Evaluating Areal Windspeeds and Wave Heights by Gaidai Risk Evaluation Method

Natural Hazards Review, Год журнала: 2024, Номер 25(4)

Опубликована: Авг. 2, 2024

Язык: Английский

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Wind turbine gearbox reliability verification by multivariate Gaidai reliability method

Results in Engineering, Год журнала: 2024, Номер 23, С. 102689 - 102689

Опубликована: Авг. 8, 2024

Reliability research is essential since WT (Wind turbines) are built to endure high wind and wave-induced stresses. Novel multivariate 2D (bivariate) reliability methods presented in this investigation being conceived by authors assist designers accurately assessment of crucial stressors, acting inside key mechanical parts, such as gearbox drivetrain. Current study made use the recently created modified Weibull-type approach. Since statistical analysis takes into consideration cross-correlations between various system components, it more suited for design than univariate analysis. To cross-validate 10-MW semi-submersible type FWT (i.e., Floating Wind Turbine) failure or damage probability, forecasted Gaidai methodology, current employed Weibull Typical load types that FWTs related parts prone, include longitudinal, bending, twisting, cyclic Stochastic nature environmental loads, on terms windspeed, direction, shear, vorticity may cause excessive nonlinear structural dynamic effects, hence components like drivetrain necessary. In dynamic, structural, aerodynamic, control aspects had been modeled, using advanced numerical techniques – dynamics has modeled utilizing SIMPACK (Multibody Simulation Method) software. risk approach provided a reliable evaluation coupled drivetrain's dynamics, given return periods interest. Weakness bivariate highlighted, comprehensive solution form novel method.

Язык: Английский

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Multivariate ocean waves dynamics in North Sea and Norwegian Sea by Gaidai reliability method

Energy Reports, Год журнала: 2024, Номер 12, С. 2346 - 2355

Опубликована: Авг. 23, 2024

Current study presents state-of-the-art approach for evaluating spatiotemporal multivariate environmental risks, especially suitable complex systems that have been either numerically simulated or physically observed. Advocated methodology provides accurate hazard risk forecasts, based on real-time in situ data. Design of offshore structures requires assessment – and naval operations require both short- long-term reliability analyses. Contemporary evaluation techniques often struggle with raw timeseries data due to intrinsic multidimensionality nonlinear interconnections among critical system's dimensions/components. In the current effectiveness Gaidai method is illustrated by utilizing significant wave heights dataset, measured within two zones: Heidrun Troll Norwegian oil fields. Analyzing waves being particularly challenging their complexity, high nonlinearity, multidimensionality, yet dynamic inter-correlations. Global warming several factors, affecting ocean sea heights. For naval, marine operating harsh weather conditions, robust methods crucial design safe operations. aims validate benchmark methodology, enabling extraction. allows efficient global damages, failures risks a wide range energy systems. Primary advantage presented lies its ability treat practically unlimited number dimensions, while existing mostly limited univariate bivariate

Язык: Английский

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Panamax cargo-vessel excessive-roll dynamics based on novel deconvolution method

Probabilistic Engineering Mechanics, Год журнала: 2024, Номер 77, С. 103676 - 103676

Опубликована: Июль 1, 2024

Язык: Английский

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Novel multivariate design concept for floating wind turbines by Gaidai multivariate reliability method and deconvolution scheme

Journal of low frequency noise, vibration and active control, Год журнала: 2024, Номер unknown

Опубликована: Авг. 22, 2024

Development of novel risk and reliability assessment methods is intended to support safer construction offshore structures, subjected environmental wave loads. Current study investigated 10-MW FWT (i.e., Floating Wind Turbine), operating under realistic conditions. While increasing safety, enhanced may eventually help reduce manufacturing maintenance costs. Excessive structural dynamics being usually caused by stressors, acting on system. Environmental loads resulting from ambient wind motions are typical for structures. work advocates a methodology that allows reliable forecasting failure/damage risks, arising excessive dynamics. Recently developed Gaidai multivariate along with state-of-the-art deconvolution method had been employed. Unlike existing approaches such as Weibull-type, GP Generalized Pareto), POT Peaks Over the Threshold), etc., recommended does not rely any pre-assumed functional class, when extrapolating failure probability tail. Practical advantages suggested combined scheme over, is, 4-parameter Weibull’s extrapolation demonstrated. Suggested makes effective use even limited underlying datasets, enabling robust accurate projections multidimensional system risks. Overall methodological performance suggests numerically stable extreme forecasts bending moments might be obtained, utilizing methodology. Deconvolution approach more than parametric techniques, due its non-parametric nature.

Язык: Английский

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ocean windspeeds forecast by Gaidai multivariate risk assessment method, utilizing deconvolution scheme

Results in Engineering, Год журнала: 2024, Номер 23, С. 102796 - 102796

Опубликована: Авг. 28, 2024

Язык: Английский

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Design prognostics for 4400 TEU container vessel by multi‐variate Gaidai reliability approach

IET Intelligent Transport Systems, Год журнала: 2025, Номер 19(1)

Опубликована: Янв. 1, 2025

Abstract This case study introduces an innovative multivariate methodology for assessing the lifetime of marine engineering systems, specifically in cargo vessel transportation. The analysis focused on stress data collected onboard a 4400 TEU container during multiple trans‐Atlantic voyages. One major challenges transport lies mitigating risk loss due to excessive whipping loads. Accurate prediction extreme levels deck panels remains difficult, primarily because nonlinear and non‐stationary nature wave ship motion interactions. Higher‐order dynamic effects, such as second‐ third‐order responses, often become significant when ships operate under adverse environmental conditions, amplifying influences. Laboratory simulations, constrained by characteristics scale similarity issues, may not always provide reliable results. Consequently, from vessels navigating weather conditions serves critical resource comprehensive assessment. primary goal this was validate demonstrate effectiveness novel evaluation approach, leveraging measurements areal pressure core dataset. Gaidai proved be robust tool failure, hazard, damage risks complex, panel hull systems.

Язык: Английский

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State-of-the-art Gaidai hypersurface risk assessment for semi-submersible wind turbines, accounting for memory effects

Energy Conversion and Management X, Год журнала: 2025, Номер unknown, С. 100946 - 100946

Опубликована: Фев. 1, 2025

Язык: Английский

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Lifetime assessment for container ship by multimodal Gaidai risk evaluation method

Deleted Journal, Год журнала: 2025, Номер 2(1)

Опубликована: Янв. 6, 2025

This study presents a novel lifetime assessment technique that may be used in cargo vessel transportation marine engineering applications. onboard measured 4400 TEU container ship panel stress data was analyzed, the during numerous trans-Atlantic crossings. The risk of loss caused by excessive whipping loads is one key issues with transportation. It challenging to predict accuracy deck stresses due complex nonlinear and nonstationary properties wave motions. 2nd higher order motion effects are typically observed when sailing severe, stormy environment, influence nonlinearity grows noticeably. Depending on flow characteristics similarity ratios employed, laboratory testing also dispute. Because this, information acquired from ships operating extreme weather conditions offers unique insight into risks evaluation, as whole. highlights multidimensional reliability approach, based inherent qualities multivariate raw underlying dataset itself. main objective current had been benchmark Gaidai using areal pressure dynamic system dataset. evaluation methodology enabled efficient failure, hazard or damage for variety non-linear hull systems.

Язык: Английский

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Experimental Gaidai multi-modal risk assessment approach for wind energy harvesters

Applications in Engineering Science, Год журнала: 2025, Номер unknown, С. 100209 - 100209

Опубликована: Фев. 1, 2025

Язык: Английский

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