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Carbon dioxide (CO2 or R744) is a promising next-generation refrigerant for mobile air-conditioning applications (MAC), which has the advantages of good heating performance in cold climates and environmental-friendly properties. This paper presents a simulation model of an integrated internal heat exchanger (IHX) and accumulator (Acc) using the finite volume method. The results are validated by a group of experimental data collected with different transcritical R744 mobile air-conditioner and heat pump (MHP) systems, and the error was within ±10%. The impacts of refrigerant mass flow rate and operating temperatures on the heat transfer rate of the IHX, improvement on refrigeration capacity and the liquid level in the Acc were studied. Results show that the net benefits of IHX are significant in AC mode, while it helps preventing flooding of the compressor in MHP mode.

This paper describes a practical and efficient approach for determining complete transient, as well as steady state response of tractor-trailer air brake systems by recording pushrod displacement and air brake service line pressure as a function to time. The test hardware utilizes easy to fabricate “clip on” transducers to measure pushrod stroke length. Data acquisition is via LABVIEW‚. All transducers are easy to temporarily affix to any tractor- trailer and require no alteration to the vehicle. A complete system check takes less time than manually measuring pushrod stroke as required under FMCSA. This system with one treadle application and release gives digital timing and displacement history of all brakes. Useful information includes: application and release profiles (pushrod velocity), shoe compliance upon seating and crack pressure release points for both tractor and trailer relay valves.

Neural networks are massively parallel computational models for knowledge representation and information processing. The capabilities of neural networks, namely learning, noise tolerance, adaptivity, and parallel structure make them good candidates for application to a wide range of engineering problems including diagnostics problems. The general approach in developing neural network based diagnostic methods is described through a case study. The development of an acoustic wayside train inspection system using neural networks is described. The study is aimed at developing a neural network based method for detection defective wheels from acoustic measurements. The actual signals recorded when a train passes a wayside station are used to develop a neural network based wheel defect detector and to study its performance. Signal averaging and scoring techniques are developed to improve the performance of the constructed neural inspection system.

The availability and low price of personal computers with suitable interface equipment has made it practical to use such a system for cylinder pressure data acquisition. With this objective, procedures have been developed to measure and record cylinder pressure on an individual crank angle basis and obtain an average cylinder pressure trace using an Apple II Plus personal computer. These procedures as well as methods for checking the quality of cylinder pressure data are described. A simplified heat release analysis technique for an approximate first look at the data quality is presented. Comparisons are made between the result of this analysis, the Krieger-Borman heat release analysis which uses complete chemical equilibrium. The comparison is made to show the suitability of the simplified analysis in judging the quality of the pressure data.