This paper discussed an extended model for flexibility analysis of chemical process. Under uncertainty, probability density function is used to describe uncertain parameters instead of hyper-rectangle, and chanceconst...This paper discussed an extended model for flexibility analysis of chemical process. Under uncertainty, probability density function is used to describe uncertain parameters instead of hyper-rectangle, and chanceconstrained programming is a feasible way to deal with the violation of constraints. Because the feasible region of control variables would change along with uncertain parameters, its smallest acceptable size threshold is presented to ensure the controllability condition. By synthesizing the considerations mentioned above, a modified model can describe the flexibility analysis problem more exactly. Then a hybrid algorithm, which integrates stochastic simulation and genetic algorithm, is applied to solve this model and maximize the flexibility region. Both numerical and chemical process examples are presented to demonstrate the effectiveness of the method.展开更多
This paper falls into two parts. In the first part, the widely used analytical-empirical method of pavement design and evaluation is discussed and in the second part two simulation models are presented to predict the ...This paper falls into two parts. In the first part, the widely used analytical-empirical method of pavement design and evaluation is discussed and in the second part two simulation models are presented to predict the design of flexible pavement. Analytical results are compared with simulation models.展开更多
文摘This paper discussed an extended model for flexibility analysis of chemical process. Under uncertainty, probability density function is used to describe uncertain parameters instead of hyper-rectangle, and chanceconstrained programming is a feasible way to deal with the violation of constraints. Because the feasible region of control variables would change along with uncertain parameters, its smallest acceptable size threshold is presented to ensure the controllability condition. By synthesizing the considerations mentioned above, a modified model can describe the flexibility analysis problem more exactly. Then a hybrid algorithm, which integrates stochastic simulation and genetic algorithm, is applied to solve this model and maximize the flexibility region. Both numerical and chemical process examples are presented to demonstrate the effectiveness of the method.
文摘This paper falls into two parts. In the first part, the widely used analytical-empirical method of pavement design and evaluation is discussed and in the second part two simulation models are presented to predict the design of flexible pavement. Analytical results are compared with simulation models.
