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Advances in Frontier Research on Engineering Structures Volume 1-2

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  • Дата: 23-01-2023, 05:46
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Advances in Frontier Research on Engineering Structures Volume 1-2Название: Advances in Frontier Research on Engineering Structures Volume 1-2
Автор: Yang Yang, Sudharshan N. Raman, Bingxiang Yuan
Издательство: CRC Press
Год: 2023
Страниц: 747+585
Язык: английский
Формат: pdf (true)
Размер: 37.2 MB

Advances in Frontier Research on Engineering Structures focuses on the research of advanced structures and anti-seismic design in civil engineering. The proceedings present the most cutting-edge research directions and achievements related to civil and structural engineering. Topics covered in the proceedings include:

· Engineering Structure and Seismic Resistance
· Structural Mechanics Analysis
· Components and Materials
· Structural Seismic Design
· 3D Printing Concrete
· Other Related Topics

FRP-confined steel UHPC (FCSRU) composite columns are a new structural form of casting ultra-high performance concrete (UHPC) in FRP tubes with built-in H-beams. UHPC has extremely high compressive strength, and if an appropriate amount of steel fiber is added on this basis, its toughness will be effectively improved. In order to solve the disadvantage of poor seismic performance of steel-UHPC columns under a high axial compression ratio, three FRP-confined steel UHPC composite columns were designed and fabricated in this paper. The seismic performance of the composite column was studied by a quasi-static test. The final failure mode, load-displacement hysteresis curve and skeleton curve for each specimen were obtained. Then the seismic performance of the composite column is studied in terms of bearing capacity, ductility, stiffness degradation and energy dissipation. The effects of the axial compression ratio and the presence or absence of shear pins are analyzed. Experiments show that all specimens will eventually form plastic hinges at the column feet, leading to composite column failure. All specimens exhibited high residual bearing capacity, energy dissipation capacity and good ductility under horizontal hysteretic loading. The horizontal bearing capacity of the composite column can be increased by increasing the axial compression ratio and welding shear studs on the profile steel flanges.

Most of the existing building acoustic measurement devices are supported and fixed by a tripod, which is not conducive to the height adjustment of the measurement equipment. At the same time, during the measurement, the surface of the measuring equipment can easily attach more dust that is inconvenient to clean, which affects the surface cleaning of the measuring equipment and the accuracy of the measured data. To better solve the issue of the height adjustment of the building acoustic measurement equipment and the cleanliness or dusting of its surface, we optimized the device design of the measuring equipment. It can not only adjust the detector position but also clean the dust on the detector surface. The device has great development significance and great development value.

The evaluation and precise prediction of safety factors can be used to design and assess slope structures’safety. However, due to the complexity of slope structure and the uncertainty of related aspects, the simple prediction model dissatisfies the accuracy requirements. Hence, the main objective of this study is to introduce a new heuristic algorithm, i.e., Harris Hawks’ Optimization (HHO), to advance the accuracy of traditional neural networks (ANN) in predicting slope safety factors. HHO was used to adjust the weights and biases of theANN model.To clarify the accuracy of the HHO-ANN algorithm in the prediction of slope safety factors, the GA-ANN model was established and assessed as the control group. Three performance indexes of mean absolute error (MAE), root mean square error (RMSE), and determination coefficient were calculated to evaluate the accuracy of the prediction model. The results clarified that the HHO-ANN model had the most dominant accuracy than other prediction models. This consequence indicates that the HHO algorithm can improve the performance of ANN and raise the reliability of the model in predicting slope SF values.

The works of this proceedings will promote development of civil and structural engineering, resource sharing, flexibility and high efficiency. Thereby, promote scientific information interchange between scholars from the top universities, research centers and high-tech enterprises working all around the world.

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