My name is Spyridon Stouraitis, and I am currently a Doctoral Candidate at the Norwegian University of Science and Technology (NTNU). Under the supervision of Associate Professor Mojtaba Mokhtari and the co-supervision of Professor Bernt Johan Leira, Professor Dong Trong Nguyen and Associate Professor Adnan Kefal (Sabanci University) I am developing an Inverse Finite Element Method for the Structural Health Monitoring of Marine Structures. This work focuses on developing a Finite Element-based approach utilizing an inverse formulation to reconstruct applied loads, stresses, and displacements in Marine Structures, by utilizing measured surface strains. Upon completion, I aim for the results of this research to provide a robust, comprehensive, and universally applicable methodology for effectively monitoring the structural response of various types and sizes of vessels and floating offshore wind turbines. The objectives of this research are as follows:

1. Transition from Preventive to Predictive Maintenance: The shift from traditional preventive maintenance, which relies on fixed schedules, to predictive maintenance represents a significant evolution in Condition-Based Maintenance practices. Predictive maintenance leverages real-time sensor data to continuously monitor the structural integrity of ship hulls, including non-accessible areas, enabling timely interventions that preempt failures.
2. Optimization of Maintenance Resources: Structural Health Monitoring (SHM) systems facilitate the strategic targeting of maintenance efforts based on real-time data, rather than following predetermined schedules. This ensures that resources are allocated efficiently to areas most in need of attention.
3. Extended Lifespan of the Vessel: Continuous monitoring of the ship’s structural integrity through SHM systems provides precise, real-time data on hull conditions and critical components. By addressing issues such as yielding, buckling, corrosion, or fatigue early, SHM prevents excessive deterioration, thereby extending the vessel's operational life and ensuring compliance with safety standards.
4. Data-Driven Decision Making: SHM-generated data influences not only maintenance but also the design of new ships and retrofitting strategies for existing vessels. Unlike aerospace engineering, where structural weight is critical, marine engineering has allowed for material overuse. SHM provides insights that can optimize future ship designs, reducing costs and weight while enhancing strength and performance.
5. Regulatory Compliance: SHM not only enhances the operational safety of vessels but also ensures compliance with the increasingly stringent standards set by regulatory bodies. This compliance facilitates smoother certification processes and boosts the confidence of stakeholders in the maritime safety practices adopted by ship operators.
6. Environmental and Financial Impact: SHM reduces the need for extensive repairs and replacements, minimizing waste and resource consumption. By prolonging the lifespan of vessel components and preventing catastrophic failures, SHM significantly lowers operational costs and reduces the demand for new vessels, allowing existing fleets to operate efficiently for longer periods.
7. Optimized Analyses with Sea Phenomena and Structural Strength Assessment: Unlike traditional Finite Element Analysis, which relies on static and predefined conditions, SHM enables dynamic assessments using real operational data. This approach enhances the understanding of local and global loading conditions, fatigue effects, and extreme events, improving the strength assessment of hull girders and the overall understanding of marine structures.
8. Exploitation of Research by Classification Societies: The research aims to provide practical methods and results for application by classification societies and shipyards, advocating for mandatory strain monitoring systems on vessels throughout their operational lifespan. The development of a Machine Learning model, informed by Inverse Finite Element Method (iFEM) analyses, will allow for real-time, precise assessments of structural conditions, enhancing vessel safety during seakeeping conditions by ensuring structural responses remain within elastic limits.

In terms of my academic background, I have attained both my Bachelor’s and Master’s degrees in Naval Architecture and Marine Engineering from the National Technical University of Athens (NTUA). Under the supervision of Professor Emmanuel Samuelides, my Master’s thesis focused on the Strength Assessment of Container Vessels. Specifically, I analyzed eight different container vessel models subjected to various torsional and bending loading conditions using the Finite Element Method (FEM). Additionally, I conducted an extended as well as comprehensive investigation of the modeling parameters and also evaluated the local strength of various structural components against compression, with particular emphasis on the buckling behavior of stiffened panels and stiffener elements from all the examined vessels. The results of all FEM analyses, both for hull girders and stiffened panel models, were validated against empirical formulas provided by the International Association of Classification Societies (IACS). In addition to my expertise in Ship Strength, Marine Structures, Mechanics of Materials, and Numerical Analysis, I also possess significant knowledge in the fields of Hydrostatics, Hydrodynamics, Ship Dynamics, and Ship Design. Furthermore, I have practical experience with relevant software applications in these areas. As an extension of my Master’s thesis work, I am currently investigating the progressive collapse of six different container vessels under combined loads, with vessel sizes ranging from 1,800 TEU to 18,000 TEU.

The following are my primary research interests, which encompass various aspects of Marine Structural Analysis and Computational Modeling:

• Structural Health Monitoring (SHM) of marine structures.
• Numerical simulation of fluid-structure interaction for the assessment of structural loads on hull girders.
• Computational methods for solution of inverse problems in mechanics.
• Numerical simulation of complex systems under compound stresses.
• Numerical methods for the solution of ill-posed problems.
• Computational modelling of linear and non-linear phenomena.
• Estimation/determination/assessment of maximum ship’s operation load.
• Multi-criteria assessment of ship-shaped structural design.
• Development of analytical formulas and iterative processes to estimate structural behavior characteristics.
• Applications of AI techniques (Neural Networks) in the prediction of structural behavior.
• Combined static and dynamic load response of marine structures.

Beyond my research pursuits, I am an avid all-mountain skier, an enthusiastic sailor with experience in offshore sailing, and an AIDA-3 level free-diver. Additionally, I hold certificates in classical music theory and specialize in Beethoven’s pianistic literature. I have received classical piano training at the Athens Conservatoire and the Piraeus Conservatoire under the guidance of the virtuoso Aikaterini Vazaiou. In my free time, I am preparing for my classical piano proficiency certificate, focusing on the works of Ludwig van Beethoven, Sergei Rachmaninoff, Wolfgang Amadeus Mozart, Johann Sebastian Bach, Claude Debussy, Maurice Ravel, and Frédéric Chopin.