This article provided a detailed analysis and discussion on the key points that affect the calibration accuracy of binocular cameras. A planar calibration board based on solid dot marker guided matching was designed, and its superiority over traditional calibration boards through experiments were verified. At the same time, an improved camera calibration method based on two-step RANSAC algorithm was proposed, and the calibration flow of binocular camera was designed for the improved calibration method. This method solves the problem of difficult target size calibration in images and has broad application prospects in the fields of online measurement of image targets and small target image recognition.

To address the issue of poor matching of lane allocation with traffic demand and composition, such as exit and entrance of highway toll stations, Electronic Toll Collection (ETC) and Manual Toll Collection (MTC), a dynamic lane control method for highway toll stations is proposed. Based on the lane control method, a mixed integer linear programming optimization model for the optimal opening scheme of toll lanes is established to achieve rational allocation of toll lanes. The results show that when the traffic demand at the entrance is significantly greater than that at the exit, dynamic control will allocate more toll lanes at the entrance. Compared with conventional control, the traffic capacity can be increased by 12.5%, 50% and 33.33%, respectively, under the three traffic schemes. When the traffic demand at the exit is greater than that at the entrance, dynamic control will allocate more toll lanes at the exit. The traffic capacity can be increased by 6.67%, 25%, and 33.33%, respectively, under the three traffic schemes. When the traffic composition at the entrance and exit matches the toll lanes, the traffic capacity and lane allocation of these two control methods are the same. In various traffic scenarios, dynamic control can adjust the lanes at the entrance and exit according to the traffic composition at the entrance of the toll station, so as to accurately match the traffic demand and capacity in all directions of the toll station, and improve the traffic efficiency of the toll station to realize intelligent expansion.

This paper provides an in-depth analysis of the thermal and mechanical properties of Ethylenediamine Graphene Aerogel (EGA) using COMSOL Multiphysics software. The study focuses on understanding the stress distribution and mechanical responses of this material under various conditions. Thermal stress applied to the bottom of a cylindrical structure revealed distinct stress patterns over time and temperature. High-stress regions were noted towards the cylinder's center, suggesting the effects of temperature fluctuations, while the upper surface experienced lower stress. The von Mises stress increased over time, indicating the material's response to heat, particularly near the heat source, and stabilized around 40 minutes, suggesting a new thermal equilibrium. A critical observation was made at a critical region from the cylinder's bottom, where a significant shift in stress patterns and performance characteristics occurred, emphasizing the need to consider these variations in design for safety and functionality. This study highlights the material’s low thermal conductivity and its role in temperature distribution, demonstrating its capability to manage thermal expansion effectively. These properties make the Ethylenediamine Graphene Aerogel suitable for high-temperature applications such as aerospace, automotive, and thermal barrier systems, and open avenues for further applications.

Plasma-surface modification method (PSMM) is an efficient and inexpensive surface processing method for various materials and has generated great interest in the field of biomedical engineering. This paper focuses on the numerous conventional plasma methods and experimental approaches applied to materials research for suitable biomedical applications, including plasma deposition, laser plasma deposition, plasma sputtering and etching, plasma polymerization, plasma spraying, plasma implantation, and so on. The distinctive benefit of plasma modification is its biocompatibility and surface properties can be enhanced on a selective basis while the bulk characteristics of the materials stay unaltered. Existing materials can hence be used and the requirement for new materials may be circumvented thereby reducing the time for the development of novel and efficient biomedical devices.

Aiming at the characteristics of complex structure, strong coupling and different multi-modal safety levels of more electric aircraft starter generator system, a safety analysis method based on the operating process and a multi-modal failure rate calculation method are proposed. This paper analyses the architecture, operating process and modals of more electric aircraft starter generator system and decomposes the system into eight operating modals. Based on the construction of SafetyLab, a domestic safety analysis platform, the structural models and failure rate calculation models of eight modals of starter generator system are established, and the top event failure rate of each modal, the highest transient failure rate and the steady state failure rate of the system are calculated for a complete safety analysis, taking a typical starter generator system as an example. The method proposed in this paper helps to solve the problem of multi-modal failure rate analysis of complex systems with different equipment involved in the operating process. The multi-modal failure rate calculation method proposed in this paper is also applicable to the safety analysis of other multi-modal complex systems.

Short-term prediction of liquefied gas concentration is helpful to assisted analysis of storage tank operation status and trend, thereby reducing the risk of accidents. Within the limited space, affected by factors such as complexity, high dimension, strong correlation and weak regularity of storage tank operation data, the existing short-term prediction method of liquefied gas concentration is difficult to ensure the real-time performance and accuracy of prediction results. Therefore, we propose a short-term prediction method of liquefied gas concentration based on mixed intelligence. Firstly, we bring in an Extreme Change Function, and calculate the weighted set kurtosis value of the feature curve to realize feature dimension reduction. Secondly, the Convolutional Neural Network is used to mine the correlation between features and extract effective feature vectors. Meanwhile, we use Long Short-Term Memory Network to learn the change law of the data, so as to obtain the predicted value of liquefied gas concentration. Finally, our method is applied to a real scenario to demonstrate that the short-term prediction method of liquefied gas concentration achieves superior results in prediction accuracy, running speed and stability compared with other methods.

In order to investigate the problem of formation collapse caused by sand leakage from segmental lining cracks, this paper selected the logical idea of the silo calculation example in PFC3D and used numerical triaxial compression to calibrate the parameters of sand particles. By simulating the changes in the contact force chain between sand particles, the bottom plate load and the porosity of the sand layer during the process of layer collapse caused by sand leakage from segmental lining cracks, the layer subsidence and sand inrush phenomena, sand flow and loss laws of the sand layer due to different openings are studied. The results show that the dynamic process of continuous formation and destruction of the soil vault leads to continuous changes in the contact force between sand particles when the segmental lining cracks cause strata subsidence. The microscopic reason for the sand intrusion disaster was that after the thickness-to-span ratio exceeded the critical value, the soil arch continued to develop towards the top surface and the top surface was connected to the opening, resulting in the inability to form a stable soil arch between the sand particles. During the loss of sand, the change in load on the bottom plate and the change in porosity at the opening corresponded to the process of destruction and formation of the soil arch. Whenever the soil arch was formed, a local peak appeared in the load curve on the bottom plate and the porosity curve at the opening. In the later stage of the sand loss process, as the loss rate increased, the frequency of soil arch formation and destruction accelerated accordingly.

Through experimental research, this paper reveals the influence of different storage temperatures and pressures on the amount of asphaltene deposition in Russian ESPO crude oil in underground water-sealed caverns. Based on Stokes' settling theory and the experimental results of asphaltene settling at different temperatures and pressures, the Stokes particle settling calculation formula was optimized for temperature and pressure terms. Finally, a particle settling calculation formula that takes into account different sedimentation systems, different crude oil systems, and different temperature and pressure conditions was achieved. The research results show that the asphaltene precipitation of the crude oil system is more affected by temperature than pressure at 10°C-30°C and 0.12MPa-0.28MPa. The precipitation amount decreases with increasing temperature, and the precipitation amount does not show an obvious correlation trend with pressure changes. The research results can provide important theoretical and practical basis for inhibiting the sedimentation loss of long-term storage of crude oil in underground water-sealed caverns.

In this paper, the acoustic signal of the underwater explosion was taken as the main research object, and the mechanical and acoustic characteristics of the underwater explosion were studied by combining theoretical research with simulation, the propagation law of shock wave and the acoustic characteristics of explosion signal with different explosion depth and charge were obtained. The results show that the underwater explosion has strong acoustic power, high sound pressure level, wide frequency coverage of explosion acoustic signal. In low frequency band, the acoustic power level decays rapidly with the increase of frequency, and its acoustic energy is very high; in higher frequency band, the acoustic power level decays slowly, and its sound energy is relatively low; bubble pulsation has a great influence on the energy distribution of acoustic power level, and the more bubble pulsation times, the greater the proportion of low-frequency energy. The research results of this article can provide a theoretical basis for the research of fuze anti-interference.

The high construction and operation costs of urban rail transit have prompted scholars to explore new urban rail transit systems and operating modes. Based on the new straddle-type rapid transit system proposed by our team, the collaborative control of intelligent formation vehicles is discussed in this paper. The mathematical formulation of straddle-type rapid transit vehicle (SRTV) operating in intelligent formation operation mode (IFOM) was first constructed, and then the formation vehicle safety protection strategy based on limited speed difference (LSD) was analyzed. Subsequently, based on the Model Predictive Control (MPC) algorithm, a formation collaborative operation controller was established for IFOM operation. Based on the typical operating scenarios of formation vehicles exiting, cruising, and entering the station, formation performance evaluation indicators were adopted, with a focus on optimizing the time for formation vehicles to exit and enter the station. The simulation results show that the formation operates well and the vehicles in the formation can safely and stably travel in formation, proving that the use of LSD speed limitation strategy and MPC formation controller can ensure the safety and stability of SRTV vehicle formation.