Geomechanics and Engineering

  • 제28권5호
  • /
  • Pages.505-520
  • /
  • 2022
  • /
  • 2005-307X(pISSN)
  • /
  • 2092-6219(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Shear behavior of geotextile-encased gravel columns in silty sand-Experimental and SVM modeling

  • Dinarvand, Reza (Department of Civil Engineering, Imam Khomeini International University) ;
  • Ardakani, Alireza (Department of Civil Engineering, Imam Khomeini International University)
  • 투고 : 2021.08.28
  • 심사 : 2022.01.21
  • 발행 : 2022.03.10
⟨ 이전 논문 다음 논문 ⟩

초록

In recent years, geotextile-encased gravel columns (usually called stone columns) have become a popular method to increasing soil shear strength, decreasing the settlement, acceleration of the rate of consolidation, reducing the liquefaction potential and increasing the bearing capacity of foundations. The behavior of improved loose base-soil with gravel columns under shear loading and the shear stress-horizontal displacement curves got from large scale direct shear test are of great importance in understanding the performance of this method. In the present study, by performing 36 large-scale direct shear tests on sandy base-soil with different fine-content of zero to 30% in both not improved and improved with gravel columns, the effect of the presence of gravel columns in the loose soils were investigated. The results were used to predict the shear stress-horizontal displacement curve of these samples using support vector machines (SVM). Variables such as the non-plastic fine content of base-soil (FC), the area replacement ratio of the gravel column (Arr), the geotextile encasement and the normal stress on the sample were effective factors in the shear stress-horizontal displacement curve of the samples. The training and testing data of the model showed higher power of SVM compared to multilayer perceptron (MLP) neural network in predicting shear stress-horizontal displacement curve. After ensuring the accuracy of the model evaluation, by introducing different samples to the model, the effect of different variables on the maximum shear stress of the samples was investigated. The results showed that by adding a gravel column and increasing the Arr, the friction angle (ϕ) and cohesion (c) of the samples increase. This increase is less in base-soil with more FC, and in a proportion of the same Arr, with increasing FC, internal friction angle and cohesion decreases.

키워드

참고문헌

  1. Abusharar, S.W. and Han, J. (2011), "Two-dimensional deep-seated slope stability analysis of embankments over stone column-improved soft clay", J. Eng. Geol., 120(1-4), 103-110. https://doi.org/10.1016/j.enggeo.2011.04.002.
  2. Adalier, K., Elgamal, A., Meneses, J. and Baez, J. (2003), "Stone columns as liquefaction countermeasure in non-plastic silty soils", Soil Dyn. Earthq. Eng., 23(7), 571-584. https://doi.org/10.1016/S0267-7261(03)00070-8.
  3. Aghili. E., Hosseinpour, I., Jamshidi, R. and Ahmadi, H. (2021), "Behavior of granular column-improved clay under cyclic shear loading", Transport Geotech., 31, https://doi.org/10.1016/j.trgeo.2021.100654.
  4. Aljanabi, Q.A., Chik, Z, Allawi, M.F., El-Shafie, A.H., Ahmed, A.N. and El-Shafie, A. (2017), "Support vector regression-based model for prediction of behavior Stone column parameters in soft clay under highway embankment", Neural Comput. Appl., https://doi.org/10.1007/s00521-016-2807-5.
  5. Alkayem. N.F., Cao, M., Zhang, Y., Bayat, M. and Su, Z. (2018), "Structural damage detection using finite element model updating with evolutionary algorithms: a survey", Neural Comput, Appl., 30(2), 389-411. https://doi.org/10.1007/s00521-017-3284-1.
  6. Alkhorshid, N.R., Araujo, L.S., Palmeira, E.M. and Zornberg, J.G. (2019), "Large-scale load capacity tests on a geosynthetic encased column", Geotext. Geomembranes., 47(5), 632-641. https://doi.org/10.1016/j.geotexmem.2019.103458.
  7. Andreou, P. and Papadopoulos, V. (2014), "Factors affecting the settlement estimation of Stone column reinforced soils", Geotech. Geol. Eng., 32, 1175-1185. https://doi.org/10.1007/s10706-014-9788-x.
  8. Ardakani, A., Gholampoor, N., Bayat, M. and Bayat, M. (2018), "Evaluation of monotonic and cyclic behavior of geotextile encased stone columns", Struct. Eng. Mech., 65(1), 81-89. https://doi.org/10.12989/sem.2018.65.1.081.
  9. Asgari, A., Oliaei, M. and Bagheri, M. (2013), "Numerical simulation of improvement of a liquefiable soil layer using Stone column and pile-pinning techniques", Soil Dyn. Earthq. Eng., 51, 77-96. https://doi.org/10.1016/j.soildyn.2013.04.006.
  10. Ashford, S.A., Rollins, K.M. and Baez, J.I. (2000), "Comparison of deep foundation performance in improved and non-improved ground using blast induced liquefaction", Proc., Geo-Denver 2000, Soil Dynamics and Liquefaction. ASCE Geotech. Special Publ., 23, 20-34.
  11. Barksdale, R.D. and Bachus, R.C. (1983), "Design and Construction of Stone Columns", Report FHWA.RD-83.026. National Information Service, Springfield, Virginia.
  12. Basack, S., Indraratna, B., Rujikiatkamjorn, C. and Siahaan. F. (207), "Modeling the Stone column behavior in soft ground with special emphasis on lateral deformation", J. Geotech. Geoenviron. Eng., 143(6), 04017016. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001652.
  13. Bergado, D.T., Singh, N., Sim, S.H., Panichayatum, B., Sampaco, C.L. and Balasubramaniam, A.S. (1990), "Improvement of soft Bangkok clay using vertical geotextile band drains compared with granular piles", Geotext. Geomembranes, 9(3), 203-231. https://doi.org/10.1016/0266-1144(90)90054-G.
  14. Cengiz, C. and Guler, E. (2018), "Seismic behavior of geosynthetic encased columns and ordinary stone columns" Geotext. Geomembranes, 46(1), 40-51. https://doi.org/10.1016/j.geotexmem.2017.10.001.
  15. Cengiz, C., Kilic, I.E. and Guler, E. (2019), "On the shear failure mode of granular column embaseded unit cells subjected to static and cyclic shear loads", Geotext. Geomembranes, 47(2), 193-202. https://doi.org/10.1016/j.geotexmem.2018.12.011.
  16. Chakraborty, A. and Goswami, D. (2017), "Prediction of slope stability using multiple linear regression (MLR) and artificial neural network (ANN)", Arab. J. Geosci., 10, 385. https://doi.org/10.1007/s12517-017-3167-x.
  17. Chen, J.F., Li, L.Y., Xue, J.F. and Feng, S.Z. (2015), "Failure mechanism of geosynthetic encased gravel columns in soft soils under embankment", Geotext. Geomembranes, 43(5), 424-431. https://doi.org/10.1016/j.geotexmem.2015.04.016.
  18. Chen, J.F., Li, L.Y., Zhang, Z., Zhang, X., Xu, C., Rajesh, S. and Feng, Z. S. (2020) "Centrifuge modeling of geosynthetic-encased stone column-supported embankment over soft clay" Geotext. Geomembranes, https://doi.org/10.1016/j.geotexmem.2020.10.021.
  19. Choobbasti, A.J. and Pichka, H. (2012). "Improvement of soft clay using installation of geosynthetic-encased stone columns: numerical study" Arab. J. Geosci., https://doi.org/10.1007/s12517-012-0735-y.
  20. Christoulas, S., Giannaros, C. and Tsiambaos, G. (1997), "Stabilization of embankment foundations by using stone columns", Geotech. Geolo. Eng., 15, 247-258. https://doi.org/10.1007/BF00880828.
  21. Dar, L.A. and Yousuf Shah, M. (2020), "Deep-seated slope stability analysis and development of simplistic FOS Evaluation models for stone column-supported embankments", T. Infrastruct. Geotechnology, https://doi.org/10.1007/s40515-020-00134-7.
  22. Das, A.K. and Deb, K. (2016), "Modeling of stone columnsupported embankment under axi-symmetric condition", Geotech. Geol. Eng., https://doi.org/10.1007/s10706-016-0136-1.
  23. Das, A.K. and Deb, K. (2019), "Response of stone column-improved ground under c-/ϕ soil embankment", Soils Found., 59, 617-632. https://doi.org/10.1016/j.sandf.2019.01.003.
  24. Das, A.K. and Deb, K. (2018), "Experimental and 3D numerical study on time dependent behavior of Stone column-supported embankments", Int. J. Geomech., ASCE., 18(4), 1-16. https://doi.org/10.1061/(ASCE)GM.1943-5622.0001110.
  25. Das, M. and Dey, A.K. (2017), "Determination of bearing capacity of stone column with application of neuro-fuzzy system", KSCE J. Civ. Eng., 1-7. https://doi.org/10.1007/s12205-017-1497-6.
  26. Das, M. and Dey, A.K. (2017), "Prediction of bearing capacity of stone columns placed in soft clay using ANN model", Geotech. Geol. Eng., https://doi.org/10.1007/s10706-017-0436-0.
  27. Das, M. and Dey, A.K. (2018), "Prediction of bearing capacity of stone columns placed in soft clay using SVR model", Arab. J. Sci. Eng., https://doi.org/10.1007/s13369-018-3513-7.
  28. Dash, S.K. and Bora, M.C. (2013), "Influence of geosynthetic encasement on the performance of gravel columns floating in soft clay", Can. Geotech. J., 50(7), 754-765. https://doi.org/10.1139/cgj-2012-0437.
  29. Deb, K. and Majee, A. (2014), "Probability-based design charts for stone column-improved ground", Geomech. Eng., 7(5), 539-552. https://doi.org/10.12989/gae.2014.7.5.539.
  30. Debnath, P. and Dey, A.K. (2018), "Prediction of bearing capacity of geogrid-reinforced stone columns using support vector regression", Int. J. Geomech., 18(2), 04017147. https://doi.org/10.1061/(ASCE)GM.1943-5622.0001067.
  31. Demir, A. and Sarici, T. (2017), "Bearing capacity of footing supported by geogrid encased stone columns on soft soil", Geomech. Eng., 12(3), 417-439. https://doi.org/10.12989/gae.2017.12.3.417.
  32. Dinavand, R. and Ardakani, A. (2019), "Behavior of geosyntheticencased granular column in silty sand soil by direct shear test", Amirkabir. J. Civ. Eng., 50(5), 961-972. https://doi.org/10.22060/ceej.2017.12979.5308.
  33. Emami, M. and Yasrebi, S. (2014), "Application of artificial neural networks in interpretation of pressuremeter test results", Modares. Civ. Eng. J., 14(20), 11-25. http://mcej.modares.ac.ir/article-16-5107-fa.html.
  34. Etezad, M., Hanna, A.M. and Ayadat, T. (2015), "Bearing capacity of a group of Stone columns in soft soil", Int. J. Geomech. ASCE., 15(2), https://doi.org/10.1061/(ASCE)GM.1943-5622.0000393.
  35. Fox, Z.P. (2011), "Critical State, Dilatancy and Particle Breakage of Mine Waste Rock", Master's thesis. Colorado State University, Fort Collins, USA.
  36. Garnier, J., Gaudin, C., Springman, S.M., Culligan, P.J., Goodings, D., Konig, D., Kutter, B., Phillips, R., Randolph, M.F. and Thorel, L. (2007), "Catalogue of scaling laws and similitude questions in geotechnical centrifuge modelling", Int. J. Phys. Model. Geotech., 7(3), 1-24. https://doi.org/10.1680/ijpmg.2007.070301.
  37. Gniel, J. and Bouazza, A. (2010), "Construction of geogrid encased Stone columns: a new proposal based on laboratory testing", Geotext. Geomembranes, 28(1), 108-118. https://doi.org/10.1016/j.geotexmem.2009.12.012.
  38. Hagan, M.T. and Menhaj, M.B. (1994), "Training feedforward networks with the marquartdt algorithm", IEEE T. Neural Networ., 5(6), 989-992. https://doi.org/10.1109/72.329697
  39. Han, J., Sheth, A.R., Porbaha, A. and Shen, S.L. (2004), "Numerical analysis of embankment stability over deep mixed foundations. Geotechnical Engineering for Transportation Projects", Proceedings of Geo-Trans 2004, 126 II. Geotechnical Special Publication, Los Angeles, CA, United States.
  40. He, S. and Li, J. (2008), "Modeling nonlinear elastic behavior of reinforced soil using artificial neural networks", Appl. Soft Comput., 9(3), 954-961. https://doi.org/10.1016/j.asoc.2008.11.013.
  41. Hong, Y.S., Wu, C.S. and Yu, S.Y. (2016), "Model tests on geotextile-encased granular columns under 1-g and undrained conditions" Geotext. Geomembranes, 44, 13-27. https://doi.org/10.1016/j.geotexmem.2015.06.006.
  42. Hong, Y.S., Wu, C.S., Kou, C.M. and Chang, C.H. (2017), "A numerical analysis of a fully penetrated encased granular column", Geotext. Geomembranes, 45(5), 391-405. https://doi.org/10.1016/j.geotexmem.2017.05.002.
  43. Hosseinpour, I., Riccio, M. and Almeida, M.S.S. (2014), "Numerical evolution of a granular column reinforced by geosynthetics using encasement and laminated disks", Geotext. Geomembranes, 42(4), 363-373. https://doi.org/10.1016/j.geotexmem.2014.06.002.
  44. Hughes, J.M.O., Withers, N.J. and Greenwood, D.A. (1975), "A field trial of the reinforcing effect of a granular column in soil", Geotechniq., 25(1), 31-44. https://doi.org/10.1680/geot.1975.25.1.31
  45. Karkush, M. and Jabba, A. (2019), "Improvement of soft soil using linear distributed floating stone column under foundation subjected to static and cyclic loading", Civ. Eng. J., 5(3), 702-711. https://doi.org/10.28991/cej-2019-03091280
  46. Khorshidi, N., Ansari, M. and Bayat, M. (2014), "An investigation of water magnetization and its influence on some concrete specificities like fluidity and compressive strength", Comput. Conceret, 13(5), 649-657. https://doi.org/10.12989/cac.2014.13.5.649.
  47. Lajevardi. S.H. and Enami. S. (2021), "Small scale behavior of stone columns encased by tires", Geomech. Eng., 25(5), 429-438. https://doi.org/10.12989/gae.2021.25.5.429.
  48. Lee, I.M. and Lee, J.H. (1996), "Prediction of pile bearing capacity using artificial neural networks", Comput. Geotech., 18(3), 189-200. https://doi.org/10.1016/0266-352X(95)00027-8.
  49. Li., L.Y., Rajesh, S. and Chen., J.F. (2020), "Centrifuge model tests on the deformation behavior of geosynthetic-encased stone column supported embankment under undrained condition", Geotext. Geomembranes, https://doi.org/10.1016/j.geotexmem.2020.11.003.
  50. Malarvizhi, S.N. and Ilamparuthi, K. (2007), "Comparative behaviour of encased stone column and conventional stone column", Soils Found., 47(5), 873-885. https://doi.org/10.3208/sandf.47.873.
  51. Malekpoor. M. and Poorebrahim. G. (2014), "Comparative study on the behavior of lime-soil columns and other types of stone columns", Geomech. Eng., 7(2), 133-148. https://doi.org/10.12989/gae.2014.7.2.133.
  52. Mashenwari, P. and Khatri, S. (2019), "Influence of inclusion of geosynthetic layer on response of combined footings on stone column reinforced earth beds", Geomech. Eng., 4(4), 263-279. https://doi.org/10.12989/gae.2012.4.4.263.
  53. Miranda, M. and Da Costa, A. (2016), "Laboratory analysis of encased stone columns", Geotext. Geomembranes, 44, 269-277. https://doi.org/10.1016/j.geotexmem.2015.12.001.
  54. Miranda, M., Da Costa, A., Castro, J. and Sagaseta, C. (2017), "Influence of geotextile encasement on the behaviour of stone columns: Laboratory study", Geotext. Geomembranes, 45, 14-22. https://doi.org/10.1016/j.geotexmem.2016.08.004.
  55. Mohanty, P. and Samanta M. (2015), "Experimental and numerical studies on response of the Stone column in layered soil", Int. J. Geosynth. Ground Eng., https://doi.org/10.1007/s40891-015-0029-z.
  56. Mohapatra, S.R., Rajagopal, K. and Sharma, J. (2016), "Direct shear tests on geosynthetic-encased granular columns", Geotext. Geomembranes, 44(3), 396-405. https://doi.org/10.1016/j.geotexmem.2016.01.002.
  57. Motalleb Nejad, M., Momeni, M.S. and Manahiloh, K.N. (2018), "Shear wave velocity and soil type microzonation using neural networks and geographic information system", Soil Dyn. Earthq. Eng., 104, 54-63. https://doi.org/10.1016/j.soildyn.2017.10.001.
  58. Murugesan, M. and Rajagopal, K. (2010), "Studies on the behaviour of single and group of geosynthetic encased stone columns", J. Geotech. Geoenviron. Eng., 136(1), 129-139. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000187.
  59. Murugesan, S. and Rajagopal, K. (2008), "Shear load tests on granular columns with and without geosynthetic encasement", Geotech. Test. J., 32(1), 35-44.
  60. Murugesan, S. and Rajagopal, K. (2010), "Studies on the behavior of single and group of geosynthetic encasemed granular columns", J. Geotec. Geoenviron. Eng., 136(1), 129-139. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000187.
  61. Naeini, S.A. and Gholampoor, N. (2014), "Cyclic behaviour of dry silty sand reinforced with a geotextile", Geotext. Geomembranes, 42(6), 611-619. https://doi.org/10.1016/j.geotexmem.2014.10.0
  62. Naeini, S.A. and Gholampoor, N. (2018), "Effect of geotextile encasement on the shear strength behavior of stone columntreated wet clays", Indian Geotech. J. https://doi.org/10.1007/s40098-018-0329-z.
  63. Najjar, Y.M. and Huang, C. (2007), "Simulating the stress-strain behavior of Georgia kaolin via recurrent neuronet approach", Comput. Geotech., 34(5), 346-361. https://doi.org/10.1016/j.compgeo.2007.06.006.
  64. Nasiri, M. and Hajiazizi, M. (2019), "An experimental and numerical investigation of reinforced slope using geotextile encased Stone column", Int. J. Geotech. Eng., https://doi.org/10.1080/19386362.2019.1651029.
  65. Pulko, B. and Logar, J. (2017), "Fully coupled solution for the consolidation of poroelastic soil around geosynthetic encased stone columns", Geotext. Geomembranes, 45(6), 616-626. https://doi.org/10.1016/j.geotexmem.2017.08.003.
  66. Rashidian, V. and Hassanlourad, M. (2013), "Predicting the shear behavior of cemented and uncemented carbonate sands using a genetic algorithm-based artificial neural network", Geotech. Geol. Eng., 2, 1-18. https://doi.org/10.1007/s10706-013-9646-2.
  67. Sadr, A., Kaliakin, V.N., Htaf. N. and Manahiloh, K.N. (2022), "Numerical study of soilbag columns and comparison to encased soil columns in loose sand", Comput. Geotech., 142, https://doi.org/10.1016/j.compgeo.2021.104588.
  68. Samui, P. (2013), "Liquefaction prediction using support vector machine model based on cone penetration data", Front Struct. Civ. Eng., 7(1), 72-82. https://doi.org/10.1007/s11709-013-0185-y.
  69. Shafigh, A., Ahmadi, H.R. and Bayat, M. (2014), "Seismic investigation of cyclic pushover method for regular reinforced concrete bridge", Struct. Eng. Mech., 78(1), 41-52 https://doi.org/10.12989/sem.2021.78.1.041.
  70. Shahin, M.A. (2010), "Intelligent computing for modeling axial capacity of pile foundations", Soil Dyn. Earthq. Eng., 47(2), 230-243. https://doi.org/10.1139/T09-094.
  71. Sitton, J.D., Zeinali, Y. and Zeinali, B.A. (2017), "Rapid soil classification using artificial neural networks for use in constructing compressed earth blocks", Constr. Build. Mater., 138, 214-221. https://doi.org/10.1016/j.conbuildmat.2017.02.006.
  72. Sivakumar, V., McKelvey, J., Graham, J. and Hughes, D. (2004), "Triaxial test on model sand columns in clay", Can. Geotech. J., 41(2), 299-312. https://doi.org/10.1139/t03-097.
  73. Smola, A.J. and Scholkopf, B. (2004), "A tutorial on support vector regression. Statistics and computing", Statist. Comput., 14(3), 199-222. https://doi.org/10.1023/B:STCO.0000035301.49549.88.
  74. Soltangharaei. V., Anay, R., Assi, L., Bayat, M., Rose, J.R., Ziehl. P. (2020), "Analyzing acoustic emission data to identify cracking modes in cement paste using an artificial neural network", Constr. Build. Mater., 267, https://doi.org/10.1016/j.conbuildmat.2020.121047.
  75. Stoeber, J.N. (2012), "Effects of Maximum Particle Size and Sample Scaling on the Mechanical Behavior of Mine Waste Rock; a Critical State Approach", Master's Thesis. Colorado State University, Fort Collins, USA.
  76. Tabchouche, S., Mellas, M. and Bouassida, M. (2017), "On settlement prediction of soft clay reinforced by a group of Stone columns", Innov. Infrastruct. Solut., 2(1), https://doi.org/10.1007/s41062-016-0049-0.
  77. Tang, L., Zhang, X. and Ling, X. (2015), "Numerical simulation of centrifuge experiments on liquefaction mitigation of silty soils using stone columns", KSCE J. Civ. Eng., 20(2), 631-638. https://doi.org/10.1007/s12205-015-0363-7.
  78. Tarawneh, B. (2017), "Predicting standard penetration test N-value from cone penetration test data using artificial neural networks", Geosci. Front., 8(1), 199-204. https://doi.org/10.1016/j.gsf.2016.02.003.
  79. Vapnik, V. N., Golowich, S.E. and Smola, A. (1996), "Support Vector Method for Function Approximation, Regression Estimation, and Signal Processing, Advances in Neural Information Processing Systems", Morgan Kaufmann, San Mateo.
  80. Wood, D.M., Dihoru, L., Sadek, T. and Lings. M. (2005), "A neural network for error prediction in a true triaxial apparatus with flexible boundaries", Comput. Geotech., 32(2), 59-71. https://doi.org/10.1016/j.compgeo.2005.01.003.
  81. Yoo, C. (2015), "Settlement behavior of embankment on geosynthetic-encased stone column installed soft ground. A numerical investigation", Geotext. Geomembranes, 43, 484-492. https://doi.org/10.1016/j.geotexmem.2015.07.014.
  82. Yoo, C. and Abbas, Q. (2020), "Laboratory investigation of the behavior of a geosynthetic encased Stone column in sand under cyclic loading", Geotext. Geomembranes, https://doi.org/10.1016/j.geotexmem.2020.02.002.
  83. Yoo, W., Kim, B. and Cho, W. (2014), "Model Test Study on the Behavior of Geotextile Encased Sand Pile in Soft Clay Ground" KSCE J. Civ. Eng., 19(3), 592-601. https://doi.org/10.1007/s12205-012-0473-4.
  84. Yu. Y., Wang. Z. and Sun. H.Y. (2020), "Optimal design of stone columns reinforced soft clay foundation considering design robustness", Geomech. Eng., 22(4), 305-318. https://doi.org/10.12989/gae.2020.22.4.305.
  85. Zhang, L. and Zhao, M. (2015), "Deformation analysis of geotextile-encased gravel columns", ASCE Int. J. Geomech., 15(3), 04014053. https://doi.org/10.1061/(ASCE)GM.1943-5622.0000389
  86. Zhang, L., Xu, Z. and Zhou, S. (2020), "Vertical cyclic loading response of geosynthetic-encased stone column in soft clay" Geotext. Geomembranes, https://doi.org/10.1016/j.geotexmem.2020.07.006.
  87. Zhang, Z., Han, J. and Ye, G. (2014), "Numerical investigation on factors for deep-seated slope stability of stone columnsupported embankments over soft clay", J. Eng. Geol., 168, 104-113. https://doi.org/10.1016/j.enggeo.2013.11.004.
  88. Zhou, Y. and Kong, G. (2019), "Deformation analysis of geosynthetic-encased stone column-supported embankment considering radial bulging", Int. J. Geomech., 19(6), 04019057. https://doi.org/10.1061/(ASCE)GM.1943-5622.0001426.
  89. Zhou, Y., Kong, G., Peng, H., Li, C., and Qin, H. (2019), "Visualization of bulging development of geosynthetic-encased stone column", Geomech. Eng. J., 18(3), 329-337 http://dx.doi.org/10.12989/gae.2019.18.3.329.