DC06 - ISAMGEO
PhD: Densely distributed sensor networks for seismic wave detection in complex environments for civil engineering applications
Work Package
WP1 - Innovative sensor technologies | |
X | WP2 - Advanced imaging using mechanical waves |
WP3 - Smart and robust structures and materials |
Objectives
DAS and MEMS have been widely used in different environments (e.g. oil wells for DAS, and many accelerometric
applications in the mechanical industry for MEMS). Yet their use in densely distributed networks for monitoring ambient noise in urban environments is still in its infancy. The main challenge lies in the capability to deploy dense networks and manage large datasets in order to retrieve spatially dense information in terms of both shallow subsoil characteristics and local seismic source localisation. These networks are designed to characterise the subsurface by means of direct, reflected, refracted and backscattered seismic waves, and particularly surface (Rayleigh) waves. The goal of the project is to develop, test and validate monitoring tools based on seismic surface waves and, more specifically, on the use of passive seismic sources (noise) for the assessment of natural risks and a detailed characterisation of the shallow subsurface, notably in urban areas. This effort will lead to determining detailed shallow subsurface structures in terms of shear wave velocity, an assessment of Peak Ground Acceleration (as an effect of local seismic amplification), and anthropogenic underground structures, also from backscattered energy migration.
Planned intersectoral, interdisciplinary and international secondments
- ULB, Arnaud Deraemaeker, 2 months, M13-M14: Training on the numerical modelling of wave propagation.
- UBRI, Anthony Croxford, 2 months, M18-M19: Training on acoustic Non-Destructive Testing methods, paper writing.
- BAM, Franziska Baensch, 2 months, M25-M26: Testing of acquisition and processing strategies at the BAM test site.