Measurement of wind field data in Southeast China.
ABSTRACT: The data presented in this article are the wind measurements acquired from a tower in Southeast China during typhoon Nesat (1709#) and typhoon Haitang (1710#). Three 3D ultrasonic anemometers Wind Master Pro were utilized to obtain 3D wind data. The anemometer works well with wind speed range of 0-65?m/s and wind angle range of 0-360°. Three direction wind speeds and wind angles were recorded per every 0.1?s. The present research analyzed wind characteristics based on recorded data. In this article, the detailed test set-up and data pre-processing methodology for the wind characteristics analysis are provided.
Project description:Short-term wind speed forecasting for Colonia Eulacio, Soriano Department, Uruguay, is performed by applying an artificial neural network (ANN) technique to the hourly time series representative of the site. To train the ANN and validate the technique, data for one year are collected by one tower, with anemometers installed at heights of 101.8, 81.8, 25.7, and 10.0 m. Different ANN configurations are applied for each site and height; then, a quantitative analysis is conducted, and the statistical results are evaluated to select the configuration that best predicts the real data. This method has lower computational costs than other techniques, such as numerical modelling. For integrating wind power into existing grid systems, accurate short-term wind speed forecasting is fundamental. Therefore, the proposed short-term wind speed forecasting method is an important scientific contribution for reliable large-scale wind power forecasting and integration in Uruguay. The results of the short-term wind speed forecasting showed good accuracy at all the anemometer heights tested, suggesting that the method is a powerful tool that can help the Administración Nacional de Usinas y Transmissiones Eléctricas manage the national energy supply.
Project description:An evolution of a previously proposed anemometer capable of detecting both the magnitude and the direction of the wind on a plane is proposed. The device is based on a recently formalized principle, consisting of combining the differential pressures measured across distinct diameters of a cylinder to estimate the wind velocity and incidence angle. Differently from previous sensors based on the same principle, the proposed anemometers use 3D printing to fabricate the channel structure that calculates the pressure combination in the fluidic domain. Furthermore, commercial sensors with low power consumption are used to read the two pressures that result from the fluidic processing. The whole fabrication procedure requires inexpensive equipment and can be adopted by small enterprises or research laboratories. Two original channel structures, predicted by previous theoretical work but never experimentally validated, are proposed. The results of detailed experiments performed in a wind tunnel are reported.
Project description:The aerodynamic performance of vehicles and animals, as well as the productivity of turbines and energy harvesters, depends on the turbulence intensity of the incoming flow. Previous studies have pointed at the potential benefits of active closed-loop turbulence control. However, it is unclear what the minimal sensory and algorithmic requirements are for realizing this control. Here we show that very low-bandwidth anemometers record sufficient information for an adaptive control algorithm to converge quickly. Our online Newton-Raphson algorithm tunes the turbulence in a recirculating wind tunnel by taking readings from an anemometer in the test section. After starting at 9% turbulence intensity, the algorithm converges on values ranging from 10% to 45% in less than 12 iterations within 1% accuracy. By down-sampling our measurements, we show that very-low-bandwidth anemometers record sufficient information for convergence. Furthermore, down-sampling accelerates convergence by smoothing gradients in turbulence intensity. Our results explain why low-bandwidth anemometers in engineering and mechanoreceptors in biology may be sufficient for adaptive control of turbulence intensity. Finally, our analysis suggests that, if certain turbulent eddy sizes are more important to control than others, frugal adaptive control schemes can be particularly computationally effective for improving performance.
Project description:This work presents a simulation framework developed under the widely used Robot Operating System (ROS) to enable the validation of robotics systems and gas sensing algorithms under realistic environments. The framework is rooted in the principles of computational fluid dynamics and filament dispersion theory, modeling wind flow and gas dispersion in 3D real-world scenarios (i.e., accounting for walls, furniture, etc.). Moreover, it integrates the simulation of different environmental sensors, such as metal oxide gas sensors, photo ionization detectors, or anemometers. We illustrate the potential and applicability of the proposed tool by presenting a simulation case in a complex and realistic office-like environment where gas leaks of different chemicals occur simultaneously. Furthermore, we accomplish quantitative and qualitative validation by comparing our simulated results against real-world data recorded inside a wind tunnel where methane was released under different wind flow profiles. Based on these results, we conclude that our simulation framework can provide a good approximation to real world measurements when advective airflows are present in the environment.
Project description:Reanalysis data and a parametric typhoon model formula are often used to prepare wind and pressure fields for storm surge hindcasting. However, their optimum selection and usage have not been well established. To enhance the accuracy of wind and pressure fields, two hybrid methods were proposed by applying a parametric typhoon model of Mitsuta-Fujii's formula, which is determined from the typhoon center to a certain radius of Rb, and then switching to the reanalysis data of ERA-Interim in the outer region through the interpolated transition bandwidth of Wb. In hybrid model I, Rb and Wb were fixed because the time-varying radius of the maximum wind speed was determined by the typhoon formula. In hybrid model II, these parameters were determined to minimize the mean difference between the reanalysis data and the fields obtained by typhoon formula in the transition band at each time step of the typhoon track. The hindcasting of eight significant typhoon events approaching Tokyo Bay was performed. This validated the proposed methods in comparison with the observed storm surge anomalies. Both models performed satisfactorily. Hybrid model II was found to be superior in terms of the balance of accuracy and preparation cost.
Project description:In this paper, the normal and extreme wind conditions for power at 12 coastal locations along China's coastline were investigated. For this purpose, the daily meteorological data measured at the standard 10-m height above ground for periods of 40-62 years are statistically analyzed. The East Asian Monsoon that affects almost China's entire coastal region is considered as the leading factor determining wind energy resources. For most stations, the mean wind speed is higher in winter and lower in summer. Meanwhile, the wind direction analysis indicates that the prevalent winds in summer are southerly, while those in winter are northerly. The air densities at different coastal locations differ significantly, resulting in the difference in wind power density. The Weibull and lognormal distributions are applied to fit the yearly wind speeds. The lognormal distribution performs better than the Weibull distribution at 8 coastal stations according to two judgement criteria, the Kolmogorov-Smirnov test and absolute error (AE). Regarding the annual maximum extreme wind speed, the generalized extreme value (GEV) distribution performs better than the commonly-used Gumbel distribution. At these southeastern coastal locations, strong winds usually occur in typhoon season. These 4 coastal provinces, that is, Guangdong, Fujian, Hainan, and Zhejiang, which have abundant wind resources, are also prone to typhoon disasters.
Project description:Concentrations of airborne chemical and biological agents from a hazardous release are not spread uniformly. Instead, there are regions of higher concentration, in part due to local atmospheric flow conditions which can attract agents. We equipped a ground station and two rotary-wing unmanned aircraft systems (UASs) with ultrasonic anemometers. Flights reported here were conducted 10 to 15 m above ground level (AGL) at the Leach Airfield in the San Luis Valley, Colorado as part of the Lower Atmospheric Process Studies at Elevation-a Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) campaign in 2018. The ultrasonic anemometers were used to collect simultaneous measurements of wind speed, wind direction, and temperature in a fixed triangle pattern; each sensor was located at one apex of a triangle with ∼100 to 200 m on each side, depending on the experiment. A WRF-LES model was used to determine the wind field across the sampling domain. Data from the ground-based sensors and the two UASs were used to detect attracting regions (also known as Lagrangian Coherent Structures, or LCSs), which have the potential to transport high concentrations of agents. This unique framework for detection of high concentration regions is based on estimates of the horizontal wind gradient tensor. To our knowledge, our work represents the first direct measurement of an LCS indicator in the atmosphere using a team of sensors. Our ultimate goal is to use environmental data from swarms of sensors to drive transport models of hazardous agents that can lead to real-time proper decisions regarding rapid emergency responses. The integration of real-time data from unmanned assets, advanced mathematical techniques for transport analysis, and predictive models can help assist in emergency response decisions in the future.
Project description:The dataset consists of 39 years of directional wave time series recorded since 1979 at the CNR-ISMAR "Acqua Alta" oceanographic research tower, located in the Northern Adriatic Sea. The extent of the time series allows us to describe the wave climate in the North Adriatic region and to identify trends and links with large scale climate patterns obtained from a single and permanent observational source. The northern part of the Adriatic Sea is characterized by two main wind and correspondingly wave regimes, strongly forced by the regional orography. The high sensitivity of this particular area to even small variations of large scale meteorological patterns allows to explore possible links of the local wave, hence wind, activity with large-scale north hemisphere circulation or weather regimes. Different wave gauges have been used since the start of the measurements, progressively upgraded and repositioned during maintenance operations. The recorded wave data have been thoroughly verified and corrected where necessary.
Project description:Due to their destructive and sporadic nature, it is often difficult to evaluate and predict the effects of typhoon on forest ecosystem patterns and processes. We used a 21-yr record of litterfall rates to explore the influence of typhoon frequency and intensity, along with other meteorological variables, on ecosystem dynamics in a subtropical rainforest. Over the past half century there has been an increasing frequency of strong typhoons (category 3; >49.6?m s-1; increase of 1.5 typhoons/decade) impacting the Fushan Experimental Forest, Taiwan. At Fushan strong typhoons drive total litterfall mass with an average of 1100?kg ha-1 litterfall typhoon-1. While mean typhoon season litterfall has been observed to vary by an order of magnitude, mean litterfall rates associated with annual leaf senescence vary by <20%. In response to increasing typhoon frequency, total annual litter mass increased gradually over the 21-year record following three major typhoons in 1994. Monthly maximum wind speed was predictive of monthly litterfall, yet the influence of precipitation and temperature was only evident in non-typhoon affected months. The response of this subtropical forest to strong typhoons suggests that increasing typhoon frequency has already shifted ecosystem structure and function (declining carbon sequestration and forest stature).
Project description:Typhoon is a major cause of multiple disasters in coastal regions of East Asia. To advance our understanding of typhoon-ocean interactions and thus to improve the typhoon forecast for the disaster mitigation, two data buoys were deployed in the western North Pacific, which captured Super Typhoon Nepartak (equivalent to Category 5) in July 2016 at distances <20 km from the typhoon's eye center. Here we demonstrate that the unprecedented dataset combined with the modeling results provide new insights into the rapid temperature drop (~1.5 °C in 4 h) and the dramatic strengthening of velocity shear in the mixed layer and below as the driving mechanism for this rapid cooling during the direct influence period of extremely strong winds. The shear instability and associated strong turbulence mixing further deepened the mixed layer to ~120 m. Our buoys also observed that inertial oscillations appeared before the direct wind influence period.