Automated process and geometry design optimization of a coal combustion reactor.

摘要

The importance of design of an optimized and efficient combustion or gasification system, the complexity of such an optimization problem with conflicting objectives and the inadequacy of traditional optimization methods in searching the entire design space and their random nature, presents the significant importance of proposing an automated multi-objective optimization method in the field of combustion and gasification design. In the current research, automated multi-objective optimization has been implemented in geometry and process design of a coal combustion reactor. Coal particles are mixed with air and are injected into the reactor via four tangential inlets to create swirl flow. A combination of single phase and multi-phase reactions has been considered to simulate the combustion process. All the steps of geometry creation, grid generation and CFD simulation have been integrated automatically using macro files to run in batch mode in an optimization platform, i.e., modeFrontier. Three multi-objective optimization problems have been solved with two, four and six input variables. The epsilon-constraint method has been implemented for multi-objective optimization. Each multi-objective optimization problem consists of individual single-objective optimization problems which are solved by the SIMPLEX method. Two conflicting objectives, i.e., NO mass fraction and CH4 mass fraction, have been selected for all optimization problems. Results from all single objective optimizations have been summarized to obtain the Pareto Set. It is presented that automated multi-objective optimization is a reliable and promising method to integrate CAD and CFD tools with optimization methods in an automated process to perform faster, more accurate, more efficient and more cost-effective designs in the field of combustion and gasification.