Asymmetrical awnings : a way to increase daylight in buildings without increasing the overheating

Different shapes of asymmetric awnings for east and west windows are investigated mathematically as well as by measurement in a model. A box with 90 cm side and a 30x30 cm window was placed outdoor in overcast weather and the daylight factor was measured at the bottom of the box when the window was unshaded or equipped with different awnings. The average daylight factor in the box decreased from 4.6% for the unshaded window to 1.0% when a full awning was used. With “the best” asymmetrical awning, the average daylight factor was 80% larger than with the full awing. Using Dutch climate, calculation of the energy from direct radiation transmitted through the window during the cooling season showed that this was decreased from 100% as an annual mean for the unshaded window down 22% with a full awing. With “the best” asymmetrical awning, 26% of the energy was transmitted. Calculation of the indoor temperature in a hypothetical row house in Netherlands show that the use of either normal or asymmetrical awnings considerable decrease the indoor temperature during the hot season. Therefore the use of asymmetrical awnings for east or west faced windows considerable can increase the daylight in buildings, with almost no change in overheating, compared to if traditional awnings are used.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.