Effect of Clothing Fabric on 20-km Cycling Performance in Endurance Athletes

Purpose: Examine the effect of synthetic fabrics (SYN, 60% polyester: 40% nylon) vs. 100% cotton fabric (CTN) on the 20-km cycling time trial (20 kmCTT) performance of competitive cyclists and triathletes.Methods: In this randomized controlled crossover study, 15 adults (5 women) aged 29.6 ± 2.7 years (mean ± SE) with a peak rate of O2 consumption of 60.0 ± 2.0 ml/kg/min completed a 20 kmCTT under ambient laboratory conditions (24.3 ± 0.7°C and 17 ± 7% relative humidity) with a simulated wind of ~3 m/s while wearing SYN or CTN clothing ensembles. Both ensembles were of snowflake mesh bi-layer construction and consisted of a loose-fitting long-sleeved shirt with full-length trousers.Results: Participants maintained a significantly (p < 0.05) higher cycling speed and power output over the last 6-km of the 20 kmCTT while wearing the SYN vs. CTN ensemble (e.g., by 0.98 km/h and 18.4 watts at the 20-km mark). Consequently, 20 kmCTT duration was significantly reduced by 15.7 ± 6.8 sec or 0.8 ± 0.3% during SYN vs. CTN trials (p < 0.05). Improved 20 kmCTT performance with SYN vs. CTN clothing could not be explained by concurrent differences in esophageal temperature, sweat rate, ratings of perceived exertion and/or cardiometabolic responses to exercise. However, it was accompanied by significantly lower mean skin temperatures (~1°C) and more favorable ratings of perceived clothing comfort and thermal sensation during exercise.Conclusion: Under the experimental conditions of the current study, athletic clothing made of synthetic fabrics significantly improved the 20 kmCTT performance of endurance-trained athletes by optimizing selected thermoregulatory and perceptual responses to exercise.

Wind and turbulence profiles in a simulated wind tunnel boundary layer

A system of Honeycomb Flat Plate (HFP) grid and cylindrical rods has been developed to accelerate the growth of a thick (32 cm) turbulent boundary layer, artificially, over rough floor of a low speed short test-section (0.61 m x 0.61 m) wind tunnel. Simulated profiles of wind velocity, longitudinal turbulence intensity and Reynolds stress are shown to have similarity to those of a neutral atmospheric boundary layer over a typical rural terrain. Longitudinal spectrum of turbulence measured at 10,30 and 100 mm above tunnel floor is shown to compare well with atmospheric spectrum and agree closely with the Kolmogoroff's -2/3 law in the inertial sub-range of the spectrum. Based on the length scale of longitudinal turbulence estimated from the spectrum, a scale of 1 :900 has been proposed for laboratory modeling of environmental problems wherein the transport of mass in a neutral atmospheric surface layer IS solely due to eddies of mechanical origin.

The 3 km Norwegian reanalysis (NORA3) – a validation of offshore wind resources in the North Sea and the Norwegian Sea

We validate a new high-resolution (3 km) numerical mesoscale weather simulation for offshore wind power purposes for the time period 2004–2016 for the North Sea and the Norwegian Sea. The 3 km Norwegian reanalysis (NORA3) is a dynamically downscaled data set, forced with state-of-the-art atmospheric reanalysis as boundary conditions. We conduct an in-depth validation of the simulated wind climatology towards the observed wind climatology to determine whether NORA3 can serve as a wind resource data set in the planning phase of future offshore wind power installations. We place special emphasis on evaluating offshore wind-power-related metrics and the impact of simulated wind speed deviations on the estimated wind power and the related variability. We conclude that the NORA3 data are well suited for wind power estimates but give slightly conservative estimates of the offshore wind metrics. In other words, wind speeds in NORA3 are typically 5 % (0.5 m s−1) lower than observed wind speeds, giving an underestimation of offshore wind power of 10 %–20 % (equivalent to an underestimation of 3 percentage points in the capacity factor) for a selected turbine type and hub height. The model is biased towards lower wind power estimates due to overestimation of the wind speed events below typical wind speed limits of rated wind power (u<11–13 m s−1) and underestimation of high-wind-speed events (u>11–13 m s−1). The hourly wind speed and wind power variability are slightly underestimated in NORA3. However, the number of hours with zero power production caused by the wind conditions (around 12 % of the time) is well captured, while the duration of each of these events is slightly overestimated, leading to 25-year return values for zero-power duration being too high for the majority of the sites. The model performs well in capturing spatial co-variability in hourly wind power production, with only small deviations in the spatial correlation coefficients among the sites. We estimate the observation-based decorrelation length to be 425.3 km, whereas the model-based length is 19 % longer.

WRF Evaluation During Storm Ophelia Using Remote Sensing and In-situ Measurements at Mace Head, Ireland

Storm Ophelia made landfall over Ireland as an extra-tropical storm on the morning of the 16th of October 2017. The storm caused major power outages, lifted roofs, caused coastal flooding in Ireland, and resulted in the loss of three lives. A model&rsquo;s capability to forecast extreme weather events such as Storm Ophelia is of utmost importance and now with a changing climate, it becomes more important to improve and enhance model forecasting capability. The Weather Research and Forecasting (WRF) model V3.9 has been configured for the Irish domain and this study presents a preliminary evaluation of the Model during Storm Ophelia. Simulated wind speed and direction were compared with hourly remote sensing (lidar) and in-situ (wind speed and wind direction at 10m) observations at the coastal site of Mace Head Atmospheric Research Station on the West coast of Ireland (53.33◦ N, 9.90 49 ◦ W). The model simulation has generally small biases in the simulated wind speed and wind direction during this case study. The model also realistically simulated the magnitude and geographical distribution of the wind speed and wind direction observed during Ophelia.

Simulated Experiment on Wind Erosion Resistance of Salix Residual in the Agro-Pastoral Ecotone

Plant residual is of great importance in retarding soil wind erosion in the agro-pastoral ecotone. However, few studies have determined the effects of sand plant residual on wind erosion resistance. Based on field surveys, the influences of Salix residual biomass of 200, 400, 600, and 800 g m−2, soil incorporated with a residual thickness of 0.5, 1.0, and 2.0 cm, and typical proportion of residual branches and leaves (2:1, 1:1, and 1:2) on wind erosion resistance were investigated using a simulated wind tunnel. The results showed the following: 1) The soil loss amount ranged from 1.56 to 40.8 kg m−2 as Salix residual biomass decreased from 800 to 0 g m−2, with a critical residual biomass value of 400 g m−2. 2) As the thickness of soil-incorporated residual increased, the soil loss amount reduced rapidly, especially for 0–9 cm above the surface accounting for 84.6% of the total. 3) Salix branch residual is more important in resisting soil wind erosion as compared with its leaves. This kind of study may provide theoretical explanations for the optimal reconstruction of sandy vegetation in the northern wind-sand regions.

A Study of Raindrop Impacts on a Wind Turbine Material: Velocity and Impact Angle Effects on Erosion MAPS at Various Exposure Times

Within renewable energy, challenging climates can impose great limitations on power generation. In wind energy, rain erosion on turbine blades can create major disruptions to air flow over the aerofoil, reducing the efficiency of the blade and immediately affecting the power output of the turbine. The defects in the materials that cause these inefficiencies are known and can be observed on turbines that have been in operation for extended periods. This work explores the transitions between different wear states for G10 Epoxy Glass under laboratory simulated wind turbine conditions in operation and measures the wear periodically to identify a progression of erosion. Mass loss data and micrographic analysis revealed samples at 45° and 60° displayed increasing erosion when examining erosion performance for angles between 15° and 90° over various exposure and velocities. Erosion maps were constructed, showing the variation of wastage and identifying the performance window of conditions where degradation is minimised.

Norwegian hindcast archive (NORA3) – A validation of offshore wind resources in the North Sea and Norwegian Sea

A new high-resolution (3 km) numerical mesoscale weather simulation spanning the period 2004–2018 is validated for offshore wind power purposes for the North Sea and Norwegian Sea. The NORwegian hindcast Archive (NORA3) was created by dynamical downscaling, forced with state-of-the-art hourly atmospheric reanalysis as boundary conditions. A validation of the simulated wind climatology has been carried out to determine the ability of NORA3 to act as a tool for planning future offshore wind power installations. Special emphasis is placed on evaluating offshore wind power-related metrics and the impact of simulated wind speed deviations on the estimated wind power and the related variability. The general conclusion of the validation is that the NORA3 data is rather well suited for wind power estimates, but gives slightly conservative estimates on the offshore wind metrics. Wind speeds are typically 5 % (0.5 ms−1) lower than observed wind speeds, giving an underestimation of offshore wind power of 10 %–20 % (equivalent to an underestimation of 3 percentage point in the capacity factor), for a selected turbine type and hub height. The model is biased towards lower wind power estimates because of overestimation of the frequency of low-speed wind events (< 10 ms−1) and underestimation of high-speed wind events (> 10 ms−1). The hourly wind speed and wind power variability are slightly underestimated in NORA3. However, the number of hours with zero power production (around 12 % of the time) is fairly well captured, while the duration of each of these events is slightly overestimated, leading to 25-year return values for zero-power duration being too high for four of the six sites. The model is relatively good at capturing spatial co-variability in hourly wind power production among the sites. However, the observed decorrelation length was estimated to be 432 km, whereas the model-based length was 19 % longer.