Search

Offshore wind power is a kind of important clean renewable energy and has attracted increasing attention due to the rapid consumption of non-renewable energy. To reduce the high cost of energy, a possible try is to utilize the combination of wind and wave energy considering their natural correlation. A combined concept consisting of a semi-submersible wind turbine and four torus-shaped wave energy converters was proposed and numerically studied under normal operating conditions. However, the dynamic behavior of the integrated system under extreme sea conditions has not been studied yet. In the present work, extreme responses of the integrated system under two different survival modes are evaluated. Fully coupled time-domain simulations with consideration of interactions between the semi-submersible wind turbine and the torus-shaped wave energy converters are performed to investigate dynamic responses of the integrated system, including mooring tensions, tower bending moments, end stop forces, and contact forces at the Column-Torus interface. It is found that the addition of four tori will reduce the mean motions of the yaw, pitch and surge. When the tori are locked at the still water line, the whole integrated system is more suitable for the survival modes. [ABSTRACT FROM AUTHOR]

[Introduction] The research aims to explore the integrated calculation method of a 10 MW semi-submersible floating wind turbine, and analyze its coupled dynamic response characteristics in 40～50 m offshore deep water areas. [Method] A 10 MW concrete semi-submersible floating wind turbine was taken as an example, and then numerical calculation was carried out by the integrated calculation method, and its coupled dynamic response under rated and survival conditions was statistically analyzed. [Result] The horizontal motion of the platform is mainly affected by the wave force, wind loading and mooring stiffness. The maximum value of motion and mooring tension occur in the survival condition, and the heave motion is mainly affected by the wave, but the mean value of the pitch/roll motion is mainly affected by the wind loading, all of which meet the design specification. [Conclusion] The integrated calculation method better considers the coupled dynamic behavior of floating wind turbines. Due to the limitation of water depth, the optimization of horizontal motion and mooring nonlinearity of offshore floating wind turbines is more important in offshore deep water areas, and the extreme response mainly occurs in survival conditions. The above conclusions provide an important reference for the research and design of the floating offshore wind turbines in offshore deep water area.

• An efficient approach is explored to evaluate the extreme response and reliability of train-bridge interaction system. • The extreme response of an innovative railway integral bridge considering various stochastic excitations is studied. • The failure probability of high-speed train running safety conditional on wind speed and running speed is assessed. • The in-site long-term wind field measured data are applied to improve the assessment accuracy. The randomness of responses in a train-bridge interaction (TBI) system induced by stochastic track irregularity and crosswind has been addressed. However, the extreme value distribution (EVD) and reliability prediction of TBI system are little known. Due to the complexity of TBI system, the prediction approach is critical to the issues of extreme value and reliability evaluation, involving the computational accuracy and efficiency. Thus, the Monto Carlo-based global maximum method, probability density evolution-based virtual time process method (VPM), and average conditional exceeding rate method (ACERM) are considered in this study. The optimal approach for the EVD prediction of bridge buffeting responses and the TBI system with or without the consideration of crosswinds is identified. An innovative 3 × 70 m integral bridge is chosen as the study case, which is an emerging type of bridge structures used in the Chinese high-speed railway lines. Its extreme responses under the single and dual stochastic excitations of track irregularity and wind turbulence are fully investigated in this study. The study results show that the VPM and ACERM are efficient and accurate to evaluate the extreme responses of a TBI system. The ACERM is recommended in assessing the train running safety due to its high computational efficiency and reasonable accuracy. When the crosswind is not a consideration, the high-speed train running safety can be ensured with high probability if the train travels on the integral bridge below the design speed of 350 km/h. However, the failure probability of wheel-rail lateral contact forces reaches 51% if predicted under the mean wind speed of 30 m/s and train speed of 120 km/h. Finally, the advantages of the integral bridge over conventional bridges (e.g., continuous girder bridge) are discussed. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aquaculture structures are being installed in progressively exposed locations, and reliable estimation of extreme net forces with return periods from 50–10000 years becomes increasingly important. As state-of-the-art methods are complex and computationally time-consuming, a simplified, but efficient method for the calculation of net forces is used. This method is verified against simulations with the SIMA software, which include a state-of-the-art load model. The simplified method, developed for regular waves, is further extended to irregular seas in the present study. Extreme forces in the ropes that support the net and transfer the net forces to the steel structure are estimated using a variety of methods ranging from long-term stochastic methods to the simpler design wave method, which is currently the industry standard. The accuracy of the design wave method is evaluated against the more advanced methods. The study showed that the computation time of the simplified method is approximately 1:30 of the advanced method. • A simplified method estimating the forces in the ropes supporting the aquaculture net under the action of wave and current is generalised to allow for irregular waves. • Comparison of extreme value estimation methods for aquaculture net force. • Long term stochastic analysis, Peak over threshold, block maxima and all sea state method. [ABSTRACT FROM AUTHOR]

With the advancement of monitoring technologies for offshore structures, sensor data are becoming increasingly available in real-time. The objective of this paper is to develop fast methods for reliability assessment of offshore structures for the extreme and fatigue failure modes, based on the latest real-time sensor data, assumed to be four months. The continuously updated assessment informs operators on the failure probability over the next few years. Reliability analysis using real-time data is challenging owing to the need to extrapolate the observed data to more severe sea states and across many orders of magnitudes of probabilities, and there is a lack of related studies. Here, the environment comprises the short-term and long-term wave characteristics. Three data-driven reliability approaches are developed for three types of wave sensor data. The first approach applies statistical models to the response when wave data are unavailable. The second relies on Gaussian Process Regression (GPR) when only the wave spectral parameters are known. The third applies the Gaussian-experienced NARX network to predict the response time series when the wave time series are recorded. The proposed approaches are applied to a jack-up platform, and implementation of benchmark reliability analysis is enabled by establishing an emulator trained from dynamic simulations for fast generation of synthetic sensor data. The GPR approach is found to show good extrapolation capabilities and able to provide relatively accurate and robust reliability predictions. • Reliability analysis of offshore structures over next few years from sensor data. • Predicting the failure probability due to extreme response and fatigue damage. • Three new methods proposed according to availability of wave data. • Case studies use a data-driven emulator trained from dynamic simulations. • Gaussian Process Regression method works well for extreme and fatigue reliability. [ABSTRACT FROM AUTHOR]

With the increasing application of floating platforms in deep waters and harsh environments, a proper assessment of the reliability of floating structures is important to ensure that these structures can operate safely during their design lives. This study outlines a practical methodology for reliability analysis of a semi-submersible platform based estimating the probability distribution of the extreme response in rough sea conditions (survival conditions). The Constrained NewWave (CNW) theory combined with Monte Carlo simulations was first applied to simulate the random wave surface elevation process in the time domain. A Gumbel distribution was the best fitting to describe the dynamically sensitive extreme response statistics under extreme waves (drift and mooring tension). The derived probability distribution of the extreme response was subsequently used in estimation of the associated limit state function, and a reliability analysis of the floating structure was conducted using the Monte Carlo method. A semi-submersible platform in a water depth of 1500 m subjected to extreme wave loads was used to demonstrate the efficiency of the proposed methodology. The probability of failure of the semi-submersible when considering mooring lines tension is greater than considering drift. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Optimal wave energy control is noncausal as the control command is optimized based on incoming wave force. Therefore, implementation of wave energy control requires forecasting of future wave force. A real-time latching control algorithm based on short-term wave force prediction is developed in this study to tackle such noncausality. The future wave forces are forecasted using a gray model. The receding horizon strategy is used to optimize the control command online, over the prediction horizon interval. Based on the predicted wave forces, the power extraction is maximized by locking and releasing the buoy alternately according to the optimized control command. Simulation results show that the power extraction is increased substantially with implementation of the developed real-time latching control algorithm, even if the future wave forces are predicted. Effects of prediction length and prediction error on the energy conversion are examined. It is found that more wave energy is harvested when a long prediction length is employed while prediction error decreases the control efficiency. The extreme load of power takeoff system increases when the wave energy control is implemented although its travel distance is hardly varied. [ABSTRACT FROM AUTHOR]

Environmental contour method is an efficient method for predicting the long-term extreme response of offshore structures. The traditional environmental contour is obtained using the joint distribution of mean wind speed, significant wave height, and spectral peak period. To improve the accuracy of traditional environmental contour method, a modified method was proposed considering the non-monotonic aerodynamic behavior of offshore wind turbines. Still, the modified method assumes constant wind turbulence intensity. In this paper, we extend the existing environmental contour methods by considering the wind turbulence intensity as a stochastic variable. The 50-year extreme responses of a monopile-based offshore wind turbine are compared using the extended environmental contour methods and the full long-term method. It is found that both the environmental contour method and the modified environmental contour method, with the wind turbulence intensity included as an individual variable, give more accurate predictions compared with those without. Using the full long-term method as a benchmark, this extended approach could reduce the nonconservatism of the environmental contour method and conservatism of the modified environmental contour method. This approach is effective under wind-dominated or combined wind-wave loading conditions, but may not be as important for wave-dominated conditions. [ABSTRACT FROM AUTHOR]

In this study we compare wave climates and their potential for wave energy conversion for the two energetic but quite different sites of Albany and Orkney. Energy capture is based on the M4 machine with well defined characteristics. The M4 machine is a self reacting system with 3 floats, each float with a circular cross-section when viewed from above. The smaller two floats are rigidly connected by a beam, and the largest float is connected to the mid float by a beam with a hinge. The machine generates power through the relative angular motion of this hinge above the middle float. The machine performance was previously assessed for various locations in the eastern North Atlantic including the European Marine Energy Centre (EMEC) site west of the Orkney Islands, Scotland, for wave power output (Santo et al., 2016a) and extreme response (Santo et al., 2017). In this study, we apply the analysis to a location off Albany on the south coast of western Australia, an area well-known for almost continuous exposure to long period swells. We use Australian Department of Transport (DOT) wave buoy data measured in 60 m of water over the period 2009 − 2017. The hourly data is close to continuous but contains some gaps corresponding to ∼ 13% of the total duration, these are patched to form a continuous wave record. Having sized the machine based on mean wave period, extreme wave height statistical analysis is performed using storm-based identification and a peaks-over-threshold technique, following Santo et al. (2016b), providing information relevant for any wave energy converter at the location. From operability and power scheme economics, we then compare the optimal size of machine, practical power output and the associated variability in power produced by an M4 machine at Albany to the open North Atlantic location off the Orkneys. This is performed with the methodology outlined in Santo et al. (2016a). For survivability, it is important to identify extremes of machine motion. Hence, extreme responses are also compared for the central hinge angle of the machine in survival mode with the power take-off turned off. We find that a much larger machine is required at Albany, because of the longer waves compared to Orkney. However, at the two very different locations the power/cost ratios are similar. [ABSTRACT FROM AUTHOR]

Global climate change models predict an increase in the frequency and intensity of extreme droughts, with uncertain ecological impacts across ecosystems. In particular, it is not clear when extreme droughts will elicit extreme ecological responses.For this study, we employed three complementary approaches to explore the relationships between extreme drought and ecosystem responses. First, we used global data mining to evaluate the relationship between extreme gross primary productivity and extreme precipitation from 1980 to 2013. Second, we conducted a meta‐analysis using 132 drought experiments across the globe to assess the response ratios (RRs) of above‐ground net primary productivity (ANPP) to extreme versus non‐extreme drought treatments. Third, we examined community and ecosystem responses in an alpine meadow to a drought gradient experiment, which included five precipitation treatment levels (1/12 P, 1/4 P, 1/2 P, 3/4 P, and P, where P is the growing season precipitation).This study had three key results. In our historical data mining, we found that extreme droughts elicited extreme ecological responses only 15.1% of the time. The meta‐analysis results indicated that there were no significant differences in the RRs of ANPP between the extreme versus non‐extreme drought treatments. The drought gradient experiment results revealed that although the four drought treatments were statistically extreme, only the most extreme drought treatment (1/12 P) significantly reduced ANPP over the 3 years. Meanwhile, species richness and asynchrony were significantly reduced under the 1/12 P treatment, which led to a significant reduction in productivity.Synthesis. These results suggest that extreme ecological responses to extreme drought may be less frequent than previously thought. But when they do occur, extreme ecological responses may be driven by plant community changes such as species asynchrony, species loss or species reordering. Our experimental results highlight the key role of community dynamics in determining the resistance of ecosystem productivity to extreme drought, which should be assessed when predicting ecological responses to climate change. [ABSTRACT FROM AUTHOR]

Abstract Recent measurements made by our research group of a super-large cooling tower indicate that its fluctuations in wind-induced responses exhibit a degree of nonstationarity, echoing similar observations reported for other structures. This might cause errors in estimates of extreme responses and misunderstanding of wind-induced effects if nonstationarity is neglected. In this study, the wind-induced response signals of a super-large cooling tower (height 190 m) in a coastal region were measured for the first time under real Reynolds number and turbulent flow conditions. After noise reduction had been performed, nonstationarity of the signals was identified within various time intervals. The mean wind effect, pulsating wind effect, probability density distribution, dynamic amplification factor, and extreme responses of the super-large cooling tower were studied based on stationary and non-stationary models. Finally, the power spectral density (PSD) and evolutionary power spectral density (EPSD) of the wind-induced response signal were analyzed. The resonance spectral expression of wind-induced responses at resonance excitation points, which is applicable to super-large cooling towers, is summarized. The wind-induced responses presented strong nonstationarity. Non-stationary models that consider response nonstationarity are important in the authentic assessment of the extreme responses of super-large cooling towers. The extreme constant calculated by the stationary model cannot provide an adequate assurance rate and reduces the economic efficiency of extreme response estimates. The vibration energy distributions of resonance excitation points in different regions of the cooling tower were similar, but the PSD functions at quasi-static points were dramatically different from each other. The energy distribution of the resonant excitation points showed a phased trend, and the proposed resonance spectral expression considers three stages of variation in the PSD function of the responses to achieve high predictive accuracy. Highlights • The wind-induced responses of a super-large cooling tower were acquired through field measurement for the first time. • Non-stationary wind-induced effects of super-large cooling tower were investigated. • Extreme response calculated by stationary model can't provide adequate assurance rate. • The evolutionary power spectral density of wind-induced response was analyzed. • The proposed resonance spectral expression achieves high prediction accuracy. [ABSTRACT FROM AUTHOR]

Abstract A linear model for efficient design evaluation of spar floating wind turbines is presented, and verified against a nonlinear time domain model with regards to long-term fatigue and short-term extreme response for two different spar designs. The model uses generalized displacements and a semi-analytical approach to establish the equations of motion for the system, which are solved in the frequency domain. The results show agreement within ± 30% for the long-term fatigue considering operational conditions, however, the linear fatigue damage estimates are sensitive to the accuracy of the estimated natural frequency of the first bending mode. The results also suggest that a small number of environmental conditions can be simulated with a nonlinear time domain model to verify and possibly tune the linear model, which then can be used to run the full long-term analysis. Short-term extreme tower base bending moments and surge and pitch motions are observed to be nearly Gaussian above cut-out wind speed, as the response is dominated by wave forces. Consequently, the linear model is able to accurately capture the upcrossing rates, which are used to calculate the characteristic largest extreme response. For an operational case near rated wind speed, the response is somewhat non-Gaussian, which gives larger discrepancies between the linear and nonlinear models. However, due to large mean values in this condition, the total error in the extreme response is reduced, and reasonable agreement is achieved. Highlights • A linear frequency domain model for spar floating wind turbines has been developed. • The model has been compared to a nonlinear time domain model. • Good agreement for tower fatigue, but results were sensitive to first bending mode. • The largest short-term extreme response were found near rated wind speed. • Extreme response were nearly Gaussian above cut-out wind-speed. [ABSTRACT FROM AUTHOR]

Abstract Considering the massive simulations required by the full long-term analysis, the environmental contour method is commonly used to predict the long-term extreme responses of an offshore renewable system during life time. Nevertheless, the standard environmental contour method is not applicable to the wind energy device due to the non-monotonic aerodynamic behaviour of the wind turbine. This study presents the development of a modified environmental counter method and its application to the extreme responses of a hybrid offshore renewable system. The modified method considers the variability of the responses by checking multiple contour surfaces so that the non-monotonic aerodynamic behaviour of the wind turbine is considered. The hybrid system integrates a floating wind turbine, a wave energy converter and two tidal turbines. Simulation results prove that the modified method has a better accuracy. Highlights • A modified environmental contour method is presented. The modified method identifies multiple environmental contours. • Extreme responses of an integrated offshore renewable energy system are examined. • The modified method has a higher estimation accuracy. [ABSTRACT FROM AUTHOR]

This study addresses short-term extreme response and fatigue damage of an integrated wind, wave and tidal energy system. The integrated concept is based on the combination of a spar type floating wind turbine, a wave energy converter and two tidal turbines. Aero-hydro-mooring coupled analysis is performed in time-domain to capture the dynamic response of the combined concept in a set of environmental conditions. The mean up-crossing rate method is used to evaluate the extreme response, which takes advantage of an extrapolation method to reduce the simulation sample size. The cumulative fatigue damage is computed based on the S-N method. Simulation results show that the tower base fore-aft bending moment is improved, in terms of extreme value and fatigue damage. Nevertheless, the tension force of a mooring line is worsened. The mooring line bears increased maximum tension due to the tidal turbine thrust force and it is subjected to higher fatigue damage load as well. [ABSTRACT FROM AUTHOR]

This paper presents a computer efficient approach to evaluate the multi-dimensional integral found in the evaluation of the long-term extreme response of marine structures. The proposed method is a hybrid combination of two numerical procedures. The first one consists of a parabolic interpolation scheme used to obtain the statistical parameters describing the short-term peaks probability distribution of the time-series responses, designated as PIM (Parabolic Interpolation Method), which reduces the total number of short-term structural analyses. The second one is an Artificial Neural Network-based surrogate model which is used to obtain long response time histories based on short finite element-based simulations. The approach is named as HPI-ANNM (Hybrid Parabolic Interpolation – Artificial Neural Network Method). The efficiency and accuracy of the proposed hybrid method is compared with the complete long-term integration method in the analysis of 100-yr characteristic values of cross-section utilization ratios of a Steel Catenary Riser (SCR) connected to a semi-submersible platform in deep water. [ABSTRACT FROM AUTHOR]

This study addresses analysis of the crosswind response of tall buildings under nonstationary wind excitations. The wind load under nonstationary wind excitation was quantified using the force parameters under stationary wind, but the effect of the time-varying mean wind speed was considered in a quasi-stationary manner. For buildings without consideration of nonlinear aerodynamic damping, the evolutionary spectral analysis approach and statistical moment equation approach are presented, which provide analytical solutions of time-varying response standard derivation (STD), extreme response, and fatigue damage. For buildings with consideration of nonlinear aerodynamic damping, the governing equations of statistical moments of the building motion including time-varying STD, or variance/covariance, and kurtosis of response were established and solved using the non-Gaussian moment closure technique. The higher-order moments involved were estimated from a kurtosis-based translation process model. Narrowband response characteristics were applied to simplify the non-Gaussian closure approach. The nonstationary extreme response and fatigue damage were further estimated from time-varying STD and kurtosis of response. The effectiveness of the analysis framework was examined through comparison with a response time history simulation. The characteristics of the crosswind response under nonstationary excitations are also discussed. [ABSTRACT FROM AUTHOR]

Installation of blades for wind turbines is challenging due to large lifting height and high precision. Assessment of blade dynamic responses during installation needs advanced simulation tools which are limited at present. This paper aims at developing an integrated simulation tool SIMO-Aero for single blade installation for both onshore and offshore wind turbines. Based on the cross-flow principle, the aerodynamic model is established by accounting for the effect of wind turbulence and dynamic stall. Then it is coupled with SIMO to achieve the integrated simulation tool SIMO-Aero which can account for blade aerodynamics, vessel hydrodynamics and system mechanical couplings. The aerodynamic code is verified by code-to-code comparisons with HAWC2. Furthermore, SIMO-Aero is applied in case studies on the wind-induced dynamic responses of a DTU 10 MW blade during installation using a jack-up crane vessel which is assumed to be rigid, including the crane, and rigidly fixed to the seabed. The characteristics of system dynamic responses prior to mating the blade onto the hub are studied. It is shown that the blade motions are dominated by the pendulum motion. Critical parameters of the installation process are identified. The extreme responses of critical parameters are further studied under turbulent winds and wind gusts. [ABSTRACT FROM AUTHOR]

For the assessment of extreme load effects needed in design of marine structures, a full long-term analysis is recognized as the most accurate approach. However, due to the very large number of structural response analyses traditionally needed for this approach, the computational effort is usually considered to increase above acceptable levels for complex structures such as floating bridges. In this paper, a framework for full long-term extreme response analysis is demonstrated for a long-span pontoon bridge subjected to wave loads. This framework utilizes some recently developed approaches which are based on the inverse first- and second-order reliability methods (IFORM and ISORM). Using the IFORM and ISORM approaches, characteristic values of the long-term extreme response are calculated in an efficient manner. By comparing with results obtained by full numerical integration, the accuracy of the methods is investigated. Particularly the ISORM method is seen to provide high accuracy. The full long-term analysis is also compared with the environmental contour method. [ABSTRACT FROM AUTHOR]

• A new solution algorithm for long-term extreme response calculation is proposed. • Gaussian process surrogate modeling is used for long-term calculations. • Long-term extreme buffeting stresses are predicted for a long-span bridge. • The algorithm is efficient and accurate for the considered application. The full long-term method (FLM) provides the most accurate estimates of the long-term (i.e., 10–100 years) extreme buffeting responses in the design of wind-sensitive structures. However, it suffers from high computational demand if the number of uncertain turbulence parameters becomes high. In this paper, we propose a new algorithm for efficient solution of the full long-term problem through sequential Gaussian Process (GP) surrogate modeling. The algorithm efficiently trains a GP surrogate model that replaces the buffeting response calculation while exploiting the specific properties of the long-term problem. The performance of the algorithm is demonstrated on a practical design problem of estimating extreme buffeting-induced stresses of a long-span suspension bridge, where the results are compared with the ones obtained from other viable methods. The results show that the algorithm achieves computational efficiency comparable to the highly efficient IFORM, while also significantly enhancing the accuracy of the response estimate. The algorithm also has the added benefit of converging to the true solution of the full long-term problem, in contrast to the IFORM solution, which converges to an approximate solution. [ABSTRACT FROM AUTHOR]

The present paper investigates the wave- and current-induced responses of the Bjørnafjord phase 5 K12 floating bridge concept based on small-scale model tests. Due to the extensive length of the bridge concept combined with relatively small wave heights governing the design, the experimental model represents a truncated section of the original bridge concept. This truncated section includes a stay-cable tower and ten floating pontoons supporting a horizontally curved bridge girder at varying altitude. The bridge girder truncation points coincide with the tower column and the location just above the first moored pontoon. The girder boundary conditions are simplified as fixed for all degrees of freedom (DOF) on either side of the model while allowing for free rotation around the longitudinal and vertical axes at the location above the otherwise moored pontoon. The instrumentation of the experimental model includes three DOF translational motions captured at 13 locations along the bridge and six DOF motion of each pontoon. Force transducers are used to capture axial forces in all ten tower stay-cables and at the two ends of the bridge girder, while strain gauges capture shear forces and bending- and torsional moments measured at 12 locations along the bridge girder. The dynamic properties of the model are investigated by subjecting the model to both regular waves and broad-banded, long-crested waves, propagating at two different wave directions corresponding to waves travelling in and out of the fjord. These tests are performed with and without collinear current to investigate the effect of current on the bridge responses. Subsequently, the effect of current is investigated for two important long-crested wave conditions, i.e. the 100-year wind wave condition and the 10000-year swell wave condition. For both wave conditions the model tests are performed without current and with 1-year and 10-year current velocities, respectively. Finally, the short-term response from the long-crested wind and swell wave conditions without current are compared to those of short-crested waves without current. Results show that both current and the directional distribution of the waves have a significant influence on the structural responses. It is recommended that both effects are properly accounted for in any future design. • An empirical study of floating bridge global responses is presented. • The bridge is subjected to wind- and swell-driven waves at two beam sea directions. • Effects of collinear current are investigated for long-crested waves. • Effects of directional distribution in the waves are investigated. • Results show that both effects have a significant influence on the responses. [ABSTRACT FROM AUTHOR]

Environmental contours are commonly applied in the design of marine structures to identify extreme environmental conditions that can give rise to extreme loads and responses. There are different methods to establish these contours, mainly the one based on the Rosenblatt transformation and the one based on Monte Carlo simulations, and in some cases significant differences can be obtained. In this paper, a method to determine environmental contours using imprecise probability models is proposed. The aim is incorporating the uncertainties that exist in the joint cumulative distribution function of the environmental variables. This is accomplishment through probability boxes defined by confidence intervals of the parameters of the joint cumulative distribution function of the environmental variables, which are proposed to be obtained with the maximum likelihood method. Furthermore, the dependence structure of the environmental variables is modeled using copulas. The proposed method is applied to obtain imprecise environmental contours for a site in the Gulf of Mexico, using extreme sea states defined by significant wave height and peak period. Then, such environmental contours are used to determine the imprecise most probable extreme response of a tension leg platform. • Method to determine environmental contours using imprecise probability models. • Imprecise environmental contours constructing using copulas theory. • Calculating of imprecise extreme response of a Tension Leg Platform. [ABSTRACT FROM AUTHOR]

Accurate prediction of the long-term extreme response for dynamic offshore structures is challenging in view of small failure probabilities arising from long-term and short-term uncertainties. The sea state fluctuates extensively over the long term, whereas in the short term, the wave elevation is a stochastic process. The rigorous “all sea states” approach considers all conceivable sea states, where each sea state involves a stochastic dynamic analysis. This approach would be computationally prohibitive if the dynamic analyses are performed in the time domain, which may be essential because of nonlinearities. The environmental contour lines approach has emerged as a fast practical method for estimating the extreme response; nevertheless, it is approximate and needs to be validated. This paper presents an efficient simulation approach for evaluating the long-term extreme response through time domain analysis. The method produces an unbiased result, as well as an error estimate. The premise is to apply subset simulation to tackle the short-term variability, while importance sampling is used to reduce sampling variability arising from long-term uncertainty (whose characteristics are more amenable to an approximate treatment for constructing an importance sampling density). Case studies are performed on a floating structure subjected to first-order and second-order (non-Gaussian) wave loads. The computational efficiency of the proposed method is found to be vastly superior to Monte Carlo simulation, with the efficiency factor exceeding five orders of magnitude for certain cases. Moreover, the proposed method is faster compared to classical subset simulation, with the improvement depending on the relative dominance of the long-term and short-term uncertainties. [ABSTRACT FROM AUTHOR]

For the assessment of extreme responses needed in design of marine structures, a full long-term analysis is recognized as the most accurate approach. However, due to the very large number of structural response analyses traditionally needed for this approach, the computational effort is usually considered to increase above acceptable levels for complex structures such as floating bridges. This paper shows that the first and second order reliability methods (FORM and SORM) found in connection with structural reliability analysis can be used in an inverse manner to efficiently obtain approximate solutions for the full long-term extreme response of structures subjected to environmental loads, and this is demonstrated for floating bridges. Very accurate results are obtained using a limited number of short-term response calculations, and by applying a fast calculation method for the short-term stochastic response, full long-term extreme responses are calculated for two different pontoon floating bridges. [ABSTRACT FROM AUTHOR]

An exact and an approximate formulation for the long-term extreme response of marine structures are discussed and compared. It is well known that the approximate formulation can be evaluated in a simplified way by using the first order reliability method (FORM), known for its computational efficiency. In this paper it is shown how this can be done for the exact formulation as well. Characteristic values of the long-term extreme response are calculated using inverse FORM (IFORM) for both formulations. A new method is proposed for the numerical solution of the IFORM problem, resolving some convergence issues of a well-established iteration algorithm. The proposed method is demonstrated for a single-degree-of-freedom (SDOF) example and the accuracy of the long-term extreme response approximations is investigated, revealing that the IFORM methods provide good estimates in a very efficient manner. The reduced number of required short-term response calculations provided by the IFORM methods is expected to make full long-term extreme response analysis feasible also for more complex systems. [ABSTRACT FROM AUTHOR]

This study deals with analysis of stochastic crosswind response of tall buildings with bilinear hysteretic restoring force character at the vicinity of vortex lock-in speed where nonlinear negative aerodynamic damping is significant. The nonlinear aerodynamic damping at a given wind speed and the hysteretic damping resulted from hysteretic restoring force are modelled as polynomial functions of amplitude of narrow-band building response. It permits analytical estimations of response statistics by using equivalent nonlinear equation (ENEL) approach, which include root-mean-square value, kurtosis, extreme value distribution and fatigue damage. Response history analysis is also performed to prove the accuracy of this analytical framework. A comprehensive parameter study is carried out to shed insights on the characteristics of inelastic crosswind response. This study also illustrates the advantage of the ENLE approach over the statistical linearization approach with assumption of Gaussian response distribution when applied to estimate inelastic crosswind response at wind speed region with negligible aerodynamic damping. This study not only presents an effective analytical approach but also sheds new insights towards improved understanding of inelastic crosswind response of tall buildings, contributing to a safer and more economical design of tall buildings against strong winds. [ABSTRACT FROM AUTHOR]

Modern sea transportation is characterized by ever larger container ships, which require direct calculation procedures and numerical tools to achieve their reliable structural design. There are different attempts to increase the ship loading capacity, as for instance a container ship with a novel mobile deckhouse enabling her to carry additional number of containers, and at the same time changing basic structural properties of the ship. This paper is related to structural design evaluation of a 19,000 TEU ultra large container ship with novel mobile deckhouse for maximizing cargo capacity, particularly relying on quasi-static approach. The ship structural design is evaluated both for fatigue and extreme loads, where conventional container ship of same particulars is used as a reference. Independent analyses of new and conventional design indicate that conventional container ship shows somewhat better performance from viewpoint of fatigue, while global extreme loading is at the same level. [ABSTRACT FROM AUTHOR]

The concept of a shared mooring system was proposed to reduce mooring and anchoring costs. Shared moorings also add complexity to the floating offshore wind farm system and pose design challenges. To understand the system dynamics, this paper presents a dynamic analysis for a dual-spar floating offshore wind farm with a shared mooring system in extreme environmental conditions. First, a numerical model of the floating offshore wind farm was established in a commercial simulation tool. Then, time-domain simulations were performed for the parked wind farm under extreme wind and wave conditions. A sensitivity study was carried out to investigate the influence of loading directions and shared line mooring properties. To highlight the influence of the shared line, the results were compared to those of a single spar floating wind turbine, and larger platform motions and higher tension loads in single lines are observed for the wind farm with shared moorings. The loading direction affects the platform motions and mooring response of the floating offshore wind farm. Comparing the investigated loading directions to the 0-deg loading direction, the variation of mean mooring tension at the fairlead is up to 84% for single lines and 16% for the shared line. The influence of the shared line properties in the platform motions and the structural responses is limited. These findings improve understanding of the dynamic characteristics of floating offshore wind farms with a shared mooring system. • A shared mooring system is applied to a dual-spar floating offshore wind farm. • Extreme wind and wave conditions are considered in the dynamic analysis. • Dynamics of the wind farm is compared with that of a single floating wind turbine. • Mooring stiffness linearization is performed to elucidate physical characteristics. • Mooring tension, tower-bottom bending moment, and platform motions are analyzed. • The influence of loading directions and shared line properties on responses is shown. [ABSTRACT FROM AUTHOR]

• Long-term extreme responses of a very long floating bridge under various inhomogeneous wave fields • The long-term extreme response is estimated utilizing a simplified environmental contour method • Cholesky decomposition techniques are applied to model a correlated and inhomogeneous wave field • A correlated inhomogeneous wave field can cause significantly large extreme axial force • Statistical and model uncertainties associated with extreme value estimation are studied Floating bridges are usually deployed in fjords where the wave fields are inhomogeneous. The wave inhomogeneity has been found to induce significant effects on dynamic responses, however, it was rarely considered during the extreme response analyses of floating bridges. The present study deals with the effects of inhomogeneous wave modeling on extreme responses of a very long end-anchored floating bridge. The inhomogeneous wave field modeling accounts for the spatial variation of wave spectral parameters as well as the coherence of wave elevations between different positions. Structural responses under various wave conditions are simulated through fully-coupled hydro-elastic simulations. The long-term extreme responses are investigated by a simplified environmental contour method, where the long-term extremes are approximated by extremes at a high quantile in carefully selected short-term sea states. The characteristics of simulated waves and responses are first analyzed to serve as a basis for extreme prediction. Uncertainties associated with extreme analyses are also studied. It is found that the coherence of wave elevations has significant influences on the standard deviation and the spatial correlation of the responses. The extreme values of the axial force vary between different modeling of inhomogeneous wave loads and become significantly larger considering partially correlated wave fields. [ABSTRACT FROM AUTHOR]

This paper presents a method for estimating environmental contours in an arbitrary number of dimensions. The method, referred to as Direct-IFORM, does not require a model for the joint distribution of the variables. It can therefore be applied in higher dimensions without degradation in performance. The method involves multiple univariate analyses under rotations of the axes to estimate return values in various directions, which are used to form a contour. The method accounts for serial correlation in the observations, which removes the positive bias that occurs when this is neglected. An efficient open-source code is provided for estimating Direct-IFORM contours. A four-dimensional example is presented for contours of wind speed, wave height, wave period and wind-wave misalignment direction. The application of the method to the design of offshore wind turbines is discussed. • Method presented for estimating contours without need to fit joint distribution. • Method applicable in higher dimensions without degradation in performance. • Method accounts for serial correlation in observations, reducing positive bias. • Open source code in MATLAB and Python provided for estimating Direct-IFORM contours. • Example presented for 4-dimensional contours of wind and wave parameters. [ABSTRACT FROM AUTHOR]

A key to successful Delphi process is to have some panellists to change their opinion as a result of considering the views of their peers. Despite this, studying the changes in opinions has not been in the research focus outside methodological approaches in the field of forecasting. In addition to forecasting, Delphi technique is also used widely in the fields of public policy and strategic decision-making in companies. We assessed opinion shift between Delphi rounds that were set up to evaluate reforms of specific agriculture and forestry policy measures. Theoretical postulates and findings from previous studies concerning consensus and extreme responses were assessed in this real-world Delphi process. The feedback in the process included both numeric and argumentative information from the previous round outcomes. We found that change in opinion was stimulated by the majority's stand whilst providing extreme responses to the arguments that were fed back meant perseverance of opinions. Additionally, interest groups showed differing response behaviour concerning the evaluated agriculture policy measures. In particular, panellists, who represented interest groups, were more persistent in their opinions compared to panellists representing other groups of expertise (e.g. administration, non-governmental organisations or research). Unlike interest groups, other groups or fields of expertise, age, gender or education did not offer elucidation over opinion change. Our results show not only the connection between changing opinions and the feedback information, but also that panellists can be analysed based on their propensity to change their opinion. This feature can be beneficial not only for policy- and decision-making but also, for example, for conflict assessments and for cases where further understanding of the group dynamics is desired. [ABSTRACT FROM AUTHOR]