoaked CBR (15.5%–30.5%) and soaked CBR (8%–22%), respectively. Pearson’s correlation coefficient performed on the variables showed that some parameters exhibited a strong positive correlation with r2 > 0.5.

Funding was the main limitation.

Comparing the results with Nigerian standards for road construction, and the AASHTO classification scheme, the subgrade soils are competent and possess excellent to good properties. The soils also exhibited very low plasticity, a high percentage of sand, high CBR and low NMC, which implies that it has the strength required for road pavement subgrades. The likely causes of the failures are, therefore, due to the use of poor construction materials, technical incompetence and poor compaction of sub-base materials, respectively.

This study demonstrates integration within a mixed-methods case study of construction phenomena, whilst ensuring reliability and validity. This is in view of the established philosophical challenges in theory generation, whereby qualitative and quantitative methods are underpinned by divergent, almost incompatible, paradigmic assumptions.

The study uses a sample case study research on the phenomenon of cost overruns, supported by a coherent flow of well-articulated philosophical arguments to idealise the logic of integration. Issues of reliability and validity were resolved along these lines, by incorporating applicable criteria from both the qualitative and qualitative strands. A detailed outline and rationalisation of the stepwise approach to achieving integration are provided, from the point of design conceptualisation, data collection, analysis and further down to theory generation.

The study generated two level-1 theories by collecting numerical data on cost overruns, geotechnical index parameters and textual data on the geotechnical practices. Another level-1 theory was generated in reflexive adaptation to unanticipated social constructs emerging from the qualitative data. All level-1 theories from the quantitative and qualitative strands were triangulated to yield two “level-2 theories”: A log-regression model and a cognitive map. The approach to integration is thus explanatory sequential, and concurrent (at the second stage of transformation in the generation of level-2 theories).

The study empirically reinforces that ontological flexibility, achievable through the use of thoughtfully designed integrated mixed-methods case studies, permits the investigation of multidimensional construction phenomena in innovative ways, relevant to provide holistic theoretical and practice-based contributions.

The study practically signposts a bespoke stepwise approach to integration, in a mixed-methods case study of construction phenomena, against the contextual backdrop of its relative novelty and lack of studies delving in-depth into the theoretical nitty-gritty.

This study aims to investigate ground-related design deficiencies as potential avenues of avoidable cost overruns, discernible from the geotechnical practices of highway agencies in the Niger Delta region of Nigeria.

The study deploys an interpretivist qualitative methodology to provide a detailed descriptive analysis of the design-related geotechnical practices of highway agencies during the pre-contract phase of highway projects. Semi-structured interviews were conducted with in-house professionals, consultants and contractors affiliated with the three highway agencies in the Niger Delta and thematically analysed to identify significant deviations from geotechnical best practices.

The study outcome shows that during the pre-contract phase, a chain of design-related geotechnical shortcomings has plagued highway projects executed in the Niger Delta. This view of practice uncovered in this study demonstrates a culture of significant deviation from best practice recommendations, which could plausibly contribute to the history of significant project cost overruns recorded in the region.

The study qualitatively spotlights gaps in the practice of highway agencies and reinforces the need for a re-orientation of the attitude to risk management, to give geotechnical concerns a priority in the financial management of highway projects executed in the Niger Delta region of Nigeria.

Nowadays, application of biopolymers on geotechnical engineering works is booming to avoid the harsh effects on environment by using conventional methods for soil treatment. In this present study, xanthan gum (XG) is used as a biopolymer to improve dispersive properties of the soils because these soils are easily prone to erosion, which may lead to the damage of many hydraulic structures.

In the present study, attempts are made to reduce the dispersive potential and increase the Strength and erosion resistance by treating the soils with various percentages of XG (0.5%, 1%, 1.5% and 2%). To assess the dispersive potential and erosion resistance of soils, tests such as double hydrometer test, pinhole erosion test, crumb test and cylinder dispersion test were conducted. Further tests were expanded for its geotechnical characteristics such as Atterberg’s limits, standard proctor test, unconfined compressive strength test, one-dimensional consolidation for various curing days. Scanning electron microscopy analysis was also carried out to know the microscopic view towards its particle orientation and bindings. Chemical tests such as sodium absorption ratio, total dissolved solids (TDS) and percentage sodium (PS), electronic conductivity and pH tests were also conducted.

The results revealed that there is a reduction in the dispersive potential of XG treated soils for all the combinations. Addition of XG decreased the PS in the soil as a result dispersivity of soil decreased. Strength and erosion resistance of soil increased with the addition of XG and 1% XG was observed to be the optimum percentage for stabilizing these types of soils.

These results will be very much helpful for engineers when they come across with dispersive soils for better handling and management.

The originality of this study was an attempt towards sustainable development by treating dispersive soils with XG and effects on various geotechnical and dispersive characterizes.