In the natural gas pipeline transportation system, the series elbows is particularly susceptible to erosion due to its special structure and the sand-producing characteristics of natural gas. The erosion behavior of the series elbows is affected by multiple factors, among which the length of the connecting pipe between the two elbows is a variable that cannot be ignored. For this reason, the computational fluid dynamics(CFD)-discrete phase model(DPM) numerical simulation method was used to study the erosion behavior of the series elbows at different spacings of sand-containing natural gas. The results show that when two elbows are installed in series, the corrosion morphology and rate of the second elbow are greatly affected by the distance between the two elbows. With the increase of the length of the middle section of the series elbow, the corrosion morphology of the first elbow is V-shaped, but the corrosion morphology of the second elbow gradually changes from a triangle to a V-shape. In addition, due to the influence of gravity on the migration trajectory of sand particles, the area with the most serious erosion and wear of the second elbow is 5° to 8° behind the upstream elbow. By analyzing the multi-angle section flow field of the second elbow, it is found that the airflow generates a more complex secondary flow at the second elbow after passing through the middle section. Therefore, the maximum erosion rate of the second elbow decreases first and then increases with the increase of the length of the middle section of the series elbows. The research results can provide certain theoretical guidance and basis for optimizing the engineering design and erosion prevention of the double elbow system.

The novel electro-hydraulic composite intelligent completion system primarily involves downhole flow control technology and multi-parameter detection technology and so on. Based on the principles of mechanical structure design, the structural design of the core component of the electro-hydraulic composite intelligent completion flow control valve was conducted, namely the throttle valve sleeve. Finite element analysis was utilized to numerically simulate and study the mechanical performance and fluid flow characteristics of the throttle valve sleeve. The the flow field characteristics under various openings, water cut rates, displacements, and working conditions were analyzed by this method. The results indicate that the downhole temperature and pressure conditions have little effect on the flow control performance of the throttle valve sleeve. The performance is stable and meets the design requirements under high temperature and high pressure (125 ℃, 50 MPa). With different openings, the pressure difference gradually increases as the flow rate increases. At a constant flow rate, the pressure difference decreases with the increase of the opening. When the flow rate and opening are constant, the pressure difference gets greater when water cut becomes larger. When the flow rate and water content are constant, the greater the control series of the throttle valve sleeve, the smaller the pressure difference. The research results can provide theoretical guidance for the structural design of intelligent completion flow control valve.

A deep learning based T-beam formwork polishing robot was designed for the problems of difficult and time consuming polishing of T-beam formwork for variable cross-section. Firstly, an adaptive polishing structure was proposed to solve the technical problem that the existing polishing device cannot fit the inner variable cross-section of the T-beam formwork, and the polishing roller was easy to get stuck in the T-beam formwork partition. Secondly, in order to realize the quantitative monitoring of the polishing quality, a YOLOv8n-DSE algorithm was proposed to identify concrete dirt and stains on the formwork, the DySample dynamic up-sampling module was introduced to enhance the anti-interference ability of the model and accelerate the calculation speed, to improve the accuracy of small target detection, the SOEP (small object enhance pyramid) module was designed to improve the detection performance of small target detection through the SPDConv(space to depth convolution) to obtain the information features of the small target and give them to the CSP(cross stage partial)-Omni-Kernel for the integration of the features. Finally, the EMA(exponential moving average)-SlideLoss was replaced to make the model more concerned with the quantitative monitoring of the concrete, allowed the model to focus more on difficult targets, which can improve the effect on difficult case detection. The accuracy, recall, and mAP(mean average precision) values are improved by 3.1%, 9.7%, and 3.2%, respectively, compared with those before the improvement. The improved model was deployed to the robot and tested in the field. The results show that the equipment meets the plant's needs for polishing variable-section T-beam formwork.

The principle of particle damping energy consumption and inertial capacity efficiency increase are widely used in structural vibration reduction control. Based on the advantages of particle damping and inertial capacity, a particle damping inertial capacity shock damper (PID) was designed, which mainly contained particle damping unit, inertial mass unit and stiffness unit. Firstly, the working principle of PID was elaborated, the mechanical analysis model of single degree of freedom was established, a small PID mock-up was produced, a variety of working conditions were set up to test the mechanical properties of the PID. Then, the mechanical properties of PID were further explored by the combined simulation method of many-body dynamics software and discrete element software. Finally, to verify its engineering application value, dynamic time-course analysis of the damping structures configured with PID and tuned mass damper (TMD) by finite element structural analysis software SAP2000. The results show that PID has excellent damping performance, when the other conditions are certain, the energy consumption effect of PID increases with the increase of vibration displacement amplitude and vibration frequency. In the building structure, PID shows better damping than TMD, it has a high engineering application value.

In order to address the problems of poor flame stability, low combustion efficiency and high lean-combustion limit in traditional direct-fired porous media burners, five porous media burners with different pore arrangements were constructed for low-concentration methane (LCM) combustion experiments, and the effects of porous media arrangements, equivalence ratios and flow rates on the combustion properties of LCM were investigated. CH₄ conversion, pollutant emissions and flue gas temperatures were also analyzed under lean combustion conditions. The results show that the E-type gradually-varied porous media burner exhibits the optimal LCM combustion adaptability, which can partially compensate for the interface temperature perturbation and improve combustion stability during LCM combustion. At an equivalence ratio of 0.39 and a flow rate of 50 L/min, the stationary combustion time of LCM in the burner exceeds 140 min and the flame position is consistently maintained at 60 mm. The LCM combustion in the E-type porous media achieves a CH₄ conversion of 99.99% with CO and NO_x emissions of 531×10^-6 and 23×10^-6, respectively, generating high-quality flue gas with a mean temperature of more than 588 ℃ that can be employed in industrial production. The research results provide an important reference for improving the utilization efficiency of low-concentration methane in coal mines and reducing methane emissions.

A calculation method of effective power based on heat transfer mathematical simulation of intercooling system was proposed for an aviation piston engine, and the heat transfer simulation model of the intercooling system was developed with VB language. The validity of the simulation model was verified by the test data. The results show that the errors between the simulation values and the test values of the intercooler cold side outlet temperature and the hot side outlet temperature are within 1.5%. Using the simulation model, the influence of fan air flow on the effective power of the aviation piston engine was studied, and the air effective power recovery was studied. The results show that with the increase of fan air volume, the amplification of fan power increases, while the amplification of engine power decreases. Under the combined effect of the two, the effective power of the engine first increases and then decreases with the increase of fan air volume. For the aviation piston engine studied, when the fan air volume is 1 400 m³/h, the effective power of the engine reaches the maximum, which is 101.6 kW. When the flight altitude is below 2 000 m, the engine effective power recovery coefficient increases slightly with the increase of flight altitude, and when the flight altitude is above 2 000 m, the engine effective power decreases significantly with the increase of flight altitude. Under the condition of 50 ℃ at sea level, the effective power recovery coefficient of the engine at 7 000 m is only 92.2%.

Sodium fire accidents in sodium technology room can generate harmful aerosols. To analyze the impact of sodium fire aerosol particle migration, a microchannel grid structure similar to real cracks was constructed using computational fluid dynamics(CFD) method based on the actual concrete crack characteristics to simulate the migration process of aerosol particles in the room wall. A two-dimensional horizontal microchannel flow model was established, considering gravity, inertial force, and the influence of Saffman lift and Brownian diffusion on particle motion was studied, and a microchannel particle motion model was constructed to numerically simulate particle retention characteristics for different gap structures. The results indicate that when the gap size is less than submillimeter, it is considered that there is no risk of causing a large amount of aerosol particle leakage in the gap. The branching corners and uneven micro structures within concrete gaps can effectively reduce the penetration coefficient of particles in the gaps and reduce leakage.

Aiming at the problems of poor accuracy, slow convergence rate and high jitter of traditional super-twisting sliding mode observer, a permanent magnet synchronous motor(PMSM) speed observation technique based on the improved super-twisting algorithm was proposed. Firstly, a segmented exponential function was used to replace the switching function to eliminate the phase delay problem due to the low-pass filter, and the adaptive sliding mode gain was designed to achieve stable tracking at different speeds. Then, in order to solve the problem that the traditional quadrature phase-locked loop failed when the motor steering was changed, an improved quadrature phase-locked loop was proposed, so that its output was independent of the rotation direction, so as to realized the correct tracking of the forward and reverse rotation. Finally, due to the wrong convergence point of the proposed improved quadrature phase locked loop, there was a 180° phase difference between the estimated position and the actual position, an adjustment function was designed to solve this problem. The simulation results show that compared with the traditional sliding mode observer, the proposed improvement method has faster response and better dynamic performance.

To address limitations in the engineering application of neural network based maximum power point tracking(MPPT) algorithms, an improved lightweight neural network MPPT algorithm was proposed. The complexity and memory usage of the neural network were reduced through a knowledge distillation compression algorithm, and a lightweight model was obtained. The inherent theoretical error of model predictions was corrected using an optimized variable step-size perturb and observe method. In the initial stage, the neural network predicted the voltage range of the maximum power point. In the later stage, disturbance observation progressively refined this range until it converged at the maximum power point. A simulation model was developed in MATLAB/Simulink, and a physical model was constructed for comparative experiments. Results indicate that the proposed algorithm achieves higher tracking efficiency, improved ripple voltage suppression, and lower resource consumption rate in embedded devices.

The advantages of renewable wind energy lead to a rapid growth in the scale of wind power, while lightning strike accidents on wind farm delivery systems have a significant impact on the new power system. The traditional lightning strike warning method requires high data types and sample sizes, and lacks consideration of relative location as well as the distribution of lightning density. A lightning strike warning method for wind farm delivery systems based on the stepped lightning strike probability calculation method was proposed. Firstly, the data of lightning points around a wind farm in Hainan, China in 2020 were analyzed, and the Monte Carlo method was used to find the center of mass of the clusters as well as the density of lightning points to fit the trajectory of the thunderclouds. Then, based on the relative position of the movement trajectory and transmission line, the stepped lightning strike probability calculation method was combined to calculate the value of the lightning strike probability in a short period of time. Finally, the simulation was combined with the operation monitoring data of a wind farm in Hainan from 2020 to 2022. The results show that the relative error of the proposed method is within 15%, and the impact of the difference in the density of lightning points on the warning accuracy is effectively reduced, which ensures the safety of the wind farm delivery system.