An application of a fuzzy classification routine suggested for fine grained soils

Abstract

Soil classification is an important stage in preliminary studies for design applications in engineering geology. A few letters or numbers assigned to a soil provide rapidly an idea to engineers. The classification of fine grained soils in national and international soil classification systems is determined using plasticity chart. However, because of the factors affecting liquid and plastic limit tests, uncertainties can arise in classification of fine-grained soils when this approach is used. Furthermore, uncertainty level has increased in case points fall sometimes on the lines or near the lines. In this study, an application of a fuzzy classification routine which was suggested before to minimize these uncertainties was performed. In the suggested method, the spatial distances of the evaluation points on the chart from the lines were considered. The membership degrees that define the fuzzified soil and plasticity were determined by using sigmoid function. Finally, fuzzy soil classes were obtained by using fuzzy operators. The suggested fuzzy classification routine, was performed on classification of 100 fine-grained soil samples ad obtained fuzzy soil classes were compared with crisp soil classes.

Keywords

• Soil classification,Plasticity chart,Uncertainties,Fuzzy set theory

İnce taneli zeminler için önerilen bulanık sınıflama sürecinin bir uygulaması

Öz

Mühendislik jeolojisinde tasarıma yönelik ön çalışmalarda zeminlerin sınıflandırılması önemli bir aşamadır. Bir zemine atanabilecek birkaç harf ya da sayı uygulayıcı mühendislere çok hızlı olarak bir fikir sağlamaktadır. Ulusal ve uluslararası zemin sınıflama sistemlerinde ince taneli zeminlerin sınıflandırılması plastisite abağı ile yapılmaktadır. Ancak, likit limit ve plastik limit deneylerini etkileyen bazı faktörlere bağlı olarak zemin sınıfının plastisite abağı ile belirlenmesi sırasında belirsizlikler oluşmaktadır. Ayrıca, tanımlama noktalarının kimi zaman sınıfları ayıran çizgiler üzerine veya yakınına düşmesi durumunda belirsizlik seviyesi artmaktadır. Bu çalışmada söz konusu belirsizlikleri en aza indirmek için daha önce geliştirilen bir bulanık sınıflama sürecinin uygulaması yapılmıştır. Söz konusu bulanık sınıflama sürecinde plastisite abağındaki tanımlama noktalarının sınırları ayıran çizgilere olan dik mekansal mesafeleri dikkate alınmıştır. Sigmoid fonk siyonu kullanılarak tanımlama noktalarının bulanık plastisite ve bulanık zemin değerleri hesaplanmıştır. Son olarak bulanık işlemciler yardımı ile bulanık zemin sınıfları elde edilmiştir. Önerilen bulanık sınıflama süreci 100 adet laboratuvar verisi üzerinde uygulanmış ve elde edilen bulanık zemin sınıfları klasik zemin sınıfları ile karşılaştırılmıştır.

Anahtar Kelimeler

• Zemin sınıflaması,Plastisite abağı,Belirsizlikler,Bulanık küme kuramı

Kaynakça

1. The American Association of State Highway Transportation Officials (AASHTO) M-145-91, “Classification of soils and soil-aggregate mixtures for highway construction purposes”. Washington, DC, 2008.
2. British Standard (BS) 5930. “Code of practice for site investigation”. British Standarts Institution, London, 1981.
3. German Institute for Standardization (DIN) 18196. “Soil Classification for Civil Engineering Purposes”. Berlin, Germany, 1988.
4. American Society for Testing and Materials (ASTM) D2487-06. “Standard Practice for Classification of Soils for Engineering Purposes (Unified Soil Classification System)”. West Conshohocken, PA, 2006.
5. Holtz RD, Kovacs WD. An Introduction to Geotechnical Engineering. Prentice Hall, New Jersey, USA, 1981.
6. Genç D. Zemin Mekaniği ve Temeller. 1. Baskı, Jeoloji Mühendisleri Odası Yayını, Yayın No: 100, Ankara, Türkiye, 2008.
7. Atterberg A. “Die plastizität der tone”. Internationale Mitteilungen für Bodenkunde, 1, 10-43, 1911.
8. ASTM D2487-11, “Standard Practice for Classification of Soils for Engineering Purposes (Unified Soil Classification System)”. ASTM International, West Conshohocken, PA, 2011.

9. Casagrande A. “Classification and identification of soils”. Trans ASCE, 133, 901-992, 1948.
10. ASTM D4318-10e1, “Standard Test Methods for Liquid Limit, Plastic Limit, and Plasticity Index of Soils”. ASTM International, West Conshohocken, PA, 2010.
11. BSI, “British Standard Methods of Test for Soils for Civil Engineering Purposes”. British Standards Institution, London, 1990.
12. Lee LT. “Freeman RB. An alternative test method for assessing consistency limits”. Geotechnical Testing Journal, 30(4), 1-8, 2007.
13. Sivakumar V, Glynn D, Cairns, P, Black JA. “A new method of measuring plastic limit of fine materials”. Géotechnique. 59(10), 813-823, 2009.
14. Haigh SK. “Mechanics of the Casagrande liquid limit test”. Canadian Geotechnical Journal, 49(9), 1015-1023, 2012.
15. Toksoz D, Yilmaz I, Hefeslioglu HA, Marschalko M. “A fuzzy classification routine for fine grained soils”. Quarterly Journal of Engineering Geology and Hydrogeology, 49(4), 344-349, 2016.
16. Zadeh LA. “Fuzzy sets”. Information and Control, 8, 338-353, 1965.
17. Alvarez Grima M. Neuro-Fuzzy Modelling in Engineering Geology. A.A. Balkema, Rotterdam, Netherlands, 244 p. 2000.
18. Provenzano P. “A fuzzy-neural network method for modeling uncertainties in soil-structure interaction problems”. Computer-Aided Civil and Infrastructure Engineering, 18, 391-411, 2003.
19. Mishra DA, Basu A. “Estimation of uniaxial compressive strength of rock materials by index tests using regression analysis and fuzzy inference system”. Engineering Geology, 160, 54-68, 2013.
20. Gong W, Wang L, Khoshnevisan S, Juang CH, Huang H, Zhang J. “Robust geotechnical design of earth slopes using fuzzy sets”. Journal of Geotechnical and Geoenvironmental Engineering, 141(1), 1-9, 2014.
21. Sezer EA, Nefeslioglu HA, Gokceoglu C. “An assessment on producing synthetic samples by fuzzy C-means for limited number of data in prediction models”. Applied Soft Computing, 24, 126-134, 2014.
22. Sai Samanth A. “Fuzzy theory application for analysis and assessment of slope stability”. The 29th International Conference of The Jangjeon Mathematical Society on Number Theory and Special Functions and its Applications, Pondicherry University, Pondicherry, India, 8-10 August 2016.
23. Mutlu B, Sezer EA, Nefeslioglu HA. “A defuzzification-free hierarchical fuzzy system (DF-HFS): Rock mass rating prediction”. Fuzzy Sets and Systems, 307, 50-66, 2017.
24. Zhang Z, Tumay MT. “Statistical to fuzzy approach toward CPT soil classification”. ASCE Journal of Geotechnical and Geoenviromental Engineering, 125(3), 179-186, 1999.
25. Odhiambo LO, Freeland RS, Yoder RE, Hines JW. “Investigation of a fuzzy-neural network application in classification of soils using ground penetrating radar imagery”. Applied Engineering in Agriculture, 20(1), 109-117, 2004.
26. Göktepe AB, Altun S, Sezer A. “Soil clustering by fuzzy c-means algorithm”. Advances in Engineering Software, 36(10), 691-698, 2005.
27. Kıyak A, Ergüven H, Karavul C. “Zemin sınıflamasında bulanık mantık uygulaması”. Uluslar Arası Deprem Sempozyumu, Kocaeli, Türkiye, 22-24 Ekim 2007.
28. Yıldırım E, Doğan E, Karavul C, Aşçı M, Özçep F, Arman H. “Bulanık mantık modeli ile zeminlerin sınıflandırılması”. Uluslar Arası Deprem Sempozyumu, Kocaeli, Türkiye, 22-24 Ekim 2007.
29. Bhargavi P, Jyothi S. “Soil classification by generating fuzzy rules”. International Journal on Computer Science and Engineering, 2(8), 2571-2576, 2010.
30. Han P, Wang J, Ma Z, Lu A, Gao M, Pan L. “Application of fuzzy clustering analysis in classification of soil in Qinghai and Heilongjiang in China. Computer and Computing Technologies in Agriculture IV, Nanchang, China, 282-289, 2010.
31. Riberio MV, Cunha LMS, Camargo HA, Rodrigues LHA. “Applying a fuzzy decision tree approach to soil classification”. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Cham, Springer-Verlag, France, 15-19 July 2014.
32. Sandhu HAS, Dubey OP. “Hydrological soil classification-A fuzzy approach”. International Journal of Research in Science and Technology, 6(2), 84-95, 2016.
33. Miloud SH, Djili K, Benidir M. “Fuzzy logic expert system for classifying solonchaks of Algeria”. Applied and Enviromental Soil Science, 2018, 1-11, 2018.
34. Şen Z. Bulanık Mantık İlkeleri ve Modelleme. 3. Baskı, Su Vakfı Yayınları, İstanbul, Türkiye 2009.
35. Negnevitsky M. Artifical İntelligence: A Guide to Intelligent Systems. Addison Wesley, London, 2002.
36. Detyniecki M. Fundamentals on Aggregation Operators. AGOP, Berkeley, 2001.