The minimum heat consumption for heat-driven binary separation processes with linear phenomenological heat transfer law

The optimal performance of heat-driven binary separation processes with linear phenomenological heat transfer law (q∝Δ(T ⁻¹)) is analyzed by taking the processes as heat engines which work between high- and low-temperature reservoirs and produce enthalpy and energy flows out of the system, and the temperatures of the heat reservoirs are assumed to be time- and space-variables. A numerical method is employed to solve convex optimization problem and Lagrangian function is employed to solve the average optimal control problem. The dimensionless entropy production rate coefficient and dimensionless enthalpy flow rate coefficient are adopted to indicate the major influence factors on the performance of the separation process, such as the properties of different materials and various separation requirements for the separation process. The dimensionless minimum average entropy production rate and dimensionless minimum average heat consumption of the heat-driven binary separation processes are obtained. The obtained results are compared with those obtained with the Newtonian heat transfer law (q∝Δ(T)). Supported by the Program for New Century Excellent Talents of China (Grant No. NCET-04-1006) and the Foundation for the Author of National Excellent Doctoral Dissertation of China (Grant No. 200136)