GZ
Gesa Ziemer
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3 records found
1
Conference paper
(2021)
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Knut V. Høyland, Torodd Skjerve Nord, Joshua Turner, Vegard Hornnes, Ersegun Deniz Gedikli, Morten Bjerkås, H. Hendrikse, T.C. Hammer, Gesa Ziemer
In the FATICE project we have addressed the fatigue damage on fixed offshore structures exposed to drifting ice. This is an important challenge in the development of energy production from offshore wind in the Baltic and involves at least five element: a) define ice statistics, b) predict the structural response (ice-structure interaction simulations), c) estimate the fatigue damage and d) carry out scale-model tests. We have used the Copernicus database and simple analytical equations to define the large-scale ice statistics and studied down-scaling to structural scale by comparing with ice load data on the Norströmsgrund lighthouse (LOLEIF and STRICE data). The VANILLA model allows for ice-structure interaction simulations and has been validated against the full-scale LOLEIF and STRICE data and against the model-scale ice in HSVA. The fully coupled and the traditional methods are compared. In the fatigue estimations studies the assumption of linear damage accumulation is challenged and load combinations from wave, wind and ice studied by assessing simulated time-series of the different loads. The main results is that sea ice cause the higher loads than wind and waves do , but the cumulative frequency of ice loads is much smaller than for wind and waves. The traditional model-scale ice tends to be too soft and/or too viscous so that a realistic breaking pattern combined with realistic force-time series is not been obtained for large aspect ratios. HVA has developed a crushing model ice (ICMI) in which the ice crystals are larger and the texture more uniform.
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In the FATICE project we have addressed the fatigue damage on fixed offshore structures exposed to drifting ice. This is an important challenge in the development of energy production from offshore wind in the Baltic and involves at least five element: a) define ice statistics, b) predict the structural response (ice-structure interaction simulations), c) estimate the fatigue damage and d) carry out scale-model tests. We have used the Copernicus database and simple analytical equations to define the large-scale ice statistics and studied down-scaling to structural scale by comparing with ice load data on the Norströmsgrund lighthouse (LOLEIF and STRICE data). The VANILLA model allows for ice-structure interaction simulations and has been validated against the full-scale LOLEIF and STRICE data and against the model-scale ice in HSVA. The fully coupled and the traditional methods are compared. In the fatigue estimations studies the assumption of linear damage accumulation is challenged and load combinations from wave, wind and ice studied by assessing simulated time-series of the different loads. The main results is that sea ice cause the higher loads than wind and waves do , but the cumulative frequency of ice loads is much smaller than for wind and waves. The traditional model-scale ice tends to be too soft and/or too viscous so that a realistic breaking pattern combined with realistic force-time series is not been obtained for large aspect ratios. HVA has developed a crushing model ice (ICMI) in which the ice crystals are larger and the texture more uniform.
Pressures at the ice-structure interface during model-scale ice-structure interaction are often measured with tactile sensors. Resulting datasets usually include large volume of data along with some measurement error and noise; therefore, it is inherently hard to extract the hidden fluctuating pressures in the system. Identifying the deterministic pressure fluctuation in ice-induced vibrations is essential to understand this complex phenomenon better. In this paper, we discuss the use of two different multivariate analysis techniques to decompose an ensemble of measured pressure data into spatiotemporal modes that gives insights into pressure distributions in ice-induced vibrations. In particular, we use proper-orthogonal decomposition (POD) and inexact robust principal component analysis (IRPCA) in conjunction with measurements of intermittent crushing at different ice speeds. Both decompositions show that most of the energy is captured in a ten-dimensional space; however, the corresponding eigenvalues are different between the decompositions. While POD-based modes have low energy contributions at the first subspace dimensions, IRPCA-based modes have larger energy contributions. This result is consistent with the reconstruction of the time history of the pressure sum using first three empirical modes, where POD and IRPCA-based modes yield similar accuracy at the same subspace dimension. Although both methods successfully illustrate the dominant pressure modes that are active in the system, IRPCA method is found to be more effective than POD in terms of differentiating the contribution of each mode because of its ability to better separate low-rank and sparse components (measurement error and/or noise) in the dataset.
...
Pressures at the ice-structure interface during model-scale ice-structure interaction are often measured with tactile sensors. Resulting datasets usually include large volume of data along with some measurement error and noise; therefore, it is inherently hard to extract the hidden fluctuating pressures in the system. Identifying the deterministic pressure fluctuation in ice-induced vibrations is essential to understand this complex phenomenon better. In this paper, we discuss the use of two different multivariate analysis techniques to decompose an ensemble of measured pressure data into spatiotemporal modes that gives insights into pressure distributions in ice-induced vibrations. In particular, we use proper-orthogonal decomposition (POD) and inexact robust principal component analysis (IRPCA) in conjunction with measurements of intermittent crushing at different ice speeds. Both decompositions show that most of the energy is captured in a ten-dimensional space; however, the corresponding eigenvalues are different between the decompositions. While POD-based modes have low energy contributions at the first subspace dimensions, IRPCA-based modes have larger energy contributions. This result is consistent with the reconstruction of the time history of the pressure sum using first three empirical modes, where POD and IRPCA-based modes yield similar accuracy at the same subspace dimension. Although both methods successfully illustrate the dominant pressure modes that are active in the system, IRPCA method is found to be more effective than POD in terms of differentiating the contribution of each mode because of its ability to better separate low-rank and sparse components (measurement error and/or noise) in the dataset.
Vertically sided offshore structures subjected to level ice are designed to withstand the effects of ice-induced vibrations. Such structures are, for example, offshore wind turbines on monopile foundations, multi-legged oil- and gas platforms or lighthouses. For the prediction of dynamic interaction between ice and structures, several phenomenological models exist. The main challenge with these models is the limited amount of data available for validation, which makes it difficult to determine their applicability. In this study, an attempt is made to validate one of the existing models. First, the parameters which define the ice in the model were derived from new model-scale experiments with a rigid rectangular structure. The model was subsequently applied to simulate the interaction between ice and two compliant rectangular structures with different structural properties. Finally, model-scale experiments were conducted for the two compliant structures. Results of the experiments and model were compared to assess the capability of the model to predict dynamic ice-structure interaction. Results show that the adopted approach allows for a definition of the input parameters of the model and accurate prediction of frequency lock-in and continuous brittle crushing for compliant structures. Intermittent crushing was not observed in the model-scale experiments due to the model-scale ice bending significantly during low ice speeds. As a consequence, the model could not be validated for this regime of interaction. The approach followed and challenges encountered during its application are discussed.
...
Vertically sided offshore structures subjected to level ice are designed to withstand the effects of ice-induced vibrations. Such structures are, for example, offshore wind turbines on monopile foundations, multi-legged oil- and gas platforms or lighthouses. For the prediction of dynamic interaction between ice and structures, several phenomenological models exist. The main challenge with these models is the limited amount of data available for validation, which makes it difficult to determine their applicability. In this study, an attempt is made to validate one of the existing models. First, the parameters which define the ice in the model were derived from new model-scale experiments with a rigid rectangular structure. The model was subsequently applied to simulate the interaction between ice and two compliant rectangular structures with different structural properties. Finally, model-scale experiments were conducted for the two compliant structures. Results of the experiments and model were compared to assess the capability of the model to predict dynamic ice-structure interaction. Results show that the adopted approach allows for a definition of the input parameters of the model and accurate prediction of frequency lock-in and continuous brittle crushing for compliant structures. Intermittent crushing was not observed in the model-scale experiments due to the model-scale ice bending significantly during low ice speeds. As a consequence, the model could not be validated for this regime of interaction. The approach followed and challenges encountered during its application are discussed.