Prediction Model of Dynamic Resilient Modulus of Cohesive Subgrade Soil Based on Triaxial Test System

Qiu, Xin; Yang, Qing; Wang, Bing Ru; Luo, Xiao

doi:10.4028/www.scientific.net/kem.579-580.873

Cited by 3 publications

(3 citation statements)

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“…Authors of [16][17][18] conclude that the increase of the deviatoric stress results in the decrease of the resilient modulus. It must be noted that most of these researchers examined cohesive soils, and there are few results about non-cohesive soils that show the increase of the resilient modulus with increasing deviatoric stress [13].…”

Section: Test Results and Analysesmentioning

confidence: 99%

Evaluation of the Resilient Modulus of the Dunaújváros Loess Soil According to the MEPDG

2022

Teh. vjesn.

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The resilient modulus (MR) of the earthworks is a basic input parameter of the new alternative design method of pavement structures. Its value depends on the stress state and the properties of the soil. In the literature several models are available that are based on directly measured results, thus they make possible to determine the value of the resilient modulus in case of different stress levels. Thanks to these models, the resilient modulus could be determined on stress levels that are not possible to make direct measurement on. It enables also to choose a correct MR value even if the expected stress state changes during the design procedure. The most widely applied model is the universal model recommended by the Mechanistic-Empirical Pavement Design Guide that can be fitted to a certain soil by regression coefficients. Several researches were conducted to determine these regression parameters to many types of soils, most of them produced the coefficients as simple numbers. However, some literature recreates the regression parameters as functions of basic soil properties, making a more complex attempt to fit the model to a given soil type. In this paper the parameters of the MEPDG model were examined and fitted to a typical soil type: the loess soil origins from Dunaújváros in Hungary. Equations were established to determine the regression coefficients as function of more simple parameters the determination of which requires simpler and less costly tests than that of the direct cyclic triaxial resilient modulus measurements.

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Section: Test Results and Analysesmentioning

confidence: 99%

Evaluation of the Resilient Modulus of the Dunaújváros Loess Soil According to the MEPDG

2022

Teh. vjesn.

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“…Xinjiang, China ML 8 Xinjiang, China ML 9 QIU et al [40] Guangdong, China CL 96 10 NG et al [41] Hong Kong, China ML 24 11 HAN and VANAPALLI [42] Indian Head, Canada CL 156 12…”

Section: Table 1 Source and Classification Of Soil Samplesmentioning

confidence: 99%

Prediction of resilient modulus for subgrade soils based on ANN approach

Zhang

Peng

et al. 2021

J. Cent. South Univ.

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：The resilient modulus (MR) of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design. In order to determine the resilient modulus of compacted subgrade soils quickly and accurately, an optimized artificial neural network (ANN) approach based on the multi-population genetic algorithm (MPGA) was proposed in this study. The MPGA overcomes the problems of the traditional ANN such as low efficiency, local optimum and over-fitting. The developed optimized ANN method consists of ten input variables, twenty-one hidden neurons, and one output variable. The physical properties (liquid limit, plastic limit, plasticity index, 0.075mm passing percentage, maximum dry density, optimum moisture content), state variables (degree of compaction, moisture content) and stress variables (confining pressure, deviatoric stress) of subgrade soils were selected as input variables. The MR was directly used as the output variable. Then, adopting a large amount of experimental data from existing literature, the developed optimized ANN method was compared with the existing representative estimation methods. The results show that the developed optimized ANN method has the advantages of fast speed, strong generalization ability and good accuracy in MR estimation.

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“…In this context, static design methods will not be able to meet the increasing requirements of subgrade and pavement materials for strength and deformation. Therefore, more attention should be paid to dynamic and creep characteristics [1][2][3][4][5][6][7][8]. Soils and rocks are natural subgrade and pavement materials in the flood plain.…”

Section: Introductionmentioning

confidence: 99%

Resilient Modulus—Physical Parameters Relationship of Improved Red Clay by Dynamic Tri-Axial Test

Yuan

Wang

et al. 2019

Applied Sciences

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As one of the important parameters used in the analysis and design of subgrade, resilient modulus is directly related to the safety, economic and life time of subgrade structure. In this paper, the characteristics of resilient modulus of improved red clay at different additive content were studied through conducting laboratory repeated load tri-axial tests. The influence of stress state, moisture content, compactness, additive types, and content on resilient modulus were analyzed. In addition, the regression analysis of resilient modulus, was carried out referencing three existing prediction models. The results showed that the Andrei model can better fit the resilient modulus of red clay and have a higher determination coefficient. However, the Andrei model and other existing prediction models, reflect only the influence of stress state on resilient modulus, without considering the influence of moisture content, compactness and additive content. Therefore, based on the Andrei model, a comprehensive prediction model, which can reflect the influence of compactness, moisture content, additive content, and stress state on resilient modulus was introduced. Good agreement between the regression results and the measured ones demonstrated the integrative ability of the introduced model.

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Prediction Model of Dynamic Resilient Modulus of Cohesive Subgrade Soil Based on Triaxial Test System

Cited by 3 publications

References 0 publications

Evaluation of the Resilient Modulus of the Dunaújváros Loess Soil According to the MEPDG

Evaluation of the Resilient Modulus of the Dunaújváros Loess Soil According to the MEPDG

Prediction of resilient modulus for subgrade soils based on ANN approach

Resilient Modulus—Physical Parameters Relationship of Improved Red Clay by Dynamic Tri-Axial Test

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