Şıkıştırılmış Kil Zeminlerin Şişme Basıncının Belirlenmesinde Bulanık Mantık Yaklaşımı

Year 2024, , 422 - 432, 23.12.2024

Ömür Çimen , Nilay Keskin

https://doi.org/10.19113/sdufenbed.1508229

Abstract

Bu çalışmada kil zeminlerde önemli bir mühendislik problemi olan şişme basıncının belirlenmesinde bulanık mantık kuralları kullanılmıştır. Bu amaçla kilin şişme basıncını etkileyen parametrelerden olan plastisite indisi, başlangıç su muhtevası ve kuru birim hacim ağırlık değerleri dikkate alınmıştır. Öncelikle şişme basıncı ve etki eden parametreler bulanık alt kümelere ayrılmıştır. Bulanık kural tabanı oluşturulmuş ve Fortran dilinde programlanmıştır. Daha sonra şişme potansiyeli yüksek olan üç kil numunesi üzerinde sabit hacimli şişme deneyleri yapılmıştır. Şişme deneyleri için altı farklı başlangıç su muhtevası ve yedi farklı kuru birim hacim ağırlıkta numuneler kompaksiyonla hazırlanmıştır. Deneyden elde edilen şişme basıncı değerleri ile bulanık mantık modelinden elde edilen değerler karşılaştırılmıştır. Şişme basıncının 40 kPa ‘ın üzerinde olduğu durumlarda, bulanık mantık modelinden elde edilen şişme basınçları ile deneysel sonuçlar arasındaki maksimum hata miktarı %10 dolaylarındayken, daha düşük şişme basıncı değerlerinde maksimum hata miktarının %30 ‘un üzerine çıktığı görülmüştür. Şişme basıncı tahmininde ortalama hata miktarı ise %9.73 olarak elde edilmiştir.

Keywords

Kil zeminler, Şişme basıncı, Bulanık mantık

Fuzzy Logic Approach in Determining Swelling Pressure of Compacted Clay Soils

Abstract

In this study, fuzzy logic rules were used to determine the swelling pressure, which is an important engineering problem in clay soils. For this purpose, plasticity index, initial water content and dry unit volume weight values, which are among the parameters affecting the swelling pressure of clay, were taken into consideration. First of all, swelling pressure and affecting parameters are divided into fuzzy subsets. The fuzzy rule base was created and programmed in Fortran language. Then, constant volume swelling experiments were performed on three clay samples with high swelling potential. For swelling experiments, samples with six different initial water contents and seven different dry unit volume weights were prepared by compaction. The swelling pressure values obtained from the experiment were compared with the values obtained from the fuzzy logic model. In cases where the swelling pressure is above 40 kPa, the maximum error amount between the swelling pressures obtained from the fuzzy logic model and the experimental results is around 10%, while it has been observed that the maximum error amount exceeds 30% at lower swelling pressure values. The average amount of error in inflation pressure estimation was obtained as 9.73%.

Keywords

Clay soils, Swelling pressure, Fuzzy logic

References

• [1] Petry, T.M., Little, D.N. 2002. Review of Stabilization of Clays and Expansive Soils in Pavements and Lightly Loaded Structures—history, Practice, and Future, J. Mater. Civ. Eng., 14 (6), 447–460.
• [2] Bell, F.G. 2007. Engineering Geology, 2nd edition, Butterworth-Heinemann.
• [3] Al-Mukhtar, M., Khattab, S., Alcover, J.F. 2012. Microstructure and geotechnical properties of lime-treated expansive clayey soil, Eng. Geol., 139-140, 17–27.
• [4] Jamsawang, P., Abdulyamet, B., Voottipruex, P., Jongpradist, P., Likitlersuang, S., Tantayopin, K. 2023. The free swell potential of expansive clays stabilized with the shallow bottom ash mixing method, Engineering Geology, 315, 107027.
• [5] El-Sohby, M.A., Rabba, E.A. 1981. Some factors affecting swelling of clayey soils, Geotech. Engineering, 12, 19-39.
• [6] Nelson, J.D. and Miller, D.J. 1992. Expansive Soils Problem and Practice in Foundation and Pavement Engineering, John Wiley & Sons, 253 p.
• [7] Elsharief, A.M., Zumrawi, M.E., Salam, A.M. 2014. Experimental Study of Some Factors Affecting Swelling Pressure, University of Khartoum Engineering Journal, 4(2), 1-7.
• [8] Smaida, A., Mekerta, B., Gueddouda, M.K. 2021. Physico-mechanical stabilization of a high swelling clay, Construction and Building Materials, 289, 123197.
• [9] Chen, F.H. 1988. Foundations on Expansive Soil, American Elsevier Science Publ., New York, 280p.
• [10] Komine, H., Ogata, N. 1994. Experimental study on swelling characteristics of compacted bentonite, Can. Geotech. J., 31, 478-490.
• [11] Erol, O., Dhowian, A.W. 1990. Swell behaviour of arid climate shales from Saudi Arabia, Quaterly journal of Engr. Geology, 23, 243-254.
• [12] Basma, A.A. 1993. Prediction of Expansion Degree for Natural Compacted Clays, Geotech. Test. J., 16(6), 542–549.
• [13] Zadeh, L.A. 1965. Fuzzy Sets, Information and Control, 8, 338-353.
• [14] Juang C.H., Wey, J.L., Elton, D.J. 1991. Model for capacity of single piles in sand using Fuzzy sets, J. Geotechnical Engineering, 17(12), 1920-1931.
• [15] Juang, C.H., Lee, D.H., Sheu, C. 1992. Mapping slope failure potential using Fuzzy sets, J. Geotechnical Engineering, 118(3), 475-494.
• [16] Juang, C.H., Huang, X.H., Holtz, R.D., Chen J.W. 1996. Determination relative density of sands from CPT using Fuzzy sets, J. Geotechnical Engineering, 122(1), 1-6.
• [17] Nawari, N.O., Liang, R. 2000. Fuzzy-based approach for determination of characteristic values of measured geotechnical parameters, Can. Geotech. J., 37, 1131-1140.
• [18] Zhang, Z. and Tümay, M.T. 1999. Statistical to fuzzy aproach toward CPT soil clasification, J. Geotechnical and Geoenviromental Engineering, 125(3), 179-186.
• [19] Çimen, Ö., Keskin, S.N. 2001. Emme kapasitesinin zamana bağlı ilerleyişinin bulanık mantıkla belirlenmesi, Mühendislikte Modern Yöntemler Sempozyumu, İstanbul, 64-71.
• [20] Çimen, Ö. 2002. Killi Zeminlerin Şişme ve Emme Özelliklerinin Belirlenmesinde Bulanık Model (Fuzzy Logic) Yaklaşımı, Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Doktora Tezi, 175s.
• [21] Avci, Y., Ekmen, A.B. 2023. Artificial intelligence assisted optimization of rammed aggregate pier supported raft foundation systems based on parametric three-dimensional finite element analysis, Structures, 56, 105031.
• [22] Ekmen, A.B., Avci, Y. 2024. Development of novel artificial intelligence functions based on 3D finite element method using February 6 Kahramanmaraş Seismic Records for earthquake effects prediction in various soils, Engineering Geology, 336, 107570.
• [23] İkizler, B., Vekli, M., Doğan E., Aytekin, M., Kocabaş F. 2014, Prediction of swelling pressures of expansive soils using soft computing methods, Neural Comput. Applic., 24, 473-485.
• [24] Hu, H., Vanapalli, S.K. 2016. Prediction of the variation of swelling pressure and 1-D heave of expansive soils with respect to suction using the soil water retention curve as a tool, Can. Geotech. J., 53, 1–22.
• [25] Erzin, Y., Erol, O. 2007. Swell pressure prediction by suction methods, Engineering Geology, 92(3-4), 133-145.
• [26] Ikechukwu A.F., Mostafa, M.M.H, 2022. Swelling Pressure Prediction of Compacted Unsaturated Expansive Soils, International Journal of Engineering Research in Africa, 59,119-134.
• [27] Elbadry, H. 2017. Simplified reliable prediction method for determining the volume change of expansive soils based on simply physical tests, HBRC Journal, 13,353-360.
• [28] Agbelele, K.J., P’Kla, A., Houanou, K.A., Dara, K.S., Degan, G., Gbaguidi Aisse G. 2020. Estimation of the Swelling Pressure of the Clayey Soils of the TCHI Depression in Benin for the Good Holding of the Equipment’s, Journal of Scientific and Engineering Research, 7(4), 183-190.
• [29] Gokceoglu, C. 2021. A practical linguistic fuzzy inference system for indirect determination of swelling pressure of expansive soils, Academia Letters.
• [30] Hozatlıoğlu, D.T., Yılmaz, I. 2023. A Fuzzy Classification Process for Swelling Soils, 10, 474-487.
• [31] Çimen, Ö., Keskin S.N., Yıldırım, H. 2012. Prediction of Swelling Potential and Pressure in Compacted Clay, Arab J Sci Eng., 37, 1535–1546.
• [32] Taherdangkoo, R., Tyurin, V., Shehab, M., Ardejani, F.D., Tang, A.M., Narmandakh, D., Butscher, C. 2023. An efficient neural network model to determine maximum swelling pressure of clayey soils, Computers and Geotechnics, 162, 105693.
• [33] Jalal, F.E., Iqbal, M., Khan, W.A., Jamal, A., Onyelowe, K. 2024. ANN‑based swarm intelligence for predicting expansive soil swell pressure and compression strength, Scientific Reports, 14, 14597.
• [34] Aneke, F., Onyelowe, K.C., Ebid, A.M. 2024. AI-Based Estimation of Swelling Stress for Soils in South Africa, Transportation Infrastructure Geotechnology, 11, 1049-1072.
• [35] Sen, Z. 2001. Bulanik Mantik ve Modelleme İlkeleri, Publications of Water Foundation, Turkey (in Turkish).
• [36] ASTM D854, 2010. Standard Test Methods for Specific Gravity of Soil Solids by Water Pycnometer, ASTM, Pennsylvania.
• [37] ASTM D1140, 2017. Standard Test Methods for Determining the Amount of Material Finer than 75-μm (No. 200) Sieve in Soils by Washing, West Conshohocken, PA, A.B.D.
• [38] ASTM D422, 2014. Standard Test Method for Particle- Size Analysis of Soils, West Conshohocken, PA, A.B.D.
• [39] ASTM D4318, 2010. Standard Test Methods for Liquid Limit, Plastic Limit, and Plasticity Index of Soils, ASTM, Pennsylvania.
• [40] ASTM D698, 2007. Standard Test Methods for Laboratory Compaction Characteristics of Soil Using Standard Effort, ASTM, Pennsylvania.
• [41] ASTM D4546. Standard Test Methods for One-Dimensional Swell or Collapse of Soils, West Conshohocken, PA, A.B.D.