Development Of The Digital Twin Of A Reconfigurable Bridge With Active Control System

Universities and Institutes of France
November 29, 2023
Offerd Salary:Negotiation
Working address:N/A
Contract Type:Other
Working Time:Full time
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7 Oct 2023

Job Information



Research Field


Computer science » Digital systems

Researcher Profile

Recognised Researcher (R2)

Leading Researcher (R4)

First Stage Researcher (R1)

Established Researcher (R3)



Application Deadline

29 Nov 2023 - 22:00 (UTC)

Type of Contract


Job Status


Offer Starting Date

16 Oct 2023

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?


Offer Description

Context: The ANR-NSTC NEMELIFT project is a franco-taiwanese collaborative research project aiming at developing an innovative crossing technology to address urban mobility issues of the city of tomorrow. The agility of the solution makes its originality. The project gathers 4 international research laboratories specialized in vibrations and contact (ISAE-SUPMECA, France) and in active control systems for civil engineering applications (NCNU, NCKU, NCUT and NUK Taiwan), and 1 industrial partner (LOCAPAL) specialized in temporary footbridges and steel structures. It is divided into 3 technical Work Packages (WP) dedicated to the development of numerical tools for the robust design of light slender assembled structure (WP1, Leader SUPMECA), the control of the bridge deflection using continuous parameters identification (WP2, Leader NCNU) and the development of a Digital Twin of this innovative technology of bridge (WP3, Leader SUPMECA). This PhD position is part of WP3.

Thesis objectives: The aim of this PhD is to implement a Digital Twin of a lightweight pedestrian bridge equipped with an active control mechanism.The Digital Twin to be developed in the NEMELIFT project will be mainly dedicated to model and control law updating and to risk assessment to ensure the highest safety for users. The developed DT will also address flow of people monitoring to optimize soft transport mode networks at the scale of the city. The implementation of a DT relies on key technologies categorized between: data related technologies, high-fidelity modelling technologies, and model- based simulation technologies. Modelling and simulation technologies are addressed in WP1. This PhD thesis will thus focuses on data acquisition and on the connection between the actual behaviour of the bridge and the associated numerical models. Virtual sensor based on image processing and computer vision techniques will be developed to provide a non-intrusive and easy to setup measurement system for the real-time characterization of civil engineering structures. Data fusion and data processing techniques will be integrated in the virtual sensor to provide meta-data relevant for high-fidelity models and control law updating. Classical probabilistic tools and uncertainty propagation techniques associated with data stream and continuously updated physical models will be considered to define indicators for predictive maintenance and risk assessment.

Funding category: Autre financement public Projet ANR PHD title: Doctorat de Génie Mécanique PHD Country: France


Specific Requirements

We are looking to motivated student with a background on computational mechanics, eventually students with a background in the development of Internet of Things (IoT) solutions. Skills on software development and/or image processing would be interesting.

Expected skills: autonomous, critical thinking, scientific approach, software development, familiar with linux operating systems Software and programming languages: python, matlab, C++, (this list is indicative, other software and languages could be proposed by the candidate if relevant) Communication: proficiency in English (in word and writting)

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