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Sarat K. Das
Sarat K. Das
Professor, Civil Engineering Department, Indian Institute of Technology(ISM), Dhanbad
Verified email at iitism.ac.in
Title
Cited by
Cited by
Year
Undrained lateral load capacity of piles in clay using artificial neural network
SK Das, PK Basudhar
Computers and Geotechnics 33 (8), 454-459, 2006
2772006
Prediction of residual friction angle of clays using artificial neural network
SK Das, PK Basudhar
Engineering Geology 100 (3-4), 142-145, 2008
1792008
Geotechnical characterization of some Indian fly ashes
SK Das, Yudhbir
Journal of Materials in Civil Engineering 17 (5), 544-552, 2005
1662005
Classification of slopes and prediction of factor of safety using differential evolution neural networks
SK Das, RK Biswal, N Sivakugan, B Das
Environmental Earth Sciences 64, 201-210, 2011
1582011
Application of artificial intelligence to maximum dry density and unconfined compressive strength of cement stabilized soil
SK Das, P Samui, AK Sabat
Geotechnical and Geological Engineering 29, 329-342, 2011
1532011
Strength and durability characteristic of alkali activated GGBS stabilized red mud as geo-material
S Alam, SK Das, BH Rao
Construction and Building materials 211, 932-942, 2019
1272019
10 Artificial neural networks in geotechnical engineering: modeling and application issues
SK Das
Metaheuristics in Water Geotech Transp Eng 45, 231-267, 2013
1022013
Properties and Assessment of Applications of Red Mud (Bauxite Residue): Current Status and Research Needs
BH Reddy, P.S., Reddy, N.G., Serjun, V.Z., Mohanty, B., Das, S.K., Reddy, Rao
Waste and Biomass Valorization 12 (1), 2020
93*2020
Slope stability analysis using artificial intelligence techniques
S Suman, SZ Khan, SK Das, SK Chand
Natural Hazards 84, 727-748, 2016
912016
Prediction of swelling pressure of soil using artificial intelligence techniques
SK Das, P Samui, AK Sabat, TG Sitharam
Environmental Earth Sciences 61, 393-403, 2010
842010
Prediction of maximum dry density and unconfined compressive strength of cement stabilised soil using artificial intelligence techniques
S Suman, M Mahamaya, SK Das
International Journal of Geosynthetics and Ground Engineering 2, 1-11, 2016
782016
Geotechnical properties of low calcium and high calcium fly ash
SK Das, Yudhbir
Geotechnical & Geological Engineering 24, 249-263, 2006
782006
Prediction of field hydraulic conductivity of clay liners using an artificial neural network and support vector machine
SK Das, P Samui, AK Sabat
International Journal of Geomechanics 12 (5), 606-611, 2012
742012
Characterization of coarse fraction of red mud as a civil engineering construction material
S Alam, SK Das, BH Rao
Journal of Cleaner Production 168, 679-691, 2017
732017
CPT-based seismic liquefaction potential evaluation using multi-gene genetic programming approach
PK Muduli, SK Das
Indian Geotechnical Journal 44, 86-93, 2014
642014
Characterization of red mud as a structural fill and embankment material using bioremediation
I Panda, S Jain, SK Das, R Jayabalan
International biodeterioration & biodegradation 119, 368-376, 2017
632017
Uplift capacity of suction caisson in clay using multivariate adaptive regression spline
P Samui, S Das, D Kim
Ocean Engineering 38 (17-18), 2123-2127, 2011
572011
A simplified model for prediction of pozzolanic characteristics of fly ash, based on chemical composition
SK Das
Cement and Concrete Research 36 (10), 1827-1832, 2006
522006
Stabilization of an expansive soil using alkali activated fly ash based geopolymer
PS Parhi, L Garanayak, M Mahamaya, SK Das
Advances in Characterization and Analysis of Expansive Soils and Rocks …, 2018
492018
Design of tailing dam using red mud
SK Rout, T Sahoo, SK Das
Central European Journal of Engineering 3, 316-328, 2013
492013
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