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<strong>Relationships between fault friction, slip time, and physical parameters explored by experiment-based friction model: A Machine Learning Approach Using Recurrent Neural Networks (RNNs)</strong>

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DataCite Commons2023-06-09 更新2024-08-18 收录
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The dataset encompasses information pertaining to the physical parameters of the experimental fault slip surface during High Velocity Rotary Shear (HVR) tests. These experiments were conducted on diorite specimens at a consistent slip velocity of 0.004 m/s under a range of normal stress conditions, specifically between 0.3 and 5.8 MPa.

本数据集收录高速旋转剪切(High Velocity Rotary Shear, HVR)试验中实验断层滑动面的物理参数相关信息。本次试验以0.004 m/s的恒定滑动速率,在0.3 MPa至5.8 MPa的法向应力区间内,对闪长岩试样进行了测试。

提供机构:
figshare
创建时间:
2023-06-06
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<strong>Relationships between fault friction, slip time, and physical parameters explored by experiment-based friction model: A Machine Learning Approach Using Recurrent Neural Networks (RNNs)</strong> 数据集图片
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