用实验和概率方法评估填埋城市固体废物的空气分类效率评估.
Lin Feng Yu1, Yu Qi Jin1, Miao Xin Yuan2
1MOE Key Laboratory of Soft Soils and Geoenvironmental Engineering, Institute of Geotechnical Engineering, Zhejiang University, Hangzhou 310058, China.
Waste management (New York, N.Y.)
|May 14, 2025
概括
这项研究开发了一个模型,以优化填埋城市固体废物 (MSW) 的空气分类,通过对废物进行核算来改善资源回收.
科学领域:
- 废物管理 废物管理
- 环境工程 环境工程
- 计算流体动力学的流体动力学.
背景情况:
- 填埋城市固体废物 (MSW) 的空气分类对于资源回收至关重要.
- 挑战包括废物异质性和非球形粒子形状.
- 优化分离效率对于有效的废物管理至关重要.
研究的目的:
- 开发一个概率框架,整合球形模型和蒙特卡洛方法来预测和优化MSW空气分类效率.
- 为了统计地描述填埋的MSW样本的形态和密度.
- 将数值模型预测与实验结果进行比较.
主要方法:
- 填埋的381个和184个MSW样本的形态 (延长,平坦度,尺寸) 和密度分布的统计特征.
- 使用具有非球形阻力系数的球形粒子,通过随机抽样生成的数值模型的开发.
- 将球形模型与蒙特卡洛程序集成在一起,以预测分离效率.
主要成果:
- 数值模型在预测与实验数据相比的分离指标时,实现了 <0.13 的根平均平方误差 (RMSE).
- 填埋的MSW显示光分的回收率 (RL) 比新鲜的MSW低,这是由于有机物降解的密度增加.
- 分离效率 (E) 呈现出取决于速度的单调趋势,在15°空气流方向和21.40 m/s时确定了最佳性能.
结论:
- 开发的概率框架准确地预测了填埋的MSW空气分类效率.
- 确定了最佳的分离参数,为设备设计提供了洞察力.
- 这项研究为废物管理中的先进模拟研究提供了基础方法.
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