Use of sand pore-size distribution to predict cement suspension groutability

The investigation reported herein aims toward the development of novel, easy-to-use models based on the pore-size distributions of sands for the groutability prediction of cement suspensions in permeation grouting projects for soil improvement. The models were determined using 367 groutability measurements obtained in this research effort by conducting injection tests into 54 sands with different gradations. The documentation of model performance was based on a large database comprising the results of 604 injection tests conducted by other researchers with ordinary and microfine cement suspensions. Suspension groutability is improved by increasing sand characteristic pore size and suspension water/cement ratio and decreasing cement characteristic grain size and suspension apparent viscosity. The proposed models developed using the Binary Logistic Regression method, exhibit coefficients of multiple determination approximately equal or greater than 0.80 and estimate successfully the outcome of the injection tests collected from other studies at rates ranging from 70% to 76%. [Display omitted] •Groutability prediction models were developed based on sand pore-size distributions.•Sand characteristic pore sizes were obtained by applying four different methods.•Binary Logistic Regression models exhibiting R2 ≥ 0.8 are presented.•Best models estimate successfully the test results of other studies at a rate of 70–76%.•Proposed models can be easily put into practice in a permeation grouting project.