Modeling of unconfined compressive strength of soil-RAP blend stabilized with Portland cement using multivariate adaptive regression spline

doi:10.1007/s11709-019-0516-8

Front. Struct. Civ. Eng.

2019, Vol. 13

Issue (4) : 787-799 https://doi.org/10.1007/s11709-019-0516-8

RESEARCH ARTICLE

Modeling of unconfined compressive strength of soil-RAP blend stabilized with Portland cement using multivariate adaptive regression spline

Ali Reza GHANIZADEH¹(

), Morteza RAHROVAN²

¹. Department of Civil Engineering, Sirjan University of Technology, Sirjan 78137-33385, Iran
². Department of Civil Engineering, Yazd University, Yazd 89195-741, Iran

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Abstract

The recycled layer in full-depth reclamation (FDR) method is a mixture of coarse aggregates and reclaimed asphalt pavement (RAP) which is stabilized by a stabilizer agent. For design and quality control of the final product in FDR method, the unconfined compressive strength of stabilized material should be known. This paper aims to develop a mathematical model for predicting the unconfined compressive strength (UCS) of soil-RAP blend stabilized with Portland cement based on multivariate adaptive regression spline (MARS). To this end, two different aggregate materials were mixed with different percentages of RAP and then stabilized by different percentages of Portland cement. For training and testing of MARS model, total of 64 experimental UCS data were employed. Predictors or independent variables in the developed model are percentage of RAP, percentage of cement, optimum moisture content, percent passing of #200 sieve, and curing time. The results demonstrate that MARS has a great ability for prediction of the UCS in case of soil-RAP blend stabilized with Portland cement (R² is more than 0.97). Sensitivity analysis of the proposed model showed that the cement, optimum moisture content, and percent passing of #200 sieve are the most influential parameters on the UCS of FDR layer.

Keywords full-depth reclamation soil-reclaimed asphalt pavement blend Portland cement unconfined compressive strength multivariate adaptive regression spline

Corresponding Author(s): Ali Reza GHANIZADEH

Just Accepted Date: 07 March 2019 Online First Date: 09 May 2019 Issue Date: 10 July 2019

Cite this article:

Ali Reza GHANIZADEH,Morteza RAHROVAN. Modeling of unconfined compressive strength of soil-RAP blend stabilized with Portland cement using multivariate adaptive regression spline[J]. Front. Struct. Civ. Eng., 2019, 13(4): 787-799.

URL:

https://academic.hep.com.cn/fsce/EN/10.1007/s11709-019-0516-8
https://academic.hep.com.cn/fsce/EN/Y2019/V13/I4/787

Fig.1 General flowchart of the present research

Tab.1 Soil material characteristics for first (SP-SC) and second (GW-GC) soil samples

Tab.2 Characteristics of base and subbase according to IHAP

Fig.2 Grain size distribution curve for first (SP-SC) and second (GW-GC) soil samples

Fig.3 Wirtgen recycler WR 2500

Fig.4 Grain size distribution for RAP material

Tab.3 Characteristics of Portland cement type II

Tab.4 Results of measured UCS for stabilized samples using SP-SC soil

Tab.5 Results of measured UCS for stabilized samples using GW-GC soil

Tab.6 Statistical parameters of training and testing datasets

Tab.7 Performance measures of MARS method

Fig.5 MARS predicted UCS against measured UCS. (a) Training data; (b) testing data

Fig.6 Degree of importance of different parameters on the UCS using CAM

Fig.7 Effect of measured error of input parameters on the MAPE of predicted UCS

Fig.8 Parametric study of UCS against OMC

Fig.9 Parametric study of UCS against RAP content

Fig.10 Parametric study of UCS against curing time

Fig.11 Parametric study of UCS against percent passing through No. 200 sieve

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