Laureate Scientific Prize McKinsey & Company 2021: Dimitrios Anastasopoulos
Thanks to the patronage of McKinsey & Company, the Research Foundation – Flanders (FWO) and the Fonds de la Recherche Scientifique – FNRS (F.R.S.-FNRS) annually award two scientific prizes in recognition of a PhD in exact sciences, applied sciences, social, economic or management sciences, or biomedical sciences. One scientific prize is awarded to a young researcher from the Flemish Community, and one to a young researcher from the Fédération Wallonie-Bruxelles. The researcher needs to demonstrate the social and economic relevance or concrete implementation of his/her PhD. The Flemish laureate of the Scientific Prize McKinsey & Company 2021 is Dimitrios Anastasopoulos of KU Leuven, who defended his PhD thesis “Structural health monitoring based on operational modal analysis from long gauge dynamic strain measurements” in February 2020. His research story is included below
Bridges are among the most important civil engineering structures. From the most iconic ones, such as the Golden Gate Bridge in San Francisco, to the less known highway overpasses, their importance as critical transportation links is unquestionable. Design standards require the highest safety factors for bridges to ensure their uninterrupted and safe operation under the most unfavorable conditions. However, structural damage and failures still occur as many structures are approaching or exceeding their original design life. Other causes of structural damage and failures include exposure to highly demanding environmental and operational loads or extreme events, such as earthquakes, faulty design, and construction errors. A recent tragic failure is that of the Polcevera Viaduct in Genoa, Italy, which collapsed on 14 August 2018, leading to 43 casualties and millions of financial losses for the whole region.
Structural failures underline the need for adequate monitoring systems that can warn the authorities on time about potential damage-related hazards in order to protect the public and avoid life loss. Several structures around the world are already being monitored with Structural Health Monitoring (SHM) systems. SHM refers to the process of implementing a reliable damage detection strategy for civil, aerospace, or mechanical engineering infrastructure that can provide timely information about a structure’s condition. Civil SHM becomes increasingly important for several reasons. The transport infrastructure in Europe and the US is aging. Many of the bridges that are currently in use were built during the economic boom of the 1950’s and have now reached the end of their design life. Most bridges also carry significantly more and heavier vehicles than originally expected. This makes bridge maintenance, inspection, and monitoring of critical importance.
Consider as an example the structural condition of the US infrastructure. In early 2021, the American Society of Civil Engineers gave the country’s overall infrastructure a grade of D+, estimating that $3 trillion will be required for repairs and replacements over the next decade. According to a 2020 US Department of Transportation report, in the US, there are about 350,000 bridges that are structurally deficient or have identified repair needs. The total cost to repair and replace these bridges is estimated to be $200 billion. This amount of bridges cannot be repaired in a short period of time, and decades might be required to fulfil this task. In order to face this huge challenge, the widespread use of low-cost SHM systems, which provide reliable information regarding the condition of a particular structure for the years to come, is crucial. This information can be elaborated in a decision support system for deciding which bridges are the most vulnerable and require immediate action, whether or not maintenance is necessary, or even if the operational life of a structure can be extended beyond its original design service life, offering safety and economic benefits.
Among the different options available, Vibration-Based Monitoring or VBM is a very attractive non-destructive approach for damage identification and condition assessment of civil structures. Damage alters the stiffness, mass or energy dissipation properties of a structure, which are properties that are directly related to its dynamic behavior as represented by the modal characteristics (natural frequencies, displacement mode shapes and damping ratios). The idea behind VBM is to identify changes in modal characteristics that are directly related to damage. The main challenge is to identify characteristics that are as sensitive as possible to structural damage and at the same time as insensitive as possible to environmental factors such as temperature. Natural frequencies are the most widely used modal characteristics for VBM purposes. However, they can exhibit a low sensitivity to certain types of damage while their sensitivity to temperature can be sufficiently high to completely mask the effect of even severe damage. On the other hand, identifying the displacement mode shapes requires a dense grid of expensive sensors, which renders their monitoring uneconomical, especially for large structures.
In my PhD thesis, I have developed a new approach to VBM based on the monitoring of strain mode shapes. Although modal strains and curvatures were previously known to be much more sensitive to local damage than other modal characteristics, their direct monitoring in a dense grid was not possible with previously existing techniques due to the extremely small strain levels occurring during ambient or operational excitation. Two new methods have been developed based on Fiber-optic Bragg Grating (FBG) technology. FBG sensors offer the required accuracy and precision and can be relatively easily implemented on a civil structure. This allows for accurately identifying the strain mode shapes of structures and offers a cost-effective and reliable alternative to displacement mode shape monitoring, thanks also to the low cost of the FBG sensors. Extensive experiments in laboratory conditions and in the field have demonstrated that strain mode shapes can be significantly less influenced by temperature compared to natural frequencies. This is a crucial advantage as a temperature-insensitive dynamic characteristic can be directly used for VBM without requiring data normalization while reducing uncertainty on damage identification. Most importantly, strain mode shapes have been proved sensitive to local damage of moderate severity, which is the key for early stage damage identification. Identifying damage in an early stage is a core principle of SHM due to the obvious safety and economic advantages that this offers. This PhD work was performed in the frame of a research project, funded by the Research Foundation-Flanders (FWO), in which the KU Leuven Structural Mechanics Section and the VUB B-Phot Team joined forces.
The high potential of SHM based on strain mode shapes is drawing the interest of infrastructure owners, such as the Belgian railway infrastructure manager Infrabel, of which several bridges are already being monitored with this technology. In order to obtain insight into the damage identification capabilities in field conditions, one of these bridges will also be artificially damaged to a small extent while it is out of service and before it is decommissioned. The proposed approach is also one of the pillars of my postdoctoral Vlaio Coock project, “Monitoring of structures and systems with optical fibers”, which is performed in collaboration with the Belgian Building Research Institute and aims at increasing the readiness level of the technology for the construction sector. Its potential is even wider as there are clear links with, e.g., aerospace and offshore engineering.
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