基于智能仿真的抽蓄电站侧式进/出水口数字孪生平台

    Digital twin platform for lateral inlet/outlet of pumped storage power station using intelligent simulation

    • 摘要: 传统数字孪生平台通常仅依托传感器实现对单点监测数据的采集,难以全面反映复杂流动特性,该研究搭建了一个结合数值仿真的五维侧式抽蓄电站进/出水口数字孪生平台,可实现对整个场的时空分布数据获取。平台由物理实体层、数字孪生层、连接层、数据层和服务层的五维体系构成,通过结合智能流体—固体仿真分析和复杂数据的实时渲染,实现在虚拟现实场景中分析进/出水口的流速分布和拦污栅的模态规律。平台集成了参数化建模、网格划分、流体仿真,统一编程接口实现流程化的数值计算,提高了计算效率。实时流场分析表明,进/出水口流动分离显著,在扩散段顶部出现回流区,导致主流集中在流道中下部。主流区和回流区的紊动强度极小,而位于主流核心区的上方和下方存在沿流向方向从扩散段起始处延伸至拦污栅断面的两处剪切区,与主流上方和下方存在小尺度涡流运动相对应,说明涡流分布与紊动强度密切相关。拦污栅结构的模态分析表明,拦污栅的第5阶模态(自振频率为66.52 Hz)振型呈现栅条、边梁和纵梁的复合弯曲振型并伴随栅条扭转,与涡脱落频率接近,存在流激振动破坏的风险。该平台解决了传统水力优化设计效率低和反馈滞后的问题,实现了侧式进/出水口和拦污栅的智能数值仿真。

       

      Abstract: Conventional digital twin platforms typically rely on the sensors to collect monitoring data at single points, thus making it difficult to capture the complex flow characteristics. In this study, a five-dimensional digital twin platform was established for the lateral inlet/outlet of a pumped storage power station. Numerical simulation was integrated to obtain the spatiotemporal distribution of the entire flow field. The platform was composed of five layers—physical entity, digital twin, connection, data and service layer. Intelligent fluid–structure simulation analysis was combined with the real-time rendering of complex data. The velocity distribution and trash rack modal patterns were within an immersive virtual reality environment. Real-time flow field analysis of the inlet/outlet was provided for the online monitoring of one-dimensional basic data, such as the velocity and discharge at each orifice, as well as complex two- and three-dimensional data, including cross-sectional velocity distribution and flow pattern evolution. High-precision flow field results show that the main flow was separated from the wall surface at both horizontal and vertical diffusion angles. A recirculation zone was formed at the top of the diffuser section, where the main stream was concentrated in the lower part of the channel. There was very low turbulence intensity in the main flow and recirculation regions. While two shear layers with relatively high turbulence intensity were observed above and below the main flow region in the streamwise direction from the beginning of the diffuser section to the trash rack cross-section. These shear layers were corresponded to small-scale vortex motions, indicating a strong correlation between vortex distribution and turbulence intensity. Modal analysis of the trash rack structure revealed that the first and second modes were mainly characterized by overall vibration of the rack frame along the z-direction, resulting from the bending modes of the main and secondary beams. In the first mode, the bars near the side beams also exhibited the outstanding torsion. While in the second mode, the torsion occurred throughout the entire bar system. The fifth mode often presented a coupled bending deformation with the bars, side beams, and longitudinal beams, together with the bar torsion. This complex vibration pattern was easily led to the large deformation and potential structural failure of the bar system. However, the main and secondary beams were supported by the bars and longitudinal beams. The high stiffness was less prone to damage. Moreover, in the lower-order modes, the optimal thickness parameters were effectively prevented to damage, where the bars shared no bending patterns that posed a serious threat to structural safety. The frequency ratio between the fifth-order mode and the vortex-shedding frequency was ranged from 2.38 to 4.58, with the lower bound falling below the code-specified threshold of 2.5. Therefore, the special attention should be given to the potential for the flow-induced excitation of the fifth-order mode of the trash rack in engineering practice, leading to the resonance and structural damage near the wall surface. The platform can be expected to realize the high efficiency and rapid feedback in the hydraulic optimization using intelligent numerical simulation of lateral inlet/outlet structures and trash racks.

       

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