At the present scenario, the action of ensuing the philosophy of reducing energy consumption and saving it for longer period without drop off in performance is increased. On the other hand, global warming and ozone layer depletion become foremost challenges. These concerns are takes place in Thermal systems like refrigerator and air conditioning. To resolve the above challenges, the nano refrigerants are used in refrigeration, which has previously got the attention due to its distinctive properties such as thermal conductivity. They also have the potential to improve the heat transfer performance of refrigeration. This project interrogated on the performance of domestic refrigeration system using normal condenser and microchannel condenser with and without nanoparticles. The Cerium oxide and Zinc oxide nanoparticles in the size of about 20-30nm and 30-50nm respectively with R134a domestic refrigerant were used. The experimentation carried out using 2 gm ofCeO2and ZnO nanoparticles in three different ratios [0.5:1.5,1:1 and 1.5:0.5] with R134a refrigerant. Hereby, the result conquered that 33.3% increase in the Actual COP of domestic refrigeration system using normal condenser with 1:1 ratio of nanoparticles when compared with the refrigeration system using microchannel condenser with and without nanoparticles.

Automatic air conditioning system is encouraged in most of the automotive especially passenger cars. This system can enable higher standard of comfort to the passengers, so the automotive industries are trying to implement the automatic air conditioning system in most of their vehicle. One the other hand manufacturing simulation is additional processing experienced in most of the manufacturing industry, to analysis the complete performance of the product or vehicle before it manufacturing. In recent decade more than 100 simulators are developed to analysis the various operation of the manufacturing and vehicle. But simulation analysis of air conditioning system and automatic air conditioning system is challenging to the engineer. They may require to spend more time to analysis the performance of the automatic air conditioning system. Thus in later period soft computing based system for the effective performance prediction of automatic air conditioning system is proposed. But the prediction accuracy of the past technique is not in the satisfactory level. Hence in this paper, a novel soft computing technique is proposed for the effective prediction of the performance of the automatic air conditioning system. In the proposed system support vector machine is used for the prediction of the performance of automatic air conditioning system. The performance of the proposed technique is compared with the ANN.

The interest of using alternative fuels in Diesel engines has been accelerated exponentially due to a foreseen scarcity in world petroleum reserves and restrictions on exhaust emissions. Alcohol which is bio-based renewable and oxygenated fuel provides a suitable alternate fuel for internal combustion engines. In this regard, exploration of potential for higher alcohols in automotive application is needed. Long chain alcohols such as pentanol and hexanol despite their analogous properties have rarely been inspected. The n-hexanol, the longer chain alcohol is used to be fueled with diesel. These oxygenated additives allow the fuel to increase combustion efficiency due to the presence of oxygen. In the present investigation, two blends of hexanol and diesel were prepared. All the blends were found to be homogenous and stable. The brake thermal efficiency for all the blends was observed to be slightly higher in comparison to neat diesel. The maximum brake thermal efficiency was obtained with B20 blend. Similarly, minimum total fuel consumption was obtained for B20 blend while rest of the blend showed a reduction in total fuel consumption. The CO emissions were found to get reduced with increase in hexanol percentage in the blends. The HC emissions were observed to increase as the percentage of hexanol increases on the blend. The NOx emissions increased with increase in engine load for all test fuels. Finally, concluded that a blend of B20% hexanol in diesel will result in better engine performance and emissions of CO2, CO, and NOx.