Academic Engagement

Academic Engagement

University of Maine's Innovative Floating Offshore Wind Concept

Completion of ABS design review helps demonstrate feasibility of the University of Maine's semisubmersible foundation concept for offshore wind facilities.

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Innovation through Collaboration

ABS and its industry and university partners are expediting innovation through collaboration and knowledge-sharing. Research conducted through joint industry projects and university partnerships targets technologies to support the future of classification, which will be continuous and more condition-risk-based. Among the critical technologies under study are sensors and autonomous inspection, materials innovation and nanotechnology. 

ABS has supported endowed academic chairs at eight campuses worldwide:

  • Chair of Naval Architecture and Marine Engineering and ABS Chair of Marine Transportation at the State University of New York Maritime College
  • School of Maritime Policy and Management at California Maritime
  • Chair of Metallurgical and Materials Engineering at Colorado School of Mines
  • Chair in Ocean Engineering at University of California at Berkeley
  • Professor in Marine and Offshore Design Performance at University of Michigan
  • Chair of Naval Architecture at Massachusetts Institute of Technology
  • Chair in Naval Architecture and Marine Engineering at the Webb Institute.



Singapore Polytechnic

An Integrated Non-destructive Coating Inspection System for Marine and Offshore Corrosion Management

ABS is collaborating with Singapore Polytechnic in the development of a vision-based coating inspection and assessment system which utilizes a deep learning technique to automate coating breakdown and corrosion (CBC) assessment. This project is funded by Singapore Maritime Institute.

Based on machine learning (ML) technology, this system can automatically assess images so as to identify and classify defects such as coating failures, corrosion, and structural damage. A database of thousands of images, which is ever expanding with more images collected from inspections, has been compiled to train and verify the system. This offers the potential for improvements in performance and efficiency over the current industry approach of visual inspection.  This methodology can also be extended to identify other defects such as fractures and buckling. 

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University of Michigan, Vanderbilt University, Stevens Institute of Technology

Data Strategy

ABS is working with the University of Michigan, Stevens Institute of Technology and Vanderbilt University to study cross-industry processes and best practices for data sourcing, management and analytics supporting risk-informed decision making. The study will explore methods to optimize data use – to improve the client’s classification experience, and drive improved operations and performance for owners and operators.

The studies will focus on several key areas including advanced data analytics, emerging inspection and monitoring technologies, data architecture, application of smart technologies, as well as the overarching data framework.  Each university brings a unique perspective and has assigned a team of distinguished researchers to focus on one or more aspects of the study, and contribute to the summary document. Additionally, the university will peer review of other universities’ recommendations.  

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National University of Singapore

Efficient Ship Design Analysis Reducing Vibration Impact on Performance

ABS and National University of Singapore are jointly developing efficient computational techniques for ship analysis and design to improve ship performance by reducing vibration and noise. The project is funded by Singapore Maritime Institute (SMI). The main goal is tackling the added mass effect on ship vibration in sea water, evaluating the magnitude and direction of vibrational energy flow in the ship structure.

Analysis tools developed will facilitate calculation of the added mass associated with ship vibration modes and will be integrated into current workflows for ship design and performance assessment.

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