A NEW DESIGN EQUATION FOR PREDICTION OF ULTIMATE BEARING CAPACITY OF SHALLOW FOUNDATION ON GRANULAR SOILS
| Autor: | Amir H. Alavi, Seyyed Mohammad Mousavi, Fazlollah Soltani, Ehsan Sadrossadat, S. M. Marandi |
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| Rok vydání: | 2014 |
| Předmět: |
Shearing (physics)
Building construction Engineering business.industry Strategy and Management prediction Numerical models Structural engineering ultimate bearing capacity linear genetic programming Shallow foundation Soil water Linear genetic programming Geotechnical engineering granular soils Bearing capacity business TH1-9745 shallow foundations Civil and Structural Engineering |
| Zdroj: | Journal of Civil Engineering and Management; Vol 19 No 1 (2013): Supplement; S78-S90 Journal of Civil Engineering and Management, Vol 19, Iss 1 (2014) |
| ISSN: | 1822-3605 1392-3730 |
| DOI: | 10.3846/13923730.2013.801902 |
| Popis: | A major concern in design of structures is to provide precise estimations of ultimate bearing capacity of soil beneath their foundations. Direct determination of the bearing capacity of foundations requires performing expensive and time consuming laboratory tests. To cope with this issue, several numerical models have been presented by researchers. This paper presents the development of a new design equation for the prediction of the ultimate bearing capacity of shallow foundations on granular soils using linear genetic programming (LGP) methodology. The ultimate bearing capacity is formulated in terms of width of footing, footing geometry, depth of footing, unit weight of sand, and angle of shearing resistance. The LGP-based design equation is established using the results of several load tests on real sized foundations presented in the literature. Validity of the model is verified using a part of laboratory data that are not involved in the calibration process. The statistical measures of coefficient of determination, root mean squared error and mean absolute error are used to evaluate the performance of the model. Sensitivity and parametric analyses are conducted and discussed. The proposed model accurately characterizes the ultimate bearing capacity resulting in a very good prediction performance. The LGP model reaches a better prediction performance than the well-known prediction equations for the bearing capacity of shallow foundations. |
| Databáze: | OpenAIRE |
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