In recent years, the energy crisis has become increasingly severe, and global attention has shifted towards the development and utilization of wind energy. The establishment of wind farms is gradually expanding to encompass forested regions. This paper aims to create a Weather Research and Forecasting (WRF) model suitable for simulating wind fields in forested terrains, combined with a long short-term time (LSTM) neural network enhanced with attention mechanisms. The simulation focuses on capturing wind characteristics at various heights, short-term wind speed prediction, and wind energy assessment in forested areas. The low-altitude observational data are obtained from the flux tower within the study area, while high-altitude data are collected using mobile radar. The research findings indicate that the WRF simulations using the YSU boundary layer scheme and MM5 surface layer scheme are applicable to forested terrains. The LSTM model with attention mechanisms exhibits low prediction errors for short-term wind speeds at different heights. Furthermore, based on the WRF simulation results, a wind energy assessment is conducted for the study area, demonstrating abundant wind energy resources at the 150 m height in forested regions. This provides valuable support for the site selection in wind farm development.

Structural health monitoring has become increasingly important in the effective evaluation of structural health conditions and the maintenance service of structures. The validity and convenience of obtaining sensor data are critical for data mining, feature extraction, and condition assessment. A fast wireless low-frequency vibration inspection system (FWLVIS) based on wireless sensor networks for offshore platform structural vibration inspection is presented in this paper. The designed system consists of intelligent acquisition equipment and eight wireless nodes with low-frequency acceleration sensors, while the entire system has 64 collection channels. The wireless nodes integrated with a vibration sensing unit, an embedded low-power micro-processing unit, a wireless transceiver unit, and a large-capacity power unit perform functions, which could perform data collection, initial analysis, data storage, and wireless transmission. The intelligent acquisition equipment integrated with a high-performance computation unit, a wireless transceiver unit, a mobile power source, and the embedded data analysis software could completely control the multi-wireless nodes, receive and analyze the data, and implement the parameter identification. Experiments are performed on a single pendulum, and then on an offshore platform model is constructed to verify the FWLVIS. The experimental results show that the system has the following characteristics: fast arrangement, high sampling rate, high resolution, and capacity for low-frequency inspection. Thus, the system has good application prospects and practical value in the field of structural health monitoring and non-destructive inspection.

In spring, the river ice melts to a certain extent and cracks to form drift ice and impact force on the bridge abutments; the river ice, due to the impact of ablation, has an internal formation of different porosities, and the level of porosity affects the mechanical properties of the river ice, so that the impact force generated by the river ice is also different. In this paper, the Heihe–Blagoveshchensk Amur River Bridge abutment is the object of river ice impact, and the discrete element method (DEM) is employed to analyze the impact process and impact force on the abutment by numerical simulation of the melting river ice. The damage characteristics of the ice rows with different ice speeds, ice thicknesses, and porosity, and the time curve of the impact force are obtained. It is found that the maximum impact force of river ice on the abutment decreases nonlinearly with the increase in river ice porosity; the peak contact force occurs with a lag time, and the damage is gradually concentrated in the vicinity of the area in direct contact with the abutment. In this paper, according to the simulation results, the relationship between river ice porosity and the maximum impact force on the bridge abutment, as well as the time parameters, is obtained by fitting, and the power loading model of the bridge abutment impacted by the river ice is established, which provides a basis for the reasonable calculation of the impact force of the ablated river ice at bridge abutments.

Accurate wind field simulation in forest areas is crucial for wind energy development but remains challenging for traditional WRF models due to complex terrain and vegetation heterogeneity. This study proposes a multi-source optimization framework integrating seasonal PBL scheme selection, localized leaf area index (LAI) adjustment, and 3DVAR data assimilation to improve WRF performance in forested terrain. The framework was validated using observations at 20 m, 50 m, and 100 m heights in Maoershan forest area. Results show that: (1) PBL schemes exhibit significant seasonal dependence—YSU performs best in spring (unstable conditions), while MYJ shows slight advantages near the surface in winter (stable conditions). (2) Localized LAI correction reduces near-surface wind speed bias by 35% and improves wind direction accuracy by 28%, with stronger effects in summer. (3) 3DVAR assimilation further enhances accuracy, achieving correlation coefficients of 0.869 for wind speed and 0.813 for wind direction, with greater improvements in summer and near the surface. (4) Winter wind power density at 100 m reaches 475 W/m², 38% higher than summer, indicating stable exploitable resources. The proposed framework provides a replicable methodology for wind field simulation in forest regions worldwide.

Foundation constraints are commonly defined according to the deformation characteristics of the supporting system; however, structural deformation is also strongly affected by external loads. Compared with inland bridges, sea-crossing bridges experience much larger horizontal loads under combined wind–wave actions, and whether foundations in hard-soil conditions can be simplified as rigidly fixed still requires verification. In this study, the m-method is used to determine the equivalent spring stiffness of each soil layer from soil parameters, and a spring-based soil–foundation interaction model is established. This spring-based model is taken as the reference to evaluate the applicability of the rigidly fixed foundation assumption. Using the Qiongzhou Strait highway–railway combined cable-stayed bridge as the engineering background, both rigidly fixed and spring-based foundation models are developed to simulate foundation constraints. The dynamic responses of a single bridge tower and of the entire bridge system under combined wind–wave loading are computed. The influences of foundation constraints on tower-top displacement, foundation reaction forces, and bending moments are investigated. The maximum discrepancy between the two approaches reaches 7.83%, providing a rational basis for selecting foundation constraint conditions in dynamic analysis and design of sea-crossing bridges.