• Energy Research

This paper presents a wind resource assessment in Venezuela using an efficient combination of spatial interpolation and orographic correction for wind mapping. Mesoscale modelling offers a relatively accurate means to model meteorological conditions by solving the continuity and momentum equations. However, this approach is both time and computationally demanding. The methodology used in this work offers a computationally inexpensive solution by combining both a simple geo-statistical Kriging method to interpolate horizontal wind speed and an orographic correction to account for changes on terrain elevation. Hourly observations of wind speed and direction for 34 masts recorded during the period 2005–2009 have been analysed in order to define a statistical model of wind resources. The resulting method, which includes an exploratory statistical analysis of the wind data, is a computationally economical alternative to mesoscale modelling. Simulations results include equivalent mean wind speeds and wind power maps which have been created to a height of 50, 80 and 120 m above the ground based on a horizontal resolution of 15×15 km. Results show that the greatest wind energy resources are located in the coastal area of Venezuela with a potential for offshore applications. Preliminary findings provide a very positive evidence for offshore exploitation of wind power. Results also suggest that wind energy resources for commercial use (utility-scale) are available in northern Venezuela, additionally; they suggest excellent conditions for wind power production for micro-scale applications, both on- and off-grid.

The reduction of transport particulate matter emissions is crucial for improving air quality. Although particulate filters are efficient in removal of particulate matter, their inclusion in modern exhaust systems results in high back pressures and thus higher fuel consumption. Consequently, there is an ever-increasing demand within the automotive industry for more accurate and reliable filter design tools. A common modelling approach is to use 0-, 1- and 2-dimensional simplified filter flow models as part of the entire exhaust system. These models fail to capture the intrinsically 3-dimensional complex flow features present in the exhaust systems. In this work, a multi-channel modelling approach is implemented for the first time to provide full coupling within a CFD simulation framework. The strength of the new methodology is that it offers for the first time the ability to: (i) capture channel-to-channel flow interactions, (ii) account for density variations within individual channels, and (iii) investigate the overall effect of a given filter configuration on the exhaust system in 3D (i.e. upstream and downstream effects). The method retains the simplicity of a 1-dimensional filter channel model while providing an insight into the 3-dimensional non-uniform flow distribution between the channels. This approach represents an important new tool for exhaust system design and optimisation. Keywords: Particulate filters, GPF, DPF, Multi-channel, Pressure drop