Session: 01-03-02 Hydrodynamics-2

Submission Number: 182310

Experimental Investigation of Hydrodynamic Forces on a Forced-Moving Circular Cylinder in a Water Channel 

Vortex-Induced Vibrations (VIV) represent a complex and nonlinear fluid–structure interaction phenomenon of critical importance to the design of offshore structures such as risers and platforms. The inherent nonlinearities of the wake dynamics, combined with the challenges of performing fully resolved CFD simulations, make the accurate prediction of VIV a difficult task. A key aspect of the phenomenon is the lock-in condition, in which the vortex shedding frequency synchronizes with the structural oscillation frequency, leading to large-amplitude vibrations that may cause structural fatigue or failure.

In this work, we aim to enhance the understanding of VIV mechanisms through controlled laboratory experiments on a forced-moving circular cylinder in a water channel. The cylinder is instrumented to measure the instantaneous lift and drag forces induced by both the flow and the prescribed motion. All measurements are acquired in real time and synchronized with the cylinder position, enabling the reconstruction of detailed position–force–time diagrams. The experimental setup allows motion to be imposed in the cross-flow, in-line, or combined directions, thus providing a versatile platform for studying fluid–structure coupling. Sensor data may also be used to simulate the cylinder motion under different physical conditions, such as variations in mass or stiffness, allowing the reproduction of realistic structural responses. The resulting dataset will support the validation of time-domain VIV models and foster the application of machine learning techniques for data-driven modeling of hydrodynamic forces.

Presenting Author: Marlon Sproesser Mathias Universidade de São Paulo

Presenting Author Biography: Professor in the Department of Mechanical Engineering at the Polytechnic School of the University of São Paulo (USP). Member of the Center for Artificial Intelligence (C4AI) at USP, with research focused on Physics-Informed Machine Learning. Holds both M.Sc. and Ph.D. degrees in Mechanical Engineering from the São Carlos School of Engineering, University of São Paulo (EESC-USP), where he worked in the Aeroacoustics, Transition, and Turbulence Group on numerical simulations of fluid flows, particularly on hydrodynamic instabilities leading to the transition to turbulence. He also holds a B.Eng. degree in Aeronautical Engineering from EESC-USP.

Authors:

Vitor Augusto Andreghetto bortolin Universidade de São Paulo
Marlon Sproesser Mathias Universidade de São Paulo
Bernardo Luiz Harry Diniz Lemos Universidade de São Paulo
Rodrigo De Lima Amaral Universidade de São Paulo
Julio Romano Meneghini Universidade de São Paulo