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Condition Monitoring of Offshore Structures




2: Mechanical Engineering

Faculty Supervisor:

Brian Anthony

Faculty email:


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Project Description

Deepwater offshore structures are at a water depth > 400 ft and these are usually at remote locations (Figure: Floating Production Storage and Offloading (FPSO) Facility in 1000m Water Depth). These structures are excited by complex forces and information about the condition of the asset, to evaluate multi-disciplinary failure mechanism(s), during operation is challenging and sometimes not possible. It is important to assess the safety and reliability of these structures to prevent incidents such as the Deepwater Horizon in Gulf of Mexico and Piper Alpha in explosion in North Sea. The objective of this work will be to determine how we can close the gap on the information we have on the condition of assets by using sensors and enable a data driven approach towards structural integrity management. Impact: This project is of interest to offshore air industry, oil and gas industry, municipalities in support of bridges.


1. This project will utilize machine learning and data analytics, condition monitoring and wear prediction skills. Background/interest in these skills are helpful and students can expect to enhance these skills through the project. 2. This project is offered as part of the MechE Alliance industry connected ELO cohorts. Applicants will be expected to participate in the cohort program to be eligible for the position. More information can be found in this Google Doc: https://drive.google.com/file/d/1YbGwDXGAvPDSN6DEDGBw-VDJWS7jnp65/view?usp=sharing This is a remote UROP opportunity.