Utility tunnel is a kind of underground tunnel structure that carries more than two types of public utility lines, and the utility tunnels built by the prefabricated method have been adopted in many modern cities due to their easy maintenance and environmental protection capabilities. However, knowledge about the seismic performance of the prefabricated utility tunnel and pipelines inside is quite limited. In this paper, a prefabricated utility tunnel newly built in Xi’an, China, is taken as the prototype; a series of shaking table tests are conducted to investigate the seismic performance of the prefabricated utility tunnel in loess foundation, using El Centro earthquake wave as the input loading. Details of the experimental setup focus on the design of the soil container, scaled model (1 : 10), sensor arrangement, and test cases. Dynamic responses including evaluation of boundary effect, the amplification factor of the ground and structure, distribution of soil pressure, characteristics of predominant frequencies, and the damage phenomena are analyzed. Dynamic strain obtained by Fiber Bragg Grating sensors releases the critical positions of the prefabricated utility tunnel during the earthquake. Moreover, the dynamic responses of the pipelines contained in the utility tunnel are also analyzed. From aforementioned results, the seismic performance of the prefabricated utility tunnel has been revealed. The results will provide a reference for the seismic design of prefabricated utility tunnels.
Groundwater control in underwater tunnels by drilling and blasting method is generally carried out by grouting ring, shotcrete lining (primary lining), and concrete lining. The permeable grouting ring and shotcrete lining have an important impact on seepage field. However, the currently published research models of related results are for homogeneous and isotropic single-layer unlined tunnels, ignoring the important effects of tunnel grouting circles and primary lining. If the conclusions of the relevant literature are directly used to guide the tunnel design, large errors may occur. Therefore, on the basis of previous studies, this article extends the tunnel seepage research model and incorporates the tunnel grouting ring and primary lining into the research model. The research model is more in line with actual working conditions. Based on the principle of mirror method, the seepage field of a drainage tunnel in an infinite aquifer is superposed with that of a water supply tunnel in an infinite aquifer, and the analytical solution to the seepage field of an grouted and shotcrete lined underwater tunnel in a semi-infinite aquifer is obtained, which is further verified by numerical analysis and experiment. In addition, the influence of grouting ring and primary lining parameters on seepage field is discussed by using partial differential analysis. The results show that the seepage flow of tunnel can be significantly alleviated by either reducing the permeability coefficient of grouting ring and primary lining or increasing the thickness of grouting ring and primary lining, but the water pressure of grouting ring and primary lining will increase.
Increasingly, today’s businesses rely on data visualization to aid in the outcome that is directly linked to the bulk of their earnings. Due to the enormous volume, speed, and accuracy requirements of data management, database professionals are becoming increasingly necessary to aid in the effective visualization of data. Assuming the information to be depicted is free of ambiguity, most visualization approaches were developed. However, this is a rare occurrence. There has been a recent upsurge in visualizations that attempt to convey a sense of unpredictability. When it comes to visual optimization, we present a novel cognitive fuzzy logic-based particle swarm optimization (CFLPSO) to optimize the data visualizations. Initially, the datasets are gathered as images as well as are denoised and enhanced by employing the bilateral three-dimensional fairing median filter (B-3D-FMF) and contrast illuminate histogram equalization (CIHE), correspondingly. Principal component analysis (PCA) is utilized in the feature extraction stage to extract the features from the enhanced data. Then, the feature integration theory is applied to the extracted features, and also a fast rectangle-packing algorithm is applied to the data visualization. And the proposed approach is employed for visual optimization. The performance of the proposed technique is examined and compared with other existing techniques to obtain the proposed technique with the greatest effectiveness of visual optimization. The findings are depicted by utilizing the Origin tool.
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