Design and Testing of a Structural Monitoring System in an Almería-Type Tensioned Structure Greenhouse

Greenhouse cultivation has gained a special importance in recent years and become the basis of the economy in south-eastern Spain. The structures used are light and, due to weather events, often collapse completely or partially, which has generated interest in the study of these unique buildings. This study presents a load and displacement monitoring system that was designed, and full scale tested, in an Almería-type greenhouse with a tensioned wire structure. The loads and displacements measured under real load conditions were recorded for multiple time periods. The traction force on the roof cables decreased up to 22% for a temperature increase of 30 °C, and the compression force decreased up to 16.1% on the columns or pillars for a temperature and wind speed increase of 25.8 °C and 1.9 m/s respectively. The results show that the structure is susceptible to daily temperature changes and, to a lesser extent, wind throughout the test. The monitoring system, which uses load cells to measure loads and machine vision techniques to measure displacements, is appropriate for use in different types of greenhouses.

A case study of climate variability effects on wind resources in South Africa

The wind energy sector is one of the most prominent sectors of the renewable energy industry. However, its dependence on meteorological factors subjects it to climate change. Studies analysing the impact of climate change on wind resources usually only model changes in wind speed. Two elements that have to be calculated in addition to wind speed changes are Annual Energy Production (AEP) and Power Density (PD). This is not only because of the inherent variability between wind speed and wind power generated, but also because of the relative magnitudes of change in energy potentially generated at different areas under varied wind climates. In this study, it was assumed that two separate locations would experience a 10% wind speed increase after McInnes et al. (2010). Given the two locations’ different wind speed distributions, a wind speed increase equal in magnitude is not equivalent to similar magnitudes of change in potential energy production in these areas. This paper demonstrates this fact for each of the case studies. It is of general interest to the energy field and is of value since very little literature exists in the Southern African context on climate change- or variability-effects on the (wind) energy sector. Energy output is therefore dependent not only on wind speed, but also wind turbine characteristics. The importance of including wind power curves and wind turbine generator capacity in wind resource analysis is emphasised.

A Statistical Model to Forecast Short-Term Atlantic Hurricane Intensity

An alternative 24-h statistical hurricane intensity model is presented and verified for 13 hurricanes during the 2004–05 seasons. The model uses a new method involving a discriminant function analysis (DFA) to select from a collection of multiple regression equations. These equations were developed to predict the future 24-h wind speed increase and the 24-h pressure drop that were constructed from a dataset of 103 hurricanes from 1988 to 2003 that utilized 25 predictors of rapid intensification. The accuracy of the 24-h wind speed increase models was tested and compared with the official National Hurricane Center (NHC) 24-h intensity forecasts, which are currently more accurate on average than other 24-h intensity models. Individual performances are shown for Hurricanes Charley (2004) and Katrina (2005) along with a summary of all 13 hurricanes in the study. The average error for the 24-h wind speed increase models was 11.83 kt (1 kt = 0.5144 m s−1) for the DFA-selected models and 12.53 kt for the official NHC forecast. When the DFA used the correctly selected model (CSM) for the same cases, the average error was 8.47 kt. For the 24-h pressure reduction models, the average error was 7.33 hPa for the DFA-selected models, and 5.85 hPa for the CSM. This shows that the DFA performed well against the NHC, but improvements can still be made to make the accuracy even better.

Firnification and the effects of wind-packing on Antarctic snow

Using firn-core data from ten widely spread Antarctic sites, the dependence of firnification on temperature, wind and accumulation rate has been examined with two empirical models. One model relates the square of the porosity to the logarithm of the overburden pressure, and yields good fit to data through the first stage of firnification up to around 0.70-0.75 Mg m −3, beyond which it severely overestimates density. All three meteorological factors enter into this model, with higher temperatures and stronger winds increasing firnification rates, whilst higher accumulation rates have the opposite effect at any given depth. A temperature increase of 10°C has the equivalent effect to a wind-speed increase of 5 m s−1, or an accumulation rate decrease of 0.10 m a−1 w.e. A second model equates the logarithm of the porosity to overburden pressure and gives a much better fit to field data at higher densities where values asymptote to the bubble-free density of pure ice. This model generally yields a poor match to field data in the upper layers, with surface densities generally overestimated. Annual mean wind speed appears to be the least important of the local variables in this case, consistent with the success of the model at greater depth in matching data profiles.