Nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is well known for engine optimization problem. Artificial neural networks(ANNs) followed by multi-objective optimization including a NSGA-Ⅱ and strength pareto evolu...Nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is well known for engine optimization problem. Artificial neural networks(ANNs) followed by multi-objective optimization including a NSGA-Ⅱ and strength pareto evolutionary algorithm(SPEA2) were used to optimize the operating parameters of a compression ignition(CI) heavy-duty diesel engine. First, a multi-layer perception(MLP) network was used for the ANN modeling and the back propagation algorithm was utilized as training algorithm. Then, two different multi-objective evolutionary algorithms were implemented to determine the optimal engine parameters. The objective of the present study is to decide which algorithm is preferable in terms of performance in engine emission and fuel consumption optimization problem.展开更多
Heat transfer of an SI engine's piston is calculated by employing three different methods based on resistor-capacitor model with the help of MATLAB code, and then the piston is thermo-mechanically analyzed using c...Heat transfer of an SI engine's piston is calculated by employing three different methods based on resistor-capacitor model with the help of MATLAB code, and then the piston is thermo-mechanically analyzed using commercial ANSYS code. The results of three methods are compared to study their effects on the piston thermal behavior. It is shown that resistor-capacitor model with less number of equations and consequently less solution time, is an appropriate method for solving problems of engine piston heat transfer. In the second part, the thermal stresses due to non-uniform temperature distribution, and mechanical stresses due to mechanical loads are calculated. Finally, the temperature distributions as a thermal load along with mechanical loads are applied to the piston to determine the total stress distribution and critical fracture zones. It is found that the amount of thermal stresses is considerable.展开更多
文摘Nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is well known for engine optimization problem. Artificial neural networks(ANNs) followed by multi-objective optimization including a NSGA-Ⅱ and strength pareto evolutionary algorithm(SPEA2) were used to optimize the operating parameters of a compression ignition(CI) heavy-duty diesel engine. First, a multi-layer perception(MLP) network was used for the ANN modeling and the back propagation algorithm was utilized as training algorithm. Then, two different multi-objective evolutionary algorithms were implemented to determine the optimal engine parameters. The objective of the present study is to decide which algorithm is preferable in terms of performance in engine emission and fuel consumption optimization problem.
文摘Heat transfer of an SI engine's piston is calculated by employing three different methods based on resistor-capacitor model with the help of MATLAB code, and then the piston is thermo-mechanically analyzed using commercial ANSYS code. The results of three methods are compared to study their effects on the piston thermal behavior. It is shown that resistor-capacitor model with less number of equations and consequently less solution time, is an appropriate method for solving problems of engine piston heat transfer. In the second part, the thermal stresses due to non-uniform temperature distribution, and mechanical stresses due to mechanical loads are calculated. Finally, the temperature distributions as a thermal load along with mechanical loads are applied to the piston to determine the total stress distribution and critical fracture zones. It is found that the amount of thermal stresses is considerable.
