No abstract

This paper presents the quantification of uncertainties in the prediction of settlements of embankments built on prefabricated vertical drains (PVDs) improved soft soil deposits based on data collected from two well-documented projects, located in Karakore, Ethiopia, and Ballina, Australia. For this purpose, settlement prediction biases and settlement distributions were statistically computed based on analyses conducted on two Class A and Class C numerical predictions made using PLAXIS 2D finite element modelling. From the results of prediction bias, Class C predictions agreed well with the field measured settlements at both sites. In Class C predictions, the computed settlements were biased to the measured values. For Class A predictions, the calculated settlement values were in the range of mean and mean minus 3SD (standard deviations) for Karakore clay, and they were within mean and mean minus 2SD limit for the Ballina soil. The contributing factors to the settlement uncertainties of the Karakore site may include variability within the soil profile of the alluvial deposit, particularly the presence of interbedded granular layer within the soft layers, and the high embankment fills, and the limited number of samples available for laboratory testing. At the Ballina test embankment site, the uncertainties may have been associated with the presence of transitional layers at the bottom of estuarine clay and sensitivity of soft soil to sample disturbances and limitations in representing all the site conditions.

This study aims at evaluating deterministic and probabilistic approaches for an analysis of the bearing capacity of a highway bridge foundation on undrained clay soil. The analysis of a rectangular concrete footing was presented for the ultimate strength limit state of the bearing resistance according to the formulation in ES EN 1991:2015 and ERA-Bridge Design Manual, which are the Ethiopian design codes for foundation structures. In the deterministic analysis, the traditional total safety factor method recommended by the ES EN 1991:2015, ERA and AASHTO LRFD method was implemented. It was assumed that design variables such as the soil parameters and loads would follow normal and lognormal distribution functions. With regard to the probabilistic methods, NESSUS-9.8 software, a statistical computer program, was used for the analysis. Comparisons were made between the results obtained from the traditional deterministic method and the reliability-based design approach. The evaluation asserts that the probabilistic approach is a better tool than the deterministic one for assessing the safety and reliability of geotechnical structures. The probabilistic design method rationally accounts for uncertainties more than the conventional deterministic method does. Thus, the author recommends that the National Design Codes of Ethiopia need to be revised and calibrated based on a reliability design format.

Subgrade strength of soils is usually evaluated using California Bearing Ratio (CBR) values. As the cost and time required to conduct CBR test are high, dynamic cone penetrometer (DCP) would be recommended and CBR value can be estimated later from DCP result using a correlation formula. In this paper, laboratory CBR of Jimma fine-grained soils has been correlated with field DCP values referring to the physical properties such as natural moisture content and field density; as these factors significantly influence the behaviour of subgrade soils. Different techniques were used to demonstrate relations that best suit to find values of CBR from DCP test. Equations were developed between CBR and dynamic cone penetrometer index (DCPI) for the total of 36 sample points and adjusted coefficient of determination becomes 0.84. A validation was also done to test the applicability of the developed correlation formula for the local soils with the given physical conditions. The correlation gave a promising relationship between CBR and DCP and can be applicable for preliminary design purpose with the due consideration of the locality circumstances.