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Spray modelling is one of the most useful techniques to characterize engine performance, efficiency and emissions. The size of droplets is one of the key variables that govern the efficiency of combustion of the liquid fuel. This study aims to develop an interactive tool using MATLAB codes that identifies the droplets and their sizes from the image taken with the long distance microscope in the spray chamber setup. In this developed method, firstly the background of the image was removed and then image processing techniques, dilation and erosion, were applied to the image file to refine the image files. Subsequently, circle detection method based on the Hough Transform algorithm with the function of imfindcircles was implemented. This function of the program allows the user to identify size droplets from the image files. A statistical study was conducted with the results automated from the MATLAB program using a different set of threshold values of black and white contrast. The results showed an optimal range for the threshold (black and white) values between 40 and 70. This optimal threshold range was established based on consideration of the correct and incorrect identification of the droplets. The results indicated that the program has the ability to identify the droplet providing size and numbers. The MATLAB program was developed using MATLAB compiler and can be used at different workstations.

There has been an increasing concern on indoor air quality in recent years due to the possible harmful effects to human health. Indoor air pollution as a result of using natural gas for cooking and heating is a common health threat, particularly for women and young children. Therefore, quantification of the type and emission levels of these pollutants is necessary in order to mitigate and monitor the emissions. Computational fluid dynamics (CFDs) can be used to model airflow and dispersion within buildings of complex geometry and layout. In the present paper, a CFD analysis is performed to determine the concentration of indoor air quality for a typical one-floor building in order to determine the optimal locations of monitoring sensors. According to this study, placing the monitoring sensors based on the maximum concentrations of the individual contaminant does not entirely overcome the problems, as the concentrations of different hazardous pollutants cannot be added. Moreover, high concentration with low duration of exposure is not a good candidate for placing the monitoring system. A risk-based methodology is proposed to determine the optimal location for the monitoring systems. Different risk management strategies are also considered as a part of the methodology to reduce the exposure risk of indoor contaminants. © The Author(s), 2011.