Characterization and Utilization of Noisy Displacement Signals from Simple Shear Device using Spectral, Linear, and Kernel Regression Methods

Small strain testing of dynamic soil properties such as threshold strains, tv , are often conducted using specialized devices such as dual-specimen simple-shear, as devices configured for large strain testing produce noisy signals in the small strain range. Working with a simple shear device originally developed for large-strain testing, we extend its low-strain capabilities by characterizing noisy signals and utilizing several statistical methods to extract meaningful responses. We utilize spectral analysis and linear regression of a transformed variable to estimate the cyclic shear strain from a noisy signal and the confidence interval on its amplitude. We utilize Kernel regression with the Nadaraya-Watson estimator and a Gaussian kernel to evaluate vertical strains response. A practical utilization of these techniques is illustrated by evaluating threshold shear strains for volume change with a procedure that takes into account uncertainties in the measured shear and vertical strains.