Key Engineering Materials Vols. 569-570

Abstract: Understanding the dynamic behaviour of offshore wind and wave energy devices is extremely important in relation to the maintenance and management of these marine assets. Since experimentation in sea may often be difficult, expensive or unnecessary at a conceptual or at pre-commercial stage, scaled experimentation in wave tanks can be central to the understanding and assessment of their dynamic responses. This paper presents scaled dynamic testing in a wave tank of a tension leg platform for supporting a wind turbine for different regular wave conditions and sea states characterised by the Bretschneider spectra. The dynamic response of the device was monitored at different locations on the device using load cells and with a camera based motion recognition system. For the analysis, a frequency response function based approach was considered to illustrate the response of the device under varied wave loading conditions. The experimentation does not assume any underlying theoretical model, apart from the consideration of Froude scaling conditions to attempt to link experimentation conditions with actual conditions. The results are important for characterisation of theoretical models and fitting parameters of such theoretical models, while identifying the limits and potential challenges of applying linear dynamic analysis in these situations. The findings are also important for establishing system identification and control strategies for undesirable levels of dynamic response. The fitted models based on physical modelling, when combined with scaled experimental responses, can also be helpful in better estimating extreme responses of the devices.

Abstract: In analyzing stochastic dynamic systems, analysis of the system uncertainty due to randomness in the loads plays a crucial role. Typically time series of the stochastic loads are simulated using traditional random phase method. This approach combined with fast Fourier transform algorithm makes an efficient way of simulating realizations of the stochastic load processes. However it requires many random variables, i.e. in the order of magnitude of 1000, to be included in the load model. Unfortunately having too many random variables in the problem makes considerable difficulties in analyzing system reliability or its uncertainty. Moreover applicability of the probability density evolution method on engineering problems faces critical difficulties when the system embeds too many random variables. Hence it is useful to devise a method which can make realization of the stochastic load processes with low, say less than 20, number of random variables. In this article we introduce an approach, so-called "physical modeling of stochastic processes", and show its applicability for simulation of the wave surface elevation.

Abstract: The aim of this study is to present an efficient and accurate method for estimation of the failure probability of wind turbine structures which work under turbulent wind load. The classical method for this is to fit one of the extreme value probability distribution functions to extracted maxima of the response of wind turbine. However this approach may contain high amount of uncertainty due to arbitrariness of the data and the distributions chosen. Therefore less uncertain methods are meaningful in this direction. The most natural approach in this respect is the Monte Carlo (MC) simulation. This however has no practical interest due to its excessive computational load. This problem can alternatively be tackled if the evolution of the probability density function (PDF) of the response process can be realized. The evolutionary PDF can then be integrated on the boundaries of the problem, i.e. the exceedance threshold of the response, which results in the accurate values of the failure probability. For this reason we propose to use the probability density evolution method (PDEM). PDEM can alternatively be used to obtain distribution of the extreme values of the response process by simulation. This approach requires less computational effort than integrating the evolution of the PDF; but may have less accuracy. In this paper we present the results of failure probability estimation by the PDEM. The results will then be compared to the extrapolated values from the extreme value distribution fits to the samples response values.

Abstract: The identification of the operational Wind Turbine (WT) dynamics is a challenging problem, due to both the complex dynamics and the non-stationarity of the vibration response. In this study the novel class of Generalized Stochastic Constraint (GSC) Time-dependent ARMA models is used for the identification of the non-stationary characteristics of acceleration vibration signals acquired in the tower top of an operating WT, in the fore-aft and lateral directions. The results demonstrate the improved performance of GSC-TARMA models compared to their conventional Smoothness Priors (SP) and Functional Series (FS) counterparts. The obtained models confirm the presence of cyclo-stationary and broader non-stationary behavior in WT vibration. The model based frozen time-varying modes of vibration are analyzed, and the modal components of the vibration accelerations are pictorially presented on the plane defined by the fore-aft and lateral axes.

Abstract: A vital aspect of ensuring the cost effectiveness of wave energy converters (WECs) is being able to monitor their performance remotely through structural health monitoring, as these devices are deployed in very harsh environments in terms of both accessibility and potential damage to the devices. The WECs are monitored through the use of measuring equipment, which is strategically placed on the device. This measured data is then compared to the output from a numerical model of the WEC under the same ocean wave conditions. Any deviations would suggest that there are problems or issues with the WEC. The development of accurate and effective numerical models is necessary to minimise the number of times the visual, or physical, inspection of a deployed WEC is required. In this paper, a numerical wave tank model is, first, validated by comparing the waves generated to those generated experimentally using the wave flume located at the National University of Ireland, Galway. This model is then extended so it is suitable for generating real ocean waves. A wave record observed at the Atlantic marine energy test site has been replicated in the model to a high level of accuracy. A rectangular floating prism is then introduced into the model in order to explore wave-structure interaction. The dynamic response of the structure is compared to a simple analytical solution and found to be in good agreement.

Abstract: The aim of the present paper is to evaluate structural health monitoring (SHM) techniques based on modal analysis for crack detection in small wind turbine blades. A finite element (FE) model calibrated to measured modal parameters will be introduced to cracks with different sizes along one edge of the blade. Changes in modal parameters from the FE model are compared with data obtained from experimental tests. These comparisons will be used to validate the FE model and subsequently discuss the usability of SHM techniques based on modal parameters for condition monitoring of wind turbine blades.

Abstract: This paper presents an investigation on the combined effect of dynamic stall and rotational augmentation on wind turbine blades. Dynamic stall and rotational augmentation have previously been studied independently. The NREL Phase VI experiment was one large scale experiment that recorded 3D measurements on rotating and pitching airfoils, and using some these data the behaviour of the unsteady CL-α polars under the influence of rotation is investigated. Unsteady DES CFD computations of the Phase VI rotor in axial operation and continuous pitching conditions (reproducing conditions similar to the N-sequence experiments) for select cases have also been carried out using the in-house flow solver EllipSys3D. The resulting set of CL-α curves for the airfoils in rotation operating at various values of the frequency, the mean, and the amplitude of the angle of attack resulting from the CFD computations as well as those from the experiments are presented and discussed. Qualitative differences between dynamic stall occurrence on rotating and stationary airfoils are highlighted, procedures employed to extract the mean angle of attack from the available experimental data are discussed, and comments are made on the application of dynamic stall models in conjunction with 3D augmentation models on the rotating wind turbine blades.

Abstract: Damage Detection problem in Structural Health Monitoring (SHM) is widely studied by many researchers, therefore lots of damage detection algorithms can be found in the literature. Feature Selection / Extraction methods are essential in the accuracy of these algorithms, they provide the suitable data to be used. The main goal of this work is to improve the input data to be the most representative for the damage detection problem. This is done using different Feature Selection / Extraction methods (PCA, UmRMR, and a combination of both). After taking the representative features, the results are tested using a damage detection method; the NullSpace in this case. The data has been collected from a Laboratory Offshore tower model. The different results are compared (different preprocessing vs Raw data) and these show how the correct preselection of the data can improve damage detection.

Abstract: The aim of the present paper is to provide a state-of-the-art outline of structural health monitoring (SHM) techniques, utilizing temperature, noise and vibration, for wind turbine blades, and subsequently perform a typology on the basis of the typical 4 damage identification levels in SHM. Before presenting the state-of-the-art outline, descriptions of structural damages typically occurring in wind turbine blades are provided along with a brief description of the 4 damage identification levels.

Abstract: In this paper an overview about floating offshore wind turbines (FOWT) including operating conditions, property and applicability of the barge, tension-leg, and spar floating platforms is described. The spar-floating offshore wind turbines (S-FOWT) have advantages in deepwater and their preliminary design, numerical modeling tools and integrated modeling are reviewed. Important conclusions about the nacelle and blade motions, tower response, effects of wind and wave loads, overall vibration and power production of the S-FOWT are summarized. Computationally-simplified models with acceptable accuracy are necessary for feasibility and pre-engineering studies of the FOWT. The design needs modeling and analysis of aero-hydro-servo dynamic coupling of the entire FOWT. This paper also familiarizes authors with FOWT and its configurations and modeling approaches.