Gopal Radhakrishnan Kannan

In order to lower hazardous emissions and improve the diesel engine characteristics, there has been a recent push for appropriate alternative fuels and improved performance tactics. In order to analyze the diesel engine behavior with variable compression ratios, the combined effect of alternate fuel and thermal barrier-coated engine crown was studied. Using Mahua Oil Methyl Esters (MOME) with various Compression Ratios (CR) ranging from 17:1, 19:1, and 21:1 at various load circumstances, the performance, emission, and combustion characteristics of the thermal barrier-coated VCR engine were examined and contrasted with those of diesel and non-coated or standard engines. Based on observed results, the adiabatic engine with a higher compression ratio of 21 (CR21-AE-B100) demonstrated the following characteristics: a higher cylinder gas pressure of 61.7 bar, a higher heat release rate of 78.6 J/oCA, a shorter ignition delay period of 9.8 oCA, a maximum brake thermal efficiency of 28.12%, the lowest Brake Specific Fuel Consumption (BSFC) of 0.3423 kg/kW h, a maximum Nitric Oxide (NO) emission of 575 ppm, and lowest smoke opacity of 37.8%.

The importance of biodiesel increases day by day due to the depletion of petroleum reserves and increasing environmental concerns. The performance, emission, and combustion characteristics of diesel engine fuelled with waste cooking palm oil-based biodiesel were improved by varying the engine parameters like fuel injection pressure injection timing and thermal barrier-coated engine components. Further, simultaneous improvement of biodiesel fuel properties, as well as engine characteristics, were achieved by implementing fuel modification such as the use of a fuel-borne catalyst added biodiesel, ternary blends, and water micro-emulsion. Modified fuels such as biodiesel-diesel-ethanol or diestrol and diestrol-microemulsion fuel engine modification on the diesel engine. Experiments were carried out on a Kirloskar make, naturally aspirated, single-cylinder, four-stroke, water-cooled, and direct injection (DI) diesel engine developing 5.2 kW at a constant speed of 1500 rpm.

In the present work, the 4 kW CO₂ laser welding process has been optimized for austenitic stainless steel (AISI 316)/ low carbon steel (AISI 1018) joint by using Taguchi based grey relational analysis. The experimental results make clear that the AISI 316/AISI 1018 laser welded joints are effectively enhanced by optimizing the input parameters. The metallurgical studies have been carried out for the optimum welded samples using an optical microscope to observe weld appearance and energy dispersive X-Ray analysis carried out to measure the nature of the matrix and chemical element distribution in the weld interface.

The present investigation is an attempt to study the effect of injection pressure and injection timing on performance, emission and combustion characteristics of a diesel engine fuelled with a blend of 30% waste cooking palm oil (WCO) methyl ester, 60% diesel and 10% ethanol (B30D60E10) or diestrol fuel using the artificial neural network (ANN) model. The experimental investigation was carried out on a single cylinder, four strokes DI diesel engine under full load (100%) condition at a constant speed of 1,500 rpm to obtain data for training and testing the proposed ANN model. Among the various networks tested the network with the combination of one hidden layer and 11 neurons within it showed the better correlation coefficient for the prediction of engine performance, emission and combustion characteristics. The ANN model was validated with the test data which was not used for training and found to be very well correlated. [Received: October 21, 2013; Accepted: September 9, 2014]

The gas tungsten arc welding (GTAW) process is generally implemented for fusion welding of stainless steel, magnesium alloys, nickel base alloys, carbon steel and low alloy steels. This study deals with the parametric modeling of gas tungsten arc (GTA) welding process for two dissimilar metals specifically stainless steel and low carbon steel. There are several process parameters influences the quality of weld strength namely arc voltage, gas flow rate, torch distance, current and welding speed to be used. Among the various process parameters, the arc voltage, gas flow rate and torch distance were considered for this analysis with the response of tensile strength. Twenty experiments were performed as per response surface methodology (RSM) based central composite face centered design for GTAW process. Comparison studies were made for predicted and experimental values of tensile or weld strength by using analysis of variance (ANOVA). It was found that developed model statistically fit on 95% confidence level.