Characterization and utilization of noisy displacement signals from simple shear device using linear and kernel regression methods
✍ Scribed by Eric Yee; Jonathan P. Stewart; Frederic P. Schoenberg
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 713 KB
- Volume
- 31
- Category
- Article
- ISSN
- 0267-7261
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✦ Synopsis
Small strain testing of dynamic soil properties such as threshold strains, g 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 in the small strain range. We utilize 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 strain 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.