A physics-guided neural network (PGNN) is proposed to predict the fatigue life of materials. In order to reduce the complexity of fatigue life prediction and reduce the data required for network training, the PGNN only predicts the fatigue performance parameters under a specific loading environment, and calculates the fatigue life by substituting the load into the fatigue performance parameters. The advantage of this is that the network does not need to evaluate the effect of numerical changes in the load on fatigue life. The load only needs to participate in the error verification, which reduces the dimension of the function that the neural network needs to approximate. The performance of the PGNN is verified using published data. Due to the reduction in the complexity of the problem, the PGNN can use fewer training samples to obtain more accurate fatigue life prediction results and has a certain extrapolation ability for the changes in trained loading environment parameters. The prediction process of the PGNN for fatigue life is not completely a black box, and the prediction results are helpful for scholars to further study the fatigue phenomenon.

This paper introduces a kind of double-row reed–nylon net combined sand barrier. Using the computational fluid dynamics (CFD) method and the Euler–Euler double-fluid model, the new sand fences’ windproof effect and airflow features are simulated under different porosities and spacings, and the optimal configuration parameters are selected. The new sand fence has better windproof performance and practical significance than double-row reed and double-row nylon net fences. The new sand fences with a porosity of 0.3–0.4 and spacing of 28 H provide a longer protection range and a better wind protection effect. Considering the serious sand damage in China’s Taklamakan Desert, the new fences’ impact on sand buildup is examined. The combined sand fences have powerful sand blocking and accumulation effects, even though there is only a small quantity of sand accumulation on the leeward side of the second row. The sand particles primarily settle between sand fences in the center and rear areas. The combination of sand fences made of different materials combines the advantages of both, improves the construction efficiency and service life, and provides a more economical and efficient sand barrier arrangement for the arrangement of wind and sand-blocking facilities around railroads and highways in desert areas.

At present, bridge crane accidents occur frequently, resulting in significant losses and casualties; to ensure the safe use of in-service bridge cranes, it is necessary to predict the residual fatigue life of in-service bridge cranes. Firstly, a static analysis of the most dangerous working conditions of in-service bridge cranes is carried out to find the fatigue failure point. Subsequently, a three-parameter Weibull distribution model is established for the characteristic parameters affecting the acquisition of the stress spectrum. Latin hypercubic sampling is applied to randomly sample the characteristic parameters to produce a random sample set of characteristic parameters for use in obtaining the stress–time history. The amplitude and mean values of the stress spectra are obtained by cycle counting using the rainflow counting method. Finally, Forman’s formula and Miner’s continuous damage accumulation theory were used to derive the remaining life prediction equations for constant and variable amplitude loads. Comparing the remaining life obtained from the simulation and test, the error is about 9.145%, which proves that the remaining life obtained from the simulation is more accurate. The results show that the combined method of simulation and testing is feasible and can predict the remaining life more accurately. In the past, the prediction of residual life was performed with either testing or simulation, which is long and costly. Simulation is low-cost and takes a short time, but the accuracy is not high. In this paper, the combination method of testing and simulation improves the efficiency of production and reduces the cost of use.

In order to meet the demand for both efficient sand particle separation and low-cost operation and maintenance in harsh high-wind-blown sand environments, a novel axial flow cyclone separator was optimized and designed. The effects of structural and operational parameters on pressure drop and separation efficiency were investigated through numerical simulations. Finally, orthogonal experiments were conducted on a 1:1 stainless-steel axial flow cyclone separator model using a wind tunnel experimental platform. The performance of the optimized cyclone separator in terms of separation efficiency and pressure drop under high-wind-blown sand conditions was studied.

This paper presents a new slant insertion-opening combination sand fence designed to reduce the hazards of traditional railway sand damage along the line. This new fence aims to decrease the disturbance caused by lateral wind on the high-speed railway and minimize the deposition of track sand particles. Numerical modeling and wind tunnel testing were employed to examine the structure’s defensive capabilities. Using the computational fluid dynamics (CFD) method and the Eulerian–Eulerian two-fluid model, the wind protection effect and airflow characteristics of the new sand fence with different slant insertion angles and spacings were simulated, and the optimal configuration parameters were selected. The study found that the new mechanical sand fence exhibits similar performance to the traditional sand fence. Since there is a “narrow tube effect”, the leeward side of the inclined plate generates a local high-speed airflow zone. In the top acceleration zone, the new mechanical sand fence efficiently lowers air velocity, thereby enhancing its protective capabilities. Moreover, the optimal protective performance of the new mechanical sand fence is achieved with an inclination angle of 15°, with improved protection observed as the angle increases. Additionally, the protective performance of double rows of these fences is influenced by the spacing between them. Increasing the distance between the two rows enhances protective performance, with the optimal protection achieved at a spacing of 25H. Beyond this distance, protective performance decreases.