A multi-attribute decision making approach of mix design based on experimental soil characterization
Amit K. BERA1, Tanmoy MUKHOPADHYAY2(), Ponnada J. MOHAN1, Tushar K. DEY3
1. Faculty of Science & Technology, The ICFAI University, Dehradun, India 2. College of Engineering, Swansea University, Swansea, UK 3. Department of Civil Engineering, National Institute of Technical Teachers’ Training and Research (NITTTR) Kolkata, India
The clay mineral composition is one of the major factors that governs the physical properties of silty sand subgrade. Therefore, a thorough knowledge of mineral composition is essential to predict the optimum engineering properties of the soil, which is generally characterized by different indices like maximum dry density (MDD), California bearing ratio (CBR), unconfined compressive strength (UCS) and free swelling index (FSI). In this article, a novel multi-attribute decision making (MADM) based approach of mix design has been proposed for silty sand – artificial clay mix to improve the characteristic strength of a soil subgrade. Experimental investigation has been carried out in this study to illustrate the proposed approach of selecting appropriate proportion for the soil mix to optimize all the above mentioned engineering properties simultaneously. The results show that a mix proportion containing approximately 90% silty sand plus 10% bentonite soil is the optimal combination in context to the present study. The proposed methodology for optimal decision making to choose appropriate combination of bentonite and silty sand is general in nature and therefore, it can be extended to other problems of selecting mineral compositions.
. [J]. Frontiers of Structural and Civil Engineering, 2018, 12(3): 361-371.
Amit K. BERA, Tanmoy MUKHOPADHYAY, Ponnada J. MOHAN, Tushar K. DEY. A multi-attribute decision making approach of mix design based on experimental soil characterization. Front. Struct. Civ. Eng., 2018, 12(3): 361-371.
Mir B A. Some studies on the effect of fly ash and lime on physical and mechanical properties of expansive clay. International Journal of Civil Engineering, 2015, 13: 203–212 https://doi.org/ijce.iust.ac.ir/article-1-1485-en.html
2
Wong L S. Formulation of an optimal mix design of stabilized peat columns with fly ash as a pozzolan. Arabian Journal for Science and Engineering, 2015, 40(4): 1015–1025 https://doi.org/10.1007/s13369-015-1576-2
3
Ogata N, Kosaki A, Ueda H, Asano H, Takao H. Execution techniques for high level radioactive waste disposal: IV design and manufacturing procedure of engineered barriers. Journal of Nuclear Fuel Cycle and Environment, 1999, 5(2): 103–121 https://doi.org/10.3327/jnuce.5.103
4
Komine H, Ogata N. Experimental study on swelling characteristics of sand-bentonite mixture for nuclear waste disposal. Soil and Foundation, 1999, 39(2): 83–97 https://doi.org/10.3208/sandf.39.2_83
Chapuis R P. Sand-bentonite liners: Predicting permeability from laboratory tests. Canadian Geotechnical Journal, 1990, 27(1): 47–57 https://doi.org/10.1139/t90-005
8
Chapuis R P. The 2000 R.M. Hardy lecture: Full-scale hydraulic performance of soil-bentonite and compacted clay liners. Canadian Geotechnical Journal, 2002, 39(2): 417–439 https://doi.org/10.1139/t01-092
9
Haug M D, Wong L C. Impact of molding water content on hydraulic conductivity of compacted sand-bentonite. Canadian Geotechnical Journal, 1992, 29(2): 253–262 https://doi.org/10.1139/t92-029
10
Kenney T C, Van Veen W A, Swallow M A, Sungaila M A. Hydraulic conductivity of compacted bentonite-sand mixtures. Canadian Geotechnical Journal, 1992, 29(3): 364–374 https://doi.org/10.1139/t92-042
11
Santucci de Magistris F, Silvestri F, Vinale F. Physical and mechanical properties of compacted silty sand with low bentonite fraction. Canadian Geotechnical Journal, 1998, 35(6): 909–925 https://doi.org/10.1139/t98-066
12
Abichou T, Benson C, Edil T. Network model for hydraulic conductivity of sand-bentonite mixtures. Canadian Geotechnical Journal, 2004, 4(4): 698–712 https://doi.org/10.1139/t04-016
13
Sivapullaiah P V, Sridharan A, Stalin V K. Hydraulic conductivity of bentonite-sand mixtures. Canadian Geotechnical Journal, 2000, 37(2): 406–413 https://doi.org/10.1139/t99-120
14
Kashir M, Yanful E K. Hydraulic conductivity of bentonite permeated with acid mine drainage. Canadian Geotechnical Journal, 2001, 38(5): 1034–1048 https://doi.org/10.1139/t01-027
15
Yoon K P, Hwang C L. Multiple Attribute Decision Making, An Introduction. London: Sage Publications, 1995
16
Kuo M S, Liang G S, Huang W C. Extensions of the multicriteria analysis with pairwise comparison under a fuzzy environment. International Journal of Approximate Reasoning, 2006, 43(3): 268–285 https://doi.org/10.1016/j.ijar.2006.04.006
17
Triantaphyllou E, Shu B, Sanchez S N, Ray T. Multi-criteria decision making: An operations research approach. Encyclopedia of electrical and electronics engineering, 1998, 15: 175–186
18
Savitha P K, Chandrasekar C. Trusted network selection using SAW and TOPSIS algorithms for heterogeneous wireless networks. International Journal of Computers and Applications, 2011, 26(8): 22–29 https://doi.org/10.5120/3125-4300
19
Asgharpour M J. Multiple Criteria Decision Making. 6th ed. Tehran: University of Tehran Press, 2008
20
Saaty T L. Decision making with the analytic hierarchy process. International Journal of Services Sciences, 2008, 1(1): 83–98 https://doi.org/10.1504/IJSSCI.2008.017590
21
Saaty T L. The Analytic Hierarchy Process. New York: McGraw-Hill, 1980
22
Grain size analysis. Bureau of Indian Standards, IS: 2720 (Part 4), 1985
23
Alther G R. The role of bentonite in soil sealing applications. Bulletin of the Association of Engineering Geologists, 1982, 19: 401–409 https://doi.org/10.2113/gseegeosci.xix.4.401
24
Determination of specific gravity fine grained soils. Bureau of Indian Standards, IS: 2720 (Part 3), 1980
25
Classification and identification of soils for general engineering purposes. Bureau of Indian Standards, IS: 1498, 1970
26
Determination of water content—dry density relation using light compaction. Bureau of Indian Standards, IS: 2720 (Part 7), 1983
27
Laboratory determination of CBR. Bureau of Indian Standards, IS: 2720 (Part 16), 1987
28
Determination of unconfined compressive strength. Bureau of Indian Standards, IS: 2720 (Part 10), 1991
29
Determination of free swell index of soils. Bureau of Indian Standards, IS: 2720 (Part 40), 1977
30
Hamdia K M, Lahmer T, Nguyen-Thoi T, Rabczuk T. Predicting the fracture toughness of PNCs: A stochastic approach based on ANN and ANFIS. Computational Materials Science, 2015a, 102: 304–313 https://doi.org/10.1016/j.commatsci.2015.02.045
31
Hamdia K M, Msekh M A, Silani M, Vu-Bac N, Zhuang X, Nguyen-Thoi T, Rabczuk T. Uncertainty quantification of the fracture properties of polymeric nanocomposites based on phase field modeling. Composite Structures, 2015b, 133: 1177–1190 https://doi.org/10.1016/j.compstruct.2015.08.051
32
Mahata A, Mukhopadhyay T, Adhikari S. A polynomial chaos expansion based molecular dynamics study for probabilistic strength analysis of nano-twinned copper. Materials Research Express, 2016, 3(3): 036501 https://doi.org/10.1088/2053-1591/3/3/036501
33
Mukhopadhyay T, Mahata A, Dey S, Adhikari S. Probabilistic analysis and design of HCP nanowires: An efficient surrogate based molecular dynamics simulation approach. Journal of Materials Science and Technology, 2016a, 32(12): 1345–1351 https://doi.org/10.1016/j.jmst.2016.07.019
34
Mukhopadhyay T, Adhikari S. Equivalent in-plane elastic properties of irregular honeycombs: An analytical approach. International Journal of Solids and Structures, 2016 b, 91: 169–184 https://doi.org/10.1016/j.ijsolstr.2015.12.006
35
Mukhopadhyay T, Naskar S, Dey S, Adhikari S. On quantifying the effect of noise in surrogate based stochastic free vibration analysis of laminated composite shallow shells. Composite Structures, 2016c, 140: 798–805 https://doi.org/10.1016/j.compstruct.2015.12.037
36
Mukhopadhyay T, Adhikari S. Free vibration analysis of sandwich panels with randomly irregular honeycomb core. Journal of Engineering Mechanics, 2016d, 142(11): 06016008 https://doi.org/10.1061/(ASCE)EM.1943-7889.0001153
37
Mukhopadhyay T, Adhikari S. Effective in-plane elastic properties of auxetic honeycombs with spatial irregularity. Mechanics of Materials, 2016e, 95: 204–222 https://doi.org/10.1016/j.mechmat.2016.01.009
Mukhopadhyay T, Adhikari S. Effective in-plane elastic moduli of quasi-random spatially irregular hexagonal lattices. International Journal of Engineering Science, 2017b, 119: 142–179 https://doi.org/10.1016/j.ijengsci.2017.06.004
40
Dey S, Mukhopadhyay T, Khodaparast H H, Kerfriden P, Adhikari S. Rotational and ply-level uncertainty in response of composite shallow conical shells. Composite Structures, 2015, 131: 594–605 https://doi.org/10.1016/j.compstruct.2015.06.011
41
Dey S, Mukhopadhyay T, Khodaparast H H, Adhikari S. Fuzzy uncertainty propagation in composites using Gram-Schmidt polynomial chaos expansion. Applied Mathematical Modelling, 2016a, 40(7–8): 4412–4428 https://doi.org/10.1016/j.apm.2015.11.038
42
Dey S, Mukhopadhyay T, Spickenheuer A, Adhikari S, Heinrich G. Bottom up surrogate based approach for stochastic frequency response analysis of laminated composite plates. Composite Structures, 2016b, 140: 712–727 https://doi.org/10.1016/j.compstruct.2016.01.039
43
Dey S, Mukhopadhyay T, Sahu S K, Adhikari S. Effect of cutout on stochastic natural frequency of composite curved panels. Composites. Part B, Engineering, 2016c, 105: 188–202 https://doi.org/10.1016/j.compositesb.2016.08.028
44
Dey S, Mukhopadhyay T, Spickenheuer A, Gohs U, Adhikari S. Uncertainty quantification in natural frequency of composite plates—An Artificial neural network based approach. Advanced Composites Letters, 2016d, 25(2): 43–48
45
Dey S, Naskar S, Mukhopadhyay T, Gohs U, Spickenheuer A, Bittrich L, Sriramula S, Adhikari S, Heinrich G. Uncertain natural frequency analysis of composite plates including effect of noise—A polynomial neural network approach. Composite Structures, 2016e, 143: 130–142 https://doi.org/10.1016/j.compstruct.2016.02.007
46
Dey S, Mukhopadhyay T, Adhikari S. Metamodel based high-fidelity stochastic analysis of composite laminates: A concise review with critical comparative assessment. Composite Structures, 2017a, 171: 227–250 https://doi.org/10.1016/j.compstruct.2017.01.061
47
Dey S, Mukhopadhyay T, Naskar S, Dey T K, Chalak H D, Adhikari S. Probabilistic characterization for dynamics and stability of laminated soft core sandwich plates. Journal of Sandwich Structures & Materials, 2016, doi: 10.1177/1099636217694229
48
Naskar S, Mukhopadhyay T, Sriramula S, Adhikari S. Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties. Composite Structures, 2017, 160: 312–334 https://doi.org/10.1016/j.compstruct.2016.10.035
49
Metya S, Mukhopadhyay T, Adhikari S, Bhattacharya G. System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines. Computers and Geotechnics, 2017, 87: 212–228 https://doi.org/10.1016/j.compgeo.2017.02.017
50
Dey S, Mukhopadhyay T, Sahu S K, Adhikari S. Stochastic dynamic stability analysis of composite curved panels subjected to non-uniform partial edge loading. European Journal of Mechanics/A Solids, 2018, 67: 108–122
51
Mukhopadhyay T, Adhikari S, Batou A. Frequency domain homogenization for the viscoelastic properties of spatially correlated quasi-periodic lattices. International Journal of Mechanical Sciences, 2017, in press. doi: 10.1016/j.ijmecsci.2017.09.004