مجله تحقیق و توسعه مواد پرانرژی
سال نهم شماره 3 (پیاپی 20، پاییز 1392)

In a motor with a liquid hydrocarbon fuel، the hydrocarbon fuel diffuses into the amine fuel and the fuel concentration changes with time. Therefore، the variation of amine fuel at each time should be predicted to ensure the safe start of the motor and the fuel storage should be recharged if the amine fuel concentration is out of specific range. In this work، the amount of hydrocarbon fuel diffusion in the amine fuel and the variation of the amine fuel concentration at different times was obtained numerically and compared with experimental data. For this reason، the corresponding diffusion coefficient was obtained firstly. The results showed that the diffusion coefficient of 9. 4*10-6cm2/s with an absolute average deviation of 0. 037 has a good conformity with experimental data at 20°C. To investigate the effect of ambient temperature on the diffusion phenomenon، a correlation was proposed to predict the variation of diffusion coefficient with temperature. The predicted concentration with this predicted diffusion coefficient showed a good agreement with experimental data. Ultimately، a correlation was proposed to predict the amine fuel concentration versus a dimensionless parameter ofz/√Dt. The prediction showed a good agreement with empirical data.

In this work tow simple approaches have been introduced to predict heat of explosion of high energetic materials. experimental heat of explosion of 74 energetic compound were collected from articles and this dataset was separated randomly into two groups، training and prediction sets، respectively، which were used for generation and evaluation of suitable models. Multiple linear regression (MLR) analysis was employed to select the best subset of descriptors and to build linear models; while nonlinear models were developed by means of artificial neural network (ANN). The obtained models with four descriptors involved show good predictive power for the test set: a squared correlation coefficient (R2) of 0. 798 and a standard error of estimation (s) of 606. 48 were achieved by the MLR model; while by the ANN model، R2 and SE were 0. 98 and 189. 4، respectively. Based on the large R2 -value and small SE values، significantly for ANN model، one can deduce that the predicted results are in good agreement with the measured values. Calculated heats of explosion are also compared with corresponding two famous cods، namely EDPHT and LOTUSE. It can be seen that the performance of the present models is better than these cods