Effects Of The Soil Properties On The Maximum Dry Density Obtained Fro

In the construction of highways, airports, and other structures, the compaction of soils is needed to improve its strength. In 1933 Proctor developed a laboratory compaction test to determine the maximum dry density of compacted soils, which can be used for specifications of field compaction. The Compaction of soils is influenced by many factors, the most common are the moisture content, the soil type and the applied compaction energy. The objective of this research is the analysis of the maximum dry density values based on the soil classification and characterization. The method of choice in the determination of the maximum dry density from different soils was the Standard Proctor Test following the procedure for the standard Proctor test as is explained in ASTM Test Designation D-698. From this investigation, the maximum dry density of eight types of sands was obtained, the sands were classified by using the Unified Soil Classification System. The influence on the maximum dry density of the type of sands, type of fines, amount of fines and distribution of the grain size was determined, followed by a sensitivity analysis that measured the influence of these parameters on the obtained maximum dry density. The research revealed some correlations between the maximum dry density of soils with the type of fines, the fines content and the Uniformity Coefficient. These correlations were measured and some particular behavioral trends were encountered and analyzed. It was found that well-graded sands have higher maximum dry density than poorly graded when the soils have the same fines content, also it was encountered that plastic fines tend to increase the maximum dry density.

Author dc:creator

• Arvelo, Andres

Contributors dc:contributor

• Kuo, Shiou-san

• Proctor
• Compaction
• maximum dry density
• optimum moisture content
• ASTM Test Designation D-698
• Civil Engineering
• Engineering

Language dc:language

English

Identifier

CFE0000261

OAI identifier oai:identifier

oai:stars.library.ucf.edu:etd-1160