Comprehensive review on mechanism analysis and numerical simulation of municipal solid waste incineration process based on mechanical grate

Abstract

Determining the status of the municipal solid waste incineration (MSWI) process due to the composition variations of MSW, operational differences of the MSWI plants, and maintenance uncertainties of the incineration devices is difficult. Moreover, the optimal control algorithms developed off-line lack the support of the incineration mechanism. These conditions complicate the cost-effective operation of the MSWI plants. The development of customized numerical simulation models can simulate the incineration effects and obtain the extreme value of key process parameters to support its operational optimal control. This article aims to review the mechanical characteristics and numerical simulation methods of the MSWI process based on mechanical grates, thus providing support for the construction of a customized numerical simulation model and the realization of a digital twin system for the actual MSWI process. First, the mechanical characteristic of the MSWI process is comprehensively analyzed. Then, the numerical simulation method based on commercial and self-developed software is summarized and compared. Furthermore, the difficulties in creating customized numerical simulations and constructing digital twin models are discussed. Finally, the conclusion and research directions are established on the basis of the concluding ideas and specific commentaries. Results show that coupling several types of software can facilitate the creation of customized simulations based on actual process data. The development of an intelligent digital twin encounters several difficulties that must be highlighted because the combination of the numerical simulation model of the entire process can analyze the mechanism and the realization of matching the model with actual process data. The current study revealed that the digital twin model based on mechanical characteristics and numerical simulations by using actual process data and artificial intelligence technology could play a significant role in the safety and operation optimization of the MSWI process.