Climate & Environment

    Natural Catastrophes

Post-Doctoral Fellowships

Spain

Listening to buildings: towards reliable early warning for structural failure and collapse

Environmental conditions, both normal and extreme, can stress natural and man-made structures beyond their stability limit. In 'sensitive' constructions such as oil and gas pipelines, artificial dams, nuclear power-plants, or bridges, structural failure can have devastating consequences. A most dramatic example occurred during the summer of 2018 in Genoa, Italy: the collapse of the Morandi bridge, which claimed the lives of 43 people. To avoid such disasters, uninterrupted structural health monitoring (SHM) is essential. With a mind to facilitate such supervision, Dr. Jordi Baro-Urbea, of the Centre for Mathematical Research of Catalonia, is developing models that will help interpret recorded acoustic emission events as a measurement of the internal state of a building. The overall project, called RheMechFail, aims to complement and improve current models for monitoring the resilience of structures under severe conditions.
«The collapse or failure of man-made structures is difficult to forecast at a reasonable mid-term without the persistent monitoring of the internal structure of its parts, Dr. Jordi Baro-Urbea explains. The deformation leading to failure is predicted to follow an avalanche process, consequence of microscopic mechanical instabilities, that can be detected by the recording of the released acoustic waves». To give us some context about the challenges in this field of engineering, the researcher adds that «because the internal state of the material is rarely accessible, active and passive acoustic emission techniques are among the most common methods of non-intrusive structural health monitoring ». In this research project, Dr. Baro-Urbean’s focuses on the passive techniques, which consists of the monitoring of the acoustic waves spontenously generated by the 'breathing' of the hidden internal cracks.

Passive acoustics as an efficient and reliable structural health monitoring strategy

RheMechFail is developing models that can interpret the statistics of recorded acoustic emission events as a measurement of the internal state of the system. «The statistical properties of the whole population (of recorded acoustic events) can be used to assess the state of the material and it’s proximity to failure», he describes, indicating that «the right determination of this relation is a stepping stone for the development of future non-intrusive structural health monitoring tools needed to deliver early warning systems». Recognising that current SHM methods often neglect to take into account the correlation between separate acoustic events, as is the case in Seismology for instance, the present project innovates by studying how event-event triggering mechanisms operate during the deformation, hence considering the interactions between microcracks. «The ultimate goal of this project is to improve the reliability of the models used in SHM by introducing the adequate history-dependent representation of the intensity». Further, the researcher specifies that «the intensity will be deduced from physical principles and fitted from the known properties of the materials».

The monitoring and maintenance of civil infrastructures remains a challenge to modern societies. In the face of Climate Change, exposing unprepared populated areas to extreme weather conditions, the issue is becoming ever more pressing. To maintain public safety, and avoid disasters, it is thus fundamental to invest in the development of reliable and efficient tools for structural health monitoring. Once it is completed, the RheMechFail project will provide fundamental tools to develop future SHM techniques, enabling more accurate short term predictions of failure, issuing early warnings, evacuation calls or emergency procedures.

Jordi
BARO-URBEA

Institution

Centre de Recerca Matemàtica

Barcelona Graduate School of Maths (BGSMath)

Country

Spain

Nationality

Spanish

ORCID Open Researcher and Contributor ID, a unique and persistent identifier to researchers