We present a methodology for the assessment of possible pre-failure bridge deformations, based on Synthetic Aperture Radar (SAR) observations. We apply this methodology to obtain a detailed 15-year survey of the Morandi bridge (Polcevera Viaduct) in the form of relative displacements across the structure prior to its collapse on August 14th 2018. We generated a displacement map for the structure from space-based SAR measurements acquired by the Italian constellation COSMO-SkyMed and the European constellation Sentinel-1A/B over the period 2009–2018. Historical satellite datasets include Envisat data spanning 2003–2011. The map reveals that the bridge was undergoing an increased magnitude of deformations over time prior to its collapse. This technique shows that the deck next to the collapsed pier was characterized since 2015 by increasing relative displacements. The COSMO-SkyMed dataset reveals the increased deformation magnitude over time of several points located near the strands of this deck between 12th March 2017 and August 2018.

Spaceborne multi-temporal interferometric synthetic aperture radar (MT-InSAR) is a monitoring technique capable of extracting line of sight (LOS) cumulative surface displacement measurements with millimeter accuracy. Several improvements in the techniques and datasets quality led to more effective, near real time assessment and response, and a greater ability of constraining dynamically changing physical processes. Using examples of the COSMO-SkyMed (CSK) system, we present a methodology that bridges the gaps between MT-InSAR and the relative stiffness method for tunnel-induced subsidence damage assessment. The results allow quantification of the effect of the building on the settlement profile. As expected the greenfield deformation assessment tends to provide a conservative estimate in the majority of cases (~71% of the analyzed buildings), overestimating tensile strains up to 50%. With this work we show how these two techniques in the field of remote sensing and structural engineering can be synergistically used to complement and replace the traditional ground based analysis by providing an extended coverage and a temporally dense set of data.

The increasing demand for underground infrastructure should be supported by innovation in monitoring and damage assessment solutions to minimise damage to surface structures caused by ground settlements. This paper evaluates the use of multitemporal synthetic aperture radar interferometry (MT‐InSAR) to calculate tunnelling‐induced deformations of buildings. The paper introduces a step‐by‐step procedure to use InSAR displacements as an input to the structural damage assessment. After a comparison between traditional and InSAR monitoring data for the London area during the Crossrail excavation, the high resolution, high density InSAR‐based displacements were used to evaluate the building deformations for a number of case studies. Results demonstrate the quality of information provided by InSAR data on soil‐structure interaction mechanisms. Such information, essential to evaluate current damage assessment procedures, is typically only collected for relatively few buildings due to the cost of traditional monitoring. A comparison between damage indicators derived from greenfield assumptions and building displacements quantifies the practical benefit of the proposed step‐by‐step procedure. This work aims at filling the gap between the most recent advances in remote sensing and the civil engineering practice, defining the first step of an automated damage assessment procedure which can impact large scale underground projects in urban areas.

Structural health monitoring (SHM) is the automation of the condition assessment process of an engineered system. When applied to geometrically large components or structures, such as those found in civil and aerospace infrastructure and systems, a critical challenge is in designing the sensing solution that could yield actionable information. This is a difficult task to conduct cost-effectively, because of the large surfaces under consideration and the localized nature of typical defects and damages. There have been significant research efforts in empowering conventional measurement technologies for applications to SHM in order to improve performance of the condition assessment process. Yet, the field implementation of these SHM solutions is still in its infancy, attributable to various economic and technical challenges. The objective of this Roadmap publication is to discuss modern measurement technologies that were developed for SHM purposes, along with their associated challenges and opportunities, and to provide a path to research and development efforts that could yield impactful field applications. The Roadmap is organized into four sections: distributed embedded sensing systems, distributed surface sensing systems, multifunctional materials, and remote sensing. Recognizing that many measurement technologies may overlap between sections, we define distributed sensing solutions as those that involve or imply the utilization of numbers of sensors geometrically organized within (embedded) or over (surface) the monitored component or system. Multi-functional materials are sensing solutions that combine multiple capabilities, for example those also serving structural functions. Remote sensing are solutions that are contactless, for example cell phones, drones, and satellites. It also includes the notion of remotely controlled robots.

This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.tust.2015.07.01