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Published on: October 21, 2016
Enhancing an existing composite model to estimate MSW settlement during the filling and post-closure phases in both
Wameed Alghazali1, Paul J Van Geel1, Shawn Kenny1
1Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, K1S 5B6, Canada.
Abstract:
The settlement of municipal solid waste (MSW) is a critical factor in estimating landfill airspace capacity before final cover placement. While numerical modelling has improved MSW settlement predictions, such methods often require significant computational resources and specialized expertise, making them less practical for field applications. Existing closed-form expressions also fail to adequately capture MSW's increasing resistance to compressibility under higher stress levels (e.g., successive MSW lift placements) and the delay in biodegradation-induced settlement under freezing temperatures. This study enhances an existing composite settlement model to address these limitations. The improved model refines the mechanical creep component by modifying the creep coefficient to incorporate the effects of increased compressibility resistance under higher overburden stress. To better represent biodegradation-induced settlement, a delay time parameter was introduced. This parameter was derived by first generating a series of degree of degradation (DOD) curves using a validated thermal-mechanical-biological (TMB) model. These curves, which characterize biodegradation progression under different temperature conditions, were then fitted using a first-order decay equation that incorporates the newly introduced delay time. By integrating this parameter, the enhanced model accounts for the lag in biodegradation-induced settlement when MSW temperatures are not favourable for microbial activity. The model was validated by comparing its predicted settlement with recorded field data from the Ste. Sophie Landfill. Its effectiveness was further demonstrated by comparing the enhanced model's predictions to those of the original model, showing substantial improvements in accuracy.
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