Using Response Surface Methodology to Assess the Performance of the Pervious Concrete Pavement

Soltani, Mojtaba; Moayedfar, Reza; Vun, Chong Vui

doi:10.1007/s42947-021-00149-4

Cited by 7 publications

(1 citation statement)

References 42 publications

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“…on the shear and uniaxial compression strengths of jointed rocks through RSM [24]. Soltani et al applied RSM to investigate the influence of cement content, water-cement ratio, and aggregate size on the compressive strength, permeability, and porosity of pavement concrete [25].…”

Section: Introductionmentioning

confidence: 99%

Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology

Zeng¹,

Zhang

Zhao

et al. 2023

Sensors

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The shear strength of granitic gneiss residual soil (GGRS) determines the stability of colluvial landslides in the Huanggang area, China. It depends on several parameters that represent its structure and state as well as their interactions, and therefore requires accurate assessment. For an effective evaluation of shear strength parameters of GGRS based on these factors and their interactions, three parameters, namely, moisture content, bulk density, and fractal dimension of grain size, were selected as influencing factors in this study based on a thorough investigation of the survey data and physical property tests of landslides in the study area. The individual effects and interaction of the factors were then incorporated by implementing a series of direct shear tests employing the response surface methodology (RSM) into the regression model of the shear parameters. The results indicate that the factors affecting shear parameters in the order of greater to lower are bulk density, moisture content, and fractal dimension, and their interactions are insignificant. The proposed model was validated by applying it to soil specimens from other landslide sites with the same parent bedrock, showing the validity of the strength regression model. This study demonstrates that RSM can be applied for parameter estimation of soils and provide reliable performance, and is also significant for conducting landslide investigation, evaluation, and regional risk assessment.

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Section: Introductionmentioning

confidence: 99%