ABCPhD CALL4SCHOLARSHIP 33 Research topic: Structural Health Monitoring. Innovative Sensors and the Value of Information (33 - Attachment 1.

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1 ABCPhD Doctoral Program in architecture built environment and construction engineering ABCPhD CALL4SCHOLARSHIP 33 Research topic: Structural Health Monitoring. Innovative Sensors and the Value of Information (33 - Attachment 1.4)

2 Funding and management of the thematic scholarships Number of scholarships: 1 (one) Monthly net income: ,00 (max 36 months) [In case of a change of the welfare rates during the three-year period, the amount could be slightly modified] Additional support: Funding for educational activities (*) : per student [for the 2 nd and 3 rd year] Starting of PhD activity: 1/11/2017 Deadline for application to the call: 11/09/2017 Research Director: Maria Pina Limongelli Research Group: Maria Pina Limongelli, Frederic Bourquin (IFSTTAR), Michael Dohler (IFSTTAR) Funding and cooperating Institutions: the scholarship is funded by Politecnico di Milano, Department ABC. (*) (purchase of study books and material, funding for participation in courses, summer schools, workshops, conferences)

3 Context of the research activity Structural Health Monitoring (SHM) is increasingly applied for collecting information on actions, structural performances, deterioration processes and damages due to extreme events. Owners and managers of infrastructures are increasingly interested in Structural Health Monitoring technologies as a support to decision making for asset maintenance. In present practice it is implicitly assumed that SHM provides a benefit when implemented, either in terms of improved safety and serviceability, or reduced life-cycle costs or both. Even with traditional monitoring strategies, this is not always the case. Inappropriate SHM strategies may, at best, lead to a loss of economical and human resources but can easily trigger unnecessary or inappropriate remedial activities which may jeopardize the safety of the structures or cause unnecessary disruption to infrastructure network users. There is thus a strong need of procedures enabling the quantification of the Value of the Information given by an SHM system, before its implementation. The focus of the thesis is on the definition of a methodology to assess the Value of the Information of Structural Health Monitoring (SHM) in a very novel configuration, namely for sensors volumeembedded inside transportation infrastructures to monitor their residual service time.

4 Motivation and objectives of the research Due to the increasing interest and diffusion of SHM technologies, there is the need to estimate the actual value of the information they provide and to optimise them for the different applications. With innovative sensors that could have additional monitoring costs, there is an even stronger incentive to clearly settle the benefit-cost ratio of these SHM techniques. In this thesis a pre-posterior Bayesian approach to this problem will be employed exploiting a large database of installations of embedded sensors made available by IFSTTAR. The thesis work plan includes therefore a double theoretical/experimental level and the application to a case study: Firstly will be defined the methodology to quantify the value of SHM using embedded strain nanosensors before their installation. As a second step the probabilistic modeling connected to the bayesian approach to decision making will be carried out exploiting an extensive experimental database that will be made available by IFSTTAR. The methodology will be applied to a real case study of a laboratory structure monitored with embedded sensors that will be made available by IFSTTAR. The results given by the methodology will be checked for several damage scenarios artificially induced in the structure.

5 Educational objectives At the end of the Doctoral Programme, the Candidate will have expertise in issues related to the optimization of SHM systems for structures and infrastructure aimed at their integrity management. Knowledge on innovative SHM techniques based on strain nanosensors will also be acquired and will be valuable for the construction market and, in particular, for those private or public companies involved in asset maintenance of structures and infrastructures. Besides acquiring skills in the field of research development and management, it is expected that the candidate will develop a publication record in recognized international journals and conferences

6 Methods and techniques that will be used to carry out the research The PhD candidate will use the following methods and techniques: Techniques for signal processing (for treatment of experimental data that will be used to build the likelihood functions and to apply the methodology to the case study) Existing algorithms for damage detection and localization (for selecting the algorithm that best describes the state of the structural system) Probabilistic modelling and Bayesian decision theory (to investigate the modelling of the likelihood functions and to define the methodology to estimate the Value of Information of data retrieved) Performance modelling of structures (for the structural and probabilistic modelling of the relation between the quantity measured by the monitoring system and the structural performance) Innovative embedded nanosensors for concrete and asphalt (characteristics of sensors and wireless transmission system and software for data storage will be defined) The work will be carried out partly at Politecnico di Milano and partly at IFSTTAR in France. The topic of this thesis is also the object of a European COST Action currently running (COST Action TU1402. Quantifying the value of Structural Health Monitoring). The PhD student will be able to take profit of the results of this project and will also have the possibility to exploit the network spending short periods at different European Institutions that will provide additional expertise to the thesis project..

7 Skills of the candidate Skills that the Candidate will develop during the PhD program: Knowledge of Structural Health Monitoring techniques; Knowledge of innovative sensing devices for SHM; Knowledge of algorithms for damage identification (detection and localization); Knowledge about decision making tools to support maintenance management; Attitude of interaction with industries and asset owners/managers to discuss research activities. Job opportunities This research proposal offers PhD candidates a broad knowledge in the field of innovative SHM technologies and of structural integrity management of structures and infrastructures that can be used afterwards in academia, in R&D departments of companies or the professional market, both in private companies or in public bodies owning or managing structures and infrastructures (buildings, bridges, pipelines for oil and gas, water, waste-water, building energy, heating/cooling and ventilation systems). The skills of the PhD candidate will be related to the real market of existing structures and infrastructures that needs efficient management of maintenance intervention throughout their entire life-cycle. Furthermore the expertise in the efficient use of innovative embedded sensors will make the PhD candidate a first choice for the market related to the Smartcity vision based on the exploitation of sensor to manage the city's asset in order to improve quality and security.