With the improvement of intelligence, the drilling industry ’s demand for real-time identification of lithology while drilling was becoming more and more urgent. An intelligent inversion method of lithology while drilling is proposed based on the acoustic signal and vibration signal ( acoustic vibration signal ) of broken rock during drilling. Firstly, the original signal samples were obtained by drilling seven different types of rocks through indoor micro-drilling experiments. During the acquisition process, the drilling parameters ( drilling speed, rotation speed, bit size ) were changed and the corresponding signal data were obtained. According to the characteristics of the collected acoustic vibration signal, the time-frequency image with signal characteristics was obtained by short-time Fourier transform. On this basis, an improved VGG16 convolutional neural network model was constructed to realize the intelligent identification of lithology, and the training, evaluation and tuning of the model are realized by hyperparameter optimization. Then, the transfer learning training strategy is introduced, and different drilling parameters were used as data labels. According to the parameter values, the source domain and the target domain were divided to realize the rapid identification of the small sample target domain. The experimental results show that the transfer learning results of the model are different with the change of drilling parameters. The lithology inversion model based on acoustic-vibration signal training has high prediction accuracy and strong generalization ability. The accuracy of the acoustic signal test set is up to 99%, and the accuracy of the vibration signal test set is up to 100%. Under the change of penetration rate, the acoustic and vibration signals are least affected, which can achieve more excellent results when used as data labels for lithology inversion, and the accuracy of lithology inversion is the highest when the penetration rate is small as the target domain. In the process of lithology inversion, different signal types are suitable for different rocks. Among them, the sound signal has the highest applicability to coarse yellow sandstone, and the vibration signal is more suitable for granite. The research results have certain reference value for improving the intelligent degree of working face drilling.

The variation law of C₄AF and C₃A corrosion products and the formation rate coefficient of CaCO₃ of cement single ore were quantitatively analyzed by SEM, XRD and TG analysis and test methods. The experimental results showed that both C₄AF and C₃A produced a large number of flocculent phases after CO₂ corrosion, but C₃A produced more lumpy and flocculent phases after corrosion than C₄AF corrosion. The relative crystallinity of C₃AH₆ decreases and the relative crystallinity of aragonite increases in the later stage of corrosion reaction, and the quantitative analysis results show that the content of CaCO₃ in C₄AF is higher than that of C₃A, and the molar formation rate of CaCO₃ in C₄AF is 28.36 mol/d and that of C₃A sample is only 4.23 mol/d after 1 day of corrosion reaction. With the extension of the corrosion reaction time to 28 days, the molar formation rate of corrosion products of C₄AF and C₃A continued to decrease, which was 1.83 mol/d and 1.48 mol/d, respectively. The coefficient of corrosion product formation α rate of C₄AF was 32.62 after fitting, which was much higher than that of C₃A single ore (2.74). The corrosion resistance of C₃A ore in CCUS environment is stronger than that of C₄AF, which not only provides theoretical guidance for the development of high performance cement materials resistant to CO₂ corrosion, but also provides a basis for the application of cement in CCUS environment.

In order to solve the problem of insufficient feature extraction of human dynamic skeleton features in abnormal behavior recognition, an unsupervised abnormal behavior recognition method based on enhanced spatiotemporal graph normalization flow was proposed. Transformer and convolution block attention module were employed to enhance the feature expression capability of the model and the performance of the abnormal behavior recognition algorithm in the global and spatiotemporal domains. Firstly, the Transformer module was incorporated into the affine layer of the normalized flow to augment the efficacy of dynamic skeleton feature information at the global level. Subsequently, the convolution attention was introduced into the convolution module of space and time graphs respectively to effectively enhance the spatial and temporal representation of dynamic skeleton features. Finally, simulation verification was conducted on the ShanghaiTech and UBnormal datasets, and the recognition accuracy attains 86.4% and 70.2% respectively, thereby demonstrating the effectiveness of the method.

The transportation via high-pressure long-tube trailers serves as a crucial method for medium-short distance transfer of flammable and explosive gases such as hydrogen and natural gas. As the core equipment in this system, the trailer filling compressor operates under continuously varying discharge pressures across wide ranges during gas loading processes. Current research and development phases face challenges in fully replicating real-world operating conditions for thermal performance testing. Addressing this requirement, this study proposes a closed-loop experimental system with gas staged recovery and continuous release functions, featuring continuous backpressure regulation capability for trailer filling compressors. The system enables the simulation of actual filling processes by creating both stable and dynamic operating conditions with wide-ranging discharge pressure variations for comprehensive compressor testing. A mathematical model of the testing system was established using zero-dimensional simulation methodology. Systematic investigations were conducted on parameter variations and operational characteristics throughout complete testing procedures, including initial pressurization, compressor startup/shutdown, and wide-range operational testing. Through optimized improvements in system configuration and component matching, critical operational constraints were achieved: gas reservoir temperatures were maintained below 85 °C during testing, and post-recovery system pressures were reduced below 1.5 MPa. These optimizations resulted in the development of a refined and rational testing system and methodology for trailer filling compressors, effectively addressing the technical challenges in simulating actual working conditions during compressor development phases.

The cornering stiffness of automobile tires is closely linked to the vehicle’s handling characteristics, and accurately estimating the tire cornering stiffness in real time is of significant importance for enhancing the stability of vehicle handling. Addressing the challenge of direct measurement of cornering stiffness, a real-time identification method based on the estimation of tire lateral force and slip angle was proposed. Firstly, considering the influence of longitudinal force on lateral force, a tire lateral force estimator was designed based on the yaw dynamics model and sliding mode observer algorithm, followed by the design of a slip angle feedback estimator based on the estimation error of lateral force. Secondly, a nonlinear tire force model that describes the relationship among tire lateral force, slip angle, and cornering stiffness was established. Taking the real-time estimated lateral force and slip angle as inputs, a recursive least squares online identification algorithm with limited memory was designed to address the issue of estimation error due to “data saturation” and improve identification accuracy. Finally, joint simulation experiments using Simulink and CarSim were conducted. The experimental results indicate that the estimation error of tire lateral force is approximately 4.153 9% on average, while the estimation error of tire slip angle is 3.285 2% on average. The identification model based on the recursive least squares method is robust to changes in road conditions, demonstrating good tracking accuracy and stability under both high and low adhesion conditions, with an average estimation accuracy of tire cornering stiffness of approximately 98.379 3%.

Due to the complex reservoir conditions and multi-scale pore structure of shale gas, the production shows significant nonlinear characteristics over time. Traditional production prediction methods, which rely on statistical analysis of geological and engineering data, find it difficult to adapt to the complexity of geological conditions and thus cannot achieve high accuracy. A method that combines the hyperbolic decline model with a composite function having time attributes was proposed. The improved A-PSO (adaptive particle swarm optimization algorithm) was used to find the optimal model parameters, establishing a composite time hyperbolic decline model. The research results show as follows. The A-PSO optimization algorithm can automatically adjust parameters and model structure according to the complexity of production data and data changes, finding the optimal parameter combination more quickly and accurately, thereby improving prediction accuracy. The production fluctuates greatly over time, making it difficult for conventional decline models to reflect its characteristics. The composite time decline model, with its strong flexibility, can consider the complexity and variability of oil and gas reservoirs, more accurately describe the production changes of shale gas wells at different stages, and provide higher fitting accuracy, making the production prediction closer to the actual value.

The length of the impactor is generally about one meter according to the current application of all kinds of impactors.As the existing impactor increases the distance between the stabilizer and the drill bit, it will cause the theoretical build slope and the lateral force of the drill bit to decrease when it is used in connection with the drill bit. This will in turn affects the drilling deviation section.In this regard, the multi-dimensional impactor with built-in drill bit can effectively solve this problem.Firstly, in order to maximize the performance of the multi-dimensional impactor with built-in drill bit and reduce the pressure loss, the PB (Plackett-Burman) screening test design was adopted to conduct screening tests on the internal parameters of the impactor. The effect of each parameter on the tool performance was as follows: Jet channel width > inlet area > Outlet area > length of oscillating cavity > width of double feedback channel > curvature radius of wall attached surface > wedge Angle. Then, BBD (Box-Behnken design) response surface method was used to provide an in-depth analysis of the top three significant impact parameters.The optimized combination of the internal structure of the multi-dimensional impacter with built-in drill bit was obtained as follows: the inlet area is 1 203.416 mm², the jet channel width is 14 mm, and the outlet area is 455 mm². Finally, the effectiveness of the optimization method was verified by the simulation of Fluent software, which met the design requirements.

The Chishui River Basin has been recognized as an important ecological security barrier in the upstream of the Yangtze River Basin. Research on the ecosystem service value of the Chishui River Basin under different future development scenarios is of great significance to carry out the environmental protection policies and the environmental protection measures. Therefore, Chishui River Basin has been selected as the research area and the FLUS (future land use simulation) model and InVEST (integrated valuation of ecosystem services and trade off) model were functioned to predict the ecosystem services, including water yield, soil conservation, and water purification, under three scenarios, such as natural development, environmental protection, and economic development in 2040. The high ecosystem services functions in all three scenarios are identified as the key protected areas. The results show as follows. There are significant changes in agriculture area and urban area under different scenarios, especially, the agriculture area under the economic development scenario has increased 510.55 km² and 1 475.76 km² compared to the natural development and environmental protection scenarios, respectively. In the environmental protection scenario, the areas with high water yield (>700 mm) and high soil conservation function (>2 000 t/hm²) account for approximately 36.81% and 47.15% of the Chishui River basin area, respectively. The proportion of key protected areas for ecosystem services functions in the Zunyi City account for approximately 62.65%. The results of this study aim to provide certain support for identifying key protected areas in the Chishui River Basin and promoting the implementation of spatial refinement protection and management.

The perforated walls of transonic wind tunnels with different parameters have a considerable influence on the flow field quality of the test section, therefore, the characterization of the perforated wall parameters is extremely essential for the design of the test section of transonic wind tunnels. The relationship between the characteristic parameters near the perforated wall of three-dimensional and two-dimensional perforated wall models was studied using the single straight perforated hole of the FL-3 wind tunnel. The mass and velocity distributions of the two-dimensional and three-dimensional perforated wall show obvious linear characteristics under different pressure difference coefficients. It is proposed that the two-dimensional perforated wall can be equivalent to the flow characteristic parameters of the three-dimensional perforated wall by the corresponding coefficient transformation under the same incoming flow Mach number when the wall pressure difference coefficient and the boundary layer displacement thickness are satisfied. A two-dimensional calculation model of the transonic wind tunnel was established, and the effects of perforated wall parameters and free stream Mach number on the flow field and flow characteristic parameters near the wall in the test section were analyzed by numerical method. When l / d = 1, the increase in perforated wall size makes the wall pressure difference coefficient increase, otherwise, the relative area of flow in the perforated wall decreases. As d = 2 mm, the flow field was proposed. When l / d > 2, ΔC_p tends to be stable. When l / d = 3, m' and S / d are the maximum values, in the Ma = 0.8 ~ 0.9 range, m' is positively correlated with the incoming Mach number, but ΔC_p changes little. The pressure difference coefficient and velocity component obtained under different perforated wall parameters have certain guiding significance for understanding the perforated wall flow and adjusting the perforated wall of the test section.

To explore the application regularity and mechanism of formulas containing Huang Qin (Scutellariae radix)-Bai Zhu (Atractylodis macrocephalae Rhizoma) (HQ-BZ) herb pair in the treatment of ICP (intrahepatic cholestasis of pregnancy). All literature on prescriptions containing HQ-BZ herb pairs against ICP was screened from the VIP, Wanfang, and CNKI databases. Subsequently, the R language was employed to analyze and summarize its medication rules and core prescriptions. Network pharmacology was used to predict the mechanism of core prescriptions against ICP, followed by molecular docking and experimental verification to confirm the potential mechanism. A total of 68 prescriptions were included, involving 67 herbs characterized mainly by cold, bitter, and spleen meridian. The core prescription “Artemisiae scopariae Herba-Rhei radix et Rhizoma-Gardeniae fructus-Scutellariae radix-Atractylodis macrocephalae Rhizoma-Poriacocos” was obtained based on the comprehensive analysis of traditional Chinese medicine data, among which quercetin, apigenin, and other key active components may act on core targets such as AKT1 (serine/threonine kinase B1), BAX (BCL2-associated X protein), and participate in PI3K-AKT (phosphatidylinositol 3-kinase/protein kinase B), apoptosis, and other multiple targets and pathways to play the role of ICP therapy. The molecular docking results showed that apigenin demonstrated superior binding affinity with the top 11 core targets compared to quercetin and beta-sitosterol. HTR-8/SVneo cell experiments proved that apigenin significantly reduced the apoptosis rate induced by TCA (taurocholic acid) and elevated the protein expression levels of Bax/Bcl-2 (P<0.01), as well as p-PI3K/PI3K, and p-AKT/AKT (P<0.01). Pre-treatment with LY294002 could reverse the anti-apoptosis effects and the expression levels of the aforementioned proteins induced by apigenin. In summary, the core prescription that includes the HQ-BZ can provide references for the clinical prescription of ICP. Apigenin, a key component of core prescription, can inhibit the apoptosis in HTR-8/SVneo cells induced by TCA and has the potential to treat ICP, and its mechanism may be related to the regulation of the PI3K-AKT signaling pathway.