چكيده به لاتين
In this study, the performance and application of MSW subsidence models were evaluated based on field data analysis for two cells made in Landfill, Kahrizak: (1) a normal cell with a height of about 5.3 m after the immediate settlement, and ( 2) A bioreactor cell with a height of about 2.5 meters after the immediate settlement. Data from these cells were collected continuously over a period of about 3 years (time-dependent session). To estimate the initial thickness of the cells, a multilayer analysis of the instantaneous settlement was performed for both cells, and then the efficiency of the sedimentation models was evaluated by summing the instantaneous and time-dependent aggregation. Simulation of normal cells and bioreactors with all sedimentation models was performed by the least square’s optimization method. The results showed in general that experimental models are of limited physical importance because they do not represent the actual behavior of MSW waste and their model parameters are of limited physical importance, as well as because accurate and complete measured data are needed to determine model parameters. MSW session modeling is not highly recommended. Models that combine mechanical and biological creep with a single mathematical function are formulated to bind time-dependent subsidence to a single process with a finite magnitude, which limits their application. The Machado and Chen models were the most accurate models for predicting both long-term and short-term meeting sessions, and provide the best performance in terms of the continuity of the predicted session. Especially the Machado model, which predicted 11-year-old sessions with an error of several centimeters, although there is a slight error in the short-term predictions of this model. The Marques, Gibson, and Babu models all had almost the same accuracy in predicting long-term waste settling in this study. Finally, for hot and dry areas such as Landfill, you can use the Machado model in combination with the instantaneous session and the Chen model, which show both time-dependent sessions as a downward display, and to reduce the error of the results averaged.
