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A platform for research: civil engineering, architecture and urbanism
Applying Rock Engineering Systems to Evaluate Shaft Resistance of a Pile Embedded in Rock
Abstract The shaft resistance of a pile ($ τ_{fm} $) embedded in rock is one of the important parameters utilized in civil engineering. Although in–situ techniques are the best methods to determine $ τ_{fm} $, they are expensive and time–consuming. Furthermore, accurate estimation of the $ τ_{fm} $ is not an easy task and relatively little research has been done in this area. To overcome these problems, in this paper, based on the basic concepts of a rock engineering systems (RES) approach, a new model for the estimation of the $ τ_{fm} $ and the risk associated is presented. The newly suggested model involves 7 effective parameters on $ τ_{fm} $ (rock type, uniaxial compressive strength of the intact rock, rock mass quality, thickness and density of the presence of soils above the rock, thickness and density of the rock), while retaining simplicity as well. To establish the model, a database from the literature was used. A comparison was also carried out between the performance of the RES-based predictive model and multiple regression models. The RES-based model demonstrated a better performance considering its greater determination coefficient (R2) and smaller mean square error compared to the other models.
Applying Rock Engineering Systems to Evaluate Shaft Resistance of a Pile Embedded in Rock
Abstract The shaft resistance of a pile ($ τ_{fm} $) embedded in rock is one of the important parameters utilized in civil engineering. Although in–situ techniques are the best methods to determine $ τ_{fm} $, they are expensive and time–consuming. Furthermore, accurate estimation of the $ τ_{fm} $ is not an easy task and relatively little research has been done in this area. To overcome these problems, in this paper, based on the basic concepts of a rock engineering systems (RES) approach, a new model for the estimation of the $ τ_{fm} $ and the risk associated is presented. The newly suggested model involves 7 effective parameters on $ τ_{fm} $ (rock type, uniaxial compressive strength of the intact rock, rock mass quality, thickness and density of the presence of soils above the rock, thickness and density of the rock), while retaining simplicity as well. To establish the model, a database from the literature was used. A comparison was also carried out between the performance of the RES-based predictive model and multiple regression models. The RES-based model demonstrated a better performance considering its greater determination coefficient (R2) and smaller mean square error compared to the other models.
Applying Rock Engineering Systems to Evaluate Shaft Resistance of a Pile Embedded in Rock
Fattahi, Hadi (author)
2018
Article (Journal)
English
Applying Rock Engineering Systems to Evaluate Shaft Resistance of a Pile Embedded in Rock
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