Improved implementation of travel time randomization for incorporating Vs uncertainty in seismic ground response

Accounting for uncertainty in shear wave velocity (Vs) profiles has been recognized to be critical to seismic ground response analysis (GRA) and probabilistic seismic hazard analysis (PSHA). Vs randomization models are among the most widely used approaches to account for this uncertainty, often referred to as aleatory variability within the context of PSHA. Researchers have investigated alternate ways of more realistically accounting for Vs uncertainty, such as randomizing the cumulative shear wave travel time (tts) instead of Vs directly. While some preliminary assessments suggest that tts randomization allows for better management of Vs uncertainty, more validations are needed to guide its use in practice. This study aims to fill a knowledge gap by performing a thorough review of the tts randomization framework and suggesting changes that will lead to improved implementation. Specifically, through the use of real experimental data and Monte Carlo simulations, we identify several issues which, if left unimproved, could lead to bias and unrealistic results. These issues particularly pertain to: (1) methods used for bounding simulated layers, (2) approaches for merging column and bedrock models, and (3) appropriate values of the lognormal standard deviation on tts (σlntts) and inter-layer correlation (ρ) for randomizing tts. For each issue, we devise recommendations and demonstrate that they provide a clear improvement on the current tts randomization framework. The revised steps put forward in this article do not require any additional model parameters, but rather, simply improve upon the existing methodology. The findings of this study enhance our understanding of the tts randomization framework, and the recommendations we provide will enable researchers and engineers to adopt it more robustly and confidently in engineering practice. ●A procedure for incorporating Vs uncertainty in seismic ground response is revisited and improved●The procedure is based on randomizing the cumulative shear wave travel time (tts), rather than absolute Vs●Real experimental data and Monte Carlo simulations are used to identify several issues with the current procedure which, if left unimproved, could lead to bias and unrealistic results●For each issue, we devise recommendations and demonstrate that they provide a clear improvement on the current tts randomization framework●The recommendations we provide will enable researchers and engineers to adopt tts randomization more rob