This article provides an overview of the current development status of prestressed segmental precast and assembled piers, Emphasis was placed on analyzing the stress characteristics of bridge piers under impact. The concept o... | Find, read and cite all the research you need on Tech Science Press

Considering the noise problem of the acquisition signals from mechanical transmission systems, a novel denoising method is proposed that combines Variational Mode Decomposition (VMD) with wavelet thresholding. The key innovat... | Find, read and cite all the research you need on Tech Science Press

This study presents a comprehensive investigation of residual strength in corroded pipelines within the Yichang-Qianjiang section of the Sichuan-East Gas Pipeline, integrating advanced numerical simulation with experimental v... | Find, read and cite all the research you need on Tech Science Press

As an evaluation index, the natural frequency has the advantages of easy acquisition and quantitative evaluation. In this paper, the natural frequency is used to evaluate the performance of external cable reinforced bridges. ... | Find, read and cite all the research you need on Tech Science Press

To investigate the influence of different longitudinal constraint systems on the longitudinal displacement at the girder ends of a three-tower suspension bridge, this study takes the Cangrong Xunjiang Bridge as an engineering... | Find, read and cite all the research you need on Tech Science Press

To address the vibration issues of wind turbine towers, this paper proposes a bidirectional tuned bellow liquid column damper (BTBLCD). The configuration of the proposed BTBLCD is first described in detail, and its energy dissipation mechanism is derived through theoretical analysis. A refined dynamic model of the wind turbine tower equipped with the BTBLCD is then developed. The vibration energy dissipation performance of the BTBLCD in multiple directions is evaluated through two-way fluid-structure coupling numerical simulations. Finally, a 1/10 scaled model of the wind turbine tower is constructed, and the energy dissipation performance of the BTBLCD is validated using a shaking table test. The results show that the vibration energy dissipation performance of the BTBLCD outperforms that of the bidirectional tuned liquid column damper (BTLCD) in multiple directions. The shaking table test and dynamic response analysis demonstrate a maximum reduction of 61.0% in acceleration and 47.9% in displacement response. Furthermore, the vibration control and energy dissipation performance of the BTBLCD are influenced by the direction and amplitude of vibrations. This study contributes to the development of more effective and versatile vibration mitigation strategies for wind turbine tower structures in various engineering scenarios.

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure. Therefore, it is particularly significant to identify the structural modal parameters according to... | Find, read and cite all the research you need on Tech Science Press

In the production processes of modern industry, accurate assessment of the system’s health state and traceability non-optimal factors are key to ensuring “safe, stable, long-term, full load and optimal” operation of the production process. The benzene-to-ethylene ratio control system is a complex system based on an MPC-PID double-layer architecture. Taking into consideration the interaction between levels, coupling between loops and conditions of incomplete operation data, this paper proposes a health assessment method for the dual-layer control system by comprehensively utilizing deep learning technology. Firstly, according to the results of the pre-assessment of the system layers and loops by multivariate statistical methods, seven characteristic parameters that have a significant impact on the health state of the system are identified. Next, aiming at the problem of incomplete assessment data set due to the uneven distribution of actual system operating health state, the original unbalanced dataset is augmented using a Wasserstein generative adversarial network with gradient penalty term, and a complete dataset is obtained to characterise all the health states of the system. On this basis, a new deep learning-based health assessment framework for the benzene-to-ethylene ratio control system is constructed based on traditional multivariate statistical assessment. This framework can overcome the shortcomings of the linear weighted fusion related to the coupling and nonlinearity of the subsystem health state at different layers, and reduce the dependence of the prior knowledge. Furthermore, by introducing a dynamic attention mechanism (AM) into the convolutional neural network (CNN), the assessment model integrating both assessment and traceability is constructed, which can achieve the health assessment and trace the non-optimal factors of the complex control systems with the double-layer architecture. Finally, the effectiveness and superiority of the proposed method have been verified by the benzene-ethylene ratio control system of the alkylation process unit in a styrene plant.