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DFNCleaner: A novel automated approach to improve DFN integration for geomechanical analysis

机译:DFnCleaner:一种新的自动化方法,提高地磁分析的DFN集成

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The challenges of integrating a discrete fracture network (DFN) model with a geomechanical analysis increase with the complexity of the DFN model, since a DFN model can include thousands of fractures and result in very complex configurations. Although it is now relatively easy to generate DFN models, to date, comparatively limited attention has been given to the solution of the challenging issues related to optimal mesh generation routines required for geomechanical simulation. For any integrated DFNGeomechanical approach to be efficient and reliable, there is a need to carefully consider the way in which the structural data are embedded in the geomechanical model at the required engineering scale. In this context, this paper introduces a novel method (DFNCleaner), to simplify fracture networks, while maintaining their characteristic properties. We also present, an automated tool (DFNQuality) that incorporates various metrics to measure the DFN quality, and outputs a proposed “Meshability Index”, which is then used to further constrain the cleaning of the original DFN model. This paper shows example of the ability of the proposed algorithm to clean pillar DFN model, and then compares the simulation results to those obtained manually by both intermediate and experienced users of hybrid Finite-Discrete Element method codes.
机译:积分的离散裂缝网络(DFN)模型与和所述DFN模型的复杂地质力学分析增加,由于DFN模型的挑战可以包括成千上万的骨折和导致非常复杂的配置。虽然现在是比较容易产生DFN模型,迄今为止,相对有限的关注已考虑到相关的地质力学模拟所需的最佳网格生成程序的具有挑战性的问题的解决方案。对于任何集成DFNGeomechanical方法是有效的,可靠的,有必要仔细考虑这样的结构数据被嵌入在所需的规模工程地质力学模型的方式。在这方面,本文介绍了一种新颖的方法(DFNCleaner),为了简化的裂缝网络,同时保持它们的特性的属性。我们还提出,一个自动化的工具(DFNQuality)并入各种度量来测量DFN质量,并输出建议“Meshability指数”,然后将其用于进一步约束原DFN模型的清洗。本文示出了所提出的算法在清洁支柱DFN模型,然后将能力例子的模拟结果,以通过的混合有限离散元方法的代码两个中间和经验的用户手动获得的那些进行比较。

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