Work

Bayesian inversion of MASW data for the characterization of railway embankments

Year: 2023

Type: conference-paper

Abstract: The renewal of railway embankments (RE) requires the characterization of their mechanical properties.Techniques classically used to study RE are mainly local, destructive, expensive and of low yields (geotechnical in situ tests, core-drillings).There is a great need in the development and deployment of non-destructive methods, allowing quick and efficient diagnosis of the RE state.Surface wave method has been deployed in a test site to determine the shear modulus along the line.The development of a surface-wave dispersion inversion algorithm according to a probabilistic approach, enables to switch from qualitative to quantitative results.Such Bayesian implementation should help the results interpretation and constrain end-users decisions.

Source: Civil-comp conferences

DOI: 10.4203/ccc.1.8.12

Authors: A. Burzawa, L. Bodet, A. Dhemaied, M. Dangeard

Institutions: Centre National de la Recherche Scientifique, École Pratique des Hautes Études, Société Nationale des Chemins de Fer Français (France), Sorbonne Université, Milieux environnementaux, transferts et interactions dans les hydrosystèmes et les sols

Language: English

Topic: Seismic Waves and Analysis

Subfield: Geophysics

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: bronze

Funders: Centre National de la Recherche Scientifique, Université Pierre et Marie Curie, Sorbonne Université