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Inverse and predictive modeling of seepage into underground openings

机译:地下洞口渗流的逆向和预测模型

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We discuss the development and calibration of a model for predicting seepage into underground openings. Seepage is a key factor affecting the performance of the potential nuclear-waste repository at Yucca Mountain, Nevada. Three-dimensional numerical models were developed to simulate field tests in which water was released from boreholes above excavated niches. Data from air-injection tests were geostatistically analyzed to infer the heterogeneous structure of the fracture permeability field. The heterogeneous continuum model was then calibrated against the measured amount of water that seeped into the opening. This approach resulted in the estimation of model-related, seepage-specific parameters on the scale of interest. The ability of the calibrated model to predict seepage was examined by comparing calculated with measured seepage rates from additional experiments conducted in different portions of the fracture network. We conclude that an effective capillary strength parameter is suitable to characterize seepage-related features and processes for use in a prediction model of average seepage into potential waste-emplacement drifts.
机译:我们讨论了用于预测地下洞口渗漏的模型的开发和校准。渗漏是影响内华达州尤卡山潜在核废料处置库性能的关键因素。开发了三维数值模型来模拟现场测试,在该测试中,水从挖掘的壁ni上方的钻孔中释放出来。对来自注气测试的数据进行了地统计分析,以推断裂缝渗透率场的非均质结构。然后针对渗入开口的水量对非均质连续体模型进行校准。这种方法导致在感兴趣的规模上估计与模型有关的,与渗流有关的参数。通过比较在裂缝网络不同部分进行的附加实验计算出的渗流率与测得的渗流率,来检验校准模型预测渗流的能力。我们得出结论,有效的毛细管强度参数适用于表征与渗流相关的特征和过程,以用于将平均渗流预测为潜在废物放置漂移的预测模型。

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