FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W327768356> ?p ?o ?g. }

• W327768356 abstract "Offshore wind energy faces three important trends: (1) wind farms grow in size, (2) monopiles are installed in deeper water, and (3) cost reduction remains the most important challenge. With wind farm size, the importance of variations in environmental site conditions across the wind farm increases. These site variations, e.g. water depth and soil conditions, can lead to significant differences of loads on support structures. For monopiles in deeper water, design is dominated by wave-induced fatigue loads. Since full fatigue load calculations are computationally demanding, they can typically not be performed for each turbine within large wind farms. Therefore, turbines must be grouped into clusters in early project phases, making time-efficient approaches essential. Optimization of design clustering is necessary to reduce design conservatism and the cost of offshore wind energy.Hence, the goal of this thesis is to investigate load site variations and clustering. Therefore, a probabilistic fatigue load estimation method is developed and verified with aero-elastic simulations in the time domain. Subsequently, the developed method is applied for an exemplary wind farm of 150 turbines in 30-40m water depth to perform– sensitivity studies of loads to changes in MSL, soil stiffness, and wave parameters,– probabilistic assessments of data, statistical and model uncertainties, and– deterministic and probabilistic design clustering.The estimation method is based on frequency domain analysis to calculate wave-induced fatigue loads, a scaling approach for wind loads, combination of wind-wave loads with quadratic superposition, and Monte-Carlo simulations to assess uncertainties. Verification confirms an accuracy of 95% for lifetime equivalent fatigue loads compared to time domain simulations. The computational speed is in the order of 100 times faster than typical time domain tools. Sensitivity studies show a significantinfluence of water depth and wave period on equivalent fatigue loads. The influence of soil on equivalent fatigue loads is minor for high soil stiffness but can increase significant for soils with low stiffness. Normal distributed input parameters in a probabilistic assessment yield a positively skewed probability distribution of equivalent fatigue loads. Design clustering is optimized based on site-specific fatigue loads using brute-force and discrete optimization algorithms. Results for the exemplary wind farm show a design load reduction of up to 13% compared to standardized design. Probabilistic clustering proved to be only relevant at cluster borders leading to a difference in allocation for 12 out of 150 turbines.Project results show that it is essential to account for load differences in large wind farms due to varying site conditions. This study improves clustering and provides a basis for design optimization and uncertainty analysis in large wind farms. Further work is needed to extend tool verification and formulate design clustering for cost optimization." @default.
• W327768356 created "2016-06-24" @default.
• W327768356 creator A5069665051 @default.
• W327768356 date "2015-05-21" @default.
• W327768356 modified "2023-09-26" @default.
• W327768356 title "Probabilistic estimation of fatigue loads on monopile-based offshore wind turbines" @default.
• W327768356 cites W114465275 @default.
• W327768356 cites W129500120 @default.
• W327768356 cites W1499506103 @default.
• W327768356 cites W1519481447 @default.
• W327768356 cites W1528971192 @default.
• W327768356 cites W1542786076 @default.
• W327768356 cites W1553261287 @default.
• W327768356 cites W1556520835 @default.
• W327768356 cites W1567243524 @default.
• W327768356 cites W1580119577 @default.
• W327768356 cites W1591608973 @default.
• W327768356 cites W1809753057 @default.
• W327768356 cites W1811329215 @default.
• W327768356 cites W1877881253 @default.
• W327768356 cites W1970873516 @default.
• W327768356 cites W1973056046 @default.
• W327768356 cites W1996757216 @default.
• W327768356 cites W2000619159 @default.
• W327768356 cites W2013047291 @default.
• W327768356 cites W2019600130 @default.
• W327768356 cites W2041023359 @default.
• W327768356 cites W2047542720 @default.
• W327768356 cites W2048752767 @default.
• W327768356 cites W2052797340 @default.
• W327768356 cites W2055615017 @default.
• W327768356 cites W2070731585 @default.
• W327768356 cites W2088354014 @default.
• W327768356 cites W2089288776 @default.
• W327768356 cites W2101655826 @default.
• W327768356 cites W2106822551 @default.
• W327768356 cites W2111311608 @default.
• W327768356 cites W2117483152 @default.
• W327768356 cites W2122292153 @default.
• W327768356 cites W2124181495 @default.
• W327768356 cites W2131523613 @default.
• W327768356 cites W2134421139 @default.
• W327768356 cites W2135737863 @default.
• W327768356 cites W2139494805 @default.
• W327768356 cites W2145777644 @default.
• W327768356 cites W2148398963 @default.
• W327768356 cites W2188885461 @default.
• W327768356 cites W219929715 @default.
• W327768356 cites W2360713393 @default.
• W327768356 cites W2494510889 @default.
• W327768356 cites W264744871 @default.
• W327768356 cites W3044376648 @default.
• W327768356 cites W3185847069 @default.
• W327768356 cites W621493298 @default.
• W327768356 cites W629747797 @default.
• W327768356 cites W1782726210 @default.
• W327768356 cites W2183615750 @default.
• W327768356 cites W3010319276 @default.
• W327768356 hasPublicationYear "2015" @default.
• W327768356 type Work @default.
• W327768356 sameAs 327768356 @default.
• W327768356 citedByCount "0" @default.
• W327768356 crossrefType "journal-article" @default.
• W327768356 hasAuthorship W327768356A5069665051 @default.
• W327768356 hasConcept C105795698 @default.
• W327768356 hasConcept C119599485 @default.
• W327768356 hasConcept C127413603 @default.
• W327768356 hasConcept C19499675 @default.
• W327768356 hasConcept C199104240 @default.
• W327768356 hasConcept C2778449969 @default.
• W327768356 hasConcept C33923547 @default.
• W327768356 hasConcept C39432304 @default.
• W327768356 hasConcept C49937458 @default.
• W327768356 hasConcept C66938386 @default.
• W327768356 hasConcept C78519656 @default.
• W327768356 hasConcept C78600449 @default.
• W327768356 hasConcept C8735168 @default.
• W327768356 hasConceptScore W327768356C105795698 @default.
• W327768356 hasConceptScore W327768356C119599485 @default.
• W327768356 hasConceptScore W327768356C127413603 @default.
• W327768356 hasConceptScore W327768356C19499675 @default.
• W327768356 hasConceptScore W327768356C199104240 @default.
• W327768356 hasConceptScore W327768356C2778449969 @default.
• W327768356 hasConceptScore W327768356C33923547 @default.
• W327768356 hasConceptScore W327768356C39432304 @default.
• W327768356 hasConceptScore W327768356C49937458 @default.
• W327768356 hasConceptScore W327768356C66938386 @default.
• W327768356 hasConceptScore W327768356C78519656 @default.
• W327768356 hasConceptScore W327768356C78600449 @default.
• W327768356 hasConceptScore W327768356C8735168 @default.
• W327768356 hasLocation W3277683561 @default.
• W327768356 hasOpenAccess W327768356 @default.
• W327768356 hasPrimaryLocation W3277683561 @default.
• W327768356 hasRelatedWork W2039734202 @default.
• W327768356 hasRelatedWork W2104608834 @default.
• W327768356 hasRelatedWork W2136861739 @default.
• W327768356 hasRelatedWork W2234505086 @default.
• W327768356 hasRelatedWork W2255047728 @default.
• W327768356 hasRelatedWork W2279145744 @default.
• W327768356 hasRelatedWork W2527325451 @default.

• next