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The aim of this study was to demonstrate the effectiveness of an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of diesel spray penetration length in an internal combustion engine. The technique involved extraction of necessary representative features from a collection of raw image data. An ANFIS was used to train the fuzzy inference system (FIS) and model the penetration length under different engine operating parameters, for example: in-cylinder pressure and temperature. The data obtained experimentally from the engine test rig was pre-processed using curve-fitting and averaging techniques. The devised mapping was compared with the experimental results and reasonable prediction was achieved. The results indicate that ANFIS can be used for modelling in-cylinder fuel spray behaviour as well as other operating parameters, potentially achieving very satisfactory results.

Anti-vibration rubbers in vehicle play an important role in restricting vibration generated from engine and road. But, degradation occurs when rubber is exposed for a long time to heat, light, ozone and etc. These make the rubber hard and lose its initial properties. The rubber change makes N.V.H performance of vehicle the worse, and gives the discomfort to the passengers. To reduce the change of rubber properties, sulfur-donor and heat stable cross-linking co-agent vulcanization system have been introduced in the developed natural rubber compounds of the anti-vibration rubber parts. These lead to a reduction of degradation of material properties, maintenance of the initial properties and increase of the fatigue life.

An automatic forced regeneration ceramic trap system with throttling before the trap, using Ce based fuel additives, for installation on light-duty diesel passenger cars is described. The system was installed on two vehicles and tested in the laboratory. The repeatability of the back pressure variation due to the soot accumulation during successive FTP cycles was determined, and the operation period of the system was defined. The operation of the system in both applications was equivalent to about 35 km of urban driving. The filtration efficiency approached 80% in FTP cycle and 90% in ECE and JAPAN 13 mode tests, while gaseous emissions and fuel consumption were practically not affected by the system.

A comparison of the performance of modern modal data analysis methods on test data from the Voyager Jupiter/Saturn payload is presented. Four different test/data-analysis combinations are compared--multiple-point sine excitation tests, single-point random-excitation tests using two different techniques of manipulating Fourier transform data, and a time-domain method for analyzing random data. Results indicate that all four methods can give comparable results. Of the four, the time-domain approach detects more modes in the test data and, at the same time, shows the greatest promise for reducing the time and cost of modal testing.