Chief expert in statistical applications, Research & Materials Division,
Harry Oppenheimer Professor of Engineering, Haifa,
(Received 24 November 1997; accepted 18 September 1998)
Reliable analysis and interpretation of the results obtained under testing in pavement design and evaluation require consideration of the nature of the values under study, including construction of the probabilistic model that describes their statistical behavior. The investigation has been focused on the testing data peculiarities related to the dynamic cone penetrometer (DCP), which has become one of the extensively used testing devices in pavement evaluation. Application of the probabilistic models containing the stochastic components in pavement design and evaluation is determined by the nature of the pavement component characteristics, including subgrade soils, formed under the influence of various factors. The probability distribution model for the DCP values has been described based on the analysis of the statistical peculiarities of the observed data. The model reflects the main features and physical essence of the DCP values. Some differences in statistical conclusions based on the models under study have been demonstrated. Models can be recommended that have a positive influence on studying relationships between the DCP characteristics and various pavement design parameters and increase the reliability of estimates and solutions in pavement structure evaluation.
Paper ID: JTE12035J