Design of a scaled wind turbine with a smart rotor for dynamic load control experiments

The ever increasing size of wind turbines poses a number of design issues for the industry, like increasing component mass and fatigue loads. An interesting concept for reducing fatigue loads is the implementation of spanwise distributed devices to control the aerodynamic loading along the span of the blade, thus mitigating fluctuations in loading and adding damping to the blade modes. This is usually referred to as the smart rotor concept. In the design of such a rotor, as compared to a traditional one, the integration of sensors and actuators poses additional design challenges. In the research discussed in this paper, a scaled smart rotor was designed and constructed to study its fatigue load reduction potential. A 1.8 m diameter rotor was manufactured and equipped with trailing‐edge flaps. The flaps were based on piezo electric Thunder actuators that allow for high‐frequent actuation. The dynamic strain behaviour of the blade was analysed for optimal placement of the sensors. Several sensors that record the strains and accelerations at different locations along the blade were implemented, but the controller was based on a piezo electric strain sensor. The rotor blades were mounted on a small turbine in the Delft University's Open Jet Facility wind tunnel and a mathematical state space model was obtained by using dedicated system identification techniques. Single‐Input Single‐Output, Multi‐Input Multi‐Output ??_∞ feedback and feedforward controllers were designed, each focusing on different parts of the load spectrum. The rotor was tested at 0 and 5° yaw angles, with and without load control. A significant reduction of the dynamic loads was attained. Copyright © 2010 John Wiley & Sons, Ltd.     

Model predictive control for wind turbines with distributed active flaps: incorporating inflow signals and actuator constraints

This paper describes the implementation of system identification and controller design techniques using model predictive control (MPC) for wind turbines with distributed active flaps for load control. An aeroservoelastic model of the 5 MW NREL/Upwind reference wind turbine, implemented in the code DU_SWAMP, is used in an industry‐based MPC controller design cycle, involving the use of dedicated system identification techniques. The novel multiple‐input multiple‐output MPC controllers, which incorporate flap actuator constraints and the use of local inflow measurement signals, are designed and implemented for various operating points. The controllers are evaluated in standard power production load cases and fatigue load reductions up to 27.3% are achieved. The distributed flaps controller scheme is also compared with simpler single‐flap single‐input single‐output and individual pitch controller schemes. Copyright © 2011 John Wiley & Sons, Ltd.     

Influence of atmospheric stability on wind turbine loads

Simulations of wind turbine loads for the NREL 5 MW reference wind turbine under diabatic conditions are performed. The diabatic conditions are incorporated in the input wind field in the form of wind profile and turbulence. The simulations are carried out for mean wind speeds between 3 and 16 m s ^{? 1} at the turbine hub height. The loads are quantified as the cumulative sum of the damage equivalent load for different wind speeds that are weighted according to the wind speed and stability distribution. Four sites with a different wind speed and stability distribution are used for comparison. The turbulence and wind profile from only one site is used in the load calculations, which are then weighted according to wind speed and stability distributions at different sites. It is observed that atmospheric stability influences the tower and rotor loads. The difference in the calculated tower loads using diabatic wind conditions and those obtained assuming neutral conditions only is up to 17%, whereas the difference for the rotor loads is up to 13%. The blade loads are hardly influenced by atmospheric stability, where the difference between the calculated loads using diabatic and neutral input wind conditions is up to 3% only. The wind profiles and turbulence under diabatic conditions have contrasting influences on the loads; for example, under stable conditions, loads induced by the wind profile are larger because of increased wind shear, whereas those induced by turbulence are lower because of less turbulent energy. The tower base loads are mainly influenced by diabatic turbulence, whereas the rotor loads are influenced by diabatic wind profiles. The blade loads are influenced by both, diabatic wind profile and turbulence, that leads to nullifying the contrasting influences on the loads. The importance of using a detailed boundary‐layer wind profile model is also demonstrated. The difference in the calculated blade and rotor loads is up to 6% and 8%, respectively, when only the surface‐layer wind profile model is used in comparison with those obtained using a boundary‐layer wind profile model. Finally, a comparison of the calculated loads obtained using site‐specific and International Electrotechnical Commission (IEC) wind conditions is carried out. It is observed that the IEC loads are up to 96% larger than those obtained using site‐specific wind conditions.Copyright © 2012 John Wiley & Sons, Ltd.     

Observation and removal of higher-order (ghost) energy-loss lines present in Mollenstedt electron velocity analyzers

Mollenstedt electron velocity analyzers, used in high-energy electron impact spectroscopy, have been found to be limited by higher-order (ghost) energy-loss lines superimposed upon the real energy-loss spectrum. The origin of these ghost lines, as well as a method of removing them experimentally, is discussed.     

A critical test of the overlap hypothesis for odor mixture perception.

The overlap hypothesis of mixture perception is based on the observation that mixtures of perceptually similar odorants tend to smell different from their components (configural), whereas mixtures of dissimilar odorants smell like their components (elemental). Because input patterns of perceptually similar odorants tend to overlap more than dissimilar ones, it has been hypothesized that component pattern overlap can predict a mixture's perceptual quality, with high overlap predicting a configural response and low overlap an elemental response. The authors used 7 pairs of odorants chosen for different degrees of overlap in their monomolecular 2-deoxyglucose activation patterns to test the theory in a go/no-go behavioral assay that measured generalization from binary mixtures to components. The authors show that individual component odorant input patterns are not sufficient to predict mixture quality, falsifying the overlap hypothesis. An important finding is that different odorant pairs with similar glomerular overlap showed opposite behavioral–perceptual responses, suggesting nonlinear effects at the receptor or glomerular level or the critical involvement of higher order areas. Thus, the authors posit that imaging the mixtures themselves may provide additional information needed to reliably predict mixture quality. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Analysis of nanoparticle agglomeration in aqueous suspensions via constant-number Monte Carlo simulation

A constant-number direct simulation Monte Carlo (DSMC) model was developed for the analysis of nanoparticle (NP) agglomeration in aqueous suspensions. The modeling approach, based on the "particles in a box" simulation method, considered both particle agglomeration and gravitational settling. Particle-particle agglomeration probability was determined based on the classical Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and considerations of the collision frequency as impacted by Brownian motion. Model predictions were in reasonable agreement with respect to the particle size distribution and average agglomerate size when compared with dynamic light scattering (DLS) measurements for aqueous TiO(2), CeO(2), and C(60) nanoparticle suspensions over a wide range of pH (3-10) and ionic strength (0.01-156 mM). Simulations also demonstrated, in quantitative agreement with DLS measurements, that nanoparticle agglomerate size increased both with ionic strength and as the solution pH approached the isoelectric point (IEP). The present work suggests that the DSMC modeling approach, along with future use of an extended DLVO theory, has the potential for becoming a practical environmental analysis tool for predicting the agglomeration behavior of aqueous nanoparticle suspensions.     

The effect of transmembrane pressure and pH on treatment of paper machine process waters by using a two-step nanofiltration process: Flux decline analysis

In this work, the treatment of paper machine whitewater obtained from paper production by using loose and tight Nanofiltration (NF) membranes in a lab-scale plant with a plate and frame module was investigated. The NF membranes were evaluated for fouling, flux decline due to concentration polarization and their suitability for removing of components present in wastewater. The loose NF membrane was used for the first step under different transmembrane pressure (8 to 32 bars) and pH (3, 5.6 and 10) values. The best filtration performances were provided under a pressure of 32 bar and a pH of 5.6. The fouling mechanism at different transmembrane pressures and pH values was investigated by “Hermia's model”. Also, fouling on pores and on the surface of NF membranes was characterized by Scanning electron microscopy (SEM) and contact angle measurements, respectively. For the advanced treatment of permeate obtained from the loose NF membrane that provided the lowest fouling and flux decline, a tight NF membrane was used in the second step. Even better retentions were achieved from experiments with this NF membrane. Results obtained in this study showed that the combination loose and tight NF membranes achieved reuse of paper machine white water for use as shower water of paper machine.     

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