Fluid-structure interaction simulation of the effects of underwater explosion on submerged structures

Yapar, O.; Basu, Prodyot K.

doi:10.1016/j.finel.2021.103678

Cited by 17 publications

(4 citation statements)

References 33 publications

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“…Gannon (2019) numerically studied the response of a stiffened submerged cylinder, focusing on the effects of the shock and bubble jet, with results measured by bubble dynamics and structural strain and displacement. Yapar & Basu (2022) introduced a novel approach using the Abaqus explicit solver coupled with the XFlow computational fluid dynamics solver to simulate the nonlinear response of submerged structures to shock waves, validated with test data for a submerged tubular structure under UNDEX pressure waves.…”

Section: Modelling Of Fluid–structure Interactionsmentioning

confidence: 99%

A review of underwater shock and fluid–structure interactions

Matos,

Galuska,

Javier

et al. 2024

Flow

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Underwater explosions are inherently complex and unique physical phenomena markedly distinct from those occurring above the surface. This distinctiveness is primarily attributed to the relatively incompressible nature of water, which fundamentally alters the propagation and impact of shock waves. The study of underwater explosions is paramount in applications such as underwater demolitions for construction and salvage operations. These applications require a comprehensive understanding in order to mitigate the disturbances’ impact on marine structures and ecosystems. Studying underwater explosions and their mitigation encompasses various disciplines, including fluid mechanics, materials science and structural engineering. The work reviewed in this study contributes significantly to enhancing safety measures in marine structures by providing critical insights into the behaviour of structures under extreme conditions. This includes understanding the behaviour of gas bubbles formed by explosions, the transmission of shock waves through different media and the resultant forces exerted on structures submerged in water. Consequently, this review is meant to aid in designing robust and resilient marine systems capable of withstanding severe loading conditions caused by underwater explosions by providing key engineering considerations. The continuous evolution of this research area is essential for advancing maritime technology, ensuring the safety of undersea operations and protecting marine environments from the adverse effects of extreme subaqueous loadings.

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Section: Modelling Of Fluid–structure Interactionsmentioning

confidence: 99%

A review of underwater shock and fluid–structure interactions

Matos,

Galuska,

Javier

et al. 2024

Flow

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“…In the two-way FSI method [28], the exchange and mapping of data between XFlow and ABAQUS with different time steps and meshes is managed using the ABAQUS cosimulation engine (CSE). To handle the difference in time step size, the CSE employs the Gauss-Seidel algorithm for synchronization, which involves a serial process where one solver lags behind the other solver, one coupling step at a time.…”

Section: Fluid-structure Co-simulationmentioning

confidence: 99%

Wind-Induced Response Assessment of CAARC Building Based on LBM and FSI Simulation

Zhang,

Wang,

Cheng

et al. 2024

Buildings

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It is very important for the wind-resistant design of high-rise buildings to assess wind-induced vibrations efficiently. The Lattice Boltzmann Method-based Large Eddy Simulation and Fluid–Structure Interaction techniques are used to identify the surface wind pressure and wind-induced dynamic response of a CAARC standard high-rise building. Compared with wind tunnel tests, a detailed analysis of the accuracy of simulated wind pressures and base moments of the CAARC model are discussed under multiple wind direction angles. The differences between one-way and two-way Fluid–Structure Interaction simulations are compared under two different reduced wind velocities. The research results show that the simulated mean surface wind pressures of building under seven wind direction conditions have an error within 15% compared to probe measurements, and the average and root mean square base bending moments agree well with the wind tunnel tests. The top transverse wind-induced vibrations of the buildings are significantly larger when the reduced wind velocity reaches 4.6, indicating that aerodynamic damping effects on structural responses should not be overlooked. The research findings of this article provide valuable technical references for the application of LBM methods in the wind load effect assessments of high-rise buildings.

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“…In this recurring model is integrated the law of conservation of energy. Indeed the transfer of energy is one of the main causes of the change in surface temperature, hence the importance of introducing the universal law of the law of conservation applicable to all lakes [44][45][46][47]. Thus combining these 2 approaches is interesting, because we can integrate our physical knowledge which works in cases where the complexity is controlled, but also benefit from the advantages of ML/DL models which make it possible to extract patterns which we do not know.…”

Section: Related Workmentioning

confidence: 99%

Optimization of the Creation of a Training Set for the Calibration of a Model Reproducing the Vibration Behavior of an Overhead Line Conductor

Amroun,

Hafid,

Ammi

2022

IJICS

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One of the applications that machine learning can offer to the world of Engineering and Fluid Mechanics in particular is the calibration of models making it possible to approximate the representation of a particular phenomenon. Indeed, the computational cost generated by some fluid mechanics models pushes scientists to use other models close to the original models but less computationally intensive in order to facilitate their handling. Among the different approaches used: machine learning coupled with some optimization methods and algorithms in order to reduce the computation cost induced. This paper proposes a new framework called OPTI-ENS: a new flexible, optimized and improved method, to calibrate a physical model, called the wake oscillator (WO), which simulates the vibratory behaviors of overhead line conductors. An approximation of a heavy and complex model called the strip theory (ST) model. OPTI-ENS is composed of an ensemble machine learning algorithm (ENS) and an optimization algorithm of the WO model so that the WO model can generate the adequate training data as input to the ENS model. ENS model will therefore take as input the data from the WO model and output the data from the ST model. As a benchmark, a series of Machine learning models have been implemented and tested. The OPTI-ENS algorithm was retained with a best Coefficient of determination (R2 Score) of almost 0.7 and a Root mean square error (RMSE) of 7.57e-09. In addition, this model is approximately 170 times faster (in terms of calculation time) than an ENS model without optimization of the generation of training data by the WO model. This type of approach therefore makes it possible to calibrate the WO model so that simulations of the behavior of overhead line conductors are carried out only with the WO model.

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Fluid-structure interaction simulation of the effects of underwater explosion on submerged structures

Cited by 17 publications

References 33 publications

A review of underwater shock and fluid–structure interactions

A review of underwater shock and fluid–structure interactions

Wind-Induced Response Assessment of CAARC Building Based on LBM and FSI Simulation

Optimization of the Creation of a Training Set for the Calibration of a Model Reproducing the Vibration Behavior of an Overhead Line Conductor

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