83 research outputs found
Performance, Emissions and Combustion Characteristics of a Single Cylinder Diesel Engine Fuelled with Blends of Jatropha Methyl Ester and Diesel
In order to meet the energy requirements, there has been growing interest in alternative fuels like biodiesels, ethyl alcohol, biogas, hydrogen and producer gas to provide a suitable diesel substitute for internal combustion engines. An experimental investigation was performed to study the performance, emissions and combustion characteristics of diesel engine fuelled with blends of Jatropha methyl ester and diesel. In the present work three different fuel blends of Jatropha methyl ester (B10, B20, B40 and B100) were used. The increments in load on the engine increase the brake thermal efficiency, exhaust gas temperature and lowered the brake specific fuel consumption. The biodiesel blends produce lower carbon monoxide & unburned hydrocarbon emission and higher carbon dioxide & oxides of nitrogen than neat diesel fuel. From the results it was observed that the ignition delays decreased with increase in concentration of biodiesel in biodiesel blends with diesel. The combustion characteristics of single-fuel for biodiesel and diesel have similar combustion pressure and HRR patterns at different engine loads but it was observed that the peak cylinder pressure and heat release rate were lower for biodiesel blends compared to those of diesel fuel combustion
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Not AvailableAn optoelectric sensor based digital seedling counter was developed for measuringseedling spacing and for
detecting the flow of seedlings through the seedling delivery tube. It was placed on the seedling delivery tube
through which the seedlings were transferred to the ground from the metering mechanism. The performance
of the developed sensor was evaluated both in the soil binas well as in actual field conditions. Seedling
spacing was calculated with the signals obtained from optical sensor in data acquisition system (DAS)
whereas seedling flow was counted by processed signals in microcontroller based digital seedling counter in
soil bin conditions. The seedling spacing was calculated by measuring the output of the optical sensor over
time and seedling flow was calculated writing a program in the circuit, to convert the optical sensor output to
calculate number of seedling falls. Number of seedling falls was programmed to be calculated and digitally
displayed on the tractor dashboard whereas seedling flow was seen in the display of oscilloscope by output
signals i.e. voltage over time. The developed sensor could successfully sense the seedling fall through the
delivery tube, counted it and displayed it digitally. It provided information to the operator regarding flow of
plants in the tube. The seedling spacing obtained in the soil bin and field conditions varied from 0+1.5 cm
and 0±3 cm, respectively for the entire range of speeds and seedlings selected. Number of seedlings counted
manually and by sensor for both soil bin and field had 0% variation.Not Availabl
Development of a solar-energy-operated vapour-absorption-type refrigerator
The design of a commercially available vapour-absorption-type electrical refrigerator was changed to make it suitable for running on solar energy. The refrigerator was attached to an east-west oriented parabolic cylindrical collector to supply heat to the generator of the refrigerator. The test results revealed that the minimum temperature in the evaporator was 3°C. The coefficient of performance of the refrigerator was 1·73. The designed collector and the heating pipe were suitable for the operation of the refrigerator by solar energy. From the analysis of the operation of the refrigerator by both electrical as well as solar energy it was found that the heat supplied to the generator and the refrigerating effect was less in the latter case. The major factors behind this are the variation of heat supply and the low intensity of solar radiation.
Performance and emission evaluation of biodiesel derived from waste restaurant oil and Moringa oleifera
Not Available
Not AvailableA 5–9–1 artificial neural network (ANN) model, with a back propagation learning algorithm,
was developed to predict draught requirements of different tillage implements in a sandy
clay loam soil under varying operating and soil conditions. The input parameters of the
network were width of cut, depth of operation, speed of operation, soil moisture content
and soil bulk density. The output from the network was the draught requirement of the
individual tillage implement. The developed model predicted the draught requirement of
mouldboard plough, cultivator and disk harrow with an error < 6.5% when compared to the
measured draught values, whereas the American Society of Agricultural and Biological
Engineers (ASABE) equation predicted these draught values with an error > 30%. Such
encouraging results indicate that the developed ANN model for draught prediction could be
considered as an alternative and practical tool for predicting draught requirement of tillage
implements under the selected experimental conditions in sandy clay loam soils. Further
work is required to demonstrate the generalised value of this ANN in other soil conditions.Not Availabl
Influence of compression ratio on combustion characteristics of a VCR engine using Calophyllum inophyllum biodiesel and diesel blends
Performance and emission analysis of blends of karanja methyl ester with diesel in a compression ignition engine
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