Process Synthesis For Leaching Process Of Hydrometallurgy

Leaching as one of the most important process in hydrometallurgy, its designation is mainly determined by the designers who based on the ore washability experiment, referring to the existing process flow and combining with his own design experience. Usually the designers do not attempt to establish the mathematical model for further optimization design. For the existing industrial production, they use operation optimization method to improve the efficiency, but there are still a large room to improve. In recent years, the process synthesis technology has achieved successful application in process industry, on that account, this article uses process synthesis technology, considering the equipment selection and operation parameters of the leaching process, taking maximizing the economic benefits of the leaching process as the goal, to optimize the leaching process design.Firstly, acquainted with the leaching process and the equipment used, analyzed the various factors that influencing the leaching efficiency, determined the leaching process synthesis optimization decision variables. Secondly, considering the pseudo homogeneous model is more suitable for the current technology, we combined material balance equations and chemical reaction rate equations for mathematical modeling of leaching equipment. Thirdly, established leaching process super structure, and analyzed the process constraint. Finally, take economic efficiency as the objective function and established the leaching process synthesis model of integrated leaching system.Leaching process synthesis optimization model can be thought of an inner layer of the nonlinear programming problem (NLP) and an outer layer of the combination optimization problems. On this basis, this thesis proposed a nesting algorithm to solve this optimization model. The algorithm first use tabu search algorithm to explore the outer layer of the MINLP problem, when the MINLP model is converted to a nonlinear problem (NLP), use the genetic algorithm to solve the nonlinear problem (NLP).Finally, simulated the theory and verified the effectiveness of the method.