Cable-membrane constructions typically exhibit significant displacement and distortion under load action, and the cable-membrane contact results in relative sliding. In this paper, the interaction force between cable and membrane is transferred through frictional contact action, and as a result, the friction coefficient must be taken into consideration for the form-finding and load analysis of air-supported membrane structures. Eight kinds of P-type membrane materials commonly used in engineering were chosen, and the friction coefficients between the various membrane and cable materials were obtained. The connection between a cable and a membrane of an air-supported membrane structure is considered a contact problem, and its initial shape analysis and wind load response analysis are carried out. The influence of the friction coefficient of a cable membrane on the wind-induced response of an air-supported membrane structure is discussed, and the results are compared with those of the cable-membrane binding model under wind load.

Introduction: DCO4 steel sheets with a finite thickness are the subject of this study. Methods: Material mechanical properties were determined through tensile and shear tests, while fracture characteristics along the thickness direction were analyzed. Scanning Electron Microscopy (SEM) observation of fracture surfaces was combined with these tests to clarify the influence of holes on the mechanical behavior of the steel sheet. Subsequently, a finite element simulation of the tensile test on steel plates was performed in ABAQUS, with plate thicknesses ranging from 0.3 mm to 1.4 mm and central hole diameters from 2 mm to 6 mm, corresponding to width-to-diameter ratios of 0.2–0.6. Results: The influence of hole shape on the stress concentration factor (SCF) was quantified. Relationships between sheet thickness, diameter-to-width ratio, and SCF were established. The results demonstrate that for a given diameter-to-width ratio, an optimal sheet thickness exists where the SCF stabilizes. Conclusion: These findings provide a theoretical basis and technical support for the engineering design of perforated DCO4 thin steel sheet components.

Accurately estimating the road adhesion coefficient is essential for ensuring vehicle driving safety. This study proposes a method that integrates a seven-degree-of-freedom vehicle model and the magic formula tire model with the eXtreme Gradient Boosting algorithm, leveraging Shapley Additive exPlanations values to determine feature importance. Based on this, a road adhesion coefficient estimation model is constructed, incorporating a Bayesian neural network and a Support vector regression to enhance interpretability. To address potential issues such as the model predicting road adhesion coefficients beyond the range present in the training data, a data fusion strategy is designed to improve generalization. Simulation results demonstrate that the fusion estimator outperforms individual models in terms of robustness, real-time performance, and prediction accuracy, especially under varying vehicle speeds and road conditions. Compared to a single estimator, the data fusion model reduced the mean square error by an average of 16.01% and 18.89%, respectively, while the root mean square error was reduced by an average of 11.33% and 16.04%, respectively. This approach provides valuable theoretical support to advance the development of vehicle active safety systems.

There are many bars in grid structures, and their topological relationships are complex, so the workload of calculations involved in researching their reliability is large. In this paper, based on the geometric topological relationship within a grid structure, a series–parallel system analysis of the structure is carried out by means of node analysis, constraint grade division, and hierarchical combination analysis, and the series–parallel analysis results for the structure are used to judge the failure of the structure. In order to avoid the problem of missing important components due to unreasonable selection of the bounding threshold when identifying failed components, an adaptive dynamic bounding threshold method with high accuracy is introduced. The failure probability value of the failure path is calculated using the direct numerical integration method, and the reliability of the whole structure is obtained. Finally, the validity of this method is verified using an example of a square pyramid grid structure. The results show that the method is feasible for series–parallel system analysis, structural failure judgment, and reliability analysis of a grid structure.

Different surface damage can cause harm to membrane structures, and traditional manual inspection methods are inefficient and prone to missed detections and false alarms. At the same time, the current mainstream detection algorithms are highly complex, which is not conducive to deployment on resource-constrained devices. To achieve automatic identification of typical surface damage in membrane structures, we construct a dataset comprising five damage types based on common types of surface damage in membrane structures and propose a lightweight identification algorithm for membrane structure surface damage, specifically EAC-YOLO. Firstly, the SPPF module is reconstructed, and the ECA lightweight attention mechanism is introduced to enhance the model’s ability to distinguish easily confused features. Secondly, ADown is introduced to replace the original down-sampling method, improving the retention ability of multi-scale damage features. Finally, the CGBlock and C3k2 modules are combined and reconstructed in the neck network to reduce the interference of damage background factors and capture more features of the damage and its surrounding environment. Experimental evaluation results on the established dataset show that the improved mAP ₅₀ value reaches 87.5%, and the number of parameters, computational cost, and model size are reduced by approximately 28, 25, and 28%, respectively, compared with the original model, demonstrating the advantages of a small size and high accuracy.

Damage to long-span truss structures may cause structural deformation, load-capacity reduction, and even collapse. The design service life of truss structures is usually 50 years, so evaluating their reliability is the utmost importance. Reliability considers the probability of failure as an analysis index. In calculating the probability of structural failure, important components are first selected to form a failure path, and then the failure probability corresponding to the failure path is calculated. A truss structure has many important components and failure paths, so calculating this probability requires extensive and thorough work. As a result, we propose selecting the important components via the approximation method to reduce the influence of the threshold of approximation. Collectively exhaustive events were established using the differential equivalent recursive algorithm to calculate the probability of structural failure. This process was considerably simplified, and validity was verified via a reliability analysis involving a three-bar truss structure, a plane truss structure, and a square pyramid truss structure. This method is suitable for selecting important components of regular truss structures.