Hasselmann and coauthors proposed the discrete interaction approximation (DIA) as the best tool replacing the nonlinear evolution term in a numerical wind-wave model. Much later, Polnikov and Farina radically improved the original DIA by means of location all the interacting four wave vectors, used in the DIA configuration, exactly at the nodes of the numerical frequency-angular grid. This provides nearly two-times enhancing the speed of numerical calculation for the nonlinear evolution term in a wind-wave model. For this reason, the proposed version of the DIA was called as the fast DIA (FDIA). In this paper we demonstrate all details of the FDIA concept for several frequency-angular numerical grids of high resolution, with the aim of active implementation the FDIA in modern versions of world-wide used wind-wave models.

The formation and localization of sporadic E(Es) layers predicted by the ions vertical drift velocity and its vertical change in the lower thermosphere during nighttime are shown analytically and by numerical simulations. The consideration of existence of a minimum negative value of the vertical change of the ions vertical drift velocity as a necessary condition of formation of Es layer and determining ions convergence rate into this layer, is extended in case of the presence of vertical wind. Upward vertical wind can shift the convergence regions upward, while downward vertical wind shift them downward, unlike the cases of presence of only meridional and zonal winds. It also changes the ion convergence rate compared to the one with just a horizontal wind. It is shown for the first time that the upward constant wind also causes the convergence of ions with maximum rate in the region where the ion-neutral collision frequency is equal to their cyclotron frequency. While demonstrating the presented theory by numerical simulations, HWM14 data is used for the meridional and zonal wind velocity profiles and the presence of its vertical component is assumed. In this case, in addition to the estimated ion drift velocity and its vertical changes, their initial distribution and ambipolar diffusion also determine the development of ion convergence/divergence processes. For small magnitude of vertical wind velocity, its significant influence on the ions/electrons behavior is demonstrated, which shows the importance of both tidal wind and wind changes caused by the propagation of atmospheric gravity waves on the formation of the Es layer. In this theoretical research it is shown that the realistic profile of the wind velocity, which takes into account the vertical component along with its zonal and meridional ones, is important for prediction of the Es layers formation, as well as regions of ion depletion.

Wave buoy measurements were carried out near the north-eastern Black Sea coast at the natural reserve Utrish in 2020-2021. In total, about 11 months of data records were collected during two stages of the experiment at 600 and 1500 meters offshore and depths of 18 and 42 meters. The measured waves propagate almost exclusively from the seaward directions. Generally, the waves do not follow the local wind directions, thus, implying a mixed sea state. Nevertheless, dimensionless wave heights and periods appears to be quite close to the previously established empirical laws for the wind-driven seas. The results of the wave turbulence theory are applied for estimates of spectral energy fluxes and their correspondence to the energy flux from the turbulent wind pulsations. These estimates are consistent with today's understanding of wind-wave interaction. It is shown that the main fraction of the wind energy flux goes to the direct Kolmogorov-Zakharov cascade to high wave frequencies and then to dissipation in small scales. Less than 1% of the wind energy flux is directed to low frequency band (the so-called inverse Kolmogorov-Zakharov cascade), thus, providing wave energy growth.

The aim of work is to derive an explicit expression for a function of vertical mixing induced by wind-waves. To this end, in the Navier-Stokes equations, a current is decomposed into four constituents: the mean flow, the wave-orbital motion, the wave-induced turbulent and the background turbulent currents. This decomposition allows separating the wave-induced Reynolds stress, Rw, from the background one, Rb. To make a statistical closure for Rw, the Prandtl approach for the background turbulent fluctuations is used that results in an implicit expression for the wave-induced vertical mixing function, Bv. Expression for Bv is specified based on the author’s results for the eddy viscosity found earlier in the frame of the three-layer concept for a wavy air–sea interface, used for modelling wind-drift currents [1]. Finally, the explicit parameterization for Bv(a, u*, z) is found as a linear function in both the wave amplitude at depth z, a(z), and the friction velocity in the air, u*. The linear dependence of function Bv(a) on the wave amplitude provides the enhanced vertical mixing induced by wind–waves in comparison with function Bv(a) having the cubic dependence found in [2], as far as the wind-wave amplitude a(z) decays exponentially with depth.

The quiet-time solar wind electrons feature non-thermal characteristics when viewed from the perspective of their velocity distribution functions. They typically have an appearance of being composed of a denser thermal “core” population plus a tenuous energetic “halo” population. At first, such a feature was empirically fitted with the Kappa velocity space distribution function, but ever since the ground-breaking work by Tsallis, the space physics community has embraced the potential implication of the Kappa distribution as reflecting the non-extensive nature of the space plasma. From the viewpoint of microscopic plasma theory, the formation of non-thermal electron velocity distribution function can be interpreted in terms of the plasma being in a state of turbulent quasi equilibrium. Such a finding brings forth the possible existence of a profound inter-relationship between the non-extensive statistical state and the turbulent quasi-equilibrium state. The present paper further develops the idea of solar wind electrons being in the turbulent equilibrium, but unlike the previous model, which involves the electrostatic turbulence near the plasma oscillation frequency (i.e., Langmuir turbulence), the present paper considers the impact of transverse electromagnetic turbulence, particularly, the turbulence in the whistler-mode frequency range. It is found that the coupling of spontaneously-emitted thermal fluctuations and the background turbulence leads to the formation of non-thermal electron velocity distribution function of the type observed in the solar wind during quiet times. This demonstrates that the whistler-range turbulence represents an alternative mechanism for producing the Kappa-like non-thermal distribution, especially close to the Sun and in the near-Earth space environment.

Wave breaking is one of the most important yet poorly understood water wave phenomena. It is via wave breaking that waves dissipate most of their energy and the occurrence of wave breaking directly influences several environmental processes, from ocean-atmosphere gas exchanges to beach morphodynamics. Large breaking waves also represent a major threat for navigation and for the survivability of offshore structures. This paper provides a systematic search for intermediate to deep water breaking waves with particular focus on the elusive occurrence of plunging breakers. Using modern remote sensing and deep learning techniques, we identify and track the evolution of over four thousand unique wave breaking events using video data collected from La Jument lighthouse during ten North Atlantic winter storms. Out of all identified breaking waves (Nb=4683), ≈22% were dominant breaking waves, that is, waves that have speeds within [0.77cp, 1.43cp], where cp is the peak wave speed. Correlations between the occurrence rate of dominant breaking waves (that is, waves per area and time per peak wave period) and wave steepness and wave age were observed. As expected, the number of identified plunging waves was small and six waves of all detected breaking waves, or 0.13%, could undoubtedly be considered as plunging waves. Two waves were also identified as unusually large, or rogue waves. Although afflicted by several technical issues, the data presented here provides a good indication that the probability of occurrence of plunging waves should be better incorporated into the design of offshore structures, particularly the ones that aim to harvest energy in offshore environments.

This study examines the wind shear coefficient (WSC) values at three coastal wind sites located in the southern region of Balochistan, Pakistan: Pasni, Ormara, and Jiwani. These WSC values were obtained using 10-minute measured wind speed data at heights of 20, 40, and 60 meters above ground level (AGL). Since wind measurements are typically recorded at lower heights due to cost and resource constraints, extrapolation techniques were employed to estimate wind speeds at higher altitudes. However, using a constant WSC value for extrapolation may lead to significant errors between extrapolated and actual wind speed measurements, impacting the energy output of wind turbines. To evaluate the effect of WSC on energy yield, the study employed power curves and frequency distributions for 2MW and 1.5MW wind turbines. Additionally, wind power density was calculated using air density derived from measured air temperature and surface pressure data, covering two years period from November 2016 to August 2018. The overall mean WSC values were found to be 0.076 at Pasni, 0.094 at Jiwani, and 0.053 at Ormara. The study further investigated the seasonal, monthly, and diurnal variations of WSC. For assessing wind resources at a height of 60m, the study utilized Wind Roses, wind power density, and Weibull parameters. Comparing the actual WSC values presented in this paper with those obtained using the 1/7 power law and measured data at 60m AGL, the energy yield from the wind turbines showed reduced output and capacity factor.

The coastal zone faces an ever-growing risk associated with climate-driven change, including sea level rise and increased frequency of extreme natural hazards. Coastal processes are governed by the dynamic ocean and atmospheric factors with constantly changing conditions. Often the location and dynamism of coastal regions makes them a formidable environment to adequately study with in-situ methods. Remote sensing methods offer an alternative to in-situ monitoring. In this study we use Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) to make measurements of basic wave parameters and wave directionality in the Hawaiian Islands and North Carolina, USA. ICESat-2 has existing Level-3a data products, Ocean Surface Height (ATL12) and Inland Water Elevation (ATL13), providing some wave and ocean surface elevation data. ATL12 provides sparse global average measurements of the sea surface elevation, slope, and roughness along ICESat-2 tracks and ATL13 provides wave metrics at variable length scales out to ~7 km from the coast and does not maintain the 0.7m along-track resolution of the primary Level-2 data product (ATL03). Our goal was to leverage the full resolution data available in ATL03 to generate wave metrics out from shore up to ~25 km. Using a combination of statistical and signal processing methods we can use ICESat-2 to generate basic wave metrics, including significant wave heights with an accuracy of ±0.5m. In some profiles we can identify wave shoaling, which could be used to infer bathymetry. In areas with complex wave dynamics, the nature of how ICESat-2 measures elevations (parallel laser altimetry beams) can make extracting some wave parameters (e.g., wavelength and directionality) more challenging. These wave metrics can provide important data in support of validating wave and tidal models and may also prove useful in ICESat-2 bathymetric corrections and satellite derived bathymetry.

Gravitational waves have been detected in the past few years from several transient events such as merging stellar mass black holes, binary neutron stars, etc. These waves have frequencies in a band ranging from a few hundred hertz to around a kilohertz to which LIGO type instruments are sensitive. LISA would be sensitive to much lower range of frequencies from SMBH mergers. Apart from these cataclysmic burst events, there are innumerable sources of radiation which are continuously emitting gravitational waves of all frequencies. These include a whole mass range of compact binary and isolated compact objects as well as close planetary stellar entities. In this work, quantitative estimates are made of the gravitational wave background produced in typical frequency ranges from such sources emitting over a Hubble time and the fluctuations in the h values measured in the usual devices. Also estimates are made of the high frequency thermal background gravitational radiation from hot stellar interiors and newly formed compact objects.

The accuracy of wind field simulation and prediction is one of the most significant parameters in the field of atmospheric science and wind energy. Limited by the observation data, there are few researches on wind energy development. A 3D Doppler wind lidar (DWL) providing the high-vertical-resolution wind data over the urban complex underlying surface in February 2018 was employed to evaluated the accuracy of vertical wind field simulation systematically for the first time. 11 PBL schemes of the Weather Research and Forecasting Model (WRF) were employed in simulation. The model results were evaluated in groups separated by weather (sunny days, haze days and windy days), observation height layers, and various observation wind speeds. The test results presented that the vertical layer altitude of the observation point position was the most important factor. The simulation is fairly well at a height of 1000-2000m, as most of the relative mean bias of wind speed and wind direction are less than 20% and 6% respectively. Below 1000 m, the wind speed and direction biases are about 30%-150% m.s-1 and 6%-30% respectively. Moreover, when the observed wind speed was lower than 5 m.s-1, the bias were usually large, and the wind speed relative mean bias is up to 50-300%. In addition, the accuracy of simulated wind profile is better in 10-15m.s-1 than other speed ranges, and is better up 1000m than below 1000m in the boundary layer. We see that the WRF boundary layer schemes have different applicability to different weather conditions. The WRF boundary layer schemes have significant differences in wind field simulation with larger error under the complex topography. A PBL scheme is not likely to maintain its advantages in the long term under different conditions including altitude and weather conditions.

In Zambia, three feasibility studies have been conducted to assess the potential of wind energy for power generation. However, these studies did not investigate the capability of local support industries to manufacture wind turbine blades and towers. This study aimed to investigate and profile the capability of Zambian industries to manufacture wind turbine blades and towers. The study used a mixed-method approach to collect data; this utilized qualitative and quantitative approaches. The population of Zambian industries was collected from the Zambia Association of Manufacturers based on the registered members. This data was used to define the population for the study; the population was arranged into three strata whose characteristics are homogeneous within the stratum. Due to the low population, the study was conducted on the whole population. The qualitative data was collected from each stratum using a quantitative data collection tool developed for each stratum and analyzed. The study considered the capability of manufacturing companies based on wind potential results for Class III and Class IV, which exist in some sites. The results have revealed that on an as-is basis, no company in Zambia can manufacture WT blades and towers unless there is a complete overhaul of some companies or total investment in new infrastructure and equipment. The findings are useful for stakeholders involved in developing the wind power sector in Zambia.

This paper addresses investigation of guided-wave excitation by angle-beam wedge piezoelectric transducers in multi-layered composite plate structure with orthotropic symmetry of the material. The aim of the present study is to determine the capability of such actuators to provide the controlled generation of an acoustic wave of a desirable type with the necessary wavelength, propagation distance and directivity. The studied CFRP panel is considered as homogenous with effective elastic moduli and anisotropic structural damping, whose parameters were determined experimentally. According to the results of dispersion analysis and taking into account the data of wave attenuation in a highly damping CFRP composite, the two types of propagating waves A0 and S0 were considered theoretically and experimentally in the frequency range 10 - 100 kHz. Using the results of a previous study, the structure of the wedge actuator was reconstructed to develop its finite element (FE) model, and a modal analysis was carried out, which revealed the most intense natural vibration modes and their eigenfrequencies within the used frequency range. Both experimental and numerical studies of the generation, propagation, directivity and attenuation of waves in the orthotropic composite panel under study revealed the influence of the angular orientation of the actuator on the formation of wave patterns and allowed to determine the capabilities of the wave's directivity control.

Taiwan developing offshore wind power to promote green energy and self-electricity production. In this study, a Light Detection and Ranging (Lidar) was set up at Chang-Hua development zone one on the sea and 10km away from the seashore. At Lidar location, WRF (3.33km & 2km grid lengths) model and WAsP were used to simulate the wind speed at various elevations. Three days mean wind speed of simulated results were compared with Lidar data. From the four wind data sets, developed five different comparisons to find an error% and R-Squared values. Comparison between WAsP and Floating Lidar was shown good consistency. Lukang meteorological station 10 years wind observations at 5m height were used for wind farm energy predictions. The yearly variation of energy predictions of traditional and TGC wind farm layouts are compared under purely neutral and stable condition. The one-year cycle average surface heat flux over the Taiwan Strait is negative (-72.5 (W/m2) and 157.13 STD), which represents stable condition. At stable condition TGC (92.39%) and 600(92.44%), wind farms were shown higher efficiency. The Fuhai met mast wind data was used to estimate roughness length and power law exponent. The average roughness lengths are very small and unstable atmosphere.

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

This paper describes the design and implementation of an ultrasonic non-contact air-coupled technique (UNCACT) using antisymmetric Lamb waves (ALW) for NDT assessment in novel composite sandwich plates of the car body shell. This technique is complemented with a C-Scan image implementation using this kind of guided waves. The finite element method using Comsol 6.1 is developed for the interpretation of the several wave modes presented in the experiments, including the ALW mode. The phase velocity method (PVM) is applied for the verification of the ALW mode in the portion of the RF signal necessary in the C-Scan image.

The paper is aimed to develop an improved acoustic-based Structural Health Monitoring (SHM) and Non-Destructive Evaluation (NDE) techniques, which provide the waves directivity emitting by the angle-beam wedge actuators in the thin-walled structures made of plastic materials and polymeric composites. Our investigation includes the dispersive analysis of the waves that can be excited in the studied plastic panel. Its results allowed to find two kinds of the generated acoustic waves - anti-symmetric Lamb waves A0 and shear horizontally polarized SH waves SS0. The bounds of the chosen frequency range for the experimental and numerical studies were accepted as a compromise between the desire to obtain high defects resolution by generating short waves, their adjustable directivity and maximum propagation length. The finite element model for the transducer was built by using the results of actuator structure experimental study. The frequency response functions for the actuator current and oscillation amplitude of the footprint surface demonstrated good agreement. The found eigenfrequencies of actuator's structure were used for the numerical and experimental study of the Lamb and SH wave generation and propagation in a thin-walled plastic panel. Our results convincingly demonstrated the satisfactory directivity of the actuated waves at their excitation on the frequencies that corresponded to the natural modes of the actuator oscillation. The authors assume that an efficient use of the proposed technique for other analyzed quasi-isotropic materials and applied actuators can be provided by a preliminary research using the similar approach and methods presented in this article.

Growing population, industrialization, and power requirements are adversely affecting the environment by increased greenhouse gases, resulting from fossil fuel burning. Global greenhouse gas mitigation targets have led the nations to promote clean and self-renewable sources of energy to address the environmental issue. Offshore wind power resources are relatively more attractive due to high winds, less turbulence, minimal visualization effects, and no interaction of infrastructure. The present study aims at conducting offshore wind power resources assessment (OWPRA) at some locations in the Gulf of North Suez. For this purpose, the long-term hourly mean wind speed (WS) and wind direction above means sea level (AMSL) and temperature and pressure data near surface is used. The data is obtained from ERA5 (fifth generation reanalysis for the global climate weather) at chosen six (L1-L6) offshore locations. The data covers a period of 43 years, between 1979 and 2021. The WS and direction are provided at 100 m AMSL while temperature and pressure are available near water surface level. At L1 to L6 locations, the log-term mean WS and wind power density (WPD) values are found to be 7.55 m/s and 370 W/m2, 6.37 m/s and 225 W/m2, 6.91 m/s and 281 W/m2, 5.48 m/s and 142 W/m2, 4.30 m/s and 77 W/m2, and 5.03 and 115 W/m2 and at 100 m AMSL; respectively. The higher magnitudes of monthly and annual windy site identifier indices (MWSI and AWSI) of 18.68 and 57.41 and 12.70 and 42.94 at L1 and L3 sites and generally lower values of wind variability indices are indicative of favourable winds source, which is also supported by higher magnitudes of mean WS, WPD, annual energy yields, plant capacity factors, and wind duration at these sites. The cost of energy, for the worst and the best cases are estimated as 10.120 USD/kWh and 1.274 USD/kWh at L5 and L1 sites corresponding to wind turbines WT1 and WT4. Based on the analysis, sites L1, L3, and L2 are recommended for wind farm development in order of preference. The wind variability and windy site identifiers indices introduced, will help decision-makers in deciding the potential windy sites with more confidence.

Wind power output is highly dependent on the wind speed at the selected site, therefore wind-speed distribution modeling is the most important step in the assessment of wind energy potential. This study aims at accurate evaluation of onshore wind energy potential in seven coastal cities in the south of Iran. Six Probability Distribution Functions (PDFs) were examined over representative stations. It has been deduced that the Weibull function, which was the most used PDF in similar studies, was only applicable to one station. Here, Gamma offered the best fit for three stations and for the other ones, Generalized Extreme Value (GEV) performed better. Considering the ranking of six examined PDFs and the simplicity of Gamma, it was identified as the effective function in the southern coasts of Iran bearing in mind the geographic distribution of stations. Besides, six turbine power curve functions were contributed to investigate the capacity factor. That was very important, as using only one function could cause under- or over-estimation. Then, stations were classified based on the National Renewable Energy Laboratory system. Last but not least, examining a range of wind turbines enabled scholars to extend this study into the practice and prioritize development of stations considering budget limits.

It is shown that de Sitter accelerated expansion of the Universe (dark energy effect) is an exact solution to the set of self-consistent stochastic nonlinear gravitational waves in the FLRW metric coming to the Universe from “nowhere”.

We present a numerical calculation of the heat transport in a Bragg mirror configuration made of materials that do not obey Fourier's law of heat conduction. The Bragg mirror is made of materials that are described by the Cattaneo-Vernotte equation. By analyzing the Cattaneo-Vernotte equation's solutions, we define the thermal wave surface impedance to design highly reflective thermal Bragg mirrors. Even for mirrors with a few layers, very high reflectance is achieved ($>90\%$). The Bragg mirror configuration is also a system that makes evident the wave-like nature of the solution of the Cattaneo-Vernotte equation by showing frequency pass-bands that are absent if the materials obey the usual Fourier's law.

Laminate structures composed of stiff plates and thin soft interlayers are widely used in aerospace, automotive and civil engineering encouraging the development of reliable non-destructive strategies for their condition assessment. In the paper, elastodynamic behaviour of such laminate structures is investigated with emphasis on its application in ultrasonic based NDT and SHM for the identification of interlayer mechanical and interfacial contact properties. A particular attention is given to the practically important frequency range, in which the wavelength considerably exceeds the thickness of the film. Three layer model with spring-type boundary conditions employed for imperfect contact simulation is used for numerical investigation. Novel effective boundary conditions are derived via asymptotic expansion technique and used for analysis of the peculiar properties of elastic guided waves in considered laminates. It is revealed that the thin and soft film influences the behaviour of the laminate mainly via the effective stiffnesses being a combination of the elastic moduli of the film, its thickness and interface stiffnesses. To evaluate each of these parameters separately (or to figure out that the available experimental data are insufficient), a step-wise procedure employing the effective boundary conditions is proposed and tested versus the laser Doppler vibrometry data for Lamb waves in Aluminium/Polymer film/Alumunium structure. The possibility of using film-related thickness resonance frequencies to estimate the film properties and contact quality is also demonstrated. Additionally, the rich family of edge waves is also investigated, and the splitting of fundamental edge waves into pairs is revealed.

The need to understand the process by which particles, including solar wind and coronal ions as well as pickup ions, are accelerated to high energies (ultimately to become anomalous cosmic rays) motivate a multi-fluid shock wave model which includes kinetic effects (e.g. ion acceleration) in an electromagnetically self-consistent framework. Particle reflection at the cross-shock potential leads to ion acceleration in the motional electric field and thus anisotropic heating and pressure in the shock layer, with important consequences for the multi-fluid dynamics. This motivates development of a multi-fluid model of solar wind electrons and ions treated as fluid, coupled self-consistently with a small population of kinetically treated ions (e.g. pickup ions.) Consideration of both the time dependent and steady state regimes, indicate that such a multi-fluid approach is necessary for resolving the, Debye scale, particle reflecting cross-shock potential and subsequent dynamics. To study charge separation effects in narrow, supersonic wave layers we consider a reduction of the system to the steady state for cold ions and hot electrons and find two types of solitary waves inherent to the reduced two-fluid system in this limiting case.

The use of wind energy has been developing fast over the last years. The global cumulative wind power capacity increased by 10.5% in 2019, most of which comes from onshore wind farms. One of the consequences of this continuous increase is the use of land for onshore wind farms. There are already cases worldwide where lack of well-established plans and strategies have caused delays in projects. The need for efficiently using land for wind farms will be mandatory in the short term. In this work, we present a numerical analysis to evaluate wind farm land-use. By defining the ratio between mechanical output power over an area as a parameter called land-use ratio, this work focused on comparing several cases of aligned and staggered layouts. Mechanical output power was estimated using a validated code based on Blade Element Momentum code, and the wake velocities and wake interaction effects were estimated using a validated wind turbine CFD model. In terms of output power, staggered designs are more efficient than aligned designs. However, the results showed that even though staggered designs produced higher output power, aligned farms with tight lateral spacing could be as efficient as staggered ones in terms of land-use but using fewer turbines. In summary, tightly aligned designs should be a tendency in the future towards efficient use of land in wind farms.

This study investigates the power production and blade fatigue of a three-turbine array subjected to active yaw control (AYC) in full-wake and partial-wake configurations. A framework of two-way coupled large-eddy simulation (LES) and aeroelastic blade simulation is applied to simulate the atmospheric boundary-layer (ABL) flow through the turbine array and the structural responses of the turbine blades. Mean power outputs and blade fatigue loads are extracted from the simulation results. By exploring the feasible AYC decision space, we find that (a) in the full-wake configuration, the local power-optimal AYC strategy with positive yaw angles endures less flapwise blade fatigue and more edgewise blade fatigue than the global power-optimal strategy; (b) in the partial-wake configuration, applying positive AYC in certain inflow wind directions achieves higher optimal power gains than that in the full-wake scenario and reduces the blade fatigue from the non-yawed benchmark. Through a theoretical analysis based on the blade element momentum theory, we reveal that the aforementioned differences in flapwise blade fatigue between the positively and negatively yawed turbine are due to the differences in the azimuthal distributions of the local relative velocity on blade sections, resulting from the combined effects of vertical wind shear and blade rotation. Furthermore, the difference in the blade force between the positively and negatively yawed front-row turbine induces different wake velocity and turbulence distributions, causing different fatigue loads on the downwind turbine exposed to the wake.

Full-scale wind turbine technology has been widely developing in the recent years and condition monitoring techniques assist at the scope of making 100\% technical availability a realistic perspective. In this context, several retrofitting techniques are being used for further improving the efficiency of wind kinetic energy conversion. This kind of interventions is costly and, furthermore, the estimation of the energy enhancement is commonly provided under the hypothesis of ideal conditions, as for example absence of wakes between nearby turbines. A precise quantification of the energy gained by retrofitting is therefore precious in real conditions, that can be very different from ideal ones. In this work, three kinds of retrofitting are studied through the operational data of test case wind farms: improved start-up through pitch angle adjustment near the cut-in, aerodynamic blade retrofitting by means of vortex generators and passive flow control devices, extension of the power curve by raising cut-out and high wind speed cut-in. SCADA data are employed and reliable methods are formulated for estimating the energy improvement from each of the above retrofitting. Further, an insight is provided about wind turbine functioning under very stressing regimes, as for example high wind speeds.

The article discusses the possibility of detecting of gravitons using recently created devices with cold atoms at picokelvin temperatures.

Recently, a rising use of wireless internet technologies has been demonstrated. The devices 18 which use these technologies emit in new spectral regions an electromagnetic radiation (EMFs) 19 which could interact with the male reproductive system. The aim of this study was to investigate in 20 vitro influence of electromagnetic fields at 27 GHz on sperm quality in Mytilus galloprovincialis. 21 Sperm samples, were collected from sexually mature males of M. galloprovincialis and placed in sea- 22 water. Once evaluated the number and quality of spermatozoa, sperm cells were exposed to elec- 23 tromagnetic fields radiated by a pyramidal horn antenna. The effect of exposure was evaluated after 24 10, 20, 30, 40 and 60 minutes with light microscope and using Eosin test. Ten replications were per- 25 formed for each time series, and statistical analysis was carried out byt-test. A significative decrease 26 in sperm motility was observed after 10 minutes of exposure and after 30 minutes most of sperms 27 were immobile and not vital. This study provides useful data on potential ecological impact of the 28 5G high-band on animal fertility, whose effect is currently under investigation.

The main goal of the paper is to compare the effects of the wave spectrum, computed using the Discrete Interaction Approximation (DIA) and the Webb–Resio–Tracy (WRT) methods, on statistical wave properties such as skewness and kurtosis. The statistical properties are obtained by integrating the three-dimensional free-surface Euler equations with a high-order spectral method combined with a phenomenological filter to account for the energy dissipation due to breaking waves. In addition, we investigate the minimum spatial domain size required to obtain meaningful statistical wave properties. The numerical simulations are performed over a physical domain of size 4.13 km × 4.13 km. The results indicate that statistical properties must be computed over an area of at least 4 km2. The results also suggest that selecting a more computationally expensive WRT method does not affect the statistical values to a great extent. The most noticeable effect is due to the energy dissipation filter that is applied. It is concluded that selecting the WRT or the DIA algorithm for computing the wave spectrum needed for the numerical simulations does not lead to major differences in the statistical wave properties. However, more accurate energy dissipation mechanisms due to wave breaking are needed.

Considering that traditional energy sources such as fossil fuel are about to deplete during the following decades, governments try to turn to renewable energy. It is commonly known that Greece has a natural advantage of abundant solar energy and wind power due to its geographical location and characteristics.The main focus of this study is to examine how wind energy potential across the Aegean Sea and continental Greece can provide a promising field for investments in Greece, considering the economic crisis, current trends and future perspectives.We firstly focus on current legislation framework considering that laws associated with such types of investment in Greece are very complex and rapidly changing. Furthermore, a case study for a hypothetical investment plan concerning a wind park located in an Aegean island will be presented. RetScreen which is a software made by the Canadian government, will be used as a decision support tool for analyzing the potential investment scenario and a financial report will follow with estimation of the overall cost, depreciation, upcoming benefits, and payback period of the investment.Data analysis concludes that wind parks still prove to be an economically viable investment, although incentives considering the guaranteed price per kwh and faster investment times must be provided by the government.

The kinetic energy transfer between the atmosphere and oceans, called wind work, affects ocean dynamics including near-inertial oscillations and internal gravity waves, mesoscale eddies, and large-scale zonal jets. For the most part, recent numerical estimates of global wind work amplitude are almost 5 times larger than those reported 10 years ago. This large increase is explained by the impact of the broad range of spatial and temporal scales covered by winds and currents, the smallest of which have only recently been uncovered by increasingly high resolution modeling efforts. However, existing satellite observations do not fully sample this broad range of scales. The present study assesses the capabilities of ODYSEA, a conceptual satellite mission to estimate the amplitude of wind work in the global ocean. To this end, we use an ODYSEA measurement simulator fed by the outputs of a km-scale coupled ocean-atmosphere model to estimate wind work globally. Results indicate that compared with numerical truth estimates, the ODYSEA instrument performs well globally, except for latitudes north of 40∘N during summer due to unresolved storm evolution. This performance is explained by the wide-swath properties of ODYSEA (a 1,700 km wide swath with 5 km posting for winds and surface currents), its twice-a-day (daily) coverage at mid-latitudes (low latitudes), and the insensitivity of the wind work to uncorrelated errors in estimated wind and current.

Considering the dynamic stall effects in engineering calculations is essential for correcting the aerodynamic loads acting on wind turbines, both during power production and stand-still cases, and impacts significantly the turbine aeroelastic stability. The employed dynamic stall model needs to be accurate and robust for a wide range of airfoils and range of angle of attack. The present studies are intended to demonstrate the performance of a recently implemented "IAG dynamic stall" model in a wind turbine design tool Bladed. The model is transformed from the indicial type of formulation into a state-space representation. The new model is validated against measurement data and other dynamic stall models in Bladed for various flow conditions and airfoils. It is demonstrated that the new model is able to reproduce the measured dynamic polar accurately without airfoil specific parameter calibration and has a superior performance compared to other models in Bladed.

For the Philippines, a country exposed to multiple natural hazards like severe wind, sustainable development includes resiliency. Severe wind hazard is brought by tropical cyclones in the Western Pacific, known as typhoons, that frequent the Philippines. Therefore, adequately evaluating the wind hazard and its impact is crucial for sustainable building design. Acknowledging the impacts of climate change on said hazards would require adaptation to its consequences which necessitate a deeper understanding on the changing behavior of typhoons in recent years. For this study, detailed wind information from the Japan Meteorological Agency from 1977-2021, the Holland-B parameter, and the radius of maximum wind speed for each typhoon, are determined for simulation of the regional cyclonic wind field. The analysis of the Holland-B parameters, which represent the steepness of the pressure gradient and tropical cyclone convection, suggest that the Holland-B parameters have been increasing since 2011. The regional wind fields caused by the typhoons also suggest an increasing trend in severe wind hazard. Seasonality for the location of severe wind hazard is also observed, with the Southern Philippines experiencing an increase (decrease) during the Northeast (Southwest) Monsoon season, and the Northern Philippines experiencing an increase (decrease) during the Southwest (Northeast) Monsoon season.

Wind energy is becoming an essential source of power for countries which have the aim to reduce greenhouse gases emission and mitigate the effects of global warming. The Wind Turbines (WTs) installed around the globe is increasing significantly every year. The dramatic increase in wind power has encountered quite a few challenges, among which the major issues are availability and reliability. The unexpected failure in WTs Gearbox (GB) ultimately increases the Operation and Maintenance (O&M) cost. The identification of faults in the earlier stages before it turns to catastrophic damage to other components of WT is crucial. This research deals with the prediction of WT failures by using a Supervisory Control and Data Acquisition (SCADA) system. The main aim is to forecast the temperature of the WTs GB to predict the impending overheating of the GB at an early stage. The earlier prediction will help to optimize the maintenance period and to save maintenance expenses and, even more important, generate warnings in due time to avoid major damages or even technical disasters. In the proposed method we compared six different machine learning (ML) models based on error and accuracy of prediction. The bagging regressor is the best ML model, which results in the mean square error of 0.33 and R of 99.8 on training data. The bagging regressor is then used to predict the fault in the WT GB, which detected the anomalous behavior of WT GB 59 days earlier than the actual failure. This model also detects the extremely unusual behavior of the GB 9 days earlier than a complete failure.

The global energy crisis has lead researchers explore other sources of energy like wind, resulting in a wide acceptance of wind turbines. Vertical axis wind turbines (VAWT) more suitable for small scale application in urban conditions than their horizontal-axis counterparts. A Helical bladed VAWT would reduce the ripple effect when compared to Straight bladed VAWT. The effect of the blade helix angle on the aerodynamic performance of VAWT using 3D numerical simulations is studied. Turbulence modelled using 4-Equation transition SST k-w model. Three different helix angles of 60, 90 and 120 of a 3 bladed VAWT operating across different tip speed ratios were studied. The 60 helical bladed VAWT was found to perform better than all other helical bladed and straight bladed VAWT. Standard deviation of the moment coefficient generated by a blade plotted against 360 of azimuth rotation revealed that the ripple effect on the shaft produced by cyclic loading of the straight blade is considerably reduced upon introduction of helix angle, with 120 helical blade giving lowest standard deviation. The analysis has been done for the percentage of power generated by each quartile of flow and the contribution of each section of the blade. A comparative study was also conducted between different helical bladed VAWT and straight bladed VAWT. Flow feature analysis also revealed the reasons behind secondary peaks and the performance improvement when tip speed ratio increases. Wake structure analysis and flow contours were also studied for a better understanding of the flow field.

The research sought to investigate the long term characteristics of wind in the Kisii region (elevation 1710m above sea level, 0.68^oS, 34.79^o E). Wind speeds were analyzed and characterized on short term (per month for a year) and then simulated for long term (ten years) measured hourly series data of daily wind speeds at a height of 10m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent; the mean wind speed, diurnal variations, daily variations as well as the monthly variations. The wind speed frequency distribution at the height 10 m was found to be 2.9ms^-1 with a standard deviation of 1.5. Based on the two month’s data that was extracted from the AcuRite 01024 Wireless Weather Stations with 5-in-1 Weather Sensor experiments set at three sites in the region, averages of wind speeds at hub heights of 10m and 13m were calculated and found to be 1.7m/s, 2.0m/s for Ikobe station, 2.4m/s, 2.8m/s for Kisii University stations, and 1.3m/s, 1.6m/s for Nyamecheo station respectively. Then extrapolation was done to determine average wind speeds at heights (20m, 30m, 50m, and 70m) which were found to be 85.55W/m², 181.75W/m², 470.4W/m² and 879.9W/m² respectively. The wind speed data was used statistically to model a Weibull probability density function and used to determine the power density for Kisii region.

The wind industry is looking for ways to accurately predict the reliability and availability of newly installed wind turbines. Failure modes, effects and criticality analysis (FMECA) is a technique utilized for determining the critical subsystems of wind turbines. There are several studies which applied FMECA for wind turbines in the literature, but no studies so far have considered different weather conditions or climatic regions. Furthermore, various design types of wind turbines have been analyzed applying FMECA but no study so far has applied FMECA to compare the reliability of geared and direct-drive wind turbines. We propose to fill these gaps by using Koppen-Geiger climatic regions and two different turbine models of direct-drive and geared-drive concepts. A case study is applied on German wind farms utilizing the WMEP database which contains wind turbine failure data from 1989 to 2008. This proposed methodology increases the accuracy of reliability and availability predictions and compares different wind turbine design types and eliminates underestimation of impacts of different weather conditions.

This paper proposes a procedure for predicting the actual wind speed for flow over complex terrain with CFD. It converts a time-series of wind speed data acquired from field observations into a time-series of actual scalar wind speed by using non-dimensional wind speed parameters which are determined beforehand with the use of CFD output. The accuracy and reproducibility of the prediction procedure were examined by simulating the flow with CFD with the use of high resolution (5 m) surface elevation data for the Noma Wind Park in Kagoshima Prefecture, Japan. The errors of the predicted average monthly wind speeds relative to the observed values were less than approximately 20%.

This article is a commentary on the publication Guo J, Hai H, Ma Y. Application of extracorporeal shock wave therapy in nervous system diseases: A review. Front Neurol. (2022) 13:963849. doi: 10.3389/fneur.2022.963849 (1). In the opinion of the authors of this commentary the information provided in the Section "Principles of ESWT" in (1) is partly incorrect and misleading. This is due to the fact that important, published knowledge regarding focused extracorporeal shock wave therapy (fESWT) and radial extracorporeal shock wave therapy (rESWT) was disregarded in (1).

This article presents the suitability analysis of onshore wind farm sites using an AHP (Hierarchical Analysis Process) multi-criteria decision-making (MCDM) approach based on geographic information system modeling (GIS). This analysis is based on different technical aspects (wind speed, elevation, slope), economic (proximity to the electricity network, proximity to roads) and social (proximity to residential areas, population density). The introduction of the factor “population density” and the constraint “required area” rarely used in previous studies makes it possible to refine the results. The data is classified into several categories in a gradual manner, namely unsuitable (0); less suitable (1); suitable (2); highly suitable (3) and most suitable (4). The results of the study show us that the largest percentage relating to spatial coverage is observed in the “suitable” range with 50.89% and the corresponding TWPP (theoretical wind power potential) is 1377.926 GW; it is followed by “highly suitable” 5.67% and a TWPP of 153.652 GW; then “less suitable” with 1.04% and a TWPP of 28.163GW. No areas were identified in “most suitable” and finally the “unsuitable” range with 42.4%. The results show that the most favorable areas are located in the part of the far north of the country corresponding to the strong wind zone. The sensitivity analysis was carried out based on scenario tests (technical, economic and equal-weight) in order to give greater visibility of choice to the different stakeholders who would like to invest in onshore wind energy in Cameroon. This study is useful in more than one way because the results obtained can help investors, the government and other stakeholders to identify potential areas for the deployment of wind energy systems in Cameroon. Furthermore, a study of hybrid solar-wind systems could improve the efficiency of electricity parks in Cameroon.

When undertaking wind assessment around buildings using large eddy simulation (LES), the implementation of the integral length scale at the inlet for inflow generation is controversial, as real atmospheric length scales require huge computational domains. While length scales significantly influence inflow generation in the domain, their effect on the downstream flow field has not yet, been investigated. In this paper, we validate the effectiveness and accuracy of implementing a reduced turbulence integral length scale for inflow generation in LES results at the rooftop of low-rise buildings and develop a technique to estimate the real local length scales using simulation results. We measure the wind locally and calculate the turbulence length scales from the energy spectrum of the wind data and simulation data. According to these results, there is an excellent agreement between the length scale from simulation and measurement when they are scaled with their corresponding freestream/inlet value. These results indicate that a reduced integral length scale can be safely used for LES to provide a reliable prediction of the energy spectrum as well as the length scales around complex geometries. The simulation results were confidently employed to obtain the best location for a wind turbine installation on low-rise buildings.

The high-resolution bistatic lidar developed at the Physikalisch-Technische Bundesanstalt (PTB) aims to overcome the limitations of conventional monostatic lidar technology which is widely used for wind velocity measurements in wind energy and meteorology applications. Due to the large measurement volume of a combined optical transmitter and receiver tilting in multiple directions, monostatic lidar generally has poor spatial and temporal resolution. It also exhibits large measurement uncertainty when operated in inhomogeneous flow, for instance, over complex terrain. In contrast, PTB’s bistatic lidar uses three dedicated receivers arranged around a central transmitter, resulting in an exceptionally small measurement volume. The coherent detection and modulation schemes used allow the detection of backscattered, Doppler shifted light down to the scale of single aerosols, realising the simultaneous measurement of all three wind velocity components. This paper outlines design details and the theory of operation of PTB’s bistatic lidar and provides an overview of selected comparative measurements. The results of these measurements have shown that the measurement uncertainty of PTB’s bistatic lidar is well within the measurement uncertainty of traditional cup anemometers, while being fully independent of its site and traceable to the SI units. This allows its use as a transfer standard for the calibration of other remote sensing devices. Overall, PTB’s bistatic lidar shows great potential to universally improve the capability and accuracy of wind velocity measurements, such as for the investigation of highly dynamic flow processes upstream and in the wake of wind turbines.

Ultrasonic based inspection of thin-walled structures often requires prior knowledge of their mechanical properties. Their accurate estimation could be achieved in a non-destructive manner employing, e.g., elastic guided waves. Such procedures require efficient approaches for experimental data extraction and processing, which is still a challenging task. An advanced automated technique for material properties identification of an elastic waveguide is proposed in this investigation. It relies on the information on dispersion characteristics of guided waves, which are extracted by applying the matrix pencil method to the measurements obtained via laser Doppler vibrometry. Two objective functions have been successfully tested, and the advantages of both approaches are discussed (accuracy vs computational costs). The numerical analysis employing the synthetic data generated via the mathematical model as well as experimental data shows that both approaches are stable and accurate. The influence of the presence of various modes in the extracted data is investigated. One can conclude that the influence of the corruptions related to the extraction of dispersion curves is not critical if the majority of guided waves propagating in the considered frequency range are presented. Possible extensions of the proposed technique for damaged and multi-layered structures are also discussed.

In this article, we show theoretically and experimentally the formation of spin-waves band gaps in a magnonic crystal that was implemented by the deposition of periodic micro-structured strips of magnetite nanoparticles. A theoretical model describing the spectra of the transmitted spin-waves bandgaps is proposed. This is achieved using a simple model based on microwave transmission line theory and considering the presence of micro-structured strips of magnetite nanoparticles on the surface. Such magnonic crystal of equally spaced micro-structured strips of magnetite nanoparticles on the surface of an yttrium iron garnet thin film has been implemented and measured. The periodic micro-structured nanoparticles are deposited on the surface of such yttrium iron garnet single-crystal film grown on a gallium-gadolinium garnet substrate via dip-coating technique. Propagation of magnetostatic surface spin-waves is studied and it is shown that the presence of such periodic structure leads to the formation of spin-wave band gaps in the transmission characteristics. The spin-wave detection has been carried out using a pair of microwave antennas and a vector network analyzer. The results show that the periodic structure formed by the magnetite strips modifies the spectra of the transmitted spin waves producing band gaps.

The motion of a circular elastic plate floating on the surface is investigated in the time–domain. The solution is found from the single frequency solutions and the method to solve for the circular plate is given using the eigenfunction matching method. Simple plane incident waves with a Gaussian profile in wavenumber space are considered and a more complex focused wave group is considered. Results are given for a range of plate and incident wave parameters are investigated. Code is provided to show how to simulate the complex motion.

In this three-part paper, we show that gravitational waves (classical and quantum) produce the accelerated de Sitter expansion at the start and by the end of the cosmological evolution of the Universe. In these periods of time, the Universe contains no matter fields but contains classical and quantum metric fluctuations, i.e. it is filled with classical gravitational waves and gravitons. In such gravitational wave and graviton dominated eras of evolution of the Universe, the de Sitter state is the exact solution to the self-consistent equations for gravitational waves and gravitons and background geometry for the empty (with no matter fields) space-time with FLRW metric. In both classical and quantum cases, this solution is of the instanton origin since it is obtained by Wick rotation with the subsequent analytic continuation to real time. The cosmological acceleration from gravitational waves and gravitons provides a transparent physical explanation to the coincidence and threshold paradoxes of dark energy avoiding recourse to the anthropic principle. The cosmological acceleration from gravitons/gravitational waves at the start of the Universe evolution produces inflation which is consistent with the observational data on CMB anisotropy.

In this paper, four probability functions are compared with the purpose of establishing a methodology to improve the accuracy of the estimated wind energy in a desert city in northwestern Mexico. For the statistical modeling, 3 time series of wind speed data were used, corresponding to the years 2017, 2018, and 2019, recorded with a sonic anemometer at a sampling frequency of 10 Hz. From these, the analysis is performed with different stationarity periods (5, 30, 60, and 600 seconds). The estimation of the parameters characterizing the probability density functions was performed using different methods; the statistical models were evaluated by the coefficient of determination and the Nash-Sutcliffe efficiency coefficient, while their accuracy by the measured quadratic error, the mean square error, the mean absolute error, and the mean absolute percentage error. It was found that Weibull with the energy pattern factor method and Gamma using the method of moments were the probability density functions that best describe the statistical behavior of the wind speed and, therefore, better estimate the energy generated, so it is concluded that the proposed methodology will allow having greater confidence, both in the estimation of the wind speed and in the small wind energy available for its use.

The most important step for the installation of a wind farm is to know the wind regime in the region, since an error in estimating this wind speed causes an error proportional to the cube of power, resulting in financial losses for investors. Therefore, knowing the methods used for predicting wind speed becomes important and the knowledge of how research and studies in this area are going helps map the subject and outline strategies for developing research in strategic areas. For this purpose, the Scopus database was used considering some keywords, such as ("forecast" OR "prevision") AND "wind" AND ("turbine" OR "power" OR "energy" or "velocity" or "speed"), considering the period since 2019, and analyzing the data of the documents found using the Bibliometrix package. With the results found, it was possible to map researchers, institutions that are developing work in this area, in addition to the most cited articles, among other aspects analyzed.

Green hydrogen is likely to play an important role in meeting the net zero targets of countries around the globe. Hence, producing green hydrogen cheaply and effectively is an important area of research. One potential option for green hydrogen production is to run electrolysers directly from offshore wind turbines, with no grid connection and hence no expensive cabling to shore. The removal of the grid presents an unusual integration challenge. The variable nature of wind turbines and farms results in a power output that can fluctuate more quickly than the electrolyser’s ability to respond without significantly stressing the electrolyser. Thus, the use of a battery, with the wind farm, becomes essential to even out some of the power variations that the electrolyser cannot deal with. In this work, a proof of concept of a wind farm control methodology designed to reduce variability in wind farm active power output is presented. Smoothing the power supplied by the wind farm to the battery reduces the size and number of battery charge cycles and helps to increase battery lifetime. Considering off-grid wind farms which exclusively power an electrolyser, this work quantifies the impact of the wind farm control method on battery lifetime for wind farms of 1, 4, 9 and 16 wind turbines. This is achieved using suitable wind farm, battery and electrolyser models. As an example, for the largest wind farm studied, consisting of 16 x 5 MW wind turbines, batteries with a lifetime of 15 years have approximately a 30 % reduction in required capacity (reduced from 14 MWh to 10 MWh) compared to operating without wind farm control. It is found that reducing the variability of the active power output of wind farms through the wind farm control methodology presented can have a significant impact on battery degradation and hence on battery lifetime. Hence, wind farm control can reduce the required battery capacity for a given lifetime or it can increase the lifetime of a given battery capacity. The work presented shows that wind farm control could play a critical role in reducing the levelised cost of green hydrogen produced from wind farms with no grid connection and paves the way for the design and testing of a full implementation of the wind farm control.

Aerodynamic performance of a floating offshore wind turbine (FOWT) is significantly influenced by platform surging motions. Accurate prediction of the unsteady aerodynamic loads is imperative for determining the fatigue life, ultimate loads on key components such as FOWT rotor blades, gearbox and power converter. The current study examines the predictions of numerical codes by comparing with unsteady experimental results of a scaled floating wind turbine rotor. The influence of platform surge amplitude together with the tip speed ratio on the unsteady aerodynamic loading has been simulated through unsteady CFD. It is shown that the unsteady aerodynamic loads of FOWT are highly sensitive to the changes in frequency and amplitude of the platform motion. Also, the surging motion significantly influences the windmill operating state due to strong flow interaction between the rotating blades and generated blade-tip vortices. Almost in all frequencies and amplitudes, CFD, LR-BEM and LR-uBEM predictions of mean thrust shows a good correlation with experimental results.

To investigate the optimum layouts of small vertical axis wind turbines, a two-dimensional analysis of dynamic fluid body interaction is performed via computational fluid dynamics for a rotor pair in various configurations. The rotational speed of each turbine rotor (diameter: D = 50 mm) varies based on the equation of motion. First, the dependence of rotor performance on the gap distance (gap) between two rotors is investigated. For parallel layouts, counter-down (CD) layouts with blades moving downwind in the gap region yield a higher mean power than counter-up (CU) layouts with blades moving upwind in the gap region. CD layouts with gap/D = 0.5–1.0 yield a maximum average power that is 23% higher than that of an isolated single rotor. Assuming isotropic bidirectional wind speed, co-rotating (CO) layouts with the same rotational direction are superior to the combination of CD and CU layouts regardless of the gap distance. For tandem layouts, the inverse-rotating configuration (IR) shows an earlier wake recovery than the CO configuration. For 16-wind-direction layouts, both the IR and CO configurations indicate similar power distribution at gap/D = 2.0. For the first time, this study demonstrates the phase synchronization of two rotors via numerical simulation.

Combining wind and solar photovoltaic (PV) generation can provide complementary renewable power production, but depends on correlated resources. This study analyzed 10 years of wind data from Naama, Algeria to evaluate the potential for evening wind generation to offset the loss of solar at sunset. Average wind speeds showed a distinct increase during evening hours, coinciding with the decrease in solar irradiance. Wind turbine simulations using a 1.5 MW turbine and the wind data showed sufficient resources for profitable power production after sunset. Statistical analyses confirmed significantly higher wind speeds and simulated power output in evening vs daylight periods (p<0.05). The Pearson correlation coefficient between evening wind speeds and decreasing solar irradiance was 0.63, supporting a strong positive relationship. These findings indicate Naama has adequate wind resources to deploy economically viable wind power capacity that can complement existing solar infrastructure and provide renewable electricity after dark , .

Advancements in technology, policies, and cost reductions have led to rapid growth in wind power production. One of the major challenges in wind energy production is the instability of wind power generation due to weather changes. Efficient power grid management requires accurate power output forecasting. New wind energy forecasting methods based on deep learning are better than traditional methods, like numerical weather prediction, statistical models, and machine learning models. This is more true for short-term prediction. Since there is a relationship between methods, climates, and forecasting complexity, forecasting methods do not always perform the same depending on the climate and terrain of the data source. This paper proposes a novel model that combines the variational mode decomposition method with a long short-term memory model, developed for next-hour wind speed prediction in a hot desert climate, such as the climate in Saudi Arabia. We compared the proposed model performance to two other hybrid models, six deep learning models, and four machine learning models using different feature sets. Also, we tested the proposed model on data from different climates, Caracas and Toronto. The proposed model showed a forecast skill between 61% to 74% based on mean absolute error, 64% to 72% based on root mean square error, and 59% to 68% based on mean absolute percentage error for locations in Saudi Arabia.

Management approaches inspired by the variability of natural disturbances are expected to produce forests in the future that will be significantly more resilient and better adapted to local environmental conditions. Due to climate change, windstorms are becoming increasingly common resulting in the destruction not only of extensive forest areas but, quite often, of small-sized and scattered forest lands that can ultimately become home to insects and disease dissemination sites. In the present study, an attempt is made to identify and record areas in the northeastern forests of Greece covered by mixed stands of conifers and broadleaves that experienced massive windthrow following local storms. Based on tree-level data, local topographic features, forest characteristics and the mechanical properties of green wood, a reliable model, to be used for the prediction of similar disturbances in the future, has been created after a thorough comparative study of the most well-known intelligent machine learning algorithms.

A modified free-wake vortex ring model is proposed to compute the dynamics of a floating horizontal-axis wind turbine. The model is divided into two parts. The near wake model uses a blade bound vortex model and trailed vortex model, which is developed based on vortex filament method. By contrast, the far wake model is based on the vortex ring method. The proposed model is a good compromise between accuracy and computational cost, for example when compared with more complex vortex methods. The present model is used to assess the influence of floating platform motions on the performance of a horizontal-axis wind turbine rotor. The results are validated on the 5MW NREL rotor and compared with other aerodynamic models for the same rotor subjected to different platform motions. It was found that the results from the proposed method are more reliable than the results from BEM theory especially at small angles of attack in the region of low wind speeds, on the one hand, and high wind speeds with blade pitch motions, on the other hand. And also the proposed method is less time consuming and has similar accuracy when comparing with more advanced vortex based methods.

Wind turbine upgrades have been spreading in the recent years in the wind energy industry, with the aim of optimizing the efficiency of wind kinetic energy conversion. This kind of interventions has material and labor costs and it is therefore fundamental to estimate realistically the production improvement. Further, the retrofitting of wind turbines sited in harsh environments might exacerbate the stressing conditions to which wind turbines are subjected and consequently might affect the residue lifetime. This work deals with a case of retrofitting: the testing ground is a multi-megawatt wind turbine from a wind farm sited in a very complex terrain. The blades have been optimized by installing vortex generators and passive flow control devices. The complexity of this test case, dictated by the environment and by the features of the data set at disposal, inspires the formulation of a general method for estimating production upgrades, based on multivariate linear modeling of the power output of the upgraded wind turbine. The method is a distinctive part of the outcome of this work because it is generalizable to the study of whatever wind turbine upgrade and it is adaptable to the features of the data sets at disposal. In particular, applying this model to the test case of interest, it arises that the upgrade increases the annual energy production of the wind turbine of an amount of the order of the 2%. This quantity is of the same order of magnitude, albeit non-negligibly lower, than the estimate based on the assumption of ideal wind conditions. Therefore, it arises that complex wind conditions might affect the efficiency of wind turbine upgrades and it is therefore important to estimate their impact using data from wind turbines operating in the real environment of interest.

Extreme-mass-ratio inspirals (EMRIs) are significant observational targets for spaceborne gravitational wave detectors, namely, LISA, Taiji, and Tianqin, which involve the inspiral of stellar-mass compact objects into massive black holes with a mass range of approximately 104∼107M⊙. EMRIs are estimated to produce long lived gravitational wave signals with more than 105 cycles before plunge, making them an ideal laboratory for exploring the strong-gravity properties of the spacetimes around the MBHs, stellar dynamics in galactic nuclei, and properties of the MBHs itself. However, the complexity of the waveform model, which involves the superposition of multiple harmonics, as well as the high-dimensional and large-volume parameter space, make the fully coherent search challenging. In our previous work, we proposed a 10-dimensional search using Particle Swarm Optimization (PSO) with local maximization over the three initial angles. In this study, we extend the search to an 8-dimensional PSO with local maximization over both the three initial angles and the angles of spin direction of the MBH where the latter contribute a time independent amplitude to the waveforms. Additionally we propose a 7-dimensional PSO search by using a fiducial value for the initial orbital frequency and shifting the corresponding 8-dimensional Time Delay Interferometry responses until a certain lag returns the corresponding 8-dimensional log-likelihood ratio maximum. The reduced dimensionality likelihoods enable us to successfully search for EMRI signals with duration of 0.5 years and signal-to-noise ratio of 50 within a wider search range than our previous study. We discuss further developments, such as using a hierarchical search to narrow down the search ranges of certain parameters, and applying Graphics Processing Units to speed up the code. These advances aim to improve the efficiency and accuracy of the EMRI search algorithm.

Swarm intelligence (SI) methods are nature-inspired metaheuristics for global optimization that exploit a coordinated stochastic search strategy by a group of agents. Particle Swarm Optimization (PSO) is an established SI method that has been applied successfully to the optimization of rugged high-dimensional likelihood functions, a problem that presents the main bottleneck across a variety of gravitational wave (GW) data analysis challenges. We present results from a first application of PSO to one of the most difficult of these challenges, namely, the search for Extreme Mass Ratio Inspiral (EMRI) in data from future spaceborne GW detectors such as LISA, Taiji, or Tianqin. We use the standard Generalized Likelihood Ratio Test formalism, with minimal use of restrictive approximations, to search 6 months of simulated LISA data and quantify the search depth, in signal-to-noise ratio (SNR), and breadth, in the ranges of the EMRI parameters, that PSO can handle. Our results demonstrate that a PSO-based EMRI search is successful over a search region that is in the ballpark of the one that current hierarchical schemes can identify. Directions for future improvements, including computational bottlenecks to be overcome, are identified.

Localized turbulence is common in geophysical flows, where the roles of rotation and stratification are paramount. In this study, we investigate the evolution of a stratified turbulent cloud under rotation. Recognizing that a turbulent cloud is composed of vortices of varying scales and shapes, we start our investigation with a single eddy. Compared to an eddy under pure rotation, the stratified eddy shows the physical manifestation of a known potential vorticity mode, appearing as a static stable vortex. In addition, the expected shift from inertial waves to inertial-gravity waves is observed. In our numerical simulations of the turbulent cloud, carried out at a constant Rossby number over a range of Froude numbers, stratification causes columnar structures to deviate from vertical alignment. This deviation increases with increasing stratification, slowing the expansion rate of the cloud. The observed characteristics of these columnar structures are consistent with the predictions of linear theory, particularly in their tilt angles and vertical growth rates, suggesting a significant influence of inertial-gravity waves. Using Lagrangian particle tracking, we have identified regions where wave activity dominates over turbulence. In scenarios of milder stratification, these inertial-gravity waves are responsible for a significant energy transfer away from the turbulent cloud, a phenomenon that attenuates with increasing stratification.

This study investigates the ionospheric variations resulting from thunderstorms that occurred between 00:00 UTC and 08:00 UTC on November 10, 2018, in the central region of Argentina, site of the RELAMPAGO-CACTI Project (Remote sensing of Electrification, Lightning, and Mesoscale/microscale Processes with Adaptive Ground Observations; Clouds, Aerosols, and Complex Terrain Interactions). The data used were the Total Electron Content (TEC), which was computed from Global Navigation Satellite System (GNSS) measurements provided by the Argentinian Continuous Satellite Monitoring Network (RAMSAC by its Spanish acronym) stations and the atmospheric electrical activity data that were provided by the Earth Networks Total Lightning Network (ENTLN). We observed that the generated disturbances have periods less than or equal to 100 minutes and peak-to-peak DVTEC amplitude values reaching up to 1.35 TECU (1 Total electron content unit =1016electrons/m2). We also noted that these atmospheric gravity waves, which show the highest peak-to-peak amplitudes, occur during periods of intense lightning activity. Finally, we found that for a day with Atmospheric Electrical Activity (AEA), the peak-to-peak amplitudes of the waves are approximately 2.91 times greater than the peak-to-peak amplitudes of a day without AEA.

(1) Background: Since the onset of the SARS-CoV-2 pandemic, seven epidemic waves have been described in Spain. Our objective was to study mortality and severity, and associated factors in our hospitalized patients; (2) Method: Retrospective cohort study was conducted on COVID-19 patients admitted to the Hospital de Fuenlabrada (Madrid, Spain) from the beginning of the pandemic until December 31, 2022; (3) Results: A total of 5,510 admissions for COVID-19 were recorded. First wave accounted for 1,823 (33%) and exhibited the highest proportion of severe patients (lowest mean oxygen saturation, 88.2%; elevated levels of CRP, IL-6, D-dimer and ferri-tin), but a below-average percentage of intubated patients (5% vs. 6.5%). Overall mortality rate was 10.3%, higher during the first wave (11.5%) and the two winter waves (third: 11.3%, sixth: 12%), although the first wave represented 39% of the total. Variables associated with mortality were age (OR 1.08,1.07-1.09), need for high-flow oxygen (OR 6.10,4.94-7.52), oncological disease (OR 1.88,1.53-2.60), dementia (OR 1.82,1.2-2.75), Charlson index (OR 1.38,1.31-1.47), and maxi-mum IL-6 levels (OR 1.001,1.000-1.001); (4) Conclusions: Variables associated with mortality in-cluded age, comorbidity, respiratory failure, and inflammation. Differences on baseline charac-teristics of patients admitted explained differences on mortality in each wave

This work deals with the evaluation of adhesive single-lap joints using ultrasonic guided waves. An adhesive bonded lap joint can be modelled as a three-layer system made up of two adherents and an adhesive. The propagation of guided waves in the joint is developed from matrix formulations. The behavior of the different guided wave modes that propagate in the bonded region is characterized and it is found that their relative amplitudes can be estimated based on the properties of the incoming wave that propagates in the non-bonded region. It was verified that the excitation of these modes is ruled by the degree in which the shapes of both modes match each other. A 3D simulation of two aluminium bonded plates using 500 kHz ultrasonic transducers in a pitch and catch configuration was implemented using the Matlab k-Wave toolbox. Scattering effects due to some produced defects located in the bond line of the lap joints were simulated. Experimental setup with some artificial defects produced in the aluminum joints were used in order to compare with the simulated. Qualitative agreement was observed for the two approaches. The observed deviation can be due to the different characteristics of the experimental and simulated defects.

The initial dilution generated by the final disposal of untreated wastewater through a submarine outfall in Santa Marta was examined with a near-field dilution model. Northward and eastward seawater velocity, salinity, and temperature profiles from a 3D hydrodynamic model were used to provide the oceanic conditions to calculate the dilution. At the wastewater discharge site, the upwelling phenomenon occurs two times a year, the major from December to March and the minor in July, eliminating the stratification condition of seawater. The results of the dilution model showed that in these periods the plume reaches the water surface achieving dilutions greater than 100. In addition, the external wave effect on the initial dilution of submarine outfall discharge in Santa Marta was determined. Surface waves increase dilution during the dry period of the year when trade winds increase the surge and start the upwelling phenomenon. The Dilution with/without waves factor is up to 1.90 for the center of the plume on the water column.

Conclusive evidence that specic long-term memory formation relies on den- dritic growth and structural synaptic changes has proven elusive. Connec- tionist models of memory based on this hypothesis are confronted with the so-called plasticity stability dilemma or catastrophic interference. Other fun- damental limitations of these models are the feature binding problem, the speed of learning, the capacity of the memory, the localisation in time of an event and the problem of spatio-temporal pattern generation. This paper suggests that the generalisation and long-term memory mechanisms are not correlated. Only the development and the improvement of the feature ex- tractors in the cortex involves structural synaptic changes. We suggest the long-term memory has a separate mechanism which involves protein synthe- sis to encode the information into the structure of these proteins. A model of memory should be capable of explaining the dierence between memorisation and learning. Learning has in our approach two dierent mechanisms. The generalisation in the brain is handled by the proper development of the links between neurons via synapses. The Hebbian learning rule could be applied only for this part of learning. Storing an internal ring pattern involves, in our approach, a new mechanism which puts the information regarding this ring pattern into the structure of special proteins in such a way that it can be retrieved later. The hypotheses introduced in this article includes a physiological assumption which has not been yet verified because it is not currently experimentally accessible. Keywords: Waves, Protein Synthesis, Resonance, Long Term Memory Preprint submitted to Neural Networks

The purpose of this paper is to study the sliding mode control as a Ricci flow process in the context of a three-story building structure subjected to seismic waves. The stability conditions result from two Lyapunov- functions, the first associated with slipping in a finite period of time, and the second with convergence of trajectories to the desired state. Simulation results show that the Ricci flow control leads to the minimization of the displacements of the floors. 3D Ricci solitons projection via a semi-conformal mapping to a surface is also studied.

The cartographic cum site-effectuated view of Shillong region of northeast India is presented here. Starting from the existing tectonics, the prevalent geological settings of the study area is comprehensively delineated. The seismic prone area is further overviewed in the context of site effects with accompaniment of available borehole information. The resonance frequency estimates form ambient noise survey along with receiver functions are outlined which implicates a heterogeneous subsurface. This further helps in segregating the region into two compelling profiles, thereby enabling us to get a deeper insight in the probable subsurface as well as heterogeneity. Eventually, the influence of topography over strata was also highlighted and interpreted as well.

Surface waves generated by Extra-Tropical Cyclones (ETCs) can significantly affect shipping, fishing, offshore oil and gas production and other marine activities. This paper presents results of satellite-data-based investigation of wind waves generated by two North Atlantic ETCs. These ETCs were fast-moving systems, inhibiting resonance (synchronism) between the group velocity of the generated waves and the ETC translation velocity. For these cases, the wave generation begins when the front-boundary of the storm appears at a given ocean location point. Since developing waves are slow, they move backward relative to the storm, grow in time, and then leave the ETC stormy area through the rear sector. Multi-satellite observations confirm such a paradigm, and reveal that the storm regions is filled up with young developing wind waves which are most developed in the rear-right sector. As observed, the energy of these waves was growing in time during the ETC life span. It is demonstrated that the extended-fetch concept (inherent for Tropical Cyclones) does not apply for ETC. Instead, by analogy, the concept of extended-duration wave growth concept is more relevant. Satellite observations well confirm the validity of duration-laws for waves generated by ETCs, and demonstrate that extended-fetch regime for observing waves can only asymptotically be achieved, - at time intervals exceeding the lifespan of considered ETCs.

The wind observations for multiple levels (40–200 m) have been conducted for a long time (2016–2020) on Jeju Island of South Korea. This study aims at understanding the vertical and temporal characteristics of lower atmosphere. Jeju Island is a region located at mid-latitude and is affected by seasonal monsoon wind. The maximum wind speed appears in the lower layer during day time and is delayed in the upper layer during latter time in diurnal cycle. In summer season, the surface layer increases up to 160 m during day time via dominant solar radiation effect, which is higher than those for other seasons. However, the maximum wind speed in winter season appears irregularly among altitudes, and the surface layer is ~100 m, which is lower than that in summer season. It can be attributed to the increase in the mean wind speed in diurnal cycle caused by the strong northwestern wind for winter season. These results imply that the relationship between near-surface and higher altitudes is primarily affected by solar radiation and seasonal monsoon winds. These results are expected to contribute to site selection criteria for wind farms and to the assessment concerning planetary boundary layer modeling.

The unsteady Ekman problem involves finding the response of the near-surface currents to wind stress forcing under linearized dynamics. Its solution can be conveniently framed in the frequency domain in terms of a quantity that is known as the transfer function, the Fourier transform of the impulse response function. In this paper, a theoretical investigation of a fairly general transfer function form is undertaken with the goal of paving the way for future observational studies. Building on earlier work, we consider in detail the transfer function arising from a linearly-varying profile of the vertical eddy viscosity, subject to a no-slip lower boundary condition at a finite depth. The linearized horizontal momentum equations are shown to transform to a modified Bessel’s equation for the transfer function. Two self-similarities, or rescalings that each effectively eliminate one independent variable, are identified, enabling the dependence of the transfer function on its parameters to be more readily assessed. A systematic investigation of asymptotic behaviors of the transfer function is then undertaken, yielding expressions appropriate for eighteen different regimes, and unifying the results from numerous earlier studies. A solution to a numerical overflow problem that arises in the computation of the transfer function is also found. All numerical code associated with this paper is distributed freely for use by the community.

This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the optimal set of physical parameterizations for representing wind patterns during this event, a year-long evaluation was conducted, covering forecast horizons of 24, 48, and 72 hours. The simulation results were compared with observational wind data from four weather stations. The findings highlight variations in the efficacy of different physical parameterization sets, with certain sets encountering challenges in accurately depicting the peak of the severe event. The most favorable results were achieved using a combination of Tiedtke (cumulus), Thompson (microphysics), TKE (boundary layer), Monin-Obukhov (surface layer), Unified-NOAH (land surface), and RRTMG (shortwave and longwave radiation). Over the one-year forecasting period, the WRF model effectively represented the overall wind pattern, including forecasts up to three days in advance (72-hour forecast horizon). Generally, the statistical metrics indicate robust model performance, even for the 72-hour forecast horizon, with correlation coefficients consistently exceeding 0.60 at all analyzed points. While the model proficiently captured wind distribution, it tended to overestimate northeast wind speed and gust intensities. Notably, forecast accuracy decreased as stations approached the ocean, exemplified by the ATPM station.

The paper presents modelling of relationships between wind velocity distributions observed in Poland and technical requirements for wind power stations design. The wind velocities distributions for various locations in Poland are determined, and expressed in Weibull distribution parameters. Theoretical computations concerning the dependence of wind power station as function of wind speed and aire physical properties are presented. Conclusions important for design of power stations fitted to atmospheric conditions in Poland are given. Wind power plants have been an important source of electricity generation for many years.Wind power modelling with the use of wind speed is used to improve the accuracy of forecasts and analyses of the power production of wind farms.

To increase the power density of the electromechanical drive train of wind turbines, journal bearings can be used as planetary gear bearings instead of rolling bearings. This technological change presents new challenges. For example, wind turbine drive systems are subject to dynamic and low-speed operating conditions which can lead to an accelerated abrasive wear of the journal bearings. In addition, oil supply failure or peak loads due to wind gusts and grid and power converter faults could potentially result in catastrophic failure due to adhesive wear in a very short time. Such operating characteristics are, therefore, critical regarding the journal bearing wear lifetime and must be considered in the design. The successful implementation of journal bearings in wind turbines depends on a reliable estimation of adhesive and abrasive wear. In this paper, five different models for the wear calculation of journal bearings are evaluated regarding their suitability of wear calculation of planetary gear bearings in wind turbines. For this purpose, the following evaluation criteria were defined: parameter uncertainty, parametrization effort, in particular number of parameters, parameterization method and load case dependency of parameters and calculation effort. In order to be able to evaluate the wear models, the wear models are numerically implemented and the wear of a test journal bearing is exemplarily calculated under load conditions, which are comparable to load conditions in a wind turbine. Relevant influences from the wind turbine system such as lubricant, material and manufacturing dependent surface influences like roughness and hardness are considered. The wear models are evaluated with respect to their fulfillment of the defined criteria. The resulting evaluation allows the selection of a wear model that can be used to calculate the wear of planetary gear journal bearings in wind turbines, considering the available input variables.

Wind energy is one of the most attractive renewable energy sources because of its low operating, maintenance, and production costs as well as its low environmental impact. The goal of this study is to discover the best locations in Bangladesh where wind farms can be built and operated efficiently. This study applied the GIS and AHP methodologies to examine the eight important parameters upon which the suitability of locations is highly dependent. This analysis finds that Bangladesh has large regions appropriate for wind farm installation, with 3718.76 km² and 16631.14 km² classified as "very high" and "high" suitability, respectively. It was also observed that wind speed, land slope, and elevation each had a height-weighted criterion of 32 %, 27 %, and 12 %, respectively, when picking suitable locations. However, the viability of this study in identifying suitable sites has been evaluated based on ROC and AUC techniques and found satisfactory as per AUC value. The knowledge gained from this study will help the sustainable and renewable energy development authority (SREDA), Bangladesh to expedite the renewable energy investment process and will ensure the great certainty. The findings of this research can be considered as baseline information in the wind energy sector.

This paper is concerned with bump-less transfer of parametrized disturbance observer based controller (DOBC) with Individual Pitch Control (IPC) strategy for full load operation of wind turbine. Aerodynamic cyclic loads are reduced by tuning multivariable DOBC with the objective to reduce output power fluctuation, tower oscillation and drive-train torsion. Furthermore tower shadow and wind shear effect are also mitigated using parametrized controller. A scheduling mechanism between two DOBC is developed and tested on Fatigue, Aerodynamics, Structures, and Turbulence ( FAST) code model of National Renewable Energy Laboratory (NREL)’s 5 MW wind turbine. The closed-loop system performance is assessed by comparing the simulation results of proposed controller with a fixed gain and Linear Parameter Varying (LPV) DOBC with Collective Pitch Control (CPC) for full load operation. It is tested with step changing wind to see the behavior of the system under step change with wind shear and tower shadow (cyclic load) effects. Also turbulent wind is applied to see the smooth transition of the controllers. It can be concluded from the results that the proposed parametrized control DOBC with IPC shows smooth transition from one controller to another by interpolation. Moreover fatigue of the gear and tower due to wind shear and tower shadow effects are reduced considerably by the proposed controller as compared to collective pitch control.

This study delves into the intricate relationships among the constituent elements, wave speed, and energy of both mechanical waves and electromagnetic waves. By establishing connections with the string vibration equation, a compelling revelation emerges. Upon equating the energy and constituent element mass of one wave cycle of a homogeneous string with those of a single wave cycle of electromagnetic waves, it is evident that the wave speed derived from the string vibration equation consistently matches the constant speed of light. From this, a hypothesis takes root: electromagnetic waves manifest as waves resulting from the vibration of a uniform, elongated string-like material. The phenomenon of superluminal speed further fortifies the validity of this conjecture.

The work contains a detailed analysis of the electromagnetic field originating from a point source placed above the layered structure.The surface impedance of the multilayer dielectric structure was determined. Based on the boundary conditions, a method for determining the surface impedance of a layered structure with a perfectly conductive screen and or a magnetic screen is presented. The resonance conditions and the conditions for the excitation of surface waves are derived. The integral expression defining the generalized impedance was analyzed with a view to adapting it to numerical implementation. This allowed the development of a computer program based on which calculations were made of the effect of excitation of waves on multilayer dielectric substrates.

Heat waves are a significant consequence of climate change threatening public health by increased morbidity and mortality. The aim of this study was to estimate individuals’ knowledge, attitudes and practice related to heat waves. We conducted an exploratory cross-sectional study in Greece during September 2023. We employed a convenience sample of 1055 participants. We used the heat wave knowledge, awareness, practice and behavior scale (HWKAPBS) to measure our outcome. We measured several socio-demographic variables, such as gender, age, educational level, etc. as potential determinants. Mean scores for the knowledge, awareness, practice and behavior factors were 12.5, 22.7, 22.2 and 12.1 respectively. Females had higher scores on the four factors compared with males. We found a positive relationship between self-perceived health status and awareness, practice and behavior about heat waves. Similarly, we identified a positive relationship between self-perceived financial status and awareness and behavior about heat waves. Increased age was associated with increased practice score, while increased educational level was associated with increased knowledge score. Additionally, behavior score was higher among participants in urban areas than those in rural areas. We found statistically significant positive correlations between the four factors. Levels of knowledge, awareness, practice and behavior about heat waves were high in our sample. Several socio-demographic variables affect participants’ knowledge, awareness, practice and behavior concerning heat waves.

We propose a toy model of a spherical universe made up of an exotic dark gas with temperature $T$ in thermal equilibrium with a black-body. Each particle of this exotic gas mimics a kind of particle of dark energy. So, each dark particle occupies a very small area of space so-called Planck area $L_p^{2}$, which represents the minimum area of the whole space-time given by the spherical surface with area $4\pi R_H^2$, where $R_H$ is the Hubble radius. We realize that such spherical surface is the surface of the black-body for representing the dark universe as if it were the surface of an expanding balloon. Thus, we are able to derive the law of universal gravitation, thus leading us to understand the cosmological anti-gravity. We estimate the tiny order of magnitude of the cosmological constant and the acceleration of expansion of the dark sphere. In this toy model, as the dark universe can be thought of as a large black body, when we obtain its power and frequency of emission of radiation, we find very low values. We conclude that such radiation and frequency of the black body made up of dark energy is a background gravitational wave with very low frequency in the order of $\sim 10^{-17}$Hz due to the slight stretching of the fabric of space-time.

When two black holes form a binary system, each black hole observes an event horizon and a curved distorted space-time region around the other black hole. In this space-time, two such regions are formed, and another black hole forms in the second region from the initial black hole, which may be termed the “image” of the first black hole. The same event occurs for the other black hole also, and an extra image of it is formed. In these conditions, the energy of the system divides between the two black holes and their images. These four new black holes that are formed interact with each other again and produce new horizons and new distorted regions. Each black hole produces an image of all the other black holes and detects the background of six black holes instead of three. Consequently, for four black holes, 24 new black holes arise. The energy of the system will be divided amongst all 24 black holes. This story continues and black holes interact with one another and produce new images. Finally, very light black holes are formed each of which is so weak that it cannot produce strong distortions of space-time. The radiated gravitational waves from these weak black holes could be detected by LIGO as well as the signature of these binary black holes. However, detected waves are only a part of very strong gravitational waves. Each time a part of these waves escapes from the system and reaches the earth, they may be regarded as emitted waves from a new binary black hole. The time between radiated signals decreases, and it may be interpreted that a new supermassive binary black hole is radiating. If radiated signals combine, an explosion of the very strong binary system could be detected.

Analyzing the records of Advanced LIGO and Virgo gravitational observatories, we found a specific time-domain asymmetry inherent only to the signals of their gravitational detectors. Experiments with different periodic signals, Gaussian and non-Gaussian noises, made it possible to conclude that the noise of gravitational detectors is an unusual mixture of signals. We also developed a specialized Pearson correlation analyzer to recognize the gravitational-wave events. It turned out that the LIGO detectors’ output signals include a significant (– 6 dB) component, which has the properties of records of reliably recognized gravitational waves. It allows us to argue that the gravitational background noise is largely due to the processes of merging astronomical objects. Since the specific signal is registered by the detectors continuously, we can consider the sub-kilohertz band gravitational oscillations field as detected. Our analysis method also allows us to estimate the contribution of the gravitational background component to the total signal energy. With its help, it will be possible not only to provide the radio-frequency estimation of the magnitude of gravitational disturbances but also, possibly, to construct a map of the gravitational noise of the sky.

Numerical methods, including machine learning methods, are now actively used in the applications related to guided wave propagation. The method proposed in this study for material properties characterization is based on the algorithm of the clustering of multivariate data series obtained as a result of the application of the matrix pencil method to the experimental data. In the proposed technique, multi-objective optimization is employed to improve the accuracy of particular parameter identification. At the first stage, the computationally efficient method based on the calculation of the Fourier transform of Green's matrix is employed iteratively and the obtained solution is used for the filter construction with decreasing bandwidth, which allows us to obtain nearly noise-free classified data (with mode separation). The filter provides data separation between all guided waves in a natural way, which is needed at the second stage, where the slower method based on the minimization of the slowness residuals is applied to the data. The method might be applied for material properties identification in plates with thin coatings/interlayers, multi-layered anisotropic laminates etc.

5G technology is evolving to satisfy several service requirements favoring high data-rate connections and lower latency times than current ones (< 1ms). 5G systems use different frequency bands of the radio wave spectrum, taking advantage of higher frequencies than previous mobile radio generations. In order to guarantee a capillary coverage of the territory for high reliability applications, it will be necessary to install a large number of repeaters because higher frequencies waves have a lower capacity to propagate in free space. Following the introduction of this new technology, there has been a growing concern about possible harmful effects on human health. The aim of this study is investigating possible short term effects induced by 5G-millimeter waves on embryonic development of Danio rerio. We have exposed fertilized eggs to 27 GHz frequency, 9.7 mW/cm2 incident power density, 23 dbm and have measured several endpoints every 24 hours. The exposure to electromagnetic fields at 27 GHz (5G) caused no significant impacts on mortality nor on morphology because the exposed larvae showed a normal detachment of the tail, presence of heart-beat and well-organised somites. A weak positivity on exposed larvae has been highlighted by immunohistochemical analysis.

Developing new technologies is essential for advancement in solar cell technologies due to their ability to only absorb light mainly in the visible light spectrum. Super crystals Nd³⁺- Eu³⁺ optical characteristics display higher absorption of light waves than single crystals of Eu³⁺ and Nd³⁺ due to a two-photon absorption energy transfer mechanism known as upconversion. Super crystals Nd³⁺- Eu³⁺ display higher absorption due to fewer light waves being transmitted through materials as reported in spectra data. Transmission spectra data reflects that Nd³⁺- Eu³⁺ nanoparticles are great candidates to enhance light absorption in solar cell devices.

Full-waveform seismic data inversion has given rise to hope for the simultaneous and automated execution of tomography and imaging by solving a nonlinear least-squares optimization problem. As previously recognized, brute force minimization by classical methods is hopeless if the data lacks low temporal frequencies. The article developed a reliable numerical method for recovering smooth velocity using model space decomposition. We present realistic synthetic examples to test the presented algorithm.

This dataset consists of integral sea state parameters of significant wave height (SWH) and mean wave period (zero-upcrossing mean wave period, MWP) data derived from the advanced synthetic aperture radar (ASAR) onboard the ENVISAT satellite over its full life cycle (2002-2012) covering the global ocean. Both parameters are calibrated and validated against buoy data. A cross-validation between the ASAR SWH and radar altimeter (RA) data is also performed to ensure that the SAR-derived wave height data are of the same quality as the RA data. These data are stored in the standard NetCDF format, which are produced for each ASAR wave mode Level1B data provided by the European Space Agency. This is the first time that a full sea state product in terms of both the SWH and MWP has been derived from spaceborne SAR data over the global ocean for a decadal temporal scale.

With improved measurement and modelling technology, variability has emerged as an essential feature in non-equilibrium processes. While traditionally, mean values and variance have been heavily used, they are not appropriate in describing extreme events where a significant deviation from mean values often occurs. Furthermore, stationary Probability Density Functions (PDFs) miss crucial information about the dynamics associated with variability. It is thus critical to go beyond a traditional approach and deal with time-dependent PDFs. Here, we consider atmospheric data from the Whole Atmosphere Community Climate Model (WACCM) and calculate time-dependent PDFs and the information length from these PDFs, which is the total number of statistically different states that a system passes through in time. Time-dependent PDFs are shown to be non-Gaussian in general, and the information length calculated from these PDFs shed us a new perspective of understanding variabilities, correlation among different variables and regions. Specifically, we calculate time-dependent PDFs and information length and show that the information length tends to increase with the altitude albeit in a complex form. This tendency is more robust for flows/shears than temperature. Also, much similarity among flows and shears in the information length is found in comparison with the temperature. This means a stronger correlation among flows/shears because of a strong coupling through gravity waves in this particular WACCM model. We also find the increase of the information length with the latitude and interesting hemispheric asymmetry for flows/shears/temperature, a stronger anti-correlation (correlation) between flows/shears and temperature at a higher (low) latitude. These results also suggest the importance of high latitude/altitude in the information budge in the Earth's atmosphere, the spatial gradient of the information as a useful proxy for the transport of physical quantities.

This paper investigates the problem of a relativistic Dirac half-integer spin free particle tunneling through a rectangular quantum-mechanical barrier. If the energy difference between the barrier and the particle is positive, and the barrier width is large enough, there is proof that the tunneling may be superluminal. For first spinor components of particle and antiparticle states, the tunneling is always superluminal regardless the barrier width. Conversely, the second spinor components of particle and antiparticle states may be either subluminal or superluminal depending on the barrier width. These results derive from studying the tunneling time in terms of phase time. For the first spinor components of particle and antiparticle states, it is always negative while for the second spinor components of particle and antiparticle states, it is always positive, whatever the height and width of the barrier. In total, the tunneling time always remains positive for particle states while it becomes negative for antiparticle ones. Furthermore, the phase time tends to zero, increasing the potential barrier both for particle and antiparticle states. This agrees with the interpretation of quantum tunneling that the Heisenberg uncertainty principle provides. This study’s results are innovative with respect to those available in the literature. Moreover, they show that the superluminal behaviour of particles occurs in those processes with high-energy confinement.

Urban wind energy has emerged as an attractive source of distributed generation in cities to achieve sustainable development goals. The advance in technologies for the use of urban wind energy has turned this source into an attractive alternative for the decarbonization of cities and the energy transition. The objectives of this work are (1) to identify the potential of wind energy through numerical weather prediction (NWP) data tools and (2) to identify the roles and responsibilities of the stakeholders involved in the decision-making process. A methodology was developed in two phases and applied to a case study in the Dominican Republic. The first phase consisted of estimating the wind energy potential for the 32 provinces at a height of 10 m using open-access geographic reference systems tools provided by NASA. In the second phase, 28 stakeholders were identified through snowball sampling. The Responsible, Accountable, Consult, and Informed (RACI) matrix tool was applied to identify the roles of the 28 institutions addressed at the country level as relevant in the decision-making process for the energy sector. The annual average wind speed and energy potential for each province were determined. It was found 24 provinces have poor potential, below &lt;4.5 m/s. In the northwest and east is where there is the greatest potential, between 4.83 - 6.63 m/s. The population density was established and was observed that the provinces with greater potential are less densely populated. Through 59 interviews 28 institutions were identified and evaluated due to their relevance in decision-making for the implementation of energy projects. The MEM has strongly categorized as “A”, electricity distribution companies as “R”, energy associations and universities as “C”, and educational and justice institutions as “I”.

Timely detection of surface damages on wind turbine blades is imperative for minimising downtime and avoiding possible catastrophic structural failures. With recent advances in drone technology, a large number of high-resolution images of wind turbines are routinely acquired and subsequently analysed by experts to identify imminent damages. Automated analysis of these inspection images with the help of machine learning algorithms can reduce the inspection cost, thereby reducing the overall maintenance cost arising from the manual labour involved. In this work, we develop a deep learning based automated damage suggestion system for subsequent analysis of drone inspection images. Experimental results demonstrate that the proposed approach could achieve almost human level precision in terms of suggested damage location and types on wind turbine blades. We further demonstrate that for relatively small training sets advanced data augmentation during deep learning training can better generalise the trained model providing a significant gain in precision.

In a previous companion study, satellite data were used to describe peculiar characteristics of ocean surface wave fields, generated by two extra-tropical cyclones (ETCs) rapidly propagating in the North Atlantic. Based on a 2D parametric wave model, further details are now provided to analyse and interpret the spatio-temporal evolution of ETC very intense generated waves. Significant wave height and wavelength values are shown to reach extreme values, 18 m and 500 m, respectively. Resulting energetic swell systems waves then radiate in the whole eastern part of North Atlantic, and more particularly in the Norwegian sea region. Moving to higher latitudes, wind forcing characteristics of ETCs evolve, with the shape of the wind field changing from quasi-cyclonic to "air jets/Icelandic lows". In this paper, the resulting swell generation and propagation, after the deformation of an individual ETC, are studied, as well. Confirmed with comparisons with multi-satellite observations, the application of the parametric-2D wave-ray model is demonstrated to provide robust and highly detailed information on wave generation under very complex wind regime changes.

We present multi-sensor measurements from satellites, unmanned aerial vehicle, marine radar, thermal profilers and repeated conductivity-temperature-depth casts made in the Kara Gates strait connecting the Barents and the Kara Seas during spring tide in August 2021. Analysis of the field data during an 18-hour period from four stations evidence that a complex sill in the Kara Gates is the site of regular production of intense large-amplitude nonlinear internal waves. Satellite data show a presence of a relatively warm northeastward surface current from the Barents Sea toward the Kara Sea attaining 0.8-0.9 m/s. Triangle-shaped measurements of three thermal profilers revealed pronounced vertical thermocline oscillations up to 40 m associated with propagation of short-period nonlinear internal waves of depression generated by stratified flow passing a system of shallow sills in the strait. The most intense waves were recorded during the ebb tide slackening and reversal when the background flow was predominantly supercritical. Observed internal waves had wavelength of ~100 m and travelled northeastward with phase speeds of 0.8-0.9 m/s. The total internal wave energy per unit crest length for the largest waves was estimated to be equal to 1.0-1.8 MJ/m.

Accurate power curve modelling is essential to continuously evaluate the performance of a wind turbine (WT). In this work, we characterize the wind power curves using SCADA data acquired at a frequency of 5 minutes in a wind farm (WF) consisting of 5 WTs. Regarding the non-parametric methods, we select artificial neural networks (ANNs) to make curve estimations. Given that, we have the curves provided by the manufacturer of the WTs given by some very precisely measured pair of wind speed and power points. We can evaluate the difference between the manufacturer characterization and the ones estimated with the data provided by the SCADA system. Before the estimation, we propose a method of filtering the anomalies based on the characteristics provided by the manufacturer. We use three-quarters of the available data for curve estimation and one-quarter for the test. One WT suffered a break in the test part, so we can check how the test estimates reflect this problem in its wind-power curve compared to the estimations obtained in the WTs that worked adequately.

Background: We studied Riveaux Road Fire, which was ignited by multiple lightning strikes in January 2019 and burnt more than 637.19 km² in southern Tasmania, Australia. Aims: We focused on fire weather, such as identification of dynamic wind and vegetation type, in a valley of the study area. Methods: We employed two methods: numerical weather model vertical sounding (NWMVS) and the use of a fire simulator, to quantify and examine the contribution of dynamic winds to fire behaviour. The NWMVSs allow rapid diagnosis of changes in wind, temperature, dew point temperature and cloud coverage. Prototype 2 is a fire simulator based on the specification of Australian Fire Danger Rating System (AFDRS). Key results: We found fires to be guided by terrain-forced channelling primarily and by downslope wind conditionally in the valleys. In addition, the fire intensity periodically changed with the magnitude of surface wind, in buttongrass moorland, in which the fire often smoulders, during the fire period according to the satellite image. Conclusions and Implications: Therefore, there should be caution for not only terrain and dynamic wind but also vegetation type during fire spread in rugged terrain.

An Indo-French campaign was conducted during May 2014 at Gadanki (13.5^oN, 79.2^oE), India, for investigating gravity wave (GW) coupling between the lower and middle atmospheres using a suite of experimental techniques. In this paper we are presenting the sources for those GWs which are observed at airglow layer (~87 km) using (OH) Airglow Imager during the campaign. For this purpose we have developed a background model atmosphere by combining the ERA-Interim, MSIS E 90 model and HWM 07 model data sets. Uniqueness of the present study lies in using near-real time background atmosphere data from simultaneous radiosonde and SVU Meteor Radar covering both source and propagation/ dissipation regions of GWs. We have observed 17 wave events and used GROGRAT model for reverse tracing to locate the source(s). When we searched for the sources near the terminal points or along the ray path, deep convection is found to occur but no strong wind shear. This indicates that the source for the observed GWs is deep convection. We have also simulated small scale waves that can reach mesosphere during different seasons (background conditions). GWs with periods less than 100 minutes and horizontal wavelengths less than 200 km are mostly reaching the mesospheric altitudes. Interestingly, it is found that only few GWs that are generated in the troposphere reach the mesospheric altitudes during the monsoon season, though strong sources like convection and wind shear persist throughout this season. Thus, background wind plays significant role in deciding the propagation of GWs in to upper atmosphere.

Under the same seismic load, different local topography will have different effects, which is an important research field in seismic engineering. Hills are connected with valleys is a very typical terrain. Taking this terrain as an example, its response to the most destructive SH waves in the earthquake is studied. By simplifying and dividing the model, the wave functions satisfying the wave equation and boundary conditions in each region are constructed by using the complex function and moving coordinate method. The equations satisfying the boundary continuity conditions are established. With the help of calculation software, the numerical results are obtained. The influence of different parameters on ground motion is discussed.

River bed materials serve multiple environmental functions as a habitat for aquatic invertebrates and fishes. At the same time, the particle size of the bed material reflects the tractive force of the flow regime in a flood and provides useful information for flood control. The traditional river bed particle size surveys, such as sieving, require time and labor to investigate river bed materials. The authors proposed a method to classify aerial images taken by unmanned aerial vehicle (UAV) using convolutional neural networks (CNN), our previous study showed that terrestrial riverbed material could be classified with high accuracy. In this study, we attempted to classify riverbed materials distributed in shallow waters where the bottom can be seen from UAVs. After training the CNN to classify the images with the same grain size as being in the same class even if the surface flow types taken overlapping the riverbed material were different, the total accuracy reached 90.3%. Moreover, the proposed method was applied to the wide-ranging area to determine the distribution of the particle size. In parallel, the microtopography was surveyed using Lidar-UAV, and the relationship between the microtopography and particle size distribution was discussed. In the steep section, coarse particles were distributed and formed a rapid. Fine particles were deposited on the upstream side of those rapids, where the slope had become gentler due to the damming. There was good agreement between the microtopographical trends and the grain size distribution.

A question of physical importance is whether finite-energy spatiotemporally localized (i.e., pulsed) generalizations of monochromatic accelerating Airy beams are feasible. For luminal solutions, this question has been answered affirmatively by Saari, Valdmann, Piksarv, Valta-Lukner and Saari, and Kaganovsky and Heyman within the framework of the paraxial geometry. The time-diffraction technique introduced by Porras recently has been motivated by Besieris and Shaarawi in terms of the Lorentz invariance of the equation governing the narrow angular spectrum and narrowband temporal spectrum paraxial approximation and has been used to derive finite-energy spatiotemporally confined subluminal, luminal, and superluminal Airy wave packets. The goal in this article is to provide exact finite-energy broadband spatiotemporally localized Airy solutions (a) to the scalar wave equation in free space; (b) in a dielectric medium moving at its phase velocity; (c) in a lossless second order temporally dispersive medium.

The cost effective design of tidal turbines requires a good estimation of the loading cycles and their extrema that are related to the unsteady fluctuations of the current velocity. Apart from the ambient turbulence, the main source of velocity fluctuations is the presence of surface waves. In the present study, we analyse the effect of waves propagating against the current on the performance and the loads of a twin vertical axis tidal turbine by an experimental approach at a 1/20 scale. Overall, the results show little or no effect of the waves on the average power and loads compared to the condition with current only, but a significant impact on their standard deviation that rises linearly with the waves amplitude. The drag, lift and pitching moment show extended ranges up to 7.5 times higher and extreme values exceedance by 60 to 100 % with irregular waves compared to the condition without waves. Those load and power fluctuation increase are fully due to the presence of waves as the coherence function between the rotor torque or the loads and the velocity spectra exceed 0.5 on the whole wave frequency bandwidth. The results also reveal a rotational sampling of the waves by the rotors that had also been observed on horizontal axis turbines. From a structural design point of view, the authors recommand to conduct tests in irregular wave conditions as the loads range and extreme values are 1.5 to 2 times higher than those encountered with regular waves of the same significant height and period.

We propose an experimental method for the unidirectional excitation of spin waves. By structuring Au nanowires arrays within a coplanar waveguide onto a thin yttrium iron garnet (YIG) film, we observe a chiral coupling between the excitation field geometry of the nanowires grating and several well-resolved propagating magnon modes. We report a propagating spin wave spectroscopy study with unprecedented spectral definition, wavelengths down to 130 nm and attenuation lengths well above the 100 μm over the 20 GHz frequency band. The proposed experiment paves the way for future non-reciprocal magnonic devices.

This article discusses the potential advantages of a data processing technique for continuous gravitational wave signals searches in the data measured by ground-based gravitational wave interferometers. Its main advantage over other techniques is that it does not need to search over the signal’s direction of propagation. Although it is a “ coherent method” (i.e. it coherently processes year-long data), it is applied to a data set obtained by multiplying the original time-series with a (half-year) time-shifted copy of it. As a result, the phase modulation due to the interferometer motion around the Sun is automatically canceled in the signal of the synthesized time-series. Although the resulting signal-to-noise ratio is not as high as that of a coherent search, it equals that of current hierarchical methods. In addition, since the signal search is performed over a parameters space of smaller dimensionality, the associated false-alarm probability should be smaller than those characterizing hierarchical methods and result in an improved likelihood of detection.

The use of convolutional neural networks (CNNs) in image classification has become the standard method of approaching computer vision problems. Here we apply pre-trained networks to classify images of non-breaking, plunging and spilling breaking waves. The CNNs are used as basic feature extractors and a classifier is then trained on top of these networks. The dynamic nature of breaking waves is exploited by using image sequences to gain extra information and improve the classification results. We also see improved classification performance in using pre-computed image features such as the optical flow between image pairs. The inclusion of the dynamic information improves the classification between breaking wave classes. We also provide corrections to the methodology from the article from which the data originates to achieve a more accurate assessment of performance.