Estimating nonlinear coupled frequency-dependent parameters in offshore engineering

Liagre, Pierre; Niedzwecki, John M.

doi:10.1016/s0141-1187(03)00029-4

Cited by 10 publications

(4 citation statements)

References 9 publications

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“…However, this will Copyright c 2018 by ASME not be the case for a snake robot with few links. WADAM and WAMIT are widely used to obtain the added mass coefficients in marine vehicles or floating structures [12], [13]. Note that WAMIT lacks a graphical user interface, and thus WADAM is considered in this paper as the 3D potential theory in WADAM is directly based on WAMIT and has a good graphical user interface.…”

Section: Fluid Parameter Identification Methodsmentioning

confidence: 99%

Fluid Parameter Identification for Underwater Snake Robots

Kelasidi

Elgenes

Kilvær

2018

Volume 7A: Ocean Engineering

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Nowadays different types of unmanned underwater vehicles (UUVs), such as remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs), are widely used for sub-sea inspection, maintenance, and repair (IMR) operations in the oil and gas industry, archaeology, oceanography and marine biology. Also, lately, the development of underwater snake robots (USRs) shows promising results towards extending the capabilities of conventional UUVs. The slender and multi-articulated body of USRs allows for operation in tight spaces where other traditional UUVs are incapable of operating. However, the mathematical model of USRs is more challenging compared to models of ROVs and AUVs, because of its multi-articulated body. It is important to develop accurate models for control design and analysis, to ensure the desired behaviour and to precisely investigate the locomotion efficiency. Modelling the hydrodynamics poses the major challenge since it includes complex and non-linear hydrodynamic effects. The existing analytical models for USRs consider theoretical values for the fluid coefficients and thus they only provide a rough prediction of the effects of hydrodynamics on swimming robots. In order to obtain an accurate prediction of the hydrodynamic forces acting on the links of the USRs, it is necessary to obtain the fluid coefficients experimentally. This paper determines the drag and added mass co-efficients of a general planar model of USRs. In particular, this paper presents methods for identifying fluid parameters based on both computational fluid dynamic (CFD) simulations and several experimental approaches. Additionally, in this paper, we investigate variations of the drag force modelling, providing more accurate representations of the hydrodynamic drag forces. The obtained fluid coefficients are compared to the existing estimates of fluid coefficients for a general model of USRs.

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Section: Fluid Parameter Identification Methodsmentioning

confidence: 99%

Fluid Parameter Identification for Underwater Snake Robots

Kelasidi

Elgenes

Kilvær

2018

Volume 7A: Ocean Engineering

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“…In this work, the impact of these nonlinear effects is firstly discussed in analytical terms, and the corresponding effect on the performance of the covariance-driven stochastic subspace identification (SSI-COV) [11], a parametric method in the time domain that tries to identify a discrete state-space model from the recorded response [12], is evaluated. It should be noted that the purpose of this work is not to characterise these sources per se, but rather to illustrate the impact that these may have in output-only identification methods (see, for instance, [13,14] for a discussion regarding the application of nonlinear modal analysis to the complex nonlinear dynamics of an offshore structure and their identification, and [15] for an extensive review of nonlinear damping identification). The document is organised as follows: firstly, a brief description of the damping model used to represent the phenomenon on floating wind turbines is given, and preliminary considerations based on simple energy laws are presented.…”

Section: Introductionmentioning

confidence: 99%

On the Effect of Nonlinear Damping Sources in Output-Only Identification Methods Applied to Floating Wind Turbines

Pimenta,

Pedrelli,

Vanelli

et al. 2024

Energies

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Output-only methods for modal identification are only strictly valid if a set of requirements are fulfilled regarding both structural and environmental conditions. A particularly challenging effect in wind turbine dynamics is the significant presence of nonlinear damping sources coming from aerodynamic forces and, in offshore applications, hydrodynamic forces on the substructure. In this work, the impact of these terms is firstly discussed in analytical terms, and then the corresponding effect on the performance of the covariance-driven stochastic subspace identification is evaluated on a single-degree-of-freedom model. The analysis is then extended to a full hydro-aeroelastic simulation of a 5 MW floating wind turbine using the open source software OpenFAST, mimicking the structural response in free decay tests and in parked conditions with turbulent wind fields. The results show that output-only identification methods are applicable in these challenging scenarios, but the results obtained must be carefully interpreted, since their dependence on the environmental conditions and motion amplitude imply that they are not directly translated into the structure properties, although still closely related to them.

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“…Numerical investigation using several wave force models and validation with experiments identified the best suited wave force model, which is a combination of potential theory based wave loading on the hullcolumn entity and Morison-type wave loading on the slender cantilevering arms and tethers. Liagre and Niedzwecki (2006) presented the non-linear coupled dynamic response of a deepwater mini TLP considering non-linear stiffness, quadratic damping, surge-pitch and sway-roll coupling. In addition, behaviour of hydrodynamic added-mass and damping coefficient was simulated using an industry standard diffractionradiation software package.…”

Section: Introductionmentioning

confidence: 99%