Abstract
The continuous cone penetration test (CPT) measurements provide an advantageous liable rapid tool for stratification and soil behavior classification that can be employed in the sustainable design of the infrastructures. However, the CPT measurements are often interpreted by geotechnical experts because of the involved complexities and uncertainties. In this study, a novel stratification and soil type behavior (SBT) classification model is developed to identify the transition and thicker layers by integrating the geotechnical knowledge with the three submodels of (a) locally estimated scatterplot smoothing (LOESS), (b) a game theory model known as Nash–Harsanyi (N–H) bargaining, and (c) grey wolf optimizer (GWO). The LOESS and integrated N–H bargaining-GWO models are, respectively, used to approximate the outliers in CPT measurements and identify the SBT and layer changes. Attractively, in the proposed model, the engineer has the opportunity to judge on the precision of the stratification profile regarding their own preferences in a project. Solving simple algebraic equations, high speed, identifying thick and the interlayer transition layers, and small required training data are the other advantages of the developed model. Finally, the applicability of the proposed model has been assessed in an example. The compared estimated and two other models’ stratification profiles highlighted the potential of the proposed model to identify thin transition layers.
Highlights
A better knowledge of the subground state is beneficial in the sustainable design and development of the infrastructures’ foundations
The focus and novelty of the present study has been the developed model itself, after describing the model, the practicality of the model is verified based on training the model using only one Cone penetration test (CPT)-based stratification profile provided by experts and comparing the results with two other published stratification models for other three testing CPT soundings
As a Game Theory model, the Nash–Harsanyi (N–H) bargaining model has been employed in different fields, Fig. 2 Soil behavior type (SBT) chart based on CPT data, proposed by Robertson [45]
Summary
A better knowledge of the subground state is beneficial in the sustainable design and development of the infrastructures’ foundations. Wang et al [63] modelled the uncertainty in the CPT-based soil stratification and classification by means of the Bayesian approach and using the Robertson chart proposed in 1990 [45]. Integrating the Nash–Harsanyi (N–H) model, as a game theory model, grey wolf optimizer (GWO), as an optimization model, and Robertson soil classification chart (1990), a model is proposed to identify the transition and the thick layers in between, as well as their corresponding SBTs. the focus and novelty of the present study has been the developed model itself, after describing the model, the practicality of the model is verified based on training the model using only one CPT-based stratification profile provided by experts and comparing the results with two other published stratification models for other three testing CPT soundings
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