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Novel Performance Evaluation Approach and Prediction of Layer Moduli for Bio-enzymatic Treated Layers Using Light Weight Deflectometer

机译:Novel Performance Evaluation Approach and Prediction of Layer Moduli for Bio-enzymatic Treated Layers Using Light Weight Deflectometer

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摘要

This study aims to establish limiting layer moduli and develop correlations for predicting layer and stiffness moduli values based on the performance evaluation of bio-enzyme-treated flexible pavement sections. Nine bio-enzyme (TerraZyme-11X)-treated flexible pavements and two traditional test sections have been selected to compare and analyze the performance in terms of coefficient of variations (COVs). A series of in situ experimental investigations was performed on the selected test sections by using light weight deflectometer and other traditional tests to assess the functional and structural condition of the test sections. The pavement sections have been observed with low-medium severity structural failures and medium-high severity functional failures at few locations. The typical range of stiffness moduli value along with mean COV among all test sections for surface, bio-enzyme-treated subbase (T-2), and treated subgrade (T-1) layers are 153-598 MPa (32.2 %), 177-236 MPa (8 %), and 124-158 MPa (4.4 %). The back-calculated layer moduli (M-R_back) of bio-enzyme-treated layers varies from 141 to 2,458 MPa for the T-2 layer and 91 to 476 MPa for the T-1+natural subgrade layer based on the surface layer deflections at 68 test locations. The results of mechanistic-empirical analysis depict that the typical range of limiting layer moduli (M-RL) at different limiting percentile values for T-2 and T-1+natural subgrade layers among all the test sections are 200 to 1,991 MPa (87 to 100 %) and 97 to 225 MPa (98 to 100 %). The results of correlation analysis for predicting M-R(_back) and stiffness moduli values depict fair to good correlation with a coefficient of correlation value of 0.778-0.965 and 0.872. Thus, this unique COV, M(RL)( )based performance evaluation, and developed correlations at a discrete and aggregate level may be considered robust and reliable to establish such commercial stabilizers.

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