No abstract

Abstract. Wind data collection in the atmospheric boundary layer benefits from short-term wind speed measurements using unmanned aerial vehicles. Fixed-wing and rotary-wing devices with diverse anemometer technology have been used in the past to provide such data, but the accuracy still has the potential to be increased. A lightweight drone for carrying an industry-standard precision sonic anemometer was developed. Accuracy tests have been performed with the isolated anemometer at high tilt angles in a calibration wind tunnel, with the drone flying in a large wind tunnel and with the full system flying at different heights next to a bistatic lidar reference. The propeller-induced flow deflects the air to some extent, but this effect is compensated effectively. The data fusion shows a substantial reduction of crosstalk (factor of 13) between ground speed and wind speed. When compared with the bistatic lidar in very turbulent conditions, with a 10 s averaging interval and with the unmanned aerial vehicle (UAV) constantly circling around the measurement volume of the lidar reference, wind speed measurements have a bias between −2.0 % and 4.2 % (root-mean-square error (RMSE) of 4.3 % to 15.5 %), vertical wind speed bias is between −0.05 and 0.07 m s−1 (RMSE of 0.15 to 0.4 m s−1), elevation bias is between −1 and 0.7∘ (RMSE of 1.2 to 6.3∘), and azimuth bias is between −2.6 and 7.2∘ (RMSE of 2.6 to 8.0∘). Key requirements for good accuracy under challenging and dynamic conditions are the use of a full-size sonic anemometer, a large distance between anemometer and propellers, and a suitable algorithm for reducing the effect of propeller-induced flow. The system was finally flown in the wake of a wind turbine, successfully measuring the spatial velocity deficit and downwash distribution during forward flight, yielding results that are in very close agreement to lidar measurements and the theoretical distribution. We believe that the results presented in this paper can provide important information for designing flying systems for precise air speed measurements either for short duration at multiple locations (battery powered) or for long duration at a single location (power supplied via cable). UAVs that are able to accurately measure three-dimensional wind might be used as a cost-effective and flexible addition to measurement masts and lidar scans.

Abstract. Conventional monostatic wind lidar (light detection and ranging) systems are well-established wind speed remote sensing devices in the field of wind energy that provide reliable measurement results for flat terrain and homogeneous wind fields. These conventional wind lidar systems use a common transmitting and receiving unit and become unacceptably inaccurate as the wind fields become increasingly inhomogeneous due to their spatial and temporal averaging procedure (large measurement volume) that is inherent to the monostatic measurement principle. The new three-component fiber laser-based wind lidar sensor developed by the Physikalisch-Technische Bundesanstalt (PTB) uses one transmitting unit (fiber laser) and three receiving units to measure the velocity vector of single aerosols in a spatially highly resolved measurement volume (with diameter d and length l) in heights from 5 m (d=300 µm, l=2 mm) to 250 m (d=14 mm, l=4 m) with a resolution of about 0.1 m s−1. Detailed comparison measurements with a 135 m high wind met mast and a conventional lidar system have proven that the high spatial and temporal resolution of the new, so-called bistatic lidar leads to a reduced measurement uncertainty compared to conventional lidar systems. Furthermore, the comparison demonstrates that the deviation between the bistatic lidar and the wind met mast lies well within the measurement uncertainty of the cup anemometers of the wind met mast for both homogeneous and inhomogeneous wind fields. At PTB, the aim is to use the bistatic wind lidar as a traceable reference standard to calibrate other remote sensing devices, necessitating an in-depth validation of the bistatic lidar system and its measurement uncertainty. To this end, a new, specially designed wind tunnel with a laser Doppler anemometer (LDA) as flow velocity reference has been erected on a platform at a height of 8 m; this allows the new wind lidar to be positioned below the wind tunnel test section to be validated for wind vector measurements that are traceable to the SI units. A first validation measurement within the wind tunnel test section is presented, showing a deviation between the bistatic lidar system and the LDA clearly below 0.1 %.

Abstract. Accurate measurements of turbulence statistics in the atmosphere are important for eddy-covariance measurements, wind energy research, and the validation of atmospheric numerical models. Sonic anemometers are widely used for these applications. However, these instruments are prone to probe-induced flow distortion effects, and the magnitude of the resulting errors has been debated due to the lack of an absolute reference instrument under field conditions. Here, we present the results of an intercomparison experiment between a CSAT3B sonic anemometer and a high-resolution bistatic Doppler lidar, which is inherently free of any flow distortion. This novel remote sensing instrument has otherwise very similar spatial and temporal sampling characteristics to the sonic anemometer and hence served as a reference for this comparison. The presented measurements were carried out over flat homogeneous terrain at a measurement height of 30 m. We provide a comparative statistical analysis of the resulting mean wind velocities, the standard deviations of the vertical wind speed and the friction velocity and investigate the reasons for the observed deviations based on the turbulence spectra and co-spectra. Our results show an agreement of the mean wind velocity measurements and the standard deviations of the vertical wind speed with a comparability of 0.082 and 0.020 m s−1, respectively. Biases for these two quantities were 0.003 and 0.012 m s−1, respectively. Slightly larger differences were observed for friction velocity. Analysis of the corresponding co-spectra showed that the CSAT3B underestimates this quantity systematically by about 3 % on average as a result of co-spectral losses in the frequency range between 0.1 and 5 s−1. We also found that an angle-of-attack-dependent transducer-shadowing correction does not improve the agreement between the CSAT3B and the Physikalisch-Technische Bundesanstalt (PTB) lidar effectively.

A statistical model for austenitic stainless steels for predicting the effect of pressurized water reactor environments on fatigue life for a range of temperatures and strain rates is developed based on analysis of available material data. The compiled fatigue curve data include not only results from America (Keller (1971), Conway (1975), Hale (1977), and Argonne National Laboratory (1999–2005)), but also from Europe (Solin (2006), Le Duff (2008–2010), De Baglion (2011, 2012), Huin (2013) …) and Japan (Kanasaki (1997)). Only fatigue data from polished specimens of wrought material tested under strain control were considered; hollow specimens were not treated herein. The fatigue life correction factor used in this paper was defined as the ratio of life in water at 300 °C (reference conditions) to that in water at service conditions. The model is recommended for predicting fatigue lives that are 103–105 cycles.