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The soil water characteristics play an important role in predicting the engineering behaviour of unsaturated soils. An experimental programme was performed using pressure plate apparatus to investigate the effect of moulding water content, compactive effort and cycles of wetting and drying on Soil Water Characteristic Curves (SWCC) of compacted marine clay. The specimens were prepared with moulding water contents (optimum, dry of optimum and wet of optimum) for both Standard Proctor and Modified Proctor compactive efforts. The results obtained were fitted to Brooks and Corey (BC) and Van Genuchten (VG) models. The study indicated that SWCC for specimens with higher compactive efforts plotted above those with lower compactive efforts. It was observed that the variation in moulding water content had no significant effect in the resulting SWCC. With the increase in the number of cycles of wetting and drying, a decrease in the water retention capacity was observed.

Biochar made from pyrolysis of biomass has wide applications as a soil amendment to reduce emission of greenhouse gases and improve the geotechnical properties of soil. Bentonite enhanced sand mixes are widely used as liner material in construction practice of landfills. Experimental investigation on partial replacement of bentonite with biochar was carried out in compacted M sand bentonite mix (80% M sand and 20% bentonite) which satisfied the requirements of liner soils. Biochar prepared from wood shavings using in-house developed pyrolysis kiln and rice husk biochar prepared using heap method were used in this study. The effect of partial replacement of 10% and 15% bentonite with both wood and rice husk biochar was studied. Examination of the results showed that in both wood and rice husk biochar samples, increase of biochar content decreased the maximum dry unit weight and increased the optimum moisture content. The samples with 10% biochar gave hydraulic conductivity less than 1×10−9 m/sec. In both wood and rice husk biochar samples, free swell, strength, and cracking potential decreased with increase in biochar content. Results indicate that both wood and rice husk biochar up to 10% can effectively replace bentonite in compacted M sand bentonite mixtures.

The molding sand used in metal casting industries produces huge amount of waste products in form of Waste foundry sand (WFS). It contains added chemicals, expansive clays, and residual metal from the casting process. Due to the constituents and the processes, the sand has gone in the past; they are not suitable to be used in concrete. Therefore, this product is usually disposed at landfills. This paper investigates the potential use of waste foundry sand in stabilizing weak marine clay subgrades for construction of road embankments. The experimental program includes characterization of WFS and marine clay deposits, determination of index properties, compaction characteristics and effect of WFS on California bearing ratio (CBR) of the marine clay subgrades. WFS added to marine clay was varied from 10 to 40% of dry weight of marine clay. It was observed that addition of up to 40% added WFS doubles the CBR value and decreases the gap between soaked and unsoaked CBR from over 60 to below 20%. Hence, it is an economic method to improve the performance of subgrade in places where water logging is common.

The study focuses on the use of lime, fly ash and combination of these materials as columnar inclusion for improving the strength and compressibility characteristics of soft Cochin marine clay. Large-scale consolidation tank was used to study compressibility characteristics. A group of five columns of different materials (lime, fly ash and a combination of both) were installed in the tank filled with marine clay in its natural moisture content. The consolidation test was continued till the settlement rate reached a value less than 1 mm/day for the different applied pressures. It was observed that clay alone took 91 days to reach target settlement, whereas the lime column took 29 days, fly ash column took 51 days and 1:1 lime–fly ash column took 39 days. The shear strength of the clay increased with the installation of the columns of different materials.

Feasibility of using marine clay modified with zeolite for the construction of landfill liner was studied. Compacted natural clays are commonly used as liner material due to their high containment, attenuation and cost-effectiveness. The material chosen for liner construction has to satisfy the standards set by Environmental Protection Agency (EPA), based on plasticity characteristics, hydraulic conductivity and shear strength. As per EPA standards, the hydraulic conductivity of the liner material should be less than 1 × 10–7 cm/sec. The feasibility of using marine clay–zeolite mixtures as landfill liner material is presented in this study, and the most acceptable zone was obtained for the same. The liner material was prepared by mixing marine clay with various percentages of zeolite (0–25%). Initially, the suitability of moist and sun-dried marine clay was assessed, because marine clay exhibits different index properties in the natural moist condition and dried condition. Experimental programme involved laboratory tests to determine the index properties, compaction characteristics, hydraulic conductivity and shear strength of marine clay and marine clay–zeolite mix. In order to study the strength development, samples were kept for curing for 7 days, 28 days and 3 months. From the results, 15–20% zeolite content in sun-dried marine clay was found to be optimum.

In the present paper, a multivariate statistical modeling study of water quality data from different places of Kozhikode Gity, Kerala, India, has been conducted applying multiple linear regression (MLR), structural equation modeling (SEM), and adaptive neuro-fuzzy inference system (ANFIS) modeling. First, we combined water quality data from different places in the study area over different time periods to obtain a unified multiple linear regression (MLR) model. By mixing three data sets from different places and time periods in four different ways, different regression models were formed with total dissolved solids (TDS) as the dependent variable and calcium, magnesium, nitrate, sodium, chloride, potassium, total hardness, and sulfate as independent variables. The effectiveness of each model was then tested against a data set, which corresponded to a different period and location. One unmixed model and three mixed models showed similar performance. An SEM was developed for the data set, which is obtained by mixing all the three data sets. The same regression coefficients are found for the SEM and the corresponding MLR. An improvement in the sample size as a result of mixing of data sets could be thought of as the reason for this phenomenon. We thus selected the MLR obtained by mixing all three data sets as our unified model. For the mixed data set, we then developed an ANFIS model with calcium, magnesium, nitrate, sodium, chloride, potassium, total hardness, and sulfate as input variables and TDS as the output variable. On the external data set, the ANFIS model showed a better performance than the MLR model.

One of the major problems being faced today in the society is solid waste disposal. Compacted clay soils are commonly used as liner materials in waste containment systems. As marine clay is abundant in the coastal belt of Kochi, this locally available soil was used in the study. Desiccation cracking of clay mass can lead to development of shrinkage cracks and also provide pathways for moisture migration into the landfill. In order to minimize the adverse effect of cracks, the behaviour of sun-dried marine clay amended with cement in different percentages of 1%, 2%, and 4% were studied. To stimulate the field conditions, the samples were subjected to alternate wetting and drying cycles. For different cement content, three cycles of alternate wetting and drying were performed. The study indicates that the extent of crack formation decreases with increase in cement content and the optimum percentage of cement amendment is 4%.

The availability of earth material has become a necessity for various infrastructural developments. Marine clay which is weak covers a major portion of the country. The scarcity in the availability of soil increases the need to improve engineering properties of soil before construction. An experimental study was undertaken to study the effectiveness of additives on stabilization of marine clay. The additives used in the present study include lime, copper slag and terrazyme. The geotechnical characteristics of moist marine clay and air-dried clay were investigated. Soil specimens were prepared by mixing these additives in varying percentages by dry weight of soil and compacted to maximum dry density at optimum moisture content. Unconfined compressive strength tests were carried out to determine strength characteristics of soil. The results indicate that there is an optimum content for each additive and among the additives used for the study terrazyme proves to be the best.

Determination of soaked california bearing ratio (CBR) and compaction characteristics of soils in the laboratory require considerable time and effort. To make a preliminary assessment of the suitability of soils required for a project, prediction models for these engineering properties on the basis of laboratory tests—which are quick to perform, less time consuming and cheap—such as the tests for index properties of soils, are preferable. Nevertheless researchers hold divergent views regarding the most influential parameters to be taken into account for prediction of soaked CBR and compaction characteristics of fine-grained soils. This could be due to the complex behaviour of soils—which, by their very nature, exhibit extreme variability. However this disagreement is a matter of concern as it affects the dependability of prediction models. This study therefore analyses the ability of artificial neural networks and multiple regression to handle different influential parameters simultaneously so as to make accurate predictions on soaked CBR and compaction characteristics of fine-grained soils. The results of simple regression analyses included in this study indicate that optimum moisture content (OMC) and maximum dry density (MDD) of fine-grained soils bear better correlation with soaked CBR of fine-grained soils than plastic limit and liquid limit. Simple regression analyses also indicate that plastic limit has stronger correlation with compaction characteristics of fine-grained soils than liquid limit. On the basis of these correlations obtained using simple regression analyses, neural network prediction models and multiple regression prediction models—with varying number of input parameters are developed. The results reveal that neural network models have more ability to utilize relatively less influential parameters than multiple regression models. The study establishes that in the case of neural network models, the relatively less powerful parameters—liquid limit and plastic limit can also be used effectively along with MDD and OMC for better prediction of soaked CBR of fine-grained soils. Also with the inclusion of less significant parameter—liquid limit along with plastic limit the predictions on compaction characteristics of fine-grained soils using neural network analysis improves considerably. Thus in the case of neural network analysis, the use of relatively less influential input parameters along with stronger parameters is definitely beneficial, unlike conventional statistical methods—for which, the consequence of this approach is unpredictable—giving sometimes not so favourable results. Very weak input parameters alone need to be avoided for neural network analysis. Consequently, when there is ambiguity regarding the most influential input parameters, neural network analysis is quite useful as all such influential parameters can be taken to consideration simultaneously, which will only improve the performance of neural network models. As soils by their very nature, exhibit extreme complexity, it is necessary to include maximum number of influential parameters—as can be determined easily using simple laboratory tests—in the prediction models for soil properties, so as to improve the reliability of these models—for which, use of neural networks is more desirable.