Study On Mass Integration For Waste Minimization

The increasing environment and resource problems have menaced the surviving of human being and the development of society. As one of the best strategies and technology means of sustainable development (SD), cleaner production (CP) has gained much attention in both the academic and industrial circles. However, how to realize CP still hasn't been settled well. From the view of process systems engineering (PSE), mass integration, which is the important supporting and realizing technology of CP, has been studied for the target of waste minimization (WM) in this dissertation. The main research work is as follows. The principle of integrative utilization of mass is proposed for the first time on the basis of foundation theory of chemical process. The framework of waste minimization for the process industry is built. The quantitative methods of WM, synthesis of mass exchange networks and mass integration, are studied. Furthermore, the superstructure mathematical model is established. Finally, the adaptive simulated annealing genetic algorithms (ASAGA) are proposed aiming at solving the mixed integer non-linear programming (MINLP) problem of process synthesis, which is proven to be an effective tool to obtain the optimal operating project of waste minimization. Detailed studies concerning these methods in this dissertation include:1. The existing researches focus on the study of strategy and qualitative methods, while cognition to the essence and evolution of process waste are often ignored, which make it difficult to determine the practical project of WM. Here, the principles of integrative utilization of material are proposed for the first time after extraction of evolution of material and generation of waste. Based on the idea of closed loop recycle, the framework of process waste minimization is built, combining qualitative methods with quantitative method. The economics of waste minimization is analyzed, which proves its advantage and difference from the traditional technology. Practically, the principles of integrative utilization of mass and energy are applied to the retrofit of quench system in the ethylene industry. The strong direction of proposed framework to the engineering practice is proved by the simulated results.2. The synthesis of mass exchange network (MEN) is an effective approach for WM. Little study on MEN has been reported in domestic although many considerable advances are take in abroad. In this dissertation, synthesis of MEN is firstly studied systematically and extentively for the first time in domestic for the sake of promoting the research of CP technology. The studying contents and researching progresses in the literature are reviewed. Here, we summarize several important visualized tools. The combinedIIIprocedure of targeting approach and mathematical programming method are discussed based on the researching methods of MEN reported in literatures.3. The nonlinear process synthesis problem involving structure optimization, i.e. selection of flow direction and unit equipment, and relative parameter determination can be formulated to a MINLP model naturally. Aiming at the process flowsheet synthesis problems, the strategies and solutions of solving the MINLP model of superstructure are analyzed in this dissertation. The mathematical model of superstructure of mass integration is established on the basis of mathematical models of process operations of single selection, interception, allocation and recycle according to the combined procedure of targeting approach and mathematical programming method. The waste treatment methods such as end-of-pipe technology, in-plant technology and mass integration are discussed and the advantage of mass integration is pointed out.4. Usually, process synthesis can be expressed as a complex combinatorial optimizing problem with non-convex, nonlinear, multi-peaks and discontinuous features. The traditional optimizing methods often fail to achieve a satisfactory result for solving such large scale MINLP problems. As the stoch...