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Assessment and Nonlinear Modeling of Wave, Tidal and Wind Energy Converters and Turbines



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Autore: Karimirad Madjid Visualizza persona
Titolo: Assessment and Nonlinear Modeling of Wave, Tidal and Wind Energy Converters and Turbines Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica: 1 online resource (290 p.)
Soggetto topico: History of engineering and technology
Soggetto geografico: Daguragu / Kalkaringi / Wave Hill (Central NT SE52-08)
Soggetto non controllato: 10 MW wind turbines
AFWT
air compressibility
air turbine
ANSYS CFX
blade back twist
blade flapwise moment
caisson breakwater application
cylinder wake
dynamic analysis
energy converter
energy harnessing
Extreme Learning Machine (ELM)
fatigue life assessment
flexible power cables
floating offshore wind turbine
floating offshore wind turbine (FOWT)
floating offshore wind turbines
flow-induced oscillations
flow-structure interaction
flower pollination algorithm (FPA)
FOWT
frequency domain model
hill-climbing method
hydrodynamics
inclined columns
integral length scales
Kirsten-Boeing
large floating platform
large-eddy simulation (LES)
maximum power point tracking (MPPT)
metamodeling
multi-segmented mooring line
negative damping
neural nets
off-shore wind farms (OSWFs)
optimization
oscillating water column
OWC
parametric study
pitch-to-stall
platform optimization
point-absorbing
power take-off (PTO)
semi-submersible
semisubmersible platform
site assessment
tank testing
Tensorflow
tidal energy
tower axial fatigue life
tower fore-aft moments
turbulence
valves
vertical axis turbine
vortex shedding
vortex-induced vibration
wake model
wave energy
wave energy converter (WEC)
wave power converting system
wave-current interaction
wave-to-wire model
wave-turbulence decomposition
wind energy
wind power (WP)
wind turbine (WT)
Persona (resp. second.): ColluMaurizio
KarimiradMadjid
Sommario/riassunto: The Special Issue "Assessment and Nonlinear Modeling of Wave, Tidal, and Wind Energy Converters and Turbines" contributes original research to stimulate the continuing progress of the offshore renewable energy (ORE) field, with a focus on state-of-the-art numerical approaches developed for the design and analysis of ORE devices. Particularly, this collection provides new methodologies, analytical/numerical tools, and theoretical methods that deal with engineering problems in the ORE field of wave, wind, and current structures. This Special Issue covers a wide range of multidisciplinary aspects, such as the 1) study of generalized interaction wake model systems with elm variation for offshore wind farms; 2) a flower pollination method based on global maximum power point tracking strategy for point-absorbing type wave energy converters; 3) performance optimization of a Kirsten-Boeing turbine using a metamodel based on neural networks coupled with CFD; 4) proposal of a novel semi-submersible floating wind turbine platform composed of inclined columns and multi-segmented mooring lines; 5) reduction of tower fatigue through blade back twist and active pitch-to-stall control strategy for a semi-submersible floating offshore wind turbine; 6) assessment of primary energy conversion of a closed-circuit OWC wave energy converter; 7) development and validation of a wave-to-wire model for two types of OWC wave energy converters; 8) assessment of a hydrokinetic energy converter based on vortex-induced angular oscillations of a cylinder; 9) application of wave-turbulence decomposition methods on a tidal energy site assessment; 10) parametric study for an oscillating water column wave energy conversion system installed on a breakwater; 11) optimal dimensions of a semisubmersible floating platform for a 10 MW wind turbine; 12) fatigue life assessment for power cables floating in offshore wind turbines.
Titolo autorizzato: Assessment and Nonlinear Modeling of Wave, Tidal and Wind Energy Converters and Turbines  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910557555603321
Lo trovi qui: Univ. Federico II
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