PROGRAM

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Registration (August 06, 2025)

14:00 – 16:00 AM

Open Conference from President of Ho Chi Minh City Open University (August 07, 2025)

08:00 – 08:15 AM

SPEAKERS:

Welcome message from the Chair of SHM&ES

08:15 – 08:30 AM

SPEAKERS:

Keynote speaker

08:30 – 9:00AM

* SPEAKER: Prof. Nicholas Fantuzzi, PhD.

The University of Bologna, Bologna, Italy.

Editor-in-Chief of the journal Composite Structures.

* Title: Enhancing Structural Integrity for Decarbonisation in Offshore Marine Environments

* Abstract:

Advancing decarbonisation within the offshore sector necessitates a thorough comprehension of structural integrity under the harsh marine conditions. This presentation addresses pivotal challenges and innovative methodologies essential to achieving this goal.

Key fatigue design issues linked to reusing transition pieces from decommissioned platforms for offshore wind energy applications are examined, underlining the demand for novel engineering solutions. Additionally, the fatigue damage assessment of jacket-type platforms is analyzed, employing global methodologies and stochastic techniques with wave spectrum data to improve prediction accuracy. Detailed stress concentration factor assessments and fatigue life evaluations of offshore tubular KT-joints further emphasize the critical factors influencing structural durability in marine settings.

The presentation also explores the role of digital twin technology in the decommissioning process, promoting sustainable reuse by repurposing decommissioned jacket platforms as wind turbine foundations. A global fatigue assessment framework is proposed for these platforms, facilitating their transformation into offshore wind infrastructure.

These findings offer valuable insights into supporting decarbonisation initiatives in the offshore sector, while prioritizing the safety and longevity of marine structures.

Keynote Speakers

09:00 – 9:30 AM

* SPEAKERS: Prof. Chan Ghee Koh

National University of Singapore

* Title: Detection of Train Wheel Flats Using Rail Pad Sensor and Model-Based Identification Algorithm

* Abstract: “Wheel flat” occurs when a wheel stops rotating while the train is moving, for example, due to emergency braking or slippery conditions. Early detection of wheel flats is important to reduce vibrations and damage of components caused by impact of wheel flats on rails. Nevertheless, it is challenging to quantify the wheel-flat size without interrupting railway operations. This keynote presentation will cover a novel methodology that combines a new sensor technology with an advanced identification algorithm to achieve this goal. (1) Sensor: An innovative rail pad sensor is proposed by surface bonding a thin multilayered sensing device beneath the rail pad for train wheel load identification. The low-cost sensor shows good linearity within the load regime tested and performs well under dynamic loadings. It does not have blind-zone problem, which is one advantage over the conventional strain gauge-based wheel load monitoring system. (2) Algorithm: A model-based identification algorithm is proposed to quantify the size of wheel flats with real time data, accounting for modeling and measurement uncertainties. By using a two-step important-point-selection approach in the time series data interpretation, the proposed algorithm extracts perceptually important points that align with the human visual identification process to represent the time series shape. These points are then further filtered using joint entropy as an information-gain metric. The proposed identification methodology has been successfully applied to a field test in which the identified flat sizes agree with the observed range of true values