Abstract
The solid waste treatment in rotary kiln produces the problem of pollution emissions. The high reaction temperature and the complex product of combustion make it difficult to detect the pollution concentration variation in the rotary kiln. Thus, rotary kiln model is developed for the solid waste treatment. The fluid flow and emission characteristics of combustion in rotary kiln are analyzed by multi-physics field finite element method. The digital twin model for solid waste treatment in rotary kiln is developed by the numerical simulation and machine learning. The digital twin model accurately predicts the flue gas components (CO, CO2, H2O) concentration fields and provides data support for the operation parameter optimization of rotary kiln. It shows the prediction error of the digital twin platform for the 40t/d-60t/d industry rotary kiln is less than 5 %. The digital twin platform provides an alternative way to effectively control the pollution emission for the rotary kiln.
| Original language | English |
|---|---|
| Article number | 125931 |
| Journal | Applied Thermal Engineering |
| Volume | 268 |
| DOIs | |
| State | Published - 1 Jun 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 12 Responsible Consumption and Production
Keywords
- Digital twin
- Machine learning
- Rotary kiln
- Simulation
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