Estimating the efficiency of the sandy soils-cement based grout interactions from Particle size distribution (PSD)

References

• Buchan, G.D., 1989a. Applicability of the simple lognormal model to particle-size distribution in soils. Soil Science, 147 (3), 155–161. doi:10.1097/00010694-198903000-00001
   Web of Science ®Google Scholar
• Buchanan, A.E. and Brock, D.W., 1989b. Deciding for others: the ethics of surrogate decision making. Cambridge University Press.
   Google Scholar
• Fredlund, M.D., Fredlund, D.G., and Wilson, G.W., 2000. An equation to represent grain-size distribution. Canadian Geotechnical Journal, 37 (4), 817–827. doi:10.1139/t00-015
   Web of Science ®Google Scholar
• Holtz, R.D. and Kovacs, W.D. (1981). An introduction to geotechnical engineering (No. Monograph).
   Google Scholar
• Hwang, S.I., et al., 2002. Models for estimating soil particle-size distributions. Soil Science Society of America Journal, 66 (4), 1143–1150. doi:10.2136/sssaj2002.1143
   Web of Science ®Google Scholar
• Hwang, S.I. and Hong, S.P., 2006. Estimating relative hydraulic conductivity from lognormally distributed particle-size data. Geoderma, 133 (3–4), 421–430. doi:10.1016/j.geoderma.2005.08.006
   Web of Science ®Google Scholar
• Karol, R.H., 1990. Chemical grouting. New York: Marcel dekker.
   Google Scholar
• Lord, R.V., 1956. Grouting of foundation sands and gravels—appendix A: tests of acrylamide-N, N’ methylene-bis-acrylamide as a grouting agent. CWI Rep. No. 506, U.S. Army Corps of Engineers. Vicksburg, Miss.: Technical Memorandum No. 3-408.
   Google Scholar
• Mebarkia, S. and Vipulanandan, C., 1992. Compressive behavior of glass-fiber reinforced polymer concrete. Journal of Materials in Civil Engineering, 4 (1), 91–105. doi:10.1061/(ASCE)0899-1561(1992)4:1(91)
   Google Scholar
• Mohammed, A. and Mahmood, W., 2018a. Statistical variations and new correlation models to predict the mechanical behavior and ultimate shear strength of gypsum rock. Open Engineering, 8 (1), 213–226. doi:10.1515/eng-2018-0026
   Web of Science ®Google Scholar
• Mohammed, A. and Mahmood, W., 2018b. Vipulanandan failure models to predict the tensile strength, compressive modulus, fracture toughness and ultimate shear strength of calcium rocks. International Journal of Geotechnical Engineering, 1–11. doi:10.1080/19386362.2018.1468663
   Google Scholar
• Mohammed, A. and Vipulanandan, C., 2018. Smart cement compressive piezoresistive, stress-strain, and strength behavior with nanosilica modification. Journal of Testing and Evaluation, 47 (2).
   Web of Science ®Google Scholar
• Mohammed, A.S., 2018. Vipulanandan model for the rheological properties with ultimate shear stress of oil well cement modified with Nano clay. Egyptian Journal of Petroleum, 27(3), 335–347.
   Google Scholar
• Mohammed, A.S., 2018a. Vipulanandan models to predict the mechanical properties, fracture toughness, pulse velocity and ultimate shear strength of shale rocks. Geotechnical and Geological Engineering, 37(2), 625–638.
   Web of Science ®Google Scholar
• Mohammed, A.S., 2018b. Vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticles. Egyptian Journal of Petroleum, 27(4), 1265–1273.
   Google Scholar
• Mohammed, A.S. and Vipulanandan, C., 2014. Compressive and tensile behavior of polymer treated sulfate contaminated CL soil. Geotechnical and Geological Engineering, 32 (1), 71–83. doi:10.1007/s10706-013-9692-9
   Google Scholar
• Neves, R.D. and De Almeida, J.F., 2005. Compressive behavior of steel fiber reinforced concrete. Structural Concrete, 6 (1), 1–8. doi:10.1680/stco.2005.6.1.1
   Google Scholar
• Ozgurel, H.G. and Vipulanandan, C., 2005. Effect of grain size and distribution on permeability and mechanical behavior of acrylamide grouted sand. Journal of Geotechnical and Geoenvironmental Engineering, 131 (12), 1457–1465. doi:10.1061/(ASCE)1090-0241(2005)131:12(1457)
   Web of Science ®Google Scholar
• Ryżak, M. and Bieganowski, A., 2011. Methodological aspects of determining soil particle‐size distribution using the laser diffraction method. Journal of Plant Nutrition and Soil Science, 174 (4), 624–633. doi:10.1002/jpln.v174.4
   Web of Science ®Google Scholar
• Schiffman, R.L. and Wilson, C.R., 1958. The mechanical behavior of chemically treated granular soils. Rensselaer Polytechnic Institute. Proc., American Society for Testing and Materials. West Conshohocken, Pa.: ASTM, Vol. 58, 1218–1244.
   Google Scholar
• Shiozawa, S. and Campbell, G.S., 1991. On the calculation of mean particle diameter and standard deviation from sand, silt, and clay fractions. Soil Science, 152 (6), 427–431. doi:10.1097/00010694-199112000-00004
   Web of Science ®Google Scholar
• Shirazi, M.A. and Boersma, L., 1984. A unifying quantitative analysis of soil texture. Soil Science Society of America Journal, 48 (1), 142–147. doi:10.2136/sssaj1984.03615995004800010026x
   Web of Science ®Google Scholar
• Slawinski, C., Walczak, R.T., and Skierucha, W., 2006. Error analysis of water conductivity coefficient measurement by instantaneous profiles method. International Agrophysics, 20 (1), 55.
   Google Scholar
• Thornley, J.H., 1990. A new formulation of the logistic Growth equation and its application to leaf area Growth. Annals of Botany, 66 (3), 309–311. doi:10.1093/oxfordjournals.aob.a088029
   Web of Science ®Google Scholar
• Vipulanandan, C. and Garas, V., 2008. Electrical resistivity, pulse velocity, and compressive properties of carbon fiber-reinforced cement mortar. Journal of Materials in Civil Engineering, 20 (2), 93–101. doi:10.1061/(ASCE)0899-1561(2008)20:2(93)
   Web of Science ®Google Scholar
• Vipulanandan, C. and Mohammed, A., 2015a. Smart cement modified with iron oxide nanoparticles to enhance the piezoresistive behavior and compressive strength for oil well applications. Smart Materials and Structures, 24 (12), 125020. doi:10.1088/0964-1726/24/12/125020
   Web of Science ®Google Scholar
• Vipulanandan, C. and Mohammed, A., 2015b. Smart cement rheological and piezoresistive behavior for oil well applications. Journal of Petroleum Science and Engineering, 135, 50–58. doi:10.1016/j.petrol.2015.08.015
   Web of Science ®Google Scholar
• Vipulanandan, C., and Mohammed, A., 2019. Magnetic field strength and temperature effects on the behavior of oil well cement slurry modified with iron oxide nanoparticles and quantified with vipulanandan models. Journal Of Testing and Evaluation, 48 (6).
   Web of Science ®Google Scholar
• Vipulanandan, C., Mohammed, A., and Ganpatye, A.S., 2018a. Smart cement performance enhancement with NanoAl2O3 for real time monitoring applications using Vipulanandan models. Offshore technology conference. Offshore technology conference.
   Google Scholar
• Vipulanandan, C., Mohammed, A., and Samuel, R. G. (2018, April). Fluid loss control in smart bentonite drilling mud modified with nanoclay and quantified with vipulanandan fluid loss model. In Offshore Technology Conference. Offshore Technology Conference, Houston, TX, USA.
   Google Scholar
• Vipulanandan, C., Mohammed, A., and Samuel, R.G., 2018b. Fluid loss control in smart bentonite drilling mud modified with nanoclay and quantified with Vipulanandan fluid loss model. Offshore technology conference. Offshore technology conference.
   Google Scholar
• Vipulanandan, C. and Mohammed, A.S., 2014. Hyperbolic rheological model with shear stress limit for acrylamide polymer modified bentonite drilling muds. Journal of Petroleum Science and Engineering, 122, 38–47. doi:10.1016/j.petrol.2014.08.004
   Web of Science ®Google Scholar
• Vipulanandan, C. and Ozgurel, H.G., 2009. Simplified relationships for particle-size distribution and permeation groutability limits for soils. Journal of Geotechnical and Geoenviromental Engineering, 135 (9), 1190–1197. doi:10.1061/(ASCE)GT.1943-5606.0000064
   Web of Science ®Google Scholar
• Vipulanandan, C. and Paul, E., 1990. Performance of epoxy and polyester polymer concrete. Materials Journal, 87 (3), 241–251.
   Google Scholar
• Weipeng, W., et al., 2015. Critical evaluation of particle size distribution models using soil data obtained with a laser diffraction method. Plot One, 10 (4), e0125048.
   Google Scholar
• Zhuang, J., Jin, Y., and Miyazaki, T., 2001. Estimating water retention characteristic from soil particle-size distribution using a non-similar media concept. Soil Science, 166 (5), 308–321. doi:10.1097/00010694-200105000-00002
   Web of Science ®Google Scholar