## 1 Introduction  
Tailings dam facilities are used to store tailings and other industrial waste discharged from a mine after ore separation [1; 2]. Uranium tailings ponds are an important component of uranium mine safety production due to their large capacity, high potential energy, and long storage time [3]. Currently, approximately 1 billion cubic meters of uranium tailings are produced worldwide [4; 5]. A breach in a uranium tailings impoundent could result in severe environmental pollution and significant harm to downstream residents. Seismic activity is the primary cause of tailings pond failures [6; 7]. Earthquakes can cause the liquefaction of tailings sands, weakening the strength of tailings materials and leading to static deformation of the dam. This can result in residual deformation in the dam structure, causing damage and reducing its overall stability [8; 9]. Therefore, studying the dynamic response characteristics under seismic loading is of great practical significance. [PERSON], [PERSON], and [PERSON] [10; 11; 12] conducted shaking table tests to analyze the acceleration, pore pressure, and displacement of the dam body under seismic waves of varying peak ground accelerations. Their findings revealed that the acceleration peaks of the dam body exhibited distinct spatial effects. Moreover, they observed that the PGA amplification coefficients measured on the slope surface consistently surpassed those in the slope. Notably, they discovered that the dynamic amplification effect on the high side slopes correlated significantly with the slope's intrinsic frequency. However, laboratory experiments are typically on a small scale, and although shake table tests have their advantages, they also have clear limitations. Model material parameters play a crucial role in numerical simulations, significantly impacting the authenticity, accuracy, and reliability of results [13; 14]. Traditional trial-and-error methods for calibrating rock mechanical parameters are both complex and time-consuming. In contrast, using finite element analysis and machine learning offers an efficient way to accurately predict these parameters [15]. The Weibull distribution can describe the heterogeneity of rock hydraulics, providing a method for parameter distribution in heterogeneous rocks [16]. The dynamic response of the dam under earthquake was simulated using finite element software, and the seismic dynamic response of the dam was analyzed in terms of acceleration, stress, displacement, liquefied area, and stability [17; 18]. The vertical dynamic response of a slope is less influenced by elevation, while the horizontal dynamic response has an obvious elevation amplification effect and topographic effect. The ground vibration amplification effect is related to the mechanical strength of the structural surface, as well as the waveform and spectral characteristics of the seismic waves [19]. [PERSON] et al. [20] conducted model testing and numerical calculations using the finite element method to observe the gradual increase in the horizontal and vertical displacements of the monitoring points on the dam body with an increase in input peak acceleration. However, the acceleration amplification coefficient showed a decreasing trend. The collapse of the tailings dam did not exhibit clear evidence of a sliding surface as the input peak acceleration increased. Instead, the collapse mode presented as uniform sliding across the entire structure. Using the OpenSees software v.3.5.0, [PERSON], [PERSON] [21] conducted an analysis on five distinct seismic motions. The study compared different boundary conditions in terms of displacement flow vectors, pore pressures, and stress-strain curves during the shaking period. The findings revealed that the viscous boundary conditions provided a more accurate representation of the actual field conditions in comparison to the fixed boundary conditions. [PERSON] et al.