PERFORMANCE OF A FOUR STROKE ADIABATIC DI DIESEL ENGINE
Extensive research is going on in the area of improvement of the engine thermal efficiency. In diesel engines approximately only one-third of the fuel energy is converted into useful work and major part of the energy is lost to cooling water. In an adiabatic engine (or insulated engine), the energy loss through cooling system is avoided by applying a layer of insulating material over the walls of the combustion chamber. The commonly used insulating materials are ceramic coatings such as silicon nitride, silicon carbide, zirconia (zirconium oxide) etc. As per the literature the partially Stabilized Zarconium (PSZ) is quite useful for the adiabatic engine application because of its excellent insulating characteristics, adequate strength and thermal expansion characteristics. Further this improves fuel economy, reduces, emissions and further reduces noise due to a lower rate of pressure rise. In the present investigations an adiabatic engine is developed with air gap insulation over the piston and cylinder liner, PSZ coated cylinder head and valves. With the higher temperatures in the combustion chambers in an adiabatic engine, widely available low cetane fuels like alcohols (which have high latent heat of vaporization) can also be burnt so that the ever-increasing demand for imported diesel can be reduced. In the present investigations a computer program has been developed in C language for an insulated engine and with that the theoretical results are obtained and then the same thing is compared with experimental results of adiabatic engine.
Computer Simulation of an LHR DI Diesel Engine
The effect on engine performance of insulating combustion chambers was simulated for a turbocharged direct injection diesel engine. We developed a low heat rejection (LHR) diesel cycle simulation. It includes a gas flow model, a heat transfer model, and a two zone combustion model. In the heat transfer model, convective and radiation heat transfer between the gas and walls was computed, taking into account the combustion chamber surface temperature swings
Detection and Counting of On-Tree Citrus Fruit for Crop Yield Estimation
In this paper, we present a technique to estimate citrus fruit yield from the tree images. Manually counting the fruit for yield estimation for marketing and other managerial tasks is time consuming and requires human resources, which do not always come cheap. Different approaches have been used for the said purpose, yet separation of fruit from its background poses challenges, and renders the exercise inaccurate. In this paper, we use k-means segmentation for recognition of fruit, which segments the image accurately thus enabling more accurate yield estimation. We created a dataset containing 83 tree images with 4001 citrus fruits from three different fields. We are able to detect the on-tree fruits with an accuracy of 91.3%. In addition, we find a strong correlation between the manual and the automated fruit count by getting coefficients of determination R2 up to 0.99.