A skeleton-based architectural point cloud fusion method was explored to address the challenges of model incompleteness in real-world 3D architectural models. The process begins with reverse modeling of the architectural scene using 3D point clouds. The acquired reverse point cloud data was combined with the original architectural design data to generate a forward point cloud model. A method based on the rotational symmetry axis (ROSA) was then applied to extract skeleton lines from both the reverse and forward point cloud models. The fusion of the forward and reverse point cloud models was achieved by skeleton matching, resulting in a reconstructed 3D model with improved completeness. Experimental validation shows that this method significantly reduces areas of model incompleteness, providing new insights and methods for 3D modeling and reverse engineering in architectural reality capture.

In order to improve the unidirectional linear resource metabolism pattern within communities and optimize the urban resource circulation system, a green productive regeneration method for urban communities based on image 3D reconstruction and multi-criteria decision making was proposed with the help of drone low-altitude photogrammetry technology and using Agisoft PhotoScan, Cloud Compare, and Yaahp. By constructing a 3D point cloud model of the community's built environment and a spatial production potential evaluation model, the suitability of different spaces for production within the community was analyzed, and regeneration design was carried out. The results show that the regenerated community using this method can meet 43.8% of its vegetable supply demand, process 87.28% of its organic waste, supplement 23.46% of its irrigation water needs, and effectively reduce food mileage carbon emissions and building energy consumption. It is concluded that the community's green productive regeneration can significantly reduce its external resource dependency, thus transforming its resource metabolism pattern.

To address the issue of bridge collisions induced by earthquakes, seismic vulnerability curves for the overall system and individual components of conventional and irregular box girder highway bridges, with and without collisions, were developed and compared based on nonlinear time history analysis using the OpenSees finite element software. Four damage states, ranging from minor to severe, were established. The fragility function was employed to elucidate the interaction between structural irregularities and collisions between the bridge deck and the abutment on the seismic vulnerability of multi-span box girder highway bridges. A conversion coefficient, r_p, was introduced to quantify the impact of collisions on the vulnerabilities of bridge components and the overall system. Traditional analysis methods, including static and simplified analyses, alongside technical seismic models, were applied to adjust the vulnerability values associated with collisions and irregularities. The findings reveal that collisions exert adverse effects on all structural components. As the damage level increase, the variability in RP values for the ductility of bridge columns and anti-falling beams also increase. Specifically, for earthquake number 2, the r_p values under damage conditions are 0.95 for mild(DC₁) and 1.02 for moderate(DC₂). Under pulse type seismic motion, collisions significantly increase the degree of damage to engineering demand parameters (EDP). For earthquake number 3, the average r_p value for foundation translation was 0.71 with collisions and 0.57 without, highlighting the significant destructive influence of collisions on foundation translation. By comparing the median values across all categories, it was observed that the median values for earthquake numbers 3 and 1A were lower than those for earthquake numbers 2 and 1B, indicating that collisions caused more severe damage under lower ground motion intensities. This study provides a valuable reference for seismic bridge design, offering insights to improve design specifications, enhance the seismic performance of bridge structures, and deliver significant engineering and practical applications.

Vertical joint steel anchor ring grouting connection (referred to as vertical seam tight splicing connection) shear wall system uses steel anchor ring connection for vertical joints, followed by secondary grouting connection. Based on actual projects of the enterprise, the feasibility of vertical joint tight fitting connection has been verified through experimental research, seismic performance analysis, and design and construction practice.

Uplift piles, in accordance with their structural properties, effectively sustain the structural uplift loads and have emerged as an efficacious solution to address the anti-floating issue. The precise determination of the internal forces within uplift piles is crucial for comprehending their load-bearing characteristics. Nevertheless, the tensile capacity of concrete is relatively feeble. Once the load attains a specific magnitude, its elastic modulus will decline, rendering the traditional axial force calculation methods inapplicable. By leveraging the optical frequency domain reflectometry(OFDR) strain measurement technology and conducting indoor model tests of uplift piles, the strain distribution and evolution patterns of both steel bars and concrete during the pulling process were analyzed. The alterations in the elastic modulus of concrete throughout the tension-failure process were thereby obtained. A method for optimizing the axial force calculation, which exploits the relationship curve between the concrete strain and elastic modulus, was put forward. This enables the accurate acquisition of the axial force of the pile body and its subsequent application in practical engineering projects. The test results indicate that under the condition of small loads, the OFDR technology can identify the locations where concrete cracks emerge based on the strain curve of the pile body. In the event of pile body failure under large loads, the elastic modulus of concrete can be rectified using the relationship curve between strain and elastic modulus. Compared with traditional calculation methods, the relative error of the axial force throughout the entire process can be confined within 5%. The viability of this approach has been corroborated in actual engineering endeavors, and the optimized axial force calculation exhibits enhanced precision.

The prediction of dynamic stress-strain relationship of composite geomembrane is one of the key problems involved in the long-term operation of seepage prevention projects of earth-rock dams. In order to study the effect of cyclic loading on the stress and strain of the composite geomembrane, cyclic loading and unloading tests were carried out under three different stress levels of 10%, 20% and 30%, and the creep tests under 10% to 80% stress levels were carried out to compare and analyze the creep and creep recovery characteristics of the composite geomembrane. The expression of strain under cyclic loading and accumulation condition was presented, and the constitutive model of composite geomembrane boundary surface under cyclic loading condition was constructed. The results show that the deformation of composite geomembrane increases instantaneously at the moment of loading and unloading, and then gradually slows down with the increase of time. After complete unloading, when the stress level is less than 30%, the deformation of the composite geomembrane can almost recover. When the stress level is greater than or equal to 40%, the residual deformation increases gradually with the increase of the stress level. The effect of cyclic loading times on the creep deformation of geomembrane is not a simple linear relationship. In addition, an improved three-parameter viscoelastic model was established, and it is verified that the model can reproduce the creep recovery process of composite geomembrane under different load levels. The research results can provide a reference for the long-term deformation analysis of composite geomembrane in earth-rock dams.

Engineered cementitious composites (ECC) have good crack width control ability and self-healing potential, which can effectively improve the performance and durability of concrete structures and has been used in various environmental conditions. The healing ability of ECC varies under different environmental conditions, and currently there is relatively little research on the healing behavior of ECC in different environments. In order to study the effects of different environmental conditions on the self-healing behavior of ECC, three different environments including 0.5 mol/L NaCl solution, saturated Ca(OH)₂ solution, and natural environment were selected. Pre-cracked specimens were placed in each of the three environments, and the healing behavior and mechanism in different environments were explored through crack closure tests, strength recovery tests, electron microscopy scanning, and energy spectrum analysis. The experimental results show that the cracks in ECC under different healing environments have varying degrees of closure. As the healing cycle gradually increases, the degree of crack healing also gradually improves. NaCl solution and saturated Ca(OH)₂ solution have a positive effect on the crack healing. The ranking of the healing ability of ECC under different environments is obtained as follows: saturated Ca(OH)₂ solution > NaCl solution > natural environment. Healing materials in natural environment mainly include calcium-silicate-hydrate (C-S-H) gel and Ca(OH)₂. The healing material at the crack site in NaCl solution is mainly filled in the form of ettringite and Ca(OH)₂. In a saturated Ca(OH)₂ solution environment, a large amount of healing material is generated at the cracks, mainly in the form of CaCO₃ filling the crack.

To address the challenges of complex geology, dense urban spaces, high component production requirements, and difficult excavation parameter control in the intelligent construction of ultra-large diameter shield tunnels, a systematic study of key links in the shield construction industry chain was conducted based on the experience and digitalization needs of completed and ongoing projects. building information modeling(BIM), big data, IoT, and artificial intelligence technologies were applied to build a digital architecture and establish a full lifecycle coding system. A data platform was developed to promote the digitalization of design data, intelligent segment production, tunnel intelligent excavation, and lifecycle management. The research shows that the parametric drive greatly improves the efficiency of digital design, optimizes the precision of segment production and drilling, and enhances the ability to control the whole life cycle. It can be seen that digital means effectively solve the technical problems in construction, improve the ability of construction control, and provide a feasible digital solution for the construction of large-diameter shield tunnel.

The double semi-trailer truck train has strong transportation capacity and relatively low transportation costs. However, compared to semi-trailers, double semi-trailer truck train has more vehicle units, resulting in higher driving difficulty and lower lateral stability at high speeds. To address this issue, a control strategy combining model predictive control (MPC) with differential braking was proposed. Based on the principles of MPC, an MPC lateral stability controller for double semi-trailer truck trains has been designed. MPC regulates the yaw moments of three vehicle units, with differential braking technology dynamically allocating braking forces to individual wheels. The double semi-trailer truck train model has been built in Trucksim, and a simplified vehicle model has been established in MATLAB/Simulink. Through joint simulation of Trucksim and MATLAB/Simulink, the effectiveness of the designed system was verified under different vehicle speeds, loads, and friction coefficients. The research results indicate that the designed controller effectively reduces the centroid yaw angle, lateral acceleration, and yaw rate of each vehicle unit, thereby enhancing the stability of double semi-trailer truck train during high-speed lane changes.

High-precision vehicle trajectory data is crucial for the realization of intelligent transportation systems. However, existing vehicle trajectory sensing technologies are limited by the range of data collection, making it challenging to obtain full-period and full-area vehicle trajectory data, which cannot meet the demands for trajectory tracking accuracy and real-time performance in practical applications. Considering the characteristics of vehicle trajectory data across radar scenarios, a cross-device vehicle trajectory tracking method was proposed based on radar data. Firstly, trajectory data was filtered based on the lower bound of the confidence interval, and the position and velocity of vehicle trajectories were smoothed and denoised using Kalman filtering. Next, the trajectory timestamp, position coordinates, speed, direction, and lane number from the radar detection area were used as model inputs, while the position information of non-overlapping areas was used as output to construct a non-overlapping area trajectory prediction model based on long short-term memory (LSTM). Subsequently, a fast dynamic time warping (DTW) algorithm based on trajectory condition constraints and search area limitations was proposed to compute trajectory similarity, enabling cross-radar device vehicle trajectory tracking. Finally, verification was conducted using overlapping and non-overlapping scenario data from radar detection on highways. Experimental results show that the trajectory tracking accuracy in overlapping scenarios reaches 92.2%, and the trajectory matching accuracy in non-overlapping areas reaches 90.3%.