Araştırma Makalesi
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Konsol Palplanş Duvarların Gömme Derinliklerinin Lineer Regresyon Analizi ile Tahmini

Yıl 2021, Sayı: 28, 1336 - 1341, 30.11.2021
https://doi.org/10.31590/ejosat.1015292

Öz

Palplanş duvarlar geoteknik mühendisliği uygulamalarında, özellikle kazı sonucunda meydana gelen yanal toprak basınçlarını karşılamak için yaygın olarak kullanılan istinat yapılarıdır. Konsol palplanş duvarların tasarımında gerekli gömme derinliğinin (D) ve palplanş kesitine etkiyecek maksimum eğilme momentinin(Mmax) hesaplanması gereklidir. İnşaat mühendisliği uygulamalarında, gömme derinliğinin (D) belirlenebilmesi için yanal toprak basınçlarının belirlenmesi ve üçüncü dereceden bir denklem çözülmesi gerekmektedir. Bu çalışma kapsamında, konsol palplanş duvarlarda gömme derinliğinin tahmini için ifade elde edilmiştir. Çoklu regresyon analizi ile elde edilen ifade ile gömme derinliğinin başarılı şekilde tahmin edilebildiği görülmüştür.

Kaynakça

  • Akbay, Z., Dalyan, İ., Akın, M. S., & Gençdal, H. B. (2020). An Application of TBEC-2018 in the Prediction of Retaining Wall Dimensions with Simple Regression Analysis. Global Journal in Civil Engineering, 2(2).
  • Bolton, M. D., Powrie, W., & Symons, I. F. (1989). The design of stiff in-situ walls retaining over consolidated clay-Part I: short-term behaviour. Ground Engineering, 22(8), 44–47.
  • Bolton, M. D., Powrie, W., & Symons, I. F. (1990a). The design of stiff in-situ walls retaining over consolidated clay-Part II: long-term behaviour (continued). Ground Engineering, 23(2), 22–28.
  • Bolton, M. D., Powrie, W., & Symons, I. F. (1990b). The design of stiff in-situ walls retaining over consolidated clay-Part II: short-term behaviour (continued). Ground Engineering, 22(9), 34–40.
  • Bransby, J. E., & Milligan, G. W. E. (1975). Soil Deformations near Cantilever Retaining Walls. Geotechnique, 24(2), 175–195.
  • Chantana, J., Kawano, Y., Kamei, A., & Minemoto, T. (2019). Description of degradation of output performance for photovoltaic modules by multiple regression analysis based on environmental factors. Optik, 179, 1063–1070. https://doi.org/10.1016/J.IJLEO.2018.11.040
  • Choi, M., & Lee, G. (2010). Decision tree for selecting retaining wall systems based on logistic regression analysis. Automation in Construction, 19(7), 917–928. https://doi.org/10.1016/J.AUTCON.2010.06.005
  • Choudry, D., Singh, S., & Goel, S. (2006). New approach for analysis of cantilever sheet pile with line load. Journal of Geotechnical and Geoenvironmental Engineering, 43(5), 540–549.
  • Coduto, D. P. (2001). Foundation Design: Principles and Practices. Prentice Hall.
  • Dagdeviren, U., & Kaymak, B. (2020). A regression-based approach for estimating preliminary dimensioning of reinforced concrete cantilever retaining walls. Structural and Multidisciplinary Optimization, 61(4), 1657–1675. https://doi.org/10.1007/s00158-019-02470-w
  • Das, B. M. (2007). Principles of Foundation Engineering, 6th Edition. Brooks/Cole Publishing Company.
  • Das, B. M. (2014). Principles of Foundation Engineering. Cengage Learning.
  • Gajan, S. (2011). Normalized Relationships for Depth of Embedment of Sheet Pile Walls and Soldier Pile Walls in Cohesionless Soils. Soils and Foundations, 51(3), 559–564. https://doi.org/10.3208/SANDF.51.559
  • Hagerty, D. J., & Nofal, M. M. (1992). Design aids-anchored bulkheads in sand. Canadian Geotechnical Journal, 29(5), 789–795.
  • Olmschenk, G., Zhu, Z., & Tang, H. (2019). Generalizing semi-supervised generative adversarial networks to regression using feature contrasting. Computer Vision and Image Understanding, 186, 1–12. https://doi.org/10.1016/J.CVIU.2019.06.004
  • Polat, Ö. (2015). A robust regression based classifier with determination of optimal feature set. Journal of Applied Research and Technology. JART, 13(4), 443–446. https://doi.org/10.1016/J.JART.2015.08.001
  • Powrie, W. (1997). Soil Mechanics: Concepts and Applications. E and FN Spon, An imprint of Chapman and Hall.
  • Rankine, W. J. (1857). II. On the stability of loose earth. Philosophical Transactions of the Royal Society of London, 147, 9–27.
  • Rowe, P. W. (1952). Anchored Sheet-pile walls. Proceedings of the Institution of Civil Engineers, 1(1), 27–70. https://doi.org/10.1680/iicep.1952.10942
  • Rowe, P. W. (1951). Cantilever sheet piling in cohesionless soil. Engineering, 316–319.
  • Sato-Ilic, M. (2017). Knowledge-based Comparable Predicted Values in Regression Analysis. Procedia Computer Science, 114, 216–223. https://doi.org/10.1016/J.PROCS.2017.09.063
  • Sitharam, T. G. (2013). Advanced Foundation Engineering. Indian Institute of Science.
  • Srivastava, A., & Malhotra, M. (2016). Earth Pressure behind a Retaining Wall under Linearly Varying Geotechnical Parameters. Indian Journal of Science and Technology, 9(Special Issue 1), 1–8. https://doi.org/10.17485/IJST/2016/V9IS1/105809
  • Zhang, J., & Thomas, L. C. (2012). Comparisons of linear regression and survival analysis using single and mixture distributions approaches in modelling LGD. International Journal of Forecasting, 28(1), 204–215. https://doi.org/10.1016/J.IJFORECAST.2010.06.002

The Prediction of Embedment Depth of Cantilever Sheet Piles Using Linear Regression Analysis

Yıl 2021, Sayı: 28, 1336 - 1341, 30.11.2021
https://doi.org/10.31590/ejosat.1015292

Öz

Sheet pile walls are commonly used retaining structures in geotechnical engineering applications, especially to meet the lateral earth pressures that occur as a result of excavation. In the design of cantilever sheet pile walls, it is necessary to calculate the required embedment depth (D) and the maximum bending moment (Mmax) that will affect the sheet pile section. In civil engineering applications, lateral earth pressures must be determined and a third-order equation must be solved in order to determine the embedment depth (D). Within the scope of this study, an expression for the estimation of embedment depth in cantilever sheet pile walls was obtained. It has been seen that the embedding depth can be successfully estimated with the expression obtained by multiple regression analysis.

Kaynakça

  • Akbay, Z., Dalyan, İ., Akın, M. S., & Gençdal, H. B. (2020). An Application of TBEC-2018 in the Prediction of Retaining Wall Dimensions with Simple Regression Analysis. Global Journal in Civil Engineering, 2(2).
  • Bolton, M. D., Powrie, W., & Symons, I. F. (1989). The design of stiff in-situ walls retaining over consolidated clay-Part I: short-term behaviour. Ground Engineering, 22(8), 44–47.
  • Bolton, M. D., Powrie, W., & Symons, I. F. (1990a). The design of stiff in-situ walls retaining over consolidated clay-Part II: long-term behaviour (continued). Ground Engineering, 23(2), 22–28.
  • Bolton, M. D., Powrie, W., & Symons, I. F. (1990b). The design of stiff in-situ walls retaining over consolidated clay-Part II: short-term behaviour (continued). Ground Engineering, 22(9), 34–40.
  • Bransby, J. E., & Milligan, G. W. E. (1975). Soil Deformations near Cantilever Retaining Walls. Geotechnique, 24(2), 175–195.
  • Chantana, J., Kawano, Y., Kamei, A., & Minemoto, T. (2019). Description of degradation of output performance for photovoltaic modules by multiple regression analysis based on environmental factors. Optik, 179, 1063–1070. https://doi.org/10.1016/J.IJLEO.2018.11.040
  • Choi, M., & Lee, G. (2010). Decision tree for selecting retaining wall systems based on logistic regression analysis. Automation in Construction, 19(7), 917–928. https://doi.org/10.1016/J.AUTCON.2010.06.005
  • Choudry, D., Singh, S., & Goel, S. (2006). New approach for analysis of cantilever sheet pile with line load. Journal of Geotechnical and Geoenvironmental Engineering, 43(5), 540–549.
  • Coduto, D. P. (2001). Foundation Design: Principles and Practices. Prentice Hall.
  • Dagdeviren, U., & Kaymak, B. (2020). A regression-based approach for estimating preliminary dimensioning of reinforced concrete cantilever retaining walls. Structural and Multidisciplinary Optimization, 61(4), 1657–1675. https://doi.org/10.1007/s00158-019-02470-w
  • Das, B. M. (2007). Principles of Foundation Engineering, 6th Edition. Brooks/Cole Publishing Company.
  • Das, B. M. (2014). Principles of Foundation Engineering. Cengage Learning.
  • Gajan, S. (2011). Normalized Relationships for Depth of Embedment of Sheet Pile Walls and Soldier Pile Walls in Cohesionless Soils. Soils and Foundations, 51(3), 559–564. https://doi.org/10.3208/SANDF.51.559
  • Hagerty, D. J., & Nofal, M. M. (1992). Design aids-anchored bulkheads in sand. Canadian Geotechnical Journal, 29(5), 789–795.
  • Olmschenk, G., Zhu, Z., & Tang, H. (2019). Generalizing semi-supervised generative adversarial networks to regression using feature contrasting. Computer Vision and Image Understanding, 186, 1–12. https://doi.org/10.1016/J.CVIU.2019.06.004
  • Polat, Ö. (2015). A robust regression based classifier with determination of optimal feature set. Journal of Applied Research and Technology. JART, 13(4), 443–446. https://doi.org/10.1016/J.JART.2015.08.001
  • Powrie, W. (1997). Soil Mechanics: Concepts and Applications. E and FN Spon, An imprint of Chapman and Hall.
  • Rankine, W. J. (1857). II. On the stability of loose earth. Philosophical Transactions of the Royal Society of London, 147, 9–27.
  • Rowe, P. W. (1952). Anchored Sheet-pile walls. Proceedings of the Institution of Civil Engineers, 1(1), 27–70. https://doi.org/10.1680/iicep.1952.10942
  • Rowe, P. W. (1951). Cantilever sheet piling in cohesionless soil. Engineering, 316–319.
  • Sato-Ilic, M. (2017). Knowledge-based Comparable Predicted Values in Regression Analysis. Procedia Computer Science, 114, 216–223. https://doi.org/10.1016/J.PROCS.2017.09.063
  • Sitharam, T. G. (2013). Advanced Foundation Engineering. Indian Institute of Science.
  • Srivastava, A., & Malhotra, M. (2016). Earth Pressure behind a Retaining Wall under Linearly Varying Geotechnical Parameters. Indian Journal of Science and Technology, 9(Special Issue 1), 1–8. https://doi.org/10.17485/IJST/2016/V9IS1/105809
  • Zhang, J., & Thomas, L. C. (2012). Comparisons of linear regression and survival analysis using single and mixture distributions approaches in modelling LGD. International Journal of Forecasting, 28(1), 204–215. https://doi.org/10.1016/J.IJFORECAST.2010.06.002
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Recep Akan 0000-0002-9277-1659

Yayımlanma Tarihi 30 Kasım 2021
Yayımlandığı Sayı Yıl 2021 Sayı: 28

Kaynak Göster

APA Akan, R. (2021). Konsol Palplanş Duvarların Gömme Derinliklerinin Lineer Regresyon Analizi ile Tahmini. Avrupa Bilim Ve Teknoloji Dergisi(28), 1336-1341. https://doi.org/10.31590/ejosat.1015292