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For many foundation Engineering problems, such as the carrying capacity of shallow
foundations and piles, lateral Earth pressure on retaining walls, and the stability of dam and
embankment slopes, the shear strength of the soils is a crucial element. Due to a lack of
resources and limited time to get soil engineering parameters, geotechnical engineers
frequently work to create statistical models that are tailored to a certain place and soil type, especially for analysis and design purposes. The study aims to predict undrained shear
strength from the Index Properties of soils found in Bonga town by statistical analysis using
statically packaged software for social science (SPSS V.27). The methodology used for this
thesis included field identification, sampling, laboratory tests, preliminary analysis of data
using scatterplot, develop model, and evaluation of model adequacy by checking the
assumption and hypothesis test for regression coef icient. The design of the study is an
experimental study that requires laboratory tests conducted on 35 representative samples by
purposive sampling technique. Using the results obtained from laboratory tests, linear, quadratic, exponential, power, and cubic regression were performed, and the fit model was
selected based on the coef icient of determination, model significance, and fulfillment of the
assumption of regression. For all test procedures, the American Society for Testing &
Material (ASTM) standard was used. For the study area the laboratory test result of natural
moisture content (NMC), liquid limit(LL), plastic limit(PL), unit weight of soil, and specific
gravity value range from 34.04 % to 52.34 %, 56.5-92.7%, 30.92-50.79%, 15.94-19.01, 2.64
to 2.80 respectively. The undrained shear strength of the study area ranges from 48.58kPa to
106.2kPa. Correlation and regression analysis shows that undrained shear strength was
significantly correlated with natural moisture content, liquid limit, Plasticity index, and dry
unit weight, and not significantly correlated with specific gravity. From the study, the best
Model is obtained from multiple linear regression (MLR) analysis by logarithmic
transformation and given by: 𝑙� 𝐶 = 0.600209+0.092788Ɣd+0.003034PL; coef icient of
determination (R
2) =0.923, P-value <.001, Tolerance=0.847 and Variance inflation factors
(VIF) =1.18, Durbin Watson=1.555 with 96.2% of accuracy. The validation of the model was
confirmed using a control sample from the study area as well as from another area. Using the
developed model, the undrained shear strength parameter can be figured as well and it is
expected to have wide application in the construction to minimize the cost, ef ort, and time for
laboratory tests of the undrained shear strength of the study area. In light of the study
findings researcher recommends it is better to perform a database preparation of laboratory
test results from all parts of Ethiopian towns and perform a predictive model for engineering
properties of soil using advanced predictive modeling technique |
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