Article
Computer Science, Interdisciplinary Applications
Shuangxi Feng, Shitao Dai, Huayang Lei
Summary: This paper proposes a method that combines an integrated nonuniform seismic random excitation method with the finite element method to solve the problem of nonuniform seismic input for geotechnical tunnel seismic design in soft soil areas. Based on this modeling, the dynamic responses of tunnels subjected to longitudinal and lateral seismic excitations are investigated. Nonuniform seismic excitation will cause greater tunnel deformation and internal forces than uniform seismic excitation.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Engineering, Geological
P. Parvanehro, M. R. Shiravand, M. Safi
Summary: The study reveals that the SRSS method leads to conservative and unrealistic responses in long bridges under non-uniform seismic excitation. An alternative combination rule is proposed, and the correlation coefficient between responses is calculated using random vibration analysis. Through Monte Carlo simulation and mathematical modeling, the proposed method shows relatively high accuracy and acceptable results.
BULLETIN OF EARTHQUAKE ENGINEERING
(2022)
Article
Engineering, Mechanical
Gang Wang, Huokun Li, Zhiyong Fu, Wei Huang, Bo Liu, Siyang Yao
Summary: Operational modal analysis is crucial in the monitoring and diagnosis of arch dam's structural health and safety. However, extracting accurate information from the vibration responses of arch dam is challenging due to background noise and small amplitudes. Traditional identification methods may lead to deviation that affects the accuracy of structural modal parameter estimation. Therefore, this paper proposes a novel methodology based on multi-level information fusion for modal parameter identification of arch dam. The proposed method identifies the structural natural frequency and damping ratio through multi-sensor data-level fusion and improves identification accuracy by identifying structural mode shapes based on dynamic feature-level fusion. The effectiveness and feasibility of the method are verified through modal results from digital and simulated signals in a 7-DOF system. An engineering case study demonstrates that the proposed method can decompose and identify closely spaced and high-frequency modes with higher accuracy, providing a new approach for modal parameter identification of arch dam.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Computer Science, Interdisciplinary Applications
Xing Li, Zhiping Wen, Huaizhi Su
Summary: The study analyzed the mechanism of dam safety monitoring model and built a model that can accurately predict uplift pressure of dams using the random forest intelligent algorithm. The results indicated that the RF model can relatively quickly and accurately predict uplift pressure of dams, with an average prediction accuracy of over 95%.
ENGINEERING WITH COMPUTERS
(2021)
Article
Environmental Sciences
Yingjia Guo, Zongzhe You, Bowen Wei
Summary: This study proposes an improved modal threshold identification method for high arch dam discharge structures, aiming to filter noise and reduce modal aliasing for better identification accuracy. The method utilizes wavelet threshold-empirical mode decomposition and random decrement technique to process vibration response data and obtain the characteristic parameters of the structure system. Engineering examples demonstrate the effectiveness of this method.
Article
Engineering, Geological
Sergio Oliveira, Andre Alegre, Ezequiel Carvalho, Paulo Mendes, Jorge Proenca
Summary: This paper focuses on the dynamic behavior of two large arch dams and proposes innovations in monitoring systems for dams. The study utilizes automatic data analysis software and 3D finite element models to simulate the dynamic behavior of the dams. The results show the evolution of natural frequencies over time and the measured accelerations during low-intensity seismic events for both dams.
BULLETIN OF EARTHQUAKE ENGINEERING
(2022)
Article
Engineering, Civil
Erfeng Zhao, Chengqing Wu
Summary: The study evaluates the performance of arch dams through modeling on defined centroid deformations, identifying the space-time distribution characteristics of deformation and developing a monitoring model. A novel prediction model is introduced to balance empirical risk and generalization ability, providing technical support for long-term operation of arch dams.
ENGINEERING STRUCTURES
(2021)
Review
Environmental Sciences
Arvindan Sivasuriyan, Dhanasingh Sivalinga Vijayan, Ravindiran Munusami, Parthiban Devarajan
Summary: Continuous monitoring of structures is crucial for predicting damages caused by environmental changes. This review article focuses on base failures in dam structures and the impact of scouring on dam structures. Structural health monitoring plays a vital role in understanding the condition and lifetime of civil structures.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Engineering, Mechanical
Denghong Chen, Ziyue Pan, Yiyuan Zhao
Summary: This study investigates the seismic damage characteristics of high arch dams considering the oblique incidence of seismic waves. The seismic wave input is converted into an equivalent nodal force of the artificial boundary, and the nonlinear dynamic response of the dam under oblique incidence is conducted. Damage measures are selected for fragility analysis, and the damage levels of the arch dam are classified. The seismic demand model and fragility curves are established to predict the probability of reaching damage levels under different seismic actions.
ENGINEERING FAILURE ANALYSIS
(2023)
Article
Engineering, Multidisciplinary
Gaochao Li, Lin Cheng, Anan Zhang, Jie Yang, Feihu Wang, Chunhui Ma
Summary: This paper investigates the application of distributed optical fiber strain sensing technology in arch dam deformation monitoring. By combining BO-LSTM with optical fiber monitoring, a three-dimensional model is established to achieve the transformation between strain and displacement. The results show that the model can accurately realize the strain-displacement transformation of arch dams.
Article
Engineering, Multidisciplinary
Yu Zhang, Zhihua Xiong, Zhuoxi Liang, Jiachen She, Chicheng Ma
Summary: Due to limited technical resources and funds in rural regions, the health monitoring technology for long-span bridges is not suitable for small-span bridges. An economical, fast, and accurate damage identification solution is urgently needed. The authors proposed a damage identification system using a machine learning algorithm for old arch bridges, which utilized vehicle-induced response as excitation and defined a damage index based on wavelet packet theory. After comparing three machine learning algorithms (BPNN, SVM, and RF), the RF model demonstrated better recognition ability. The authors also optimized the RF model using Particle Swarm Optimization (PSO) to identify different damage levels of old arch bridges with a sensitive damage index. The proposed framework is practical and promising for structural damage identification in old bridges in rural regions.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Biochemistry & Molecular Biology
Larissa Fruehe, Tristan Cordier, Verena Dully, Hans-Werner Breiner, Guillaume Lentendu, Jan Pawlowski, Catarina Martins, Thomas A. Wilding, Thorsten Stoeck
Summary: The study compared the performance of two different methods (supervised machine learning and indicator value calculation) in inferring ecological quality using DNA metabarcodes as biological indicators, and recommended using bacterial DNA metabarcodes in combination with supervised machine learning for classification.
Article
Engineering, Geological
Yi-Xiang Qiu, Jin-Ting Wang, Ai-Yun Jin, Yan-Jie Xu, Chu-Han Zhang
Summary: Shear keys are commonly used on contraction joints to improve seismic behavior of arch dams. This paper proposes a geometric simplification method for simulating shear key arrangement, allowing for more accurate representation of the nonlinear dynamic behavior of shear keys.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2021)
Article
Geosciences, Multidisciplinary
Yao Li, Katsuichiro Goda
Summary: This article presents a novel approach that utilizes machine learning to estimate multi-hazard loss resulting from cascading earthquake and tsunami events. The study demonstrates that the combination of random forest model and seismic and tsunami monitoring data can effectively predict highly nonlinear multi-hazard loss. In practical applications, incorporating multiple monitoring stations and sensors significantly enhances the model's forecasting power and accuracy.
GEOMATICS NATURAL HAZARDS & RISK
(2023)
Article
Forestry
Juan F. Maciel-Najera, M. Socorro Gonzalez-Elizondo, Jose Ciro Hernandez-Diaz, Carlos A. Lopez-Sanchez, Claudia Edith Bailon-Soto, Artemio Carrillo-Parra, Christian Wehenkel
Summary: This study investigated the relationship between understorey plant species and soil variables, finding that soil factors have a stronger impact on understorey plants. Given the importance of understorey cover in forest system functioning, it is recommended that understorey vegetation be considered in integrated management and conservation practices.
Article
Engineering, Geological
Yi-Xiang Qiu, Jin-Ting Wang, Chu-Han Zhang
Summary: This paper proposes an integrated framework for the input of earthquake motions in dam-water-foundation rock systems, which can simplify the pre-processing work and improve efficiency.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2022)
Article
Materials Science, Multidisciplinary
Huite Wu, Jianwen Pan, Jinting Wang
Summary: The research shows that the Young's moduli and peak stresses of C-S-H increase with rising strain rates and decrease resulting from the increasing Ca/Si ratios. This study reveals the influence of diverse Ca/Si ratios and various strain rates on C-S-H from molecular insight.
MATERIALS TODAY COMMUNICATIONS
(2022)
Article
Engineering, Civil
Meng-Zhong Zhang, Lei Zhang, Xiang-Chao Wang, Wei Su, Yi-Xiang Qiu, Jin-Ting Wang, Chu-Han Zhang
Summary: This paper proposes a practical framework for the seismic analysis of dams based on a source-to-structure simulation. The framework combines physics-based numerical simulations to generate site-specific ground motions and finite element methods to simulate the dam's dynamic response. The study demonstrates the utility of the proposed simulation framework for accurately predicting seismic responses in dams.
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
(2023)
Article
Engineering, Civil
Hao Ding, Okyay Altay, Jin-Ting Wang, Anupam Das, Tian-Yu Zhou
Summary: This article analyzes the dynamic response of toroidal-tuned liquid column dampers (TTLCDs) under unidirectional and bidirectional excitation scenarios. The results reveal that the liquid responses of TTLCDs excited unidirectionally provide a good prediction for those excited bidirectionally, and the bidirectional response of TTLCDs can be simplified as the linear superposition of the response in two principal directions.
JOURNAL OF EARTHQUAKE ENGINEERING
(2023)
Article
Materials Science, Multidisciplinary
Huite Wu, Jianwen Pan, Jinting Wang
Summary: Interfacial transition zones (ITZs) between cement paste and aggregates play a significant role in the mechanical characteristics of cementitious materials. This study focuses on the ITZ between calcium silicate hydrate (C-S-H) and silicon dioxide (SiO2) at the nanoscale and presents numerical modeling of the interface using molecular dynamics simulations. Uniaxial tensile tests were conducted to investigate the mechanical characteristics of the C-S-H-SiO2 systems with different ITZ thicknesses and strain rates. The simulations reveal that the thickness of the ITZ negatively affects the mechanical characteristics of the system. Additionally, increasing the ITZ thickness leads to a decrease in the mechanical characteristics of the system. This study contributes to a better understanding of the influencing mechanism of ITZ thickness and strain rate on the mechanical characteristics of composite C-S-H-SiO2 systems.
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
(2022)
Article
Engineering, Civil
Xiang-Chao Wang, Jin-Ting Wang
Summary: The traditional spectral matching methods fail to provide ground motions with site-related physical backgrounds. This study introduces a physics-based spectral matching (PBSM) method to generate fully site-related broadband ground motions that are compatible to the target spectrum. The method constructs a 3D numerical model and uses adjoint simulations to calculate strain Green's tensors, reducing the variable space dimension and allowing for optimization algorithms to find the physics-based and spectrum-matched ground motions. The method has been applied to the Xiluodu dam in China, showing promising results.
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
(2023)
Article
Engineering, Mechanical
Hao Ding, Tian-Yu Zhou, Jin-Ting Wang, Okyay Altay, Jian Zhang
Summary: In this study, a new method is proposed to harvest energy from mechanical vibrations of structures by combining the tuned liquid column damper (TLCD) and the Savonius type hydrokinetic turbine (STHT) in a green power production way. The hydrokinetic energy is converted into electrical energy during the vibration control process. Shaking table tests are performed to investigate the starting performance and energy conversion efficiency, and an optimized circuit configuration is revealed for power maximization. The feasibility and characteristics of the approach in energy harvesting are demonstrated.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Marine
Hao Ding, Wei Wang, Jun-Feng Liu, Jin-Ting Wang, Zhi-Ji Le, Jian Zhang, Guang-Ming Yu
Summary: This study experimentally investigates the impact of size effects of the toroidal tuned liquid column damper (TTLCD) on control efficiency using the real-time hybrid simulation technique. The results show that the effects of experimental scale on control efficiency and liquid response are insignificant, and a larger length ratio leads to stronger performance. The TTLCD is found to be an efficient additional damping device in monopile wind turbines.
Article
Chemistry, Physical
Huite Wu, Jianwen Pan, Jinting Wang
Summary: This paper proposes a new composite C-S-Hs model to more realistically represent the layered feature of C-S-H. The larger interlayer space in the model allows for sufficient water adsorption and arrangement of C-S-H cells. The random arrangement of multiple C-S-H cells and additional water molecule adsorption significantly affect the composite C-S-Hs system. Uniaxial tension tests with different strain rates show that the mechanical properties of the composite C-S-Hs model are closer to those of cementitious materials on the macroscopic scale. The simulation results highlight the impact of strain rate and interlayer spacing on the characteristics of the multiple C-S-Hs model.
CHEMICAL PHYSICS LETTERS
(2023)
Article
Engineering, Civil
Hao Ding, Okyay Altay, Jin-Ting Wang
Summary: This study investigates the efficiency of toroidal tuned liquid column dampers (TTLCDs) in controlling the lateral vibration of monopile supported offshore wind turbines. The TTLCDs are capable of simultaneously matching the natural frequencies of the wind turbines in both fore-aft and side-side directions. A mathematical model of the TTLCDs inside the nacelle is derived and a simulation interface between MATLAB/Simulink and FAST is established. A design procedure for TTLCDs in monopile wind turbines is provided. Numerical calculations are performed considering different wind velocities, wave-wind misalignment angles and working conditions, taking into account fatigue and ultimate load cases. A parametric analysis is conducted on the flow resistance coefficient of TTLCDs. The results demonstrate that TTLCDs can effectively control lateral vibrations and improve the structural performance of monopile wind turbines against wind and wave loads.
ENGINEERING STRUCTURES
(2023)
Article
Engineering, Multidisciplinary
Guang-Heng Luo, Jin-Ting Wang, Jian-Wen Pan
Summary: This study aims to apply the surface wave transmission (SWT) method, previously used for concrete crack detection, to concrete crack monitoring by proposing a U-shaped sensor array configuration with multi-input and multi-output properties. The scale of conventional SWT is extended from 1-D to 2-D based on the proposed sensor array, facilitating broad utilization in concrete crack monitoring. Simulations are carried out to analyze the feasibility of SWT in concrete crack monitoring by investigating the influence of different signal-to-noise ratios and heterogeneous concrete properties. The results demonstrate the potential of the proposed sensor array in concrete crack monitoring and its potential application in practical engineering.
Article
Engineering, Multidisciplinary
Changwei Liu, Jianwen Pan, Jinting Wang
Summary: An LSTM-based anomaly detection model is proposed in this paper for the deformation of arch dams. By combining real-time deformation prediction and control limit determination, the model can accurately predict displacement changes of the dam and send alarms in case of abnormal conditions.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Multidisciplinary Sciences
Xiang-Chao Wang, Jin-Ting Wang, Chu-Han Zhang
Summary: This study introduces a full-scenario analysis method for evaluating the maximum credible earthquake hazard for a specific fault by considering all uncertainties of potential future earthquakes. The method is applied in seismic hazard analysis at the Xiluodu dam in China, showing potential application value in earthquake engineering.
NATURE COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Jianwen Pan, Wenju Liu, Changwei Liu, Jinting Wang
Summary: This paper proposes a spatiotemporal deformation field behavior model based on a convolutional neural network (CNN) for arch dams. The model incorporates climatological data, water pressure, and constraint fields to accurately predict deformation. Compared to traditional hydraulic-seasonal-time (HST) and finite element models, the CNN-based model achieves higher prediction accuracy.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
