Abstract:
Compaction is a way of eliminating air out of the voids of a soil by mechanical means.
Compaction is mandatory in different fields of civil engineering such as in highway, airfield,
embankments, and dams; to reduce compressibility and permeability of a soil hence increases
the shear strength and bearing capacity of a soil. A laboratory tests called standard Proctor and
modified proctor tests were advanced to determine the maximum dry density and optimum
moisture content of a soil. In this study standard compaction is used.
However, in huge projects conducting laboratory tests by using proctor tests consume time,
money, a lot of effort or energy and required a large quantity of samples. An effort to make
correlation between compaction characteristics and Atterberg limits of fine grained soil found in
Addis Ababa which allows us to estimate the compaction parameters of fine grained soils from
Atterberg limits is done in this thesis.
To develop the correlation, a total 10 test pits have been excavated and a total of 20 disturbed
samples (primary data) were collected from different places, 2 samples from each test pits at
different depths ranging from 1.00m to 3.00m. And 36 secondary data (laboratory results) were
collected from AACRA. After the samples were collected, they were transported to Gondwana
engineering laboratory and different laboratory tests (Atterberg limits, grain size analysis,
specific gravity and compaction tests) has been conducted. After the tests were conducted, the
recorded data was analyzed using descriptive and analytical methods, and then correlation
between compaction characteristics and Atterberg limits of fine grained soil using regression
analysis has been done. Regression analysis was conducted by using EXCEL and SPSS software.
And from the statistical analysis part one can observe that there is a relatively good correlation
between OMC and PL and similarly a good correlation is observed between MDD and LL, PL
and PI together. The equations found are listed below.
1. OMC = 0.916 * PL - 0.030 * PI - 0.875, R
2 = 0.807
2. MDD = - 0.18* PL - 0.027 * PI + 21.182, R
2 = 0.835
