Effect of spatial variation of spoil material properties on slope displacements under rapid drawndown of pit lakes
In many European countries, lignite or brown coal is used as a fuel source in steam-electric power generation. Upon completion of mining activities, a reclamation plan is imperative to ensure environmental and social prosperity of local areas. Abandoned mine pits are often reclaimed by creating a pi...
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Veröffentlicht in: | Górnictwo Odkrywkowe 2022-10, Vol.LXIII (4), p.33-39 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In many European countries, lignite or brown coal is used as a fuel source in steam-electric power generation. Upon completion of mining activities, a reclamation plan is imperative to ensure environmental and social prosperity of local areas. Abandoned mine pits are often reclaimed by creating a pit lake. Reclamation of large lignite open pit mine sites may use large amounts of previous overburden materials or “spoils” to create the slopes of the pit lake. Spoils are anthropogenic materials with large spatial variation in properties, hence, considering mean values of shear strength and hydraulic parameters to assess stability and seasonal displacements will not fully simulate actual field conditions. This paper considers the effect of spatial variation on slope stability and ground movements during rapid drawdown events (a critical case) using coupled flow-deformation 2D finite element analyses, incorporating unsaturated soil suctions above the phreatic surface. Effects of heterogeneity and randomness of spoils on the response of the slope are considered through random field modelling and the Monte-Carlo simulation technique. Four lognormally distributed random variables (spoil cohesion, friction angle, void ratio, and permeability coefficient) are examined. The effect of spatial variability of spoils is shown to be important; a significant number of the random field analyses resulted in larger displacements compared to a benchmark deterministic analysis adopting uniform mean parameter values. |
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ISSN: | 0043-2075 |
DOI: | 10.5604/01.3001.0053.8057 |