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首页> 外文期刊>Bulletin of engineering geology and the environment >A new approach for estimation of the rock mass deformation modulus: a rock engineering systems-based model
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A new approach for estimation of the rock mass deformation modulus: a rock engineering systems-based model

机译:一种估算岩体变形模量的新方法:基于岩石工程系统的模型

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AbstractThe deformation modulus of a rock mass is one of the crucial parameters used in the design of surface and underground rock engineering structures. Due to the problems in determining the deformability of jointed rock masses at the laboratory scale, various in-situ test methods have been developed. Although these methods are currently the best techniques, they are expensive and time-consuming, and present operational problems. To overcome this difficulty, in this paper, based on the basic concepts of a rock engineering systems (RES) approach, a new model for the prediction of the deformation modulus of a rock mass is presented. The newly proposed approach involves seven effective parameters (depth, rock quality designation, uniaxial compressive strength, the discontinuity density, the condition of discontinuities, the groundwater condition, and an adjustment for the orientation of discontinuities) pertinent to the deformation modulus of a rock mass, yet keeping simplicity as well. The performance of the RES model is compared with multiple regression models. The estimation abilities offered using RES and multiple regression models were presented by using field data obtained from road and railway construction sites in Korea. The results achieved indicate that the RES-based model predictor with the least mean square error and a higher coefficient of determination (R2) performs better than the multiple regression models.
机译: Abstract 岩体的变形模量是用于岩体的关键参数之一地下和地下岩石工程结构的设计。由于在实验室规模上确定节理岩体的可变形性方面的问题,已经开发了各种原位测试方法。尽管这些方法目前是最好的技术,但它们昂贵且费时,并且存在操作问题。为了克服这一困难,本文基于岩石工程系统(RES)方法的基本概念,提出了一种预测岩体变形模量的新模型。新提出的方法涉及与岩体变形模量有关的七个有效参数(深度,岩石质量指定,单轴抗压强度,间断密度,间断条件,地下水条件以及对间断方向的调整)。 ,同时保持简洁性。将RES模型的性能与多个回归模型进行比较。利用韩国道路和铁路建设现场获得的实地数据,展示了使用RES和多元回归模型提供的估算能力。取得的结果表明,基于RES的模型预测变量具有最小的均方差和较高的确定系数( R 2 ),其性能优于多元回归模型。

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