Jet Grout Yöntemi İle Zemin İyileştirme ve Deplasman Tahmini: Vaka Analizi

Yıl 2020, Sayı: 18, 290 - 299, 15.04.2020

Gizem Mısır

Öz

Konya ili Meram ilçesinde kohezif bir zemin üzerinde inşa edilecek bir yaşam kompleksi için Jet Grout yöntemi ile temel zemini güçlendirme çalışması yapılmıştır. İlgili sahada taşıma gücü ve oturma problemi nedeni ile 3351 adet 60 cm çapında ve 15 m uzunluğunda 1.6x1.6 m karelaj ile Jet Grout kolonları imal edilmiştir. Sahada süreklilik ve yükleme testleri yapılarak, imalatların kalite kontrolleri gerçekleştirilmiştir. Bu çalışmada, deplasman tahmini için rastgele seçilen 25 jet grout kolonu üzerinde gerçekleştirilen yükleme test sonuçları kullanılmıştır. Sonuç olarak, önerilen güçlendirme projesinin, emniyetli bir şekilde proje yükü altında sorunsuz olarak çalıştığı tespit edilmiştir. Arazi çalışmaları yanında, yükleme-boşaltma çevrimine uygun olarak meydana gelecek deplasmanların öngörülmesi de önem arz etmektedir. Zeminde meydana gelecek oturmaların tahmini ve değerlendirmesi, sınırlı miktardaki uygulanabilir veri nedeniyle inşaat mühendisliği uygulamalarında önemli sorunlardan biri olmaya devam etmektedir. Bu araştırmada, deplasman değerlerini irdelemek için Quasi-Newton eğitim algoritması tabanlı yapay sinir ağı önerilmiştir. YSA modelleri, gradyan bilgileri kullanılarak her bir yinelemede ters Hessianın yaklaşımı ile tasarlanmıştır. Jet grout uzunluğu, çapı ve uygulanan kuvvetler girdi parametresi olarak alınmıştır. Sonuçlar, önerilen algoritmanın özellikle incelenen zemin alanları için yer değiştirmeyi tahmin etmede etkili olduğunu göstermiştir.

Anahtar Kelimeler

Jet Grout Yöntemi, Arazi Kazık Yükleme Deneyi, Yapay Sinir Ağları, Zemin İyileştirme

Ground Improvement with Jet Grout Method and Displacement Prediction: A Case Study

Öz

Jet Grout application project has been carried out as a soil improvement technique for a living complex to be built on a cohesive soil in Meram district of Konya. Due to the bearing capacity and settlement problems in the related area, a total number of 3351 pieces of Jet Grout columns were implemented in a 1.6 x 1.6 m configuration with a diameter of 60 cm and a length of 15 m. At the site quality controls of the implementations were carried out by conducting integrity and in-situ loading tests. In this study, in-situ loading test results that has been obtained from 25 randomly selected jet grout columns been used to predict the displacements. According to the test results, it was determined that the proposed improvement project operates safely performance under the project load without any problems. In addition to the field studies, it is also important to predict displacements that will occur in accordance with the loading-unloading cycle. Displacement prediction and evaluation remains as one of the significant problems in the civil engineering applications due to very limited applicable data. In this research, Quasi-Newton training algorithm based artificial neural network was proposed for evaluating the displacement values. ANN models were designed with the approximation of the inverse Hessian at each iteration by using gradient information. Jet grout length, diameter and applied forces were taken as input parameters. The results showed that the proposed algorithm is efficient in predicting the displacement especially for the examined ground areas.

Anahtar Kelimeler

Jet Grout Method, In-Situ Pile Loading Test, Artificial Neural Networks, Soil Improvement

Kaynakça

• Akan R., Keskin S. N., & Uzundurukan S. (2015). Multiple Regression model for the prediction of unconfined compressive strength of jet grout columns. Procedia Earth and Planetary Science, Volume 15, Pages 299-303.
• Altun F., Kişi Ö., & Aydin K. (2008). Predicting the compressive strength of steel fiber added lightweight concrete using neural network. Comput Mater Sci. 42(2):259–65.
• Bayesteh, H., & Sabermahani, M. (2020). Field study on performance of jet grouting in low water content clay. Engineering Geology, 105314 Volume 264.
• Durgunoğlu H. T., Chinchelli M., Emrem C., & Hurley T. (2004). Soil ımprovement with jet-grout columns: a case study from the 1999 Kocaeli Earthquake. Fıfth Internatıonal Conference on Case Hıstorıes In Geotechnıcal Engıneerıng.
• Düzceer, R., & Gökalp, A. (2003). Construction and quality control of jet grouting applications in Turkey. Third International Conference on Grouting and Ground Treatment.
• Güllü H. (2017). A novel approach to prediction of rheological characteristics of jet grout cement mixtures via genetic expression programming. Neural Computing and Applications, Volume 28, 407–420.
• James C. Ni, & Wen-Chieh C. (2014). Quality control of double fluid jet grouting below groundwater table: Case history. Soils and Foundations Volume 54, Issue 6, December 2014, Pages 1039-1053.
• Lenard M. J., Alam P., & Madey G. R. (1995). The Application of Neural Networks and a qualitative response model to the auditor’s going concern uncertainty decision. Decis Sci. 26(2):209–27.
• Long S. S., Feng W. Z., Yang J. & Eu Ho C. (2013). Generalized approach for prediction of jet grout column diameter. Journal of Geotechnical and Geoenvironmental Engineering, Vol. 139, Issue 12.
• Paliwal M., & Kumar U. A. (2009). Neural networks and statistical techniques: A review of applications. Expert Syst Appl [Internet]. 36(1):2–17.
• Ripley B. D. (1994). Neural Networks and related methods for classification. R Stat Soc. 56(3):409–56.
• Shen, S L, Wang, Z F, & Cheng, W C (2017). Estimation of lateral displacement induced by jet grouting in clayey soils. Géotechnique, 67(7), 621–630.
• Smith A., Mason A. K. (1997). Cost estimation predictive modeling: Regression versus neural network. Eng Econ. 42(2):137–61.
• Wang, Z. F., Shen, S. L., Ho, C. E., & Kim, Y. H. (2013). Investigation of field-installation effects of horizontal twin-jet grouting in Shanghai soft soil deposits. Canadian Geotechnical Journal, 50(3), 288–297.
• Wong R. K. .N., Weng Y. F., Leong G. K. & Cheng S. H. (2020). A case study of effectiveness of large diameter jet grout for soil ımprovement works in soft marine clay. Geotechnics for Sustainable Infrastructure Development. Lecture Notes in Civil Engineering, vol 62. Springer, Singapore.
• Vu M. N. & Le Q. H. (2020). Large soil-cement column applications in Vietnam. Geotechnics for Sustainable Infrastructure Development. Lecture Notes in Civil Engineering, vol 62. Springer, Singapore