EU urgently needs to increase the development of secure and green energy, and this includes renewables such as Offshore wind energy. An expansion of Offshore wind will include the Baltic where sea ice is one of the major uncertainties. To ensure that the wind turbines are safe for people and the environment, while keeping them economically competitive betterguidelines and regulations should be developedcollaboratively by European industry and academia. There are unsolved challenges with respect to ice action on structures for offshore wind. However, in the current draft for Horizon Europe WorkProgramme 2023-2024 on Climate, Energy and Mobility1, the challenges related to sea ice with regards toOffshore wind energy are not mentioned. In order to meet the crucial green energy goals, it is our statement that it is imperative to include sea ice in the final version.

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EU urgently needs to increase the development of secure and green energy, and this includes renewables such as Offshore wind energy. An expansion of Offshore wind will include the Baltic where sea ice is one of the major uncertainties. To ensure that the w ind turbines are safe for people and the environment, while keeping them economically competitive better guidelines and regulations should b e developed collaboratively by European industry and academia. There are unsolved challenge s with respect to ice action on structures for offshore wind. However, in the current draft for Horizon Europe Work Programme 2023-2024 on Climate, Energy and Mobility1, the challenges related to sea ice with regards to Offshore wind energy are not mentioned. In order to meet the crucial green energy goals, it is our statement that it is imperative to include sea ice i n the final version.@en

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.@en

The authors regret their mistake in the definition of the model parameters in Eq. (8) on page 277. The correct equation for the parameter C ₂ is: C2=Ft3/N3vt The authors would like to apologise for any inconvenience caused.

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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.@en

Identifying the modal parameters of structures located in ice-infested waters may be challenging due to the interaction between the ice and structure. In this study, both simulated data from a state-of-the-art ice–structure interaction model and measured data of ice–structure interaction were both used in conjunction with a covariance-driven stochastic subspace identification method to identify the modal parameters and their corresponding variances. The variances can be used to assign confidence to the identified eigenfrequencies, and effectively eliminate the eigenfrequencies with large variances. This enables a comparison between the identified eigenfrequencies for different ice conditions. Simulated data were used to assess the accuracy of the identified modal parameters during ice–structure interactions, and they were further used to guide the choice of parameters for the subspace identification when applied to measured data. The measured data consisted of 150 recordings of ice actions against the Norströmsgrund lighthouse in the Northern Baltic Sea. The results were sorted into groups defined by the observed ice conditions and governing ice failure mechanisms during the ice–structure interaction. The identified eigenfrequencies varied within each individual group and between the groups. Based on identified modal parameters, we suggested which eigenmodes play an active role in the interaction processes at the ice–structure interface and discussed the possible sources of errors.

This article is part of the theme issue ‘Environmental loading of heritage structures’.@en

Interaction of sea or lake ice with vertically sided offshore structures may result in severe structural vibrations commonly referred to as ice-induced vibrations. With the surge in offshore wind developments in sub-arctic regions this problem has received increased attention over the last decade, whereas traditionally the topic has been mainly associated with lighthouses and structures for hydrocarbon extraction. It is important for the safe design of these offshore structures to have the ability to predict the interaction between ice and structure in an expected scenario. A model for simulation of the interaction between a drifting ice floe and a vertically sided offshore structure is presented. The nonlinear speed dependent ductile and brittle deformation and local crushing of ice are considered phenomenologically. A one-dimensional sea ice dynamics model is applied to incorporate the effects of floe size, wind and current. The structure is modelled by incorporating its modal properties obtained from a general-purpose finite element software package. Alternatively, the model can be coupled to in-house design software for fully coupled simulations. Examples of application of the model to simulate dynamic ice-structure interaction are provided. Simulation results are validated with public data from forced vibration experiments, small-scale intermittent crushing and frequency lock-in, and full-scale interaction with the Norströmsgrund lighthouse. Effects of floe size and environmental driving forces on the development of ice-induced vibrations in full-scale are studied. It is shown that sustained frequency lock-in vibrations of the structure can only develop for very specific combinations of environmental driving forces and ice floe size. In all other cases, the ice floe slows down and comes to a stop, or accelerates to a drift speed which exceeds the range where frequency lock-in develops. This results in only a few cycles of vibration per interaction event, such as observed for the Norströmsgrund lighthouse in the Baltic Sea.@en

The traditional wind load assessment for long-span bridges rely on assumed models for the wind field and aerodynamic coefficients from wind tunnel tests, which usually introduces some uncertainties. It is therefore desired to develop tools that can utilize full-scale vibration response data from existing bridges in order to study the wind loading in detail for in-situ conditions. This paper presents a novel case study of inverse identification of dynamic wind loads on the 1310 m long Hardanger bridge, a suspension bridge equipped with a network of accelerometers. The identification method used is an extented Kalman-type filter for joint input, state, and parameter estimation. A system model considering the still-air modes in addition to a quasi-steady submodel for the self-excited forces of the bridge is presente. The coefficients for self-excited lift and pitching moment are considered unknown and are jointly estimated with the buffeting forces.

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Numerical predictions of the dynamic response of complex structures are often uncertain due to uncertainties inherited from the assumed load effects. Inverse methods can estimate the true dynamic response of a structure through system inversion, combining measured acceleration data with a system model. This article presents a case study of full-field dynamic response estimation of a long-span floating bridge: the Bergøysund Bridge in Norway. This bridge is instrumented with a network of 14 triaxial accelerometers. The system model consists of 27 vibration modes with natural frequencies below 2 Hz, obtained from a tuned finite element model that takes the fluid-structure interaction with the surrounding water into account. Two methods, a joint input-state estimation algorithm and a dual Kalman filter, are applied to estimate the full-field response of the bridge. The results demonstrate that the displacements and the accelerations can be estimated at unmeasured locations with reasonable accuracy when the wave loads are the dominant source of excitation.

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The signature and occurrence of frequency lock-in (FLI) vibrations of full-scale offshore structures are not well understood. Although several structures have experienced FLI, limited amounts of time histories of the responses alongside measured met-ocean data are available in the literature. This paper presents an analysis of 61 measured events of resonant vibrations of the Norströmsgrund lighthouse from 2001 until 2003. The vibrations of most of these events did not reach a steady state; thus, they violate an often-quoted criterion for frequency lock-in vibrations and remain outside any modes of ice-induced vibrations suggested in standards. Met-ocean data from both in situ measurements and from the Copernicus marine service information database are further used to better understand the occurrence of resonant ice-induced vibrations. All events between 2001 and 2003 occurred during days with ice concentrations of 8–10/10, closely packed consolidated drift ice. The locally measured ice velocity and thickness ranged from 0.023 to 0.075 m s⁻¹ and from 0.26 to 1.9 m, respectively. These measurements included level ice, rafted ice and ridged ice. The events of resonant vibrations are further compared with measurements from the same structure between 1979 and 1988. Most events of resonant vibrations were recorded in the winter of 1988, followed by the winters of 2003 and 1980. The winter of 1988 had fewer freezing degree days (FDD) than the 65-year average, whereas the winters of 2003 and 1980 had more FDD than the 65-year average.

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The sea ice interaction with a structure may cause system changes and affect the feasibility of common approaches to track modal parameters. In this paper, a covariance-driven stochastic subspace identification method is used to identify the natural frequencies from 190 time series of ice actions against a lighthouse structure. The results are sorted into groups defined by the observed ice conditions and governing ice failure mechanisms during the ice-structure interaction. The identified natural frequencies vary substantially within each individual group and between the groups. Recordings with flexural failures and a north-south ice-drift direction consistently rendered the same identified frequencies, whereas crushing seemed to create large amounts of variability in the identified frequencies. The results show the need for more high-fidelity data to assess whether modern system identification methods can be used to monitor system changes and support decision-making for operations of structures in ice-infested waters, such as offshore wind structures.

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Ice forces on bottom-founded structures can be measured by load panels or identified from response measurements. This paper presents a comparison between the measured and identified dynamic ice forces acting on the Nordströmsgrund lighthouse. The dynamic ice forces are identified from the measured responses using a recently developed joint input-state estimation algorithm in conjunction with a reduced-order finite element model. A convincing agreement between the measured and identified forces was found. The response predictive ability of the algorithm is further used to estimate the response of the structure at unmeasured locations including at the ice-action point.

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Knowledge of excitation loads on bridges are important for reliable design. Load models are however prone to uncertainties. Force identification using dynamic response measured on full-scale structures can be used to reduce the
uncertainty. In this contribution, numerical simulations are performed to examine the feasibility of force identification on the floating pontoon Bergsoysund Bridge. We present a practical case study in which wave excitation forces and motion
induced forces are estimated using only acceleration output. The sensor network considered represents the monitoring system currently installed on the bridge. A reduced order model with 26 modes is used to represent the structure in the identification. Wave force time series are generated by Monte Carlo simulations, and the acceleration response is obtained from a frequency domain solution of the equations of motion. The generated acceleration data is polluted with noise and subsequently used for identification. The results show that a joint input-state estimation algorithm is able to adequately identify a subset of hydrodynamic forces acting on the pontoons in the presence of both measurement and model errors. The translational forces are identified with a larger accuracy than the moments. Lastly, considerations and improvements for an analysis with experimental field data are presented.@en

The Norwegian Public Roads Administration is reviewing the possibility of using floating bridges as fjord crossings. The dynamic behaviour of very long floating bridges with novel designs are prone to uncertainties. Studying the dynamic behaviour of existing bridges is valuable for understanding the in-situ performance. We present a case study of the Bergsøysund Bridge, a 840 m long floating pontoon bridge located in Norway. An extensive monitoring system is installed on the bridge, including a network of accelerometers. A finite element model of the bridge is established. Using the measured acceleration output and recently developed Kalman filter based methods (a joint input-state (JIS) estimation algorithm and a dual Kalman filter (DKF)), we estimate accelerations at unmeasured locations. It is shown that the estimated response from the DKF agrees well with direct reference measurements. For the JIS, numerical instabilities in the estimates occur due to ill-conditioning of the matrices used in the system inversion.@en

A simplified model of a typical bottom-founded structure was forced through ice sheets in a laboratory experiment to study ice-induced vibrations. The ice forces exerted on the structure are identified in conjunction with the response of the entire structure using a joint input-state estimation algorithm. Novel insights into iceinduced vibration phenomena are obtained by comparing, on different time scales, measured and estimated response quantities and forces/pressures. First, the identified forces, ice velocities and time-frequency maps of the measured responses are presented for a series of ice-induced vibration tests. It is shown that the ice forces excite more than onemode of the structure and that the transition ice velocity atwhich the vibrations shift fromthe first to the second mode increases with reduced foundation stiffness and reduced superstructure mass. Second, a detailed analysis of the interaction between the structure and the ice edge is performed on a smaller time scale by comparing the locally measured pressures at the ice-structure interface to the identified structural responses and forces. It is shown that structural vibrations at a frequency higher than the dominant vibration frequency cause cyclic loading of the ice edge during intermittent crushing. These vibrations led to an increasing loading rate prior to ice failure. During an event that shows the tendencies of frequency lock-in vibrations, the structural response was dominated by a single vibration frequency. @en

A measurement campaign at the Hanko-1 channel marker in the Gulf of Finland is planned in order to monitor the forces leading to ice-induced vibrations by means of force identification. It is planned to identify the ice forces using a joint input-state estimation algorithm in conjunction with a modally reduced order model. The methodology is presented together with a finite element model and a detailed analysis that determines the optimal sensor network. The novel approach used to determine the optimal response measurement types and locations ensures the identifiability of the dynamic ice forces from only a limited number of sensors and a selection of vibration modes. The optimal sensor locations are discussed in view of specific challenges posed by the arctic environment.
INTRODUCTION@en