Mean Wind Research Articles

Effects of irrigation‐induced surface thermodynamics changes on wind speed in the Heihe River basin, Northwest China

AbstractThe Heihe River Basin, located in Northwest China, serves as a major commodity grain base in China due to its state‐of‐the‐art irrigation system. The rapid increase in soil moisture caused by irrigation can alter the land–atmosphere energy fluxes and regulate regional climate. However, the effects and mechanisms of irrigation on wind speed related to thermodynamics remain unclear. Here, we carried out two 10‐year numerical simulations using the Weather Research and Forecast (WRF) model incorporating a real‐time irrigation scheme. By comparing the simulation differences (including and excluding irrigation), we found that irrigation significantly decreased the daily mean and maximum wind speed at 10 m above ground by 0.30 and 0.55 m·s−1, respectively, in the irrigated area during the growth season. Such surface wind slowdown could be explained by irrigation‐induced surface air cooling and, hence, intensifying atmospheric column stability, weakening turbulent momentum transport, as well as opposite‐to‐prevailing winds vector anomaly caused by increased southward pressure gradient. Meanwhile, we also found wind slowdown mainly occurs below 1100 m while acceleration effect above that level. It was highlighted that the surface wind slowdown effect of irrigation substantially improved the performance of the WRF model. Due to the surface wind slowdown effect of irrigation, the positive bias of daily mean and maximum wind speed simulated by the WRF model was reduced by 15.3% and 27.4%, respectively. Our findings implicate the potential importance of irrigation in improving the performance of climate models as well as in explaining the phenomenon of global stilling.

Long-term trend of surface wind speed in the Guangdong-Hong Kong-Macau Greater Bay Area during 1980–2020: Spatiotemporal variation and urbanization effect

Understanding the surface wind speed variations is important for the climate and air quality assessment in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), known as the world class urban agglomeration in China. This study investigates the spatial and temporal variations of surface mean wind speed (MWS) in the GBA from 1980 to 2020, drawing upon ground observations and reanalysis data. After accounting for station relocations, the observed wind speed demonstrated a fluctuating declining trend of −0.036 m∙s−1 per decade over the examined period in line with reanalysis data. Wind speeds were found stronger during winter and daytime than summer and nighttime. The southern coastal regions exhibited higher MWS compared with northern mountainous areas. The Empirical Orthogonal Function (EOF) revealed the dominant mode of MWS changes was characterized by a cyclical pattern lasting over 20 years, probably influenced by atmospheric circulation. The urbanization reduced the observed wind speeds by 4.71% - 10.11% over the past decade (2011−2020) in urban areas of the GBA based on urban-minus-rural (UMR), observation-minus-reanalysis (OMR), and urban impact factor (UIF) methods. The long-term spatio-temporal analyses of MWS could benefit the climate and air quality studies and provide data support for regional and micro-scale modeling in the GBA.

Assessment of Wind over Complex Terrain Considering the Effects of Topography, Atmospheric Stability and Turbine Wakes

This study proposes a microscale flow model to estimate mean wind speed, fluctuating wind speed and wind direction over complex terrain considering the effects of topography, atmospheric stability, and turbine wakes. Firstly, the effect of topography is considered using Computational Fluid Dynamics (CFD). Next, a mesoscale model is presented to account for the effect of atmospheric stability. The effect of turbine wakes on the mean and fluctuating wind speeds are then represented by an advanced wake model. The model is validated using the measurement data of a wind farm located in the North of Japan. The measured wind data by Lidar at a reference height are horizontally extrapolated to a nearby met mast hub height and validated by a cup anemometer. Moreover, a novel averaging method is proposed to calculate a directional equivalent Monin–Obukhov length scale to account for the effect of atmospheric stability. Finally, the measured wind data at the reference height are vertically extrapolated and validated at the lidar location. The predicted mean and fluctuating wind speeds show good agreement with the measurements.

Wind Potential Assessment for Songkhla, Thailand

The analysis and evaluation of wind energy projects are important to understand their economic and environmental suitability for installation and operation. Using wind data from the Meteorological Department, Used WAsP software for calculating, simulating, and analyzing the Annual Energy Production (AEP) and then applied it to calculate the Levelized Cost of Electricity (LCOE) of wind turbines installed in the Songkhla province area. The selected areas are suitable for all three models of wind turbines in the simulation. From the wind data analysis, wind direct was found that in the east sector (sector 4), there is the highest wind frequency at the wind station. The simulation results from Laem son-on area and Hua khao area show suitable mean wind speeds for wind farm installations. In the wind turbine simulation, three models were compared: Bonus 300 kW MkIII, Bonus 1.3 MW, and PowerWind 56 900 kW. At the Songkhla cape area, the positions with the highest AEP were 132.485 MWh, 344.419 MWh, and 332.597 MWh, respectively. Hua Khao area, the positions with the highest AEP were 225.284 MWh, 586.303 MWh, and 540.045 MWh, respectively. In the LCOE calculations for all model of wind turbines, at both Laem Son- On and Hua Khao locations, the most cost-effective wind turbine is the Bonus 300 kW. It has an LCOE of $142.43/MWh and $83.76/MWh, respectively. Therefore, the most cost-effective location is Hua Khao.

Effects of subcutaneous drain on wound dehiscence and infection in gynecological midline laparotomy: Secondary analysis of a Korean Gynecologic Oncology Group study (KGOG 4001)

ObjectiveTo identify the effects of subcutaneous drain insertion on wound dehiscence and infection in patients who underwent gynecological midline laparotomy. MethodsThis analysis identified the secondary endpoints of the KGOG 4001 study, a prospective, multicenter, non-blind, randomized controlled trial. Patients scheduled to undergo midline laparotomy for gynecological diseases and, with body mass index<35 kg/m2, were randomized (1:1) to treatment (with subcutaneous drain) and control (without subcutaneous drain) groups from February 2021 to December 2021. We compared the incidence rate of wound dehiscence 4 weeks post-surgery and the cumulative incidence rate of wound dehiscence and infection up to 4 weeks post-surgery between the two groups. ResultsOf 174 patients randomized to the treatment (n = 84) and control (n = 90) groups, 12 were excluded owing to loss to follow-up; finally, 162 patients (treatment, n = 79; control, n = 83) were included in intention-to-treat analysis. The frequency of cancer surgery (79.7 % vs. 77.1 %, p = 0.683), mean surgery time (227.7 vs. 226.7 min, p = 0.960), and mean wound length (24.2 vs. 24.3 cm, p = 0.933) were comparable between two groups. No significant differences were observed in the incidence rate of wound dehiscence 4 weeks post-surgery (1.3 % vs. 2.4 %, p > 0.999), cumulative incidence rate of wound dehiscence (8.9 % vs. 6.0 %, p = 0.491), and cumulative incidence rate of wound infection (1.3 % vs. 0.0 %, p = 0.488) up to 4 weeks post-surgery between the two groups. ConclusionSubcutaneous drain insertion is not associated with a significant improvement in the incidence of wound dehiscence and infection in patients who undergo gynecological midline laparotomy. Clinical trial registrationClinicalTrials.gov, NCT04643197.

Impact of natural urban terrain on the pedestrian wind environment in neighborhoods: A CFD study with both wind and buoyancy-driven scenarios

The impact of topography on airflow has been studied at different scales, however the influence of urban natural terrain on local wind conditions is unclear. In this study, the impact of natural urban terrain on mean wind speed at the pedestrian level is investigated. A numerical study is conducted using a Large Eddy Simulation (LES) model for a high-density residential neighbourhood in Singapore with the natural terrain and a flat surface. The following two wind variations are examined (1) low wind speed and high temperature conditions for which the atmospheric boundary layer exhibits unstable thermal stratification; (2) annually averaged wind conditions with neutral thermal stratification. The results show that the overall impact of natural urban terrain on pedestrian wind speed is pronounced when the wind environment exhibits unstable thermal stratification i.e. buoyancy driven flows, compared with wind driven flows. For both cases, the results indicate a localized effect based on building density and proximity to steep terrain with spatial averages as high as approximately 0.8 m/s. In areas characterized by low density, fewer surrounding buildings, or open spaces, it is advisable to model the topography when it is shallow or steeply sloping. For medium density built areas, natural urban terrain modelling is also recommended. However, it is observed that in a high-density region, pedestrian wind flow is more strongly affected by the surrounding buildings than the terrain. These results are potentially important to balance computational cost and accuracy in urban wind simulations in urban areas with various densities and microclimate scenarios.

Direct measurements of sea spray particle fluxes using a high temporal resolution optical particle counter over the coastal ocean

ABSTRACT Sea spray particles play a key role in transferring momentum, heat, and gas across the atmosphere–ocean interface at high wind speeds and represent an important source of cloud condensation nuclei which affect the genesis, chemistry, and radiative properties of marine clouds. Here, we present direct measurements of sea spray particle fluxes obtained using an eddy covariance technique through the use of a newly developed high temporal resolution optical particle counter. With this instrumentation measurements were made over the coastal ocean during a 5-week field campaign conducted at an observation pier from November to December 2021. Our optical particle counter was capable of measuring size spectra at a rate of 10 Hz in 8 channels covering a range of mean radii between 0.3 and 15. The power spectra of particle number density followed the Kolmogorov −2/3 power law. The shape of the cospectrum of the particle number density flux was basically similar to that of the cospectra of the heat and gas fluxes. The measured sea spray particle fluxes at mean wind speeds of up to 21 m s−1 were dominated by an upward flux, which likely represents aerosol production caused by the bursting of bubbles at the ocean surface.

Comparing annual extreme winds in Iran predicted by numerical weather forecasting and Gram-Charlier statistical model with meteorological observation data

Iran has been experiencing severe dust storms due to strong wind speeds that cause sand erosion. This erosion is particularly pronounced in the semi-arid and arid zones. Wind speed predictions using numerical weather forecasting (NWF) are indispensable; however, the applicability of NWF for predicting extreme annual wind speeds is not well known. To validate the NWF model, this study compared NWF-model-predicted 3-hour averaged wind speeds over one year and those observed at 390 weather stations. In addition, a statistical model was employed to estimate the probability densities of wind speeds for both the observational data and the NWF output. As an NWF model, the mesoscale Weather Research and Forecasting (WRF) model was utilized to simulate wind speeds. The results indicate that the observation data are consistent with the modeled datasets regarding the relationships among the mean, standard deviation, and skewness, whereas the WRF model tends to overestimate the mean wind speeds. In addition, the predictability of annual extreme wind speeds was determined using the peak factor. Moreover, skewness has emerged as an influential parameter for predicting extreme winds. Finally, the Gram-Charlier series model was utilized to estimate probability density functions of the wind speeds, demonstrating its effectiveness in capturing positively skewed distributions. The present analyses broaden the use of both NWF outputs and statistical methods to predict extreme wind speeds in Iran.

Mathematical Differential Analysis of Atlantic Ocean Wind to Electrical Energy Generation in Lekki Peninsular Lagos Nigeria

This article is a pragmatic approach on the evaluation of wind energy production and it’s estimation in the coastal area of Lagos Nigeria. The work focuses on the accessibility of wind energy production in Lagos Nigeria through analyzing wind data in the look up tables using proficient probability function. Here, three approaches are itemized; Analysis of sets of actual time series data, theoretical Weibull probability function using seven numerical methods and the comparison of theory and the analysis. Two important parameters are used in this analysis are the Weibull shape factor “k” and Weibull scale factor “c”. Theory involves the calculation using seven popular methods of moments (MM), standard deviation method (STDM) or empirical method (EM), maximum likelihood method (MLM), modified maximum likelihood method (MMLM), second modified maximum likelihood method (SMMLM), graphical method (GM) or least mean square method (LSM), energy pattern factor method (EPFM). The performance of the numerical methods has been tested by five methods; RMSE, X2, IA, MAPE and RRMSE. The results expatiate on Actual and theoretical technique being used to find out wind energy conversion per 1 km2. In this paper, a differential performance method for accuracy check has been proposed as an error indicator between the wind energy calculated by theoretical Weibull function and the one by actual time-series data. The wind speed data was measured from January 2018 to December 2021 in the Lekki peninsular area of Lagos State. The suitability values for these parametric; shape and scale parameters of Weibull distribution are determined in selecting the best location for the installation the wind turbine generators. The measured annual mean wind speed and mean wind power are 10.11 ms-1 and 10.4 KWm-2, respectively.

Assessment of Wind Energy Potential at Three Prime Locations in Saudi Arabia: Analysis of Sharma, Qurayyat and Sakaka Sites

Purpose: The research aims to assess the wind energy potential at three chosen sites in Saudi Arabia Sharma, Al Qurayyat, and Sakaka over a five-year period from 2019 to 2023. The main goal is to determine the most favorable locations for wind farm development based on wind speed characteristics, Weibull distribution parameters, and wind power density (WPD). Materials and Methods: The wind speed data for the chosen locations was obtained from NASA's wind website and analyzed using the Weibull distribution to determine the shape (k) and scale (c) parameters, which are indicative of wind speed distribution. Critical metrics such as mean wind speed, WPD, and the most probable wind speed were computed to evaluate the wind energy potential. The Vestas V150-4.2 MW turbine was utilized to estimate potential energy output, considering the variability and reliability of wind resources at the specified locations. The study utilized tables, figures, and wind rose diagrams to highlight important wind parameters like mean wind speed, Weibull parameters, WPD, and Vmax for each location. Flowcharts were also used to summarize the methodology and conclusions, ensuring a clear and comprehensive presentation of the data. Findings: The analysis showed that Qurayyat consistently had the highest mean wind speed and WPD, indicating excellent wind energy potential. Sharma and Sakaka also displayed significant wind resources, with high mean wind speeds and substantial WPD values. The Weibull parameters indicated that all three sites have favorable wind characteristics for energy production. The estimated energy output using the Vestas V150-4.2 MW turbine ranged from 12,809 to 17,807 MWh/yr at Site 18, 14,095 to 15,170 MWh/yr at Site 24, and 14,013 to 15,832 MWh/yr at Site 31. Implications to Theory, Practice and Policy: The study presents a thorough evaluation of the wind energy potential in the Al-Jawf and Tabuk regions of Saudi Arabia. It contributes to a deeper understanding of wind resource distribution and its significance for the development of renewable energy. The study provides valuable insights for wind farm developers and policymakers by identifying the most promising locations for investment in wind energy infrastructure. Furthermore, it emphasizes the need for detailed site-specific analyses to optimize wind energy deployment, aligning with Saudi Arabia's broader renewable energy objectives.

A Numerical Study of Smoke Concentration Distribution near Low-Intensity Fires: Sensitivity to Vertical Canopy Structure and Fire Heat Source Strength

Abstract Broadly speaking, prediction of the negative impacts of prescribed fire on air quality is limited by gaps in our understanding of the underlying fire, fuels, and atmospheric processes. These knowledge gaps hinder our ability to accurately predict smoke concentration distributions, leading to unintended smoke intrusions into nearby communities and subsequent threats to public health and safety. In this study, numerical simulations are performed using the Flexible Particle Weather Research and Forecasting (FLEXPART-WRF) Model, a Lagrangian particle dispersion model, with particle motion driven by output from a full-physics atmospheric model with a forest canopy submodel and 10-m horizontal grid spacing [Advanced Regional Prediction System (ARPS)-CANOPY], to address two research questions. First, what is the relationship between near-fire (within ∼50–150 m of fire) smoke concentration distribution and (i) vertical canopy structure and (ii) fire heat source strength? Second, what roles do mean transport (i.e., transport by the mean wind) and turbulent diffusion play in shaping the near-fire smoke concentration distribution? To address these questions, simulations are run with 25 combinations of plant area density profile and fire sensible heat flux magnitude, and smoke is represented by particles with diameters ≤ 2.5 μm (PM2.5). Results show that near-fire PM2.5 concentration distribution is primarily controlled by vertical canopy structure, with fire heat source strength primarily controlling the PM2.5 concentration magnitude. Analysis of the underlying ARPS-CANOPY variables driving the FLEXPART-WRF particle dispersion helps elucidate the roles of mean transport and turbulent diffusion. In total, the study findings suggest that the vertical distribution of canopy vegetation and fire heat source strength are important factors influencing PM2.5 dispersion and concentration distribution near low-intensity fires.

A new power prediction model for wind power generation

Abstract A wind power generation forecast model based on WOA-SVM is presented to exploit effective information in different data sets completely. This model addresses the difficulties associated with parameter selection, low prediction accuracy, and susceptibility to local optima in short-term wind energy prediction. The model systematically investigates the relationship between various wind parameters (mean wind speed, maximum wind speed, minimum wind speed, mean wind direction, and mean hull position) and wind power. It then evaluates the model’s performance using mean absolute error and coefficient of determination. The predictive outcomes of the WOA-SVM model are contrasted with those of the SVM model, PSO-SVM model, and extreme learning machine (ELM) model, utilising authentic data from a wind farm located in northern China in the year 2021. The overall evaluation indicates that the WOA-SVM model outperforms the other models in short-term wind energy prediction, demonstrating superior prediction accuracy.

Study of boundary layer characteristics during the landfalling of a Nisarga cyclone

One of the most important parameters in meteorology is the mean wind profile in the tropical cyclone boundary layer. The vertical profile of wind speed and wind direction were measured during the period of the Nisarga cyclone from May 31st, 2020, to June 5th, 2020, using the newly installed Phased Array Doppler Sodar system at the Center for Space and Atmospheric Science (CSAS), Sanjay Ghodawat University, Kolhapur (16.74° N, 74.37° E; near India's western coast). Our analysis revealed that the maximum mean wind speed was 17 m/s on June 3, 2020, at 10:00 IST. It also shows the change in wind direction from southwest to southeast on June 2 and 3, 2020. Daily high-resolution reanalysis data in the domain, 0–25°N, 65–110°E, during the period from May 31st to June 5th, 2020, revealed the variation of the atmospheric pressure of the Nisarga cyclone from 1000 to 1008 hPa, sea surface temperature (SST) between 30 °C and 31 °C, outgoing longwave radiation (OLR) between 100 and 240 Wm-2, wind speed between 3 and 15 m/s, and low values of vertical wind shear (VWS) were observed to the north of Nisarga track. These observations may provide more insights for the study of boundary layer turbulence during cyclonic activities.

Reduced-order modelling of floating offshore wind turbine: Aero-hydro-elastic stability analysis

A reduced-order aero-hydro-elastic analysis tool for performing the stability analysis on floating offshore wind turbines is presented. In this work, a high-order non-linear aero-elastic model initially developed for onshore wind turbines is extended by utilizing a super-element body, which models the floating platform, the mooring system and the hydrodynamic contributions. The turbine structure is modelled by a Finite beam Element Method, and the aerodynamic loads are modelled by the Blade Element Momentum method coupled with a Beddoes-Leishman type dynamic stall model in a state-space formulation. The linearization is performed around steady state equilibrium at any given mean wind speeds, rotor speeds and collective blade pitch angles utilizing Coleman transformation to remove the periodic terms. The order reduction is based on two projections to reduce the number of structural states and aerodynamic states separately using the structural modal project matrix and the aerodynamic shape functions. Concurrently, we investigate the effect of unsteady aerodynamic states on the stability analysis of a floating wind turbine. The results show the low-order aero-hydro-elastic model expands the scope of numerical tools available for conducting structural modal analysis and aero-hydro-elastic stability analysis on floating wind turbines.

Robustness of LiDAR-assisted controller towards measurement uncertainty

Many studies have concluded that LiDAR-assisted control can be used to increase annual energy production (AEP) as well as reduce extreme loads and fatigue damage on blades, tower, and main bearing components. However, most studies assume perfect LiDAR measurements and do not consider large measurement uncertainties on LiDAR measurements. In this study we evaluate the potential benefits in terms of fatigue load reduction from using a simple robust feedforward controller. In addition, we evaluate the impact of measurement uncertainties exemplified by a time shift between the expected time the wind hits the rotor and the actual time it hits the rotor as well as a mean wind speed measurement bias. Results shows that fatigue loads can be reduced up to 7% on the tower sections and up to 4% on other main components. However, these results only applies when the LiDAR is assumed to give perfect information about what is hitting the rotor plane. The load reduction degrades with the magnitude of a time shift of the arriving LiDAR wind measurements. A delay up to 2.5 seconds still gives reasonable load reductions. Furthermore, a positive wind speed bias does not affect the performance of the LiDAR-assisted controller, whereas a negative bias significantly deteriorates performance.

A stably-stratified atmospheric inflow assimilated to measured mean profiles interacting with a wind park

In this paper, a simulation chain is presented. This method comprises the precursor large-eddy simulation (LES) of a stably-stratified atmospheric boundary layer (ABL), the assimilation of the simulated mean velocities to measured wind profiles, and finally a simulation of the generated turbulent ABL flow passing through two wind turbines in a row. The high-resolved precursor simulation with a horizontal grid spacing of 3 m accounts for the characteristic turbulence of the stably-stratified ABL. Using an assimilation technique, the horizontal velocities are adapted accurately to the measured mean wind profiles for the WiValdi wind farm site at Krummendeich. The wakes of two wind turbines in a row with the assimilated inflow is successfully computed. With the simulation chain presented, it is possible to generate realistic atmospheric inflows for wind-turbine simulations with manageable computational effort.

Constrained synthetic wind fields from high-resolution 3D WindScanner measurements

The limited spatial and temporal resolution of wind measurements within the inflow of a wind turbine requires statistical modeling of synthetic wind fields, integrating actual measurements or derived statistics along with selected turbulence models. The short-range WindScanner technology enhances atmospheric wind measurements with high resolution in both spatial and temporal dimensions. This contribution utilizes 3D turbulent inflow measurements from three synchronized WindScanner to generate synthetic turbulent wind fields. Both, mean wind field parameters and turbulent time series are analyzed, and different input configurations for the constrained wind field generation are evaluated.Our findings indicate the presence of periods characterized by dominant horizontal shear and veer events, with wind speed and direction differences up to 1.53 ms−1 or 8.45° across the rotor span. Additionally, the study reveals that the optimal measurement configuration for constrained turbulence modeling varies depending on the specific evaluated location and velocity component being analyzed. Another observation is that excessive constraints, placed too closely, may lead to overfitting, thereby diminishing the representativeness of the synthetic field for the lateral velocity component.

Assessing canopy models across forest edges on flat terrain

Computational modelling of atmospheric flows in forested areas is crucial for wind resource assessment, wind farm design and turbine siting, enabling the identification of low wind speed and high turbulence regions. However, when setting up a RANS simulation in a forested area, the question arises: what is the most appropriate canopy model? In this study, employing VENTOS-2D (RANS with k-ε turbulence model), we identified the most suitable of seven canopy models to simulate the mean flow characteristics (wind speed) and second-order flow statistics (turbulent kinetic energy and shear stress) of the flow over a forest edge at the Island of Falster, by comparing against anemometer measurements and LES results. All models exhibited similar profiles for the mean wind speed, with a normalised RMSE of approximately 0.300. Regarding turbulent kinetic energy, the Lopes model outperformed the others, achieving an RMSE of 0.002. Lastly, for the Reynolds shear stress, Liu and Svensson’s models showed the lowest RMSE values (1.756 and 1.609), while others were over 4× larger (RMSE > 7). In summary, the performance of each model varies with the variable in focus, which is related to the model’s derivation method. However, considering all three analysed variables, Liu emerged as the most effective.

Gust-detection from velocity azimuth display Doppler wind lidar profiling at the WiValdi research park.

This study presents a new retrieval for gusts from Doppler wind lidar (DWL) velocity azimuth display (VAD) scans. The scanning mode which is presented allows for retrieval of mean wind speed, vertical wind speed, turbulence kinetic energy and peak gust speed with a single strategy. It is validated against sonic anemometer measurements at 90 m above ground and a reference DWL gust mode with faster scanning speed at the boundary-layer field site Falkenberg of the DWD. The new algorithm is then run on a multi-year dataset to obtain statistics of gusts at the WiValdi research park. It enables analyses not only at hub height, but also up to 500 m aloft with a reasonable availability above 60%. A case study of a convective cold pool shows the potential of the method to detect and analyze the vertical and horizontal structure of gusts with the proposed method. It highlights the importance of measurements throughout the boundary layer to understand the related physical processes to wind ramps and gusts.

A Novel Surgical Approach For Upper Eyelid Blepharoplasty

Purpose: To report the surgical results of the patients with dermatochalasis (DC) who underwent upper eyelid blepharoplasty (UEB) with the cautery method was aimed. Materials and Methods: UEB surgery was performed by cautery method in 36 eyes of 18 patients due to DC. Pencil-tipped cautery was used to cut to sagging and marked skin area and was removed. Patients were examined preoperatively and postoperatively on the 1st day, 3rd day, 2nd week, 3rd month and 6th month. Results: The mean age was 54.6±7.9 years (range, 46 to 67 years) and 10 of were female and 8 were male. Mean operation time (1 session for 2 upper eyelid (UE)) was 36.7 ± 5.8 minutes (range, 28 to 46 minutes). Mean wound healing time was 7.7 ± 1.6 days (range, 5 to 12 days). Skin ecchymosis persisted for approximately 24.8±3.7 days (range, 19 to 38 days). Suture marks did not appear in 34 patients (%94), they were present in 2 patients 6 months after surgery. Statistically significant change was detected in the 6-month period in terms of skin ecchymosis and suture scar disappearance (p