Current Issue : October-December Volume : 2023 Issue Number : 4 Articles : 5 Articles
To address the rapidly growing demands of traffic congestion, more highway bridges have been constructed, especially curved bridges. With more curved bridges designed and constructed, people have conducted a comprehensive analysis of the structural performance. Due to the nature of the structural complexity of curved bridges, dynamic responses of the curve bridges vary dramatically from the standard linear bridges. Although some work has been conducted to investigate the curved bridge dynamic analysis under seismic inputs, the framework for analyzing the curved bridges’ vulnerability under various angles of inputs is still lacking. In this paper, we conducted a series of curved bridge seismic analyses based on different inputs and conducted a parametric study of the bridge performance using finite element models. We conducted time history analyses by applying seismic inputs to investigate the bridge dynamic responses based on different angle inputs and other different structural parameters. We developed an approach identifying the most vulnerable direction of the seismic inputs and the strongest dynamic responses for curved bridges based on time series analysis. This approach was validated with the dynamic analysis of a simplified bridge model. The method developed in this paper will help improve the curved bridge design code and further provide suggestions about mitigating seismic response for device design....
Surface damage detection, geometry measurement and monitoring are important for assessing the condition and risk of concrete structures. Therefore, to effectively assess the damage to a concrete structure, a 3D laser scanner accurately estimates the damage within a short timeframe and with less cost than the traditional inspection approaches. This study presents a framework for automated surface damage detection and structural health monitoring of a concrete structure using a X7 laser scanner (Trimble, Westminster, CO, USA). The methodology includes the use of 3D laser scanning technology to capture the 3D geometry of the concrete structure, followed by a detailed analysis of the data to identify any areas of damage or crack. The isodata and object-based image analysis (OBIA) techniques were applied to a 2D image generated from 3D cloud points. Overall accuracy (>89.6) and kappa statistics (>0.83) of both classification techniques exhibit good agreement between the classified and reference image. The OBIA technique was shown to be more effective in detecting minor cracks (<5 mm) and damage on a concrete structure. It was observed that the proposed approach is effective at identifying and monitoring the structural health of a concrete structure. The ability to continuously monitor the structure in this manner allows for early detection of damage and can aid in the maintenance and repair of the structure. Furthermore, this approach can robustly perform structural health monitoring and damage estimation....
A simplified theoretical model of the AERORail vehicle-bridge coupling system and a corresponding numerical simulation system in Simulink are established. Based on several widely used methods for modelling and simplifying vehicle systems, the Simulink simulation system used in this study, including the vehicle system and the bridge (AERORail) system, is presented. Identification examples using a moving load model and a simplified 1/4-scale vehicle model are established.Thesimulation results agree with the data of the simplified dynamic model, with errors between 2.9% and 4.72%, and a satisfactory accuracy is achieved even for singlepoint signal identification, thereby verifying the correctness of the simplified dynamic model of the AERORail system and the improved time-domain method based on the method of moments....
In recent years, 3D laser scanning technology has been applied to tunnel engineering. Although more intelligent than traditional measurement technology, it is still challenging to estimate the real-time deformation of NATM tunnel excavation from laser detection and ranging point clouds. To further improve the measurement accuracy of 3D laser scanning technology in the tunnel construction process, this paper proposes an improved Kriging filtering algorithm. Considering the spatial correlation of the described object, the optimization method of point cloud grid filtering is studied. By analyzing the full-space deformation field of the tunnel lining, the deformation information of the measuring points on the surface of the tunnel lining is extracted. Based on the actual project, through the on-site monitoring comparison test, the three-dimensional laser point cloud data are grid processed and analyzed, and the deformation data obtained from the test are compared with the data measured by traditional methods. The experimental results show that the Kriging filtering algorithm can not only efficiently identify and extract the tunnel profile visualization data but also efficiently and accurately obtain the tunnel deformation.Themeasurement results obtained by using the proposed technology are in good agreement with those obtained by using traditional monitoring methods. Therefore, tunnel deformation monitoring based on 3D laser scanning technology can better reflect the evolution of the tunnel full-space deformation field under certain environmental conditions and can provide an effective safety warning for tunnel construction....
In actual concrete arch dam engineering scenarios, the dynamic data obtained by the health monitoring system of an arch dam are incomplete.Thedata acquired typically depend on the state of the dam structure, that is, whether it is intact or incomplete. Besides, the future environmental loads of the structure are unpredictable. Thus, environmental noise is also uncertain. In practical engineering, the use of a damage identification model constructed based on incomplete information is problematic in scenarios with variable loads. Consequently, detecting the water level in actual arch dam projects after an earthquake and determining the impact of environmental uncertainty are necessary. Accordingly, this paper proposes a denoising contractive sparse deep autoencoder (DCS-DAE) model based on domain adaptation. The core idea of the proposed method is to constrain the data probability distribution of feature spaces in the source and target domains using maximum mean discrepancy. This fusion enables the DCS-DAE model to be capable of feature extraction. Moreover, it resolves the problem in which the objective function cannot be applied to other similar scenarios because of the lack of consistency constraints of feature spaces in the source and target domains. Four working conditions are designed to reproduce the uncertainty of structural modeling and the variability of water levels. The conditions are based on the postseismic water level detection requisites of dams in practical engineering. The results show that the proposed anomaly detection model enhances the generalization performance of the DCS-DAE in terms of feature design. Hence, the constructed model can “infer other things from one fact.” The results of this study are meaningful for the real-time cross-domain monitoring of structures under variable load conditions, providing a driving force to apply similar methods to practical arch dam projects....
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