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首页> 外文期刊>International Journal of Rock Mechanics and Mining Sciences >Rockburst assessment in deep geotechnical conditions using true-triaxial tests and data-driven approaches
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Rockburst assessment in deep geotechnical conditions using true-triaxial tests and data-driven approaches

机译：使用真正的三轴测试和数据驱动方法在深层岩土内条件下的摇滚乐评估

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Deep underground excavations in mining and civil engineering are subjected to high in-situ stresses which can cause rockburst. Rockburst is an instantaneous release of a large amount of strain energy stored in rockmass that can lead to injuries, deaths, and damage to infrastructures. Many studies have been done regarding rockburst, however, there is no practical model to predict the stress level that rockburst occurs (i.e. maximum rockburst stress) and its related risk (i.e. rockburst risk index) based on real rockburst tests, and the main rock mechanical properties. In this study, a comprehensive database of true-triaxial unloading tests on rocks having a wide range of properties was compiled. The agglomerative hierarchical clustering (AHC) analysis was carried out on the original database to evaluate the presence of natural groups and outliers. Then, the stepwise selection and elimination (SSE) procedure were employed for dimension reduction of the problem and identifying the most influential attributes on rockburst parameters. Afterward, two robust non-linear algorithms, including gene expression programming (GEP) and classification and regression tree (CART) were used to develop the predictive models for rockburst maximum stress and its risk index. The validation verification of the proposed models using several indices proved the high prediction performance of the developed non-linear models. Finally, a parametric analysis was carried out to evaluate the influence of each input parameter on the corresponding output. The proposed models in this study are practical and do not require any presupposition about rockburst mechanism, which makes them be used easily in practice by engineers at the design and progress stages of the underground projects.
机译：采矿和土木工程中的深层地下挖掘经受高地应力，这可能导致摇滚乐。 Rockburst是一种瞬间释放储存在岩石的大量应变能量，可能导致基础设施的伤害，死亡和损坏。许多研究已经完成岩爆，然而，没有实际模型可以预测岩爆发生的压力水平（即最大摇滚压力）及其基于真正的岩石测试的相关风险（即摇滚风险指数），以及主要岩石机械特性。在这项研究中，编制了一个综合的真正的Trizial卸载测试数据库，在具有各种属性的岩石上进行了编制。在原始数据库上进行了附聚层次聚类（AHC）分析，以评估天然组和异常值的存在。然后，采用逐步选择和消除（SSE）程序进行问题的维度降低，并识别岩爆参数上最具影响力的属性。之后，使用两个稳健的非线性算法，包括基因表达编程（GEP）和分类和回归树（推车）来开发岩石最大应力的预测模型及其风险指数。使用多个指标的建议模型的验证验证证明了开发的非线性模型的高预测性能。最后，执行参数分析以评估每个输入参数对相应输出的影响。本研究中的拟议模型实用，不需要任何关于摇滚乐机制的预设，这使得它们通过工程师在地下项目的设计和进展阶段进行实践中可以轻松使用。

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