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Mian C. Wang - One of the best experts on this subject based on the ideXlab platform.

  • Artificial Neural Network Prediction Models for Soil Compaction and Permeability
    Geotechnical and Geological Engineering, 2008
    Co-Authors: Sunil K. Sinha, Mian C. Wang
    Abstract:

    This paper presents Artificial Neural Network (ANN) prediction models which relate permeability, maximum dry density (MDD) and Optimum Moisture Content with classification properties of the soils. The ANN prediction models were developed from the results of classification, compaction and permeability tests, and statistical analyses. The test soils were prepared from four soil components, namely, bentonite, limestone dust, sand and gravel. These four components were blended in different proportions to form 55 different mixes. The standard Proctor compaction tests were adopted, and both the falling and constant head test methods were used in the permeability tests. The permeability, MDD and Optimum Moisture Content (OMC) data were trained with the soil’s classification properties by using an available ANN software package. Three sets of ANN prediction models are developed, one each for the MDD, OMC and permeability (PMC). A combined ANN model is also developed to predict the values of MDD, OMC, and PMC. A comparison with the test data indicates that predictions within 95% confidence interval can be obtained from the ANN models developed. Practical applications of these prediction models and the necessary precautions for using these models are discussed in detail in this paper.

Agus Setyo Muntohar - One of the best experts on this subject based on the ideXlab platform.

  • stabilization of residual soil with rice husk ash and cement
    Construction and Building Materials, 2005
    Co-Authors: E A Basha, Hilmi Bin Mahmud, Roslan Hashim, Agus Setyo Muntohar
    Abstract:

    Abstract Stabilization of residual soils is studied by chemically using cement and rice husk ash. Investigation includes the evaluation of such properties of the soil as compaction, strength, and X-ray diffraction. Test results show that both cement and rice husk ash reduce the plasticity of soils. In term of compactability, addition of rice husk ash and cement decreases the maximum dry density and increases the Optimum Moisture Content. From the viewpoint of plasticity, compaction and strength characteristics, and economy, addition of 6–8% cement and 10–15% rice husk ash is recommended as an Optimum amount.

Asuri Sridharan - One of the best experts on this subject based on the ideXlab platform.

  • Prediction of Compaction Behaviour of Soils at Different Energy Levels
    Uluslararası Muhendislik Arastirma ve Gelistirme Dergisi, 2015
    Co-Authors: Yesim Gurtug, Asuri Sridharan
    Abstract:

    Compaction tests forms one of the important aspects in geotechnical engineering practice. These tests are time consuming and require large quantity of soil also. In this paper based on the results of the compaction tests carried out for different soils of varying plasticity characteristics at different compaction energies and on published data, it has been brought that there is a good correlation between the Optimum Moisture Content and plastic limit for the . In addition to this one can predict the modified compaction parameters just knowing the plastic limit of the soil. For the present investigation, three different soils from North Cyprus (Tuzla, Degirmenlik and Akdeniz) and a soil from Turkey (highly plastic montmorillonitic clay) were chosen. These soils are heavily in use for civil engineering activities like construction of pavements, embankments and earth retaining structures. Compaction tests were carried out at three different energy levels for the four soils described.. They are standard Proctor test (SP), reduced modified Proctor (RMP) and modified Proctor (MP). For the standard Proctor, the compaction energy works out to be 593.7 kJ/m 3 . In the modified Proctor test, the compaction energy works out to be 2693.3 kJ/m 3 . In the reduced modified Proctor test the procedure is same as modified Proctor except the number of layers are three instead of five. The compaction energy works out to be 1616 kJ/m 3 . [1] Based on the experimental results obtained for maximum dry density vs. Optimum Moisture Content for the four different soils with different compaction energy levels it has been found that irrespective of soil type and compaction energy levels both the maximum dry density and Optimum Moisture Content are linearly related with a very high correlation coefficient of R= 0.994. Results obtained from laboratory tests as well as from literature show that the correlation between maximum dry density and OMC for different soils, compacted for two compaction energy levels is very good. It is thus seen that one can predict OMC knowing the plastic limit with reasonable accuracy. Having obtained OMC one can get the maximum dry density from equation(1) obtained in this study. From experimental results it has been found that both OMC and maximum dry density of Proctor’s test results and that of modified Proctor’s test results of authors’ as well as data collected from literature correlate very well. It is seen that the correlation is highly satisfactory. Having obtained both OMC and maximum dry density for Proctor’s energy level one can get the OMC and maximum dry density for modified Proctor condition also.

  • Effect of compaction energy on CBR and compaction behaviour
    Proceedings of the Institution of Civil Engineers - Ground Improvement, 2015
    Co-Authors: P. Vinod, Asuri Sridharan, Rosalint Jolly Soumya
    Abstract:

    The study reported herein examines the effect of compaction energy on the compaction characteristics and California bearing ratio (CBR) value of soils. The study involved two soils of widely varying plasticity, and led to a logarithmic relationship between the maximum dry density and compaction energy, and the relationship between the Optimum Moisture Content and compaction energy is represented by a second-degree polynomial equation. Correlation between the CBR value and compaction energy is represented by a two-parameter linear model. The numerical values of the coefficients in the developed correlations are almost independent of the method of energy reduction and marginally dependent on the soil type. The study also re-establishes that the Optimum Moisture Content and maximum dry density of fine-grained soils are uniquely related, with the correlation being independent of the energy ratio.

  • Compaction Behaviour and Prediction of its Characteristics of Fine Grained Soils with Particular Reference to Compaction Energy
    Soils and Foundations, 2004
    Co-Authors: Yesim Gurtug, Asuri Sridharan
    Abstract:

    Field compaction of fine grained soils usually involves different equipments with the compaction energy varying significantly. Hence the compaction characteristics (maximum dry unit weight and Optimum Moisture Content) need to be obtained at different compaction energies. Thus knowledge of compaction behaviour and its characteristics of fine grained soils at different compaction energies assumes great importance from the viewpoint of practical significance. In this paper the effect of compaction energy on the behaviour and compaction characteristics of fine grained soils has been brought out. It has been seen that the Optimum Moisture Content bears a good relation with plastic limit and the maximum dry unit weight correlating well with the dry unit weight of soil at plastic limit for all compaction energies studied. Apart from the experimental data obtained by the authors, extensive results from literature have also been used in the analysis. In view of large quantities of soils from different borrow pits to be tested for their potential use, the above correlation with plastic limit enables not only saving of time but also cost of investigation for preliminary design.

Sunil K. Sinha - One of the best experts on this subject based on the ideXlab platform.

  • Artificial Neural Network Prediction Models for Soil Compaction and Permeability
    Geotechnical and Geological Engineering, 2008
    Co-Authors: Sunil K. Sinha, Mian C. Wang
    Abstract:

    This paper presents Artificial Neural Network (ANN) prediction models which relate permeability, maximum dry density (MDD) and Optimum Moisture Content with classification properties of the soils. The ANN prediction models were developed from the results of classification, compaction and permeability tests, and statistical analyses. The test soils were prepared from four soil components, namely, bentonite, limestone dust, sand and gravel. These four components were blended in different proportions to form 55 different mixes. The standard Proctor compaction tests were adopted, and both the falling and constant head test methods were used in the permeability tests. The permeability, MDD and Optimum Moisture Content (OMC) data were trained with the soil’s classification properties by using an available ANN software package. Three sets of ANN prediction models are developed, one each for the MDD, OMC and permeability (PMC). A combined ANN model is also developed to predict the values of MDD, OMC, and PMC. A comparison with the test data indicates that predictions within 95% confidence interval can be obtained from the ANN models developed. Practical applications of these prediction models and the necessary precautions for using these models are discussed in detail in this paper.

Zainuddin Md Yusoff - One of the best experts on this subject based on the ideXlab platform.

  • geotechnical assessment of palm oil fuel ash pofa mixed with granite residual soil for hydraulic barrier purposes
    Malaysian Journal of Civil Engineering, 2016
    Co-Authors: Nik Norsyahariati Nik Daud, Abubakar Sadiq Muhammed, Zainuddin Md Yusoff
    Abstract:

    This paper assesses the geotechnical properties of granite residual soil treated with palm oil fuel ash (POFA), a waste from the palm oil factory for the purposes of hydraulic barrier in landfills. Granite residual soil treated with up to 40% palm oil fuel ash (by dry weight of the soil) was compacted using standard proctor compactive effort at the Optimum Moisture Content. Index properties, hydraulic conductivity (k), volumetric shrinkage strain (VSS) and unconfined compressive strength (UCS) tests were carried out. Results showed that the index properties of samples met the minimum requirement for it to be used ass a liner. The maximum dry density and Optimum Moisture Content decreased and increased respectively. The influence of POFA treatment on the geotechnical properties generally showed an improvement with up to 15% POFA which gave the acceptable results with regards to its usability as a hydraulic barrier material in landfill.

  • strength assessment of granite residual soil treated with palm oil fuel ash pofa as hydraulic barrier
    7th International Congress on Environmental Geotechnics : iceg2014, 2014
    Co-Authors: Nik Norsyahariati Nik Daud, Abubakar Sadiq Muhammed, Zainuddin Md Yusoff
    Abstract:

    Laboratory study was carried out to evaluate the shear strength properties of granite residual soil treated with up to 15% palm oil fuel ash (POFA) relevant to the design and construction of landfill containment (i.e. cover or base liner). Index properties, compaction and unconfined compression strength (UCS) tests were carried out on the soil - POFA mixture. Samples for the unconfined compression test were prepared using two compactive energies namely the Standard and Modified Proctor at moulding water Content between -2% to +4% of the Optimum Moisture Content obtained from the compaction curve. The maximum dry density and Optimum Moisture Content decreased and increased respectively for both compactive efforts. The results showed that the shear strength values increased with addition POFA and also at higher compactive effort, however the values decreased at higher moulding water Content irrespective of POFA Content and compactive effort. The strength values of granite residual soil - POFA mixture samples that met or exceeded the minimum required strength were drawn in an envelope to define the zones where Moisture Content and dry density produced the acceptable shear strength for the application of hydraulic barrier. Furthermore, the addition of POFA broadened the range of moulding water Content of samples which produced acceptable strength on the compaction curve.