Aiming at the problem of high water content and low degree of recovery of low permeability heavy oil reservoir in Guan128 block of Dagang Oilfield, the microscopic seepage law and residual oil characteristics of viscosity reducers flooding were studied through indoor experiments, and the planar wave and characteristics and residual oil distribution law were quantitatively analysed with the help of AI intelligent recognition. The experimental results show that after the viscosity reducer emulsification of crude oil, the emulsion aggregates and can block the water-driven flux channels, the advantageous transport channels of oil droplets increase, improve the wave and reach coefficient, and reduce the oil saturation. AI image identified pore throat droplets of oil, the wall membrane oil, the residual oil in the dead corner and the residual oil without wave and flake oil and other types of residual oil distribution, and the formation mechanism was analyzed, and measures of surfactants injection and encryption of the network of wells were put forward, and the blocking of high seepage channels was adjusted. Adding viscosity-reducing agent system can reduce the starting pressure gradient and improve the fluidity of heavy oil. After the conversion of water drive to chemical drive, the oil washing effect of residual oil in the pores and throat and residual oil in the dead space is improved, and the recovery rate is increased by 15.28%. The research results provide important theoretical reference for the research on the mechanism of efficient oil enhancement and field application of viscosity-reducing agent injection in the late stage of water-drive development of low-permeability heavy oil reservoirs.

When utilizing double skin composite shear walls as the primary components for resisting lateral forces in buildings, it is crucial to ensure proper horizontal connection of the walls. Currently, traditional bolt connections and welding are the main methods used for horizontal connection of these walls. However, these methods present significant challenges during construction and do not fully exploit the structural advantages of the wall. Based on the structural characteristics of this type of wall, a new type of horizontal joint connection node was designed for the upper and lower layers of the wall. This new design featured a socket-type square semi-grouted sleeve connection. The influence of steel bar diameter, sleeve length, grouting material strength, and sleeve form on the tensile performance of this new connection node was explored using finite element simulation. The results indicate that this new node effectively connects the horizontal joints of double skin composite shear walls with several advantages including convenient construction and reliable performance. Furthermore, it is observed that failure mainly occurs on connecting steel bars which achieves an “equivalent cast-in-place” goal for prefabricated double skin composite shear walls.

To solve the problem of insufficient extraction of sport features by dual stream networks in current action recognition, which leads to low recognition accuracy, a action recognition method based on sport feature enhancement two-stream networks was proposed to improve accuracy. The network was divided into spatial stream and temporal stream, with the same structure but different inputs. The input of the spatial stream network was a video frame sequence, while the input of the temporal stream network was a video frame difference sequence. The network structure used Resnet50 as the backbone network, replacing the 3×3 convolution with the proposed global sport feature module and local sport feature module, fully extracting video sport information, and finally combining spatial and temporal stream to output the results. The results show that the accuracy of the model on the UCF101 and HMDB51 datasets reaches 96.8% and 75.3%, which is superior to traditional algorithms.

In order to improve the engineering characteristics of silty soil in yellow plain area with low strength, easy deformation and poor bonding ability, mechanical testing and scanning electron microscope (SEM) were used to add different contents of xanthan gum(XG), The mechanical properties and improvement mechanism of XG, lignin fiber (LF) and curing age were studied. The results show that both XG and LF as improved materials can increase the compressive strength of silty sand. With the increase of XG content, the compressive strength of silty sand first increases and then decreases. With the increase of LF content, the compressive strength of silt will increase, and the improvement effect will be weakened by adding too much LF. When the two materials are added to the silt simultaneously, the compressive strength of the silt is higher than that of one material alone. XG produces high viscosity gel when it encounters water, the loose silty soil is tightly cemented together, and the strength of the soil is improved. LF contains large molecular groups, forming a spatial network structure with surrounding soil particles, which strengthens the joint force between soils. The research results can provide reference values for the silty soil subgrade improvement project in the yellow plain area.

To explore the reasonable lining section thickness of shallow buried soft soil excavation channels under vehicle loads, two-dimensional finite element models were established using load structure method and strata structure method, respectively. The stress characteristics and safety factors of subway excavation channels under different burial depths, vehicle loads, and lining thicknesses were quantified. The research results indicate that regardless of the presence or absence of vehicle loads, the maximum bending moment of the tunnel is located at the arch foot or arch shoulder, and the minimum safety factor is located at the arch crown. According to the original design reinforcement, regardless of whether there is vehicle load, the safety factor decreases with increasing burial depth and increases with increasing secondary lining. Under shallow burial conditions, the safety factors calculated by the load structure method are smaller than those calculated by the stratum structure method. The calculation results of load structure method show that under vehicle load and surrounding rock pressure, the secondary lining thickness is 60, 90, 100 cm respectively, and the burial depth does not exceed 8, 12, 14.6 m respectively, meeting the safety factor requirements of the specifications. The calculation results of the stratum structure method show that under vehicle load and surrounding rock pressure, when the thickness of the secondary lining is 60, 80, 100 cm respectively, its burial depth does not exceed 12, 15.5, 19 m, which can meet the safety factor requirements of the specifications.

In response to the shortcomings in the construction of temporary support for tunnels, a assembly of temporary support was proposed, and the new structure was studied from the aspects of temporary support shape, assembly structure, and stress deformation. Taking the Shaojiatang Tunnel as the background, on-site monitoring data was collected and compared with traditional temporary support structures using finite element software. It can be concluded that excavation of the tunnel’s rear tunnel will have adverse effects on the deformation of the previous tunnel. Vertical temporary support has better control over the left and right arch waists, surface settlement, and total convergence deformation of the tunnel. Compared with traditional curved structures, it decreases by 16%, 20%, 55%, and 14%, respectively. Moreover, vertical temporary support can restore stability faster and shorten the dismantling distance. By using vertical temporary support, the initial support force of the tunnel is smaller and safer compared to the curved support, and the maximum vertical and lateral stresses are reduced by 58% and 73%, respectively. The mechanical characteristics of temporary support local structures were simulated using ABAQUS software. The results show that the forces and deformations of both prefabricated vertical and traditional temporary support structures can meet the requirements of the specifications. However, prefabricated temporary support structures have more advantages in construction efficiency and economic benefits, and choosing prefabricated temporary support is more suitable.

CO₂ foam fracturing can reduce reservoir damage and contribute to the stimulation of unconventional oil and gas reservoirs. However, there needs to be more quantitative methods to evaluate the influence of the CO₂-H₂O ratio of foam fracturing fluid on the conductivity, and the optimization of foam fracturing fluid system is insufficient. To select the CO₂ foam fracturing fluid system suitable for the conglomerate reservoir in the Mahu Basin, proppant embedment experiments were carried out with the treatment of foam fluid with different CO₂-H₂O ratios at simulated reservoir conditions, and each interval of embedment depth was obtained. A conductivity model considering the heterogeneous proppant embedment was established to calculate the effects of different foam fluids on improving the conductivity and analyze its mechanism. The results show that using CO₂ to replace part of the water-based fracturing fluid can reduce the degree of proppant embedment. With the increase of the CO₂-H₂O ratio, the effect of improving the conductivity weakens and reaches the upper limit gradually, increasing by about 12% compared with that of water-based fracturing fluid. When the ratio is 7∶3, the conductivity of samples with low clay content (<20%) increases to the upper limit. However, the conductivity of samples with high clay mineral content (≥20%) is more sensitive to the influence of the CO₂-H₂O ratio, and the upper limit is lower. CO₂ foam fracturing fluid can improve the hydrological capacity of the propped fracture-formation system. The research results can reference the CO₂-H₂O ratio optimization of the CO₂ foam fracturing fluid system.

In order to mitigate the impact of wind power fluctuations on the power grid, a hybrid energy storage system (HESS) control strategy was proposed, which optimized the parameters of variational mode decomposition (VMD) using the mayfly algorithm (MA). Firstly, the sliding average algorithm was employed to determine the wind power grid connected power that met the grid standards. Then, a fitness function was constructed by combining two evaluation criteria, and the optimal parameters of the VMD algorithm were determined using the mayfly algorithm. The optimal parameters were then introduced into the VMD algorithm to decompose the hybrid energy storage power, realizing the initial allocation of the hybrid energy storage power. Finally, fuzzy control was utilized to optimize the state of charge (SOC) of the energy storage devices, adjusting the power commands of supercapacitors and lithium batteries. The results indicate that the proposed strategy not only enables adaptive decomposition and rational allocation of hybrid energy storage power, effectively mitigating wind power fluctuations but also ensures the SOC of the energy storage devices remains within a reasonable range, achieving safe and stable operation of the HESS.

In order to solve the problems of large training parameters and low text recognition rate of convolutional recurrent neural networks (CRNN) handwritten Chinese character recognition network model, a novel method for handwritten Chinese character recognition based on attention bi-directional long short-term memory network(AT-BLSTM) and knowledge distillation (KD) technology was proposed. By assigning different weights to the input vector features of AT-BLSTM network, the model training data set was more efficient and accurate. Through KD technology, the knowledge acquired from a large high-performance model was transferred to a small model, which ensured the accuracy of the model, reduced the training parameters and internal storage ratio, and obtained a lightweight training model with better performance. Through the comparison of multiple groups of experiments, the accuracy of Chinese character recognition is increased by 6.7%, and the training parameters are reduced by 15.94 M. The recognition accuracy of this network model reaches 97.9%, and the recognition effect of Chinese characters is better.

In order to study the influence of the tank environment on the results of the seaplane model test, for the first time in this field, a series of whole aircraft model tests were conducted using the same seaplane model in two towing tanks to study the aerodynamic and hydrodynamic characteristics of the whole aircraft model in the two towing tanks, the test results and environmental differences were analyzed. The results show that the towing tank environment has a significant impact on the aerodynamic characteristics of the seaplane model, but by compensating the aerodynamic characteristics of the seaplane model in each towing tank during the test, the interference of the test environment on the water resistance results could be avoided, so as to obtain a more satisfactory water resistance test result. Among the boundary effects of the towing tank, the blockage effect has the greatest impact on the aerodynamic characteristics of the seaplane model. Compared with 2.51% relative blockage ratio 0.67%, the aerodynamic drag coefficient of the seaplane model is 0.1~0.2 larger, and the lift coefficient is at least 0.2.Because the typical high-speed coasting state is used for aerodynamic compensation to calculate, so the compensation effect is only achieved at the corresponding speed and produce some deviation at other speeds, resulting in a certain deviation in the test result, but it will not have a significant impact on the test result because the deviation is so small. The research findings provide guidance for model hydrodynamic tests and performance analysis of seaplanes in China.