a b s t r a c tA high fidelity approach for wind turbine aero-elastic simulations including explicit representation of the atmospheric wind turbulence is presented. The approach uses a dynamic overset computational fluid dynamics (CFD) code for the aerodynamics coupled with a multi-body dynamics (MBD) code for the motion responses to the aerodynamic loads. Mann's wind turbulence model was implemented into the CFD code as boundary and initial conditions. The wind turbulence model was validated by comparing the theoretical one-point spectrum for the three components of the velocity fluctuations, and by comparing the expected statistics from the CFD simulated wind turbulent field with the explicit wind turbulence inlet boundary from Mann model. Extensive simulations based on the proposed coupled approach were conducted with the conceptual NREL 5-MW offshore wind turbine in an increasing level of complexity, analyzing the turbine behavior as elasticity, wind shear and atmospheric wind turbulence are added to the simulations. Results are compared with the publicly available simulations results from OC3 participants, showing good agreement for the aerodynamic loads and blade tip deflections in time and frequency domains. Wind turbulence/turbine interaction was examined for the wake flow. It was found that explicit turbulence addition results in considerably increased wake diffusion. The coupled CFD/MBD approach can be extended to include multibody models of the shaft, bearings, gearbox and generator, resulting in a promising tool for wind turbine design under complex operational environments.
A high-fidelity simulation framework is presented to investigate wind turbine aero-servo-elastic behavior, coupling dynamic overset computational fluid dynamics (CFD) and multibody dynamics (MBD) approaches. The Gearbox Reliability Collaborative (GRC) project gearbox was up-scaled in size and installed in the NREL 5-MW offshore wind turbine to demonstrate drivetrain dynamics. Generator torque and blade pitch controllers were implemented to simulate operational conditions of commercial wind turbines. Interactions between wind turbulence, rotor aerodynamics, elastic blades, drivetrain dynamics at the gear-level and servo-control dynamics were studied. Results show that gear contact causes dynamic transmission error within the drivetrain, and results in a decreased turbine thrust and rotational speed. The generator torque controller optimizes efficiency below rated wind speed, while the blade pitch controller properly regulates the turbine near rated power and generator speed at higher than rated wind speed under both uniform and turbulent winds. The pitch controller effectively reduces turbine thrust, blade tip deflections, and velocity deficit of the wake, benefiting both standalone turbines and wind farms. The tool and methodology developed show promise to study complex aerodynamic/mechanic systems, being the first time a complete wind turbine simulation includes CFD of the rotor/tower aerodynamics, wind turbulence, elastic blades, gearbox dynamics and feedback control.
This study examined whether peripheral inflammatory injury increases the levels or changes the disposition of substance P (SubP) in the rostral ventromedial medulla (RVM), which serves as a central relay in bulbospinal pathways of pain modulation. Enzyme immunoassay and reverse transcriptase quantitative polymerase chain reaction were used to measure SubP protein and transcript, respectively, in tissue homogenates prepared from the RVM and the periaqueductal gray and cuneiform nuclei of rats that had received an intraplantar injection of saline or complete Freund's adjuvant (CFA). Matrix Assisted Laser Desorption/Ionization Time of Flight analysis confirmed that the RVM does not contain hemokinin-1, which can confound measurements of SubP because it is recognized equally well by commercial antibodies for SubP. Levels of SubP protein in the RVM were unchanged four hours, four days and two weeks after injection of CFA. Tac1 transcripts were similarly unchanged in the RVM four days or two weeks after CFA. In contrast, the density of SubP immunoreactive processes in the RVM increased 2-fold within four hours and 2.7-fold four days after CFA injection; it was unchanged at two weeks. SubP-immunoreactive processes in the RVM include axon terminals of neurons located in the periaqueductal gray and cuneiform nucleus. Substance P content in homogenates of the periaqueductal gray and cuneiform nucleus was significantly increased four days after CFA, but not at four hours or two weeks. Tac1 transcripts in homogenates of these nuclei were unchanged four days and two weeks after CFA. These findings suggest that there is an increased mobilization of SubP within processes in the RVM shortly after injury accompanied by an increased synthesis of SubP in neurons that project to the RVM. These findings are consonant with the hypothesis that an increase in SubP release in the RVM contributes to the hyperalgesia that develops after peripheral inflammatory injury.
We formulate ill-posedness of inverse problems of estimation and prediction of Coronavirus Disease 2019 (COVID-19) outbreaks from statistical and mathematical perspectives. This is by nature a stochastic problem, since e.g., random perturbation in parameters can cause instability of estimation and prediction. This leaves us with a plenty of possible statistical regularizations, thus generating a plethora of sub-problems. We can mention as examples stability and sensitivity of peak estimation, starting point of exponential growth curve, or estimation of parameters of SIR (Susceptible-Infected-Removed) model. Moreover, each parameter has its specific sensitivity, and naturally, the most sensitive parameter deserves a special attention. E.g., in SIR model, parameter b is more sensitive than parameter c. In a simple exponential epidemic growth model, parameter b is more sensitive than the parameter a. We also discuss on statistical quality of COVID-19 incidence prediction, where we justify an exponential curve considering the microbial growth in ideal conditions for epidemic. The empirical data from Iowa State, USA, Hubei Province in China, New York State, USA, and Chile justifies an exponential growth curve for initiation of epidemics outbreaks.
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