Structural health monitoring in the context of a Micon 65/13 horizontal axis wind turbine was described in this paper as a process in statistical pattern recognition. Simulation data from a calibrated model with less than 8% error in the fi rst 14 natural frequencies of vibration was used to study the operational response under various wind states as well as the effects of three types of damage in the blade, low speed shaft and yaw joint. It was shown that vertical wind shear and turbulent winds lead to different modal contributions in the operational response of the turbine suggesting that the sensitivity of operational data to damage depends on the wind loads. It is also shown that there is less than a 4% change in the wind turbine natural frequencies given a 25% reduction in the stiffness at the root of one blade. The modal assurance criterion was used to analyse the corresponding changes in modal defl ections, and this criterion exhibited nearly orthogonal changes because of the three damage scenarios suggesting that the modal defl ection determines which damage is observable at a given frequency for a given wind state. The` modal contribution is calculated as a damage feature, which changes as much as 100% for 50% reductions in blade root stiffness, but only the blade damage is detected using this feature. Operational data was used to study variations in the forced blade response to determine the likelihood that small levels of damage can be detected amidst variations in wind speed across the rotor plane. The standard deviation in measured data was shown to be smallest for the span and edge-wise measurements at 1P due to gravity, which provides the dominant forcing function at this frequency. A 3% change in the response in the span and edge-wise directions because of damage is required to detect a change of three standard deviations in contrast to the 90% change in fl ap direction response that is required to detect a similar change because of damage. The dynamic displacement in the span direction is then used to extract a damage feature from the simulation data that provides the ability to both locate and quantify the reduction in stiffness in the blade root.
In the past decade wind energy installations have increased exponentially driven by reducing cost from technology innovation and favorable governmental policy. Modern wind turbines are highly efficient, capturing close to the theoretical limit of energy available in the rotor diameter. Therefore, to continue to reduce the cost of wind energy through technology innovation a broadening of scope from individual wind turbines to the complex interaction within a wind farm is needed. Some estimates show that 10 -40% of wind energy is lost within a wind farm due to underperformance and turbine-turbine interaction. The US Department of Energy has recently announced an initiative to reshape the national research focus around this priority. DOE, in recognizing a testing facility gap, has commissioned Sandia National Laboratories with the design, construction and operation of a facility to perform research in turbine-turbine interaction and wind plant underperformance. Completed in 2013, the DOE/SNL Scaled Wind Farm Technology Facility has been constructed to perform early-stage high-risk cost-efficient testing and development in the areas of turbine-turbine interaction, wind plant underperformance, wind plant control, advanced rotors, and fundamental studies in aero-elasticity, aero-acoustics and aerodynamics. This paper will cover unique aspects of the construction of the facility to support these objectives, testing performed to create a validated model, and an overview of research projects that will use the facility.
Offshore wind turbines are an attractive source for clean and renewable energy for reasons including their proximity to population centers and higher capacity factors. One obstacle to the more widespread installation of offshore wind turbines in the USA, however, is that recent projections of offshore operations and maintenance costs vary from two to five times the land-based costs. One way in which these costs could be reduced is through use of a structural health and prognostics management (SHPM) system as part of a condition-based maintenance paradigm with smart loads management. This paper contributes to the development of such strategies by developing an initial roadmap for SHPM, with application to the blades. One of the key elements of the approach is a multiscale simulation approach developed to identify how the underlying physics of the system are affected by the presence of damage and how these changes manifest themselves in the operational response of a full turbine. A case study of a trailing edge disbond is analysed to demonstrate the multiscale sensitivity of damage approach and to show the potential life extension and increased energy capture that can be achieved using simple changes in the overall turbine control and loads management strategy. The integration of health monitoring information, economic considerations such as repair costs versus state of health, and a smart loads management methodology provides an initial roadmap for reducing operations and maintenance costs for offshore wind farms while increasing turbine availability and overall profit.
<div> <div> <p> </p><div> <div> <div> <p>We present the CHAL336 benchmark set—the most comprehensive database for the assessment of chalcogen-bonding (CB) interactions. After careful selection of suitable systems and identification of three high-level reference methods, the set comprises 336 dimers each consisting of up to 49 atoms and covers both σ- and π-hole interactions across four categories: chalcogen-chalcogen, chalcogen-π, chalcogen-halogen, and chalcogen-nitrogen interactions. In a subsequent study of DFT methods, we re-emphasize the need for using proper London dispersion corrections when treating noncovalent interactions. We also point out that the deterioration of results and systematic overestimation of interaction energies for some dispersion-corrected DFT methods does not hint at problems with the chosen dispersion correction, but is a consequence of large density-driven errors. We conclude this work by performing the most detailed DFT benchmark study for CB interactions to date. We assess 109 variations of dispersion-corrected and -uncorrected DFT methods, and carry out a detailed analysis of 80 of them. Double-hybrid functionals are the most reliable approaches for CB interactions, and they should be used whenever computationally feasible. The best three double hybrids are SOS0-PBE0-2-D3(BJ), revDSD-PBEP86-D3(BJ), and B2NCPLYP-D3(BJ). The best hybrids in this study are ωB97M-V, PW6B95-D3(0), and PW6B95-D3(BJ). We do not recommend using the popular B3LYP functional nor the MP2 approach, which have both been frequently used to describe CB interactions in the past. We hope to inspire a change in computational protocols surrounding CB interactions that leads away from the commonly used, popular methods to the more robust and accurate ones recommended herein. We would also like to encourage method developers to use our set for the investigation and reduction of density-driven errors in new density functional approximations. </p> </div> </div> </div> </div> </div>
This accounts for 1.25% of all U.S. electricity generated and enough to power 7 million homes. As wind energy becomes a key player in power generation and in the economy, so does the performance and reliability of wind turbines. To improve both performance and reliability, smart rotor blades are being developed that collocate reference measurements, aerodynamic actuation, and control on the rotor blade. Towards the development of a smart blade, SNL has fabricated a sensored rotor blade with embedded distributed accelerometer measurements to be used with operational loading methods to estimate the rotor blade deflection and dynamic excitation. These estimates would serve as observers for future smart rotor blade control systems. An accurate model of the rotor blade was needed for the development of the operational monitoring methods. An experimental modal analysis of the SNL sensored rotor blade (a modified CX-100 rotor blade) with embedded DC accelerometers was performed when hung with free boundary conditions and when mounted to a Micon 65/13 wind turbine. The modal analysis results and results from a static pull test were used to update an existing distributed parameter CX-100 rotor analytical blade model. This model was updated using percentage error estimates from cost functions of the weighted residuals. The model distributed stiffness parameters were simultaneously updated using the static and dynamic experimental results. The model updating methods decreased all of the chosen error metrics and will be used in future work to update the edge-wise model of the rotor blade and the full turbine model.
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