Computer Simulation for Haulage Performance of Power Tiller
The presence of a large number of marginal and small land holdings in India has rendered the power tiller to be the most suitable farm equipment for field operations, in view of its compact size, profitability and versatility, but the transport work which is also required to carry the farm produce is yet to be proved. Keeping these in mind, user friendly software was developed for predicting the haulage performance of power tiller to meet requirements in educational and research organizations. The developed software requires input parameters such as power tiller, trolley and operating conditions. The developed software was validated by conducting experiments with a 6.7 kW power tiller using a suitable trolley on tarmacadam road at various payloads and road slopes. The draft, slip, fuel consumption and speed were measured and other haulage performance parameters were calculated based on measured values to validate the developed software. The results simulated by software indicate lower draft and slip in the range of 1-23 and 2-9% with respect to the experimental data, however, higher transport productivity was in the range of 3-12%.
Short communication: Tractor_PT: A traction prediction software for agricultural tractors
Traction prediction modelling, a key factor in farm tractor design, has been driven by the need to find the answer to this question without having to build physical prototypes. A wide range of theories and their respective algorithms can be used in such predictions. The ''Tractors and Tillage'' research team at the Polytechnic University of Madrid, which engages, among others, in traction prediction for farm tractors, has developed a series of programs based on the cone index as the parameter representative of the terrain. With the software introduced in the present paper, written in Visual Basic, slip can be predicted in two- and four-wheel drive tractors using any one of four models. It includes databases for tractors, front tyres, rear tyres and working conditions (soil cone index and drawbar pull exerted). The results can be exported in spreadsheet format.
Prediction of a representative point for rail temperature measurement by considering longitudinal deformation
Monitoring rail temperature is very important for determining the safe running speed of trains and to prevent buckling. In general, the maximum variation of the internal rail temperature can be >7 ℃ depending on the point of measurement. However, there is as yet no sufficient information about how to predict the measurement point to represent the thermal deformation due to temperature distribution. In this study, the authors report a new point, called the representative measurement point, at which the rail temperature can be measured. This point considers the average deformation of the rail through structural analysis by adopting experimental and actual rail temperature data. The authors designed and installed a measurement system similar to an actual rail environment. Using the system, various data were acquired (internal/surface rail temperature and weather data) for 10 months. On the basis of these data, an analysis was done to calculate the average deformation point through thermal analysis. Finally, the representative measurement point was proposed as the position at which the average deformation point converges regardless of weather or seasons. The authors believe that the method described herein is advantageous in that it could be used in a high-accuracy temperature-monitoring system and for predicting thermal deformation and buckling.