Systemic Modeling of Soil Structure Dynamics for Civil Engineering Works in Calabar South

Systemic Modeling of Soil Structure Dynamics for Civil Engineering Works in Calabar South

The remarkable complexity of soil and its importance to a wide range of civil engineering works presents major challenges to the modeling of soil processes. Several attempts have been made in systematic modeling of soil processes that emerged with advances in analog and digital computers in the 20th century, there has been great progress across a broad range of space and time scales (pores to catchments and seconds to decades). Yet, our current understanding of the complexity of soil processes and the ability to observe these processes at ever-increasing resolution point to significant gaps in representing this critical compartment of the soil suitability for engineering purposes. The growing importance of soil in a host of topics and its central role in a range of civil engineering works, climate, food security, and other global terrestrial processes make quantification and modeling of soil processes an urgent challenge for the soil mechanics, geotechnical engineers, and soil scientist. We focused on identifying various key challenges in modeling soil application of the Multi-Linear Regression Analysis (MLRA) model for predicting soil properties in Calabar South which offers a technical guide and solution in foundation design problems in the area. Forty-five soil samples were collected from fifteen different boreholes at a different depth and 270 tests were carried out for CBR, MC, SG, LL, PL test and GS with mechanical sieve analysis of sizes, 2.36 mm, 1.18 mm, 600 μ, 425 μ, 300μ, 212μ, 150μ, and 75μ. This study uses Multi Linear Regression Analysis to formulate a model that relates CBR to other soil parameters. The Multi Linear Regression Analysis was developed which gave a good coefficient of correlation R2, 0.9454 benchmarking that the model is stable to predict CBR at 50.9% and with ±3.4% error. This conclusion is drawn since the value of R2 increases with an increase in the numbers of variables [1]

Author(s) Details

J. G. Egbe
Department of Civil Engineering, Cross River University of Technology, Calabar, Nigeria.

Dr. D. E. Ewa
Department of Civil Engineering, Cross River University of Technology, Calabar, Nigeria.

S. E. Ubi
Department of Civil Engineering, Cross River University of Technology, Calabar, Nigeria.

G. B. Ikwa
Department of Civil Engineering, Cross River University of Technology, Calabar, Nigeria.

View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/176

Editor 251News

Related Posts

leave a comment

Create Account



Log In Your Account