Investigation On Steady Temperature Field Of Piston In Marine Diesel Engine

The thermal loads on pistons may lead to hot crack, scuffing of cylinder bore and piston ring cementation,etc,which restricts the improvement of diesel engines. Steady temperature field of piston is initial data for the calculation of thermal loads, which need to be calculated and analyzed in order to supply reference for the decrease of thermal loads. The improvement of old models and design of new models need to consider the parameters which may impact the temperature field. The exploration of the influence rules of these parameters is important for the promotion of piston.On the basis of empirical formula this paper use optimal design combined with reverse method to obtain the applicable boundary conditions to 620 diesel piston steady temperature field. Optimal design combined with reverse method is likely to break the restriction of locations and convergence fast,which applies to ascertain the heat transfer coefficient for piston surface with known measuring point temperature.Set reasonable finite element model in order to simulate the steady temperature field for piston, the error of result which is calculated by optimal design combined with reverse is less than 2% compared to the experiment value. This method provides new ideas for solving piston steady temperature field efficiently.Influence factors of feature point temperature in steady temperature field of pistons are studied in order to find the effect of different parameters on the temperature field of the piston.First the thesis analyses the influence of 45 different parameters including medium temperature parameter, the coefficient of heat transfer parameters and structure parameter to the temperature field by a single variable. Second, calculate the quantitative percentage of key parameters to the influence of feature points temperature,and relative coefficients of primary and secondary factor which is under the condition of no interaction and interaction between related parameters and feature point temperature. Finally, establish each feature point temperature regression model using partial least squares method which make the correlation parameters of each feature point temperature as independent variables and each feature point temperature value as the response variable. The result of comparing the predicted value of the regression model and the calculated value of simulation proves that the model has a predictive ability.This study provides the basis for reducing heat load, matching design parameters and arranging the measuring point and also provides a reference for other similar aspects of the changes...