BEARING CAPACITY ANALYSIS OF SUBSOILS, FOR SHALLOW AND DEEP FOUNDATION IN UYO TOWN, EASTERN NIGER DELTA, NIGERIA
Journal: INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE TECHNOLOGIES (Vol.6, No. 4)Publication Date: 2022-07-05
Authors : Ehibor Imo-Owo. U Tse Akaha.C.;
Page : 20-35
Keywords : Bearing Capacity Analysis; Shallow Foundation; Deep Foundation; Bearing Capacity Maps; Geotechnical Maps;
Abstract
The Geotechnical properties of soils in Uyo town were analyzed to determine the bearing capacity and generate maps for shallow and deep foundation designs. Eleven geotechnical boreholes were drilled to a maximum depth of 20 meters each across Uyo town. Standard penetration tests and cone penetration tests were also carried out on the field. Soil samples were retrieved during the field investigation for various laboratory tests including liquid limits, plastic limit, bulk density, shear strength and particle size distribution. The general soil profile consists of silty clays, sandy clays, and sand from top to bottom. The silty clays are firm, low compressibility clays with liquid limit and plastic limit percentages between 32%-45% and 10%-45% respectively, cohesion averages of 4˚ to 12˚ and angles of internal friction between 48KN/m2-68KN/m2. Ultimate bearing capacities of this horizon range from 354.6kN/m2 to 866.7kN/m2. The sandy clays are also firm, low to intermediate plasticity clays with liquid limit and plasticity indexes of 29% - 42% and 9%-15% respectively. Their cohesion averages range between 50KN/m2-65KN/m2 and angles of internal friction between 6˚-12˚. The ultimate bearing capacities of this clay range from 482.5KN/m2 to 906.2KN/m2. The sand is a poorly graded, medium dense sand with standard penetration test N-values between 8 to 23. Pile bearing capacities of the sand gave ultimate and allowable bearing capacities between 10262.9KN-11510.2KN and 4105.2KN-4604.1KN respectively. The sand substratum is a suitable termination depth for piles.
Other Latest Articles
- BITCOIN PRICE PREDICTION WITH COVID-19 SENTIMENT USING LSTM NEURAL NETWORK
- STOCK PRICE PREDICTION USING SUPPORT VECTOR REGRESSION AND KNEAREST NEIGHBORS: A COMPARISON
- THE USE OF GEOGRAPHIC INFORMATION SYSTEMS IN PREVENTING ILLEGAL EXCAVATIONS FOR THE DESTRUCTION OF CULTURAL HERITAGE
- SPACIO-TEMPORAL DYNAMIC OF THE VEGETATION AND DEGRADATION FACTORS OF THE VEGETATION COVER AROUND LAGDO LAKE, NORTH CAMEROON
- FREEGANISM IN CONSUMPTION SOCIETY: A NETNOGRAPHIC RESEARCH STUDY
Last modified: 2022-09-03 14:12:49