Chaire de Recherche sur la Valorisation des Matières Résiduelles (CRVMR), Department of Chemical Engineering, Polytechnique Montreal, Montreal, Canada.
Ville de Montréal, Montreal, Canada.
Waste Manag. 2022 May 1;144:533-542. doi: 10.1016/j.wasman.2022.04.025. Epub 2022 Apr 26.
Material recovery facilities (MFRs) play an important role in today's waste management systems to maximize recycling efficiency for several waste materials. These facilities face multiple challenges, often due to a poor understanding of the mechanisms occurring within the sorting equipment. Improving modeling techniques of these unit operations appear to be a promising opportunity to mitigates these challenges. Mechanical sorting efficiency of municipal solid waste is often predicted from simple transfer coefficients, which are obtained for a specific set of operating conditions of the sorting equipment and sorting sequence configuration. When these transfer coefficients are used in situations that are different to those in which they were obtained, poor predictions can be expected. To overcome these limitations, a new predictive tool, based on the integration of mechanistic models and transfer coefficients, is presented. Mechanistic models are developed only for the most influential unit operations in a MRF, in order to predict their sorting efficiency based on the physical phenomena occurring. Integration of these models with the use of transfer coefficients for the other unit operations allows the entire predictive tool to remain as simple as possible while providing high prediction accuracy and flexibility. The use of the tool is validated with a real case study of a material recovery facility. Results indicate a good prediction of the mass flows of the facility. Moreover, a new modeling technique is proposed for the representation of a ballistic separator based on the shape factor of the waste items.
物料回收设施（MFRs）在当今的废物管理系统中发挥着重要作用，可最大限度地提高多种废物的回收效率。这些设施面临着多种挑战，通常是由于对分选设备内发生的机制缺乏了解。改进这些单元操作的建模技术似乎是缓解这些挑战的一个有前途的机会。城市固体废物的机械分选效率通常根据简单的传递系数来预测，这些传递系数是针对特定的分选设备操作条件和分选序列配置获得的。当这些传递系数用于与获得它们的条件不同的情况下时，可能会出现预测不佳的情况。为了克服这些限制，提出了一种新的预测工具，该工具基于机械模型和传递系数的集成。机械模型仅为 MRF 中最具影响力的单元操作开发，以便根据发生的物理现象预测其分选效率。将这些模型与其他单元操作的传递系数结合使用，可以使整个预测工具保持尽可能简单，同时提供高精度和灵活性。该工具的使用通过对物料回收设施的实际案例研究进行了验证。结果表明，该设施的质量流得到了很好的预测。此外，还提出了一种基于废物物品形状因数的弹道分离器的新建模技术。
