Search published articles


Showing 2 results for Circular Footing

S. N. Moghaddas Tafreshi, Gh. Tavakoli Mehrjardi, M. Ahmadi,
Volume 9, Issue 4 (12-2011)
Abstract

The results of laboratory model tests and numerical analysis on circular footings supported on sand bed under incremental

cyclic loads are presented. The incremental values of intensity of cyclic loads (loading, unloading and reloading) were applied

on the footing to evaluate the response of footing and also to obtain the value of elastic rebound of the footing corresponding

to each cycle of load. The effect of sand relative density of 42%, 62%, and 72% and different circular footing area of 25, 50,

and 100cm2 were investigated on the value of coefficient of elastic uniform compression of sand (CEUC). The results show that

the value of coefficient of elastic uniform compression of sand was increased by increasing the sand relative density while with

increase the footing area the value of coefficient of elastic uniform compression of sand was decreases. The responses of footing

and the quantitative variations of CEUC with footing area and soil relative density obtained from experimental results show a

good consistency with the obtained numerical result using “FLAC-3D”.


H. Shahnazari, M. A. Shahin, M. A. Tutunchian,
Volume 12, Issue 1 (1-2014)
Abstract

Due to the heterogeneous nature of granular soils and the involvement of many effective parameters in the geotechnical behavior of soil-foundation systems, the accurate prediction of shallow foundation settlements on cohesionless soils is a complex engineering problem. In this study, three new evolutionary-based techniques, including evolutionary polynomial regression (EPR), classical genetic programming (GP), and gene expression programming (GEP), are utilized to obtain more accurate predictive settlement models. The models are developed using a large databank of standard penetration test (SPT)-based case histories. The values obtained from the new models are compared with those of the most precise models that have been previously proposed by researchers. The results show that the new EPR and GP-based models are able to predict the foundation settlement on cohesionless soils under the described conditions with R2 values higher than 87%. The artificial neural networks (ANNs) and genetic programming (GP)-based models obtained from the literature, have R2 values of about 85% and 83%, respectively which are higher than 80% for the GEP-based model. A subsequent comprehensive parametric study is further carried out to evaluate the sensitivity of the foundation settlement to the effective input parameters. The comparison results prove that the new EPR and GP-based models are the most accurate models. In this study, the feasibility of the EPR, GP and GEP approaches in finding solutions for highly nonlinear problems such as settlement of shallow foundations on granular soils is also clearly illustrated. The developed models are quite simple and straightforward and can be used reliably for routine design practice.

Page 1 from 1     

© 2020 All Rights Reserved | International Journal of Civil Engineering

Designed & Developed by : Yektaweb