The WSRJ is an international peer reviewed, online and print version journal published by Boya Century Publishing. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of science and technology. We bring together Scientists, Field Engineers, Scholars and Students of related fields. WSRJ is a monthly, open access, peer reviewed and fully refereed international journal with minimal processing charge.
Synaptic Plasticity of Memristors Based on ZnO Thin Films Fabricated by PLD
Cu/ZnO/Cu memristive devices with planar-structure were successfully fabricated using pulsed laser deposition (PLD) technology by regulating substrate temperature. At a substrate temperature of 500 °C, ZnO thin film of the device exhibits smooth and uniform surface morphology demonstrated by systematic characterization. Such memristive devices show excellent dynamic resistive switching behavior under electrical pulse stimulation, with their resistance states capable of being precisely modulated by the polarity, amplitude, and duration of electrical pulses. Leveraging this tunable resistive switching property, the devices successfully emulate various biological synaptic behaviors including excitatory postsynaptic current and paired-pulse facilitation, demonstrating promising potential for applications in neuromorphic computing.
Memristor; Synaptic Plasticity; Resistance Switching; ZnO; PLD.
Copyright (c) 2026 World Scientific Research Journal https://creativecommons.org/licenses/by-nc/4.0
A Review of the Application of Low-Carbon Concepts in Civil Engineering Structural Design
Against the background of global warming and China's "Dual Carbon" strategy, the low-carbon transformation of the civil engineering industry has become imperative. As a critical stage in the whole life cycle of engineering projects, structural design serves as an important approach to achieving carbon emission reduction. This paper systematically reviews the connotation of the low-carbon concept and its integration paths with structural design, summarizes key technologies including low-carbon building materials, innovative structural systems, and efficient energy utilization, and analyzes their application effects based on typical engineering cases. In view of existing challenges in technology, economy, policy and public awareness, countermeasures are proposed for the future intelligent, standardized and industrialized development. The results show that integrating low-carbon concepts into structural design can effectively reduce life-cycle carbon emissions, which is of great significance for promoting the green and sustainable development of civil engineering and supporting the achievement of the "Dual Carbon" goals.
Low-carbon Concept, Civil Engineering, Structural Design, Life Cycle.
Research on Agricultural Machinery Operation Path Planning for Irregular Fields in Hilly Areas
Aiming at the problems of complex shape of irregular fields, frequent turning of agricultural machinery operation and low operation efficiency in hilly and mountainous areas, a path planning method of agricultural machinery operation based on minimum turning times was proposed. Firstly, the field boundary model is constructed by using Gauss-Kruger projection and grid method, and the irregular fields are divided into convex polygons, concave polygons and complex polygons according to the theory of computer graphics. Secondly, the field classification is realized by concave and convex judgment and polygon subdivision, and the safe operation area is constructed on this basis. Then, the simulated annealing algorithm is used to search the best operation direction, the operation angle is determined with the minimum number of turns as the optimization goal, and the reciprocating straight path is generated based on the active side table method. Finally, combined with the constraints such as the minimum turning radius of agricultural machinery, the turning decision model is constructed to realize the complete operation path planning. The simulation results of typical hilly fields show that the proposed method can achieve more than 90 % operation coverage in different types of irregular fields and effectively reduce the number of turns, which has good applicability and practical value.
Hilly area, Irregular plots, Agricultural machinery operation, Path planning, Turning number optimization.
Research on Lightweight Wound Recognition Algorithm and System for UAV in Accident Emergency Treatment
Aiming at the problems of slow manual rescue response for emergency hemostasis at accident scenes, single emergency function of emergency UAVs, insufficient lightweight degree of airborne wound recognition algorithms, and poor hemostatic effect of traditional hemostatic materials, this paper takes YOLOv5s as the basic model. Through channel pruning, INT8 quantization and knowledge distillation, a lightweight wound recognition algorithm suitable for edge deployment on UAVs is developed. Integrating temperature-sensitive self-expanding nanofiber hemostatic materials and an umbrella-type precise delivery mechanism, a fully automatic emergency UAV system is constructed. Experimental results show that the optimized algorithm model is only 89.2 KB in size, with a wound recognition accuracy of 93.6% in complex scenes and an inference speed of 34.2 fps, which meets the requirements of real-time airborne deployment. The hemostatic material expands completely within 28 s at 37 ℃ with an expansion ratio of 2.4 times, and the in vitro coagulation time is 76 s, improving hemostasis efficiency by 72% compared with traditional gauze. In a level 4 wind environment, the system delivery error is controlled at 2.1 cm, and the total hemostasis time is 110 s. The system realizes integrated operations of automatic wound recognition, precise delivery and rapid hemostasis, which can improve emergency efficiency at accident scenes and provide technical support for emergency medical rescue.
Accident site first aid; UAV; Lightweight wound recognition; YOLOv5s; Self-expanding nanofibers; Precise delivery.
Research Status and Trends of Maize Planters for Hilly and Mountainous Areas
Hilly and mountainous areas are important maize-producing regions in China. However, due to complex terrain, limited economic conditions, and a lack of suitable machinery, the mechanization level of maize sowing in these regions has long lagged behind that of plain areas, becoming a key bottleneck restricting industrial development. Focusing on maize seeders suitable for hilly and mountainous areas, this paper begins with the types of seed metering devices, summarizing mechanical types such as fluted roller, cell wheel, spoon wheel, and turntable structures, as well as typical representatives of pneumatic seed metering devices, and analyzes their working principles and applicable characteristics. On this basis, relevant research progress both domestively and internationally is reviewed: foreign countries started earlier and have continuously advanced in areas such as precision seeding, pneumatic metering, structural optimization, and electric drive; since the 1980s, China has developed various small-scale seeders—including hand-held, pedal-operated, self-propelled, and electromagnetic vibration types—for small plots and complex terrain, achieving certain progress in adaptability. However, from the perspective of practical application, current small-scale maize seeders still commonly suffer from insufficient reliability, poor adaptability, and weak versatility, with a notable shortage of specialized models suitable for hilly and mountainous areas. Considering actual agricultural production needs and technological development trends, future improvements in such seeders should focus on multi-function integration, intelligent control, and environmental sustainability to better accommodate the planting conditions and mechanization development requirements of hilly and mountainous regions.
Hilly and mountainous areas, maize planter, mechanization.
Development of a Regional Photovoltaic Baseline Dataset for Qinghai Province
To support the operational needs for detailed assessment of solar resources and PV power forecasting in high-altitude regions of Qinghai Province, this study conducted the standardization and development of a PV dataset, along with end-to-end quality control, based on 15-minute interval measured data from June 2021 to June 2022 at four typical PV power plants in Qinghai Province. Missing values were imputed using physical threshold constraints and linear/co-periodic mean interpolation. A combined outlier detection model utilizing DBSCAN density clustering and random forest regression was constructed to automatically identify and remove invalid values, abnormal spikes, and physically implausible data. The results show that after quality control, the valid data rate for total radiation increased from less than 30% to 87.5%, with a correlation coefficient of 0.92 relative to meteorological parameters and a root mean square error of 48.7 W·m⁻². The data quality meets the requirements for solar resource assessment and power forecasting.
Photovoltaic data, Data processing, Quality control, DBSCAN, Isolation Forest.
Research Status and Trend of Vision and Laser in Agricultural Machinery Navigation
With the aging of the population and the development of urban and rural integration, the shortage of agricultural productivity restricts the development of agricultural economy. The automatic navigation technology of agricultural machinery can effectively reduce the input of manpower in agricultural production, which is the key direction of agricultural machinery automation research. In the agricultural environment with lush vegetation, the signal interference is more serious, and the visual and laser sensors are less affected in this case, which is widely used in the research of agricultural machinery navigation. This paper mainly summarizes the methods of vision and laser navigation information acquisition in agricultural machinery navigation, analyzes the advantages and disadvantages of different types of sensors, and points out the research status of multi-source data fusion methods. Finally, the problems and development trends of vision and laser technology in agricultural machinery navigation are proposed.
Vision, Lidar, Data fusion, Agricultural machinery navigation.
Research Progress and Prospects of Detection Technology for Tri-Rare Elements in Coal from the Lianghuai Coalfield
"Triple-rare" minerals (referring to rare elements, scattered elements, and rare earth elements) are key strategic resources supporting the new generation of information technology, new energy, and high-end equipment manufacturing, and their safe supply has risen to the national strategic height. Coal-bearing associated tripleple-rare elements, as important alternative resources to traditional minerals, show great development potential worldwide. As a core energy base in East China, the Lianghuai Coalfield contains abundant lithium, gallium, germanium, and rare earth element resources in its deep coal-bearing strata. However, the superposition of multi-stage tectonic movements and magmatic hydrothermal fluids has resulted in high ash and high sulfur content of coal and extremely complex occurrence states of tripleple-rare elements, posing severe challenges to analytical and detection technologies. This paper systematically combs the research progress of tripleple-rare elements in coal at home and abroad, and focuses on analyzing the core bottlenecks faced by detection technologies under the special geological background of the Lianghuai Coalfield. The research shows that the international community has established a genetic classification system for rare earth elements in coal and a general detection method based on low-ash and low-sulfur coal, but there is a significant mismatch in geological background. Domestically, preliminary achievements have been made in the geochemical characteristics and enrichment rules of tripleple-rare elements in the Lianghuai Coalfield, but the detection system still has shortcomings such as insufficient pertinence, lack of special reference materials, and weak regional research foundation. Finally, this paper discusses the development trend of detection technology for tripleple-rare elements in coal, and proposes that establishing a targeted digestion system based on element occurrence states, constructing a quality control network adapted to the regional geological background, and improving the resource availability evaluation standards are the key research directions in the future, which can provide technical support for the precise exploration and high-value utilization of tripleple-rare resources in the Lianghuai Coalfield.
Geochemistry; Triple-rare Elements (Rare Elements, Scattered Elements, Rare Earth Elements); Lianghuai Coalfield.
Sensory-Guided Characterization of Key Aroma Compounds in Five Five-Grain Strong-Flavor Baijiu Samples
Five-grain strong-flavor Baijiu is characterized by its intense pit aroma and mellow, sweet, and clean taste, and it plays a pivotal role in the Chinese Baijiu market. Its production is based on key processes including solid-state fermentation in mud pits, continuous fermented grain supplementation, mixed steaming and distillation, and the use of medium- to high-temperature Daqu. In terms of aroma composition, ethyl hexanoate is the predominant compound and, together with ethyl lactate, ethyl acetate, ethyl butyrate, and other esters, forms a well-balanced and complex flavor system. In this study, the five-grain strong-flavor Baijiu samples were produced using sorghum as the primary raw material, supplemented with rice, glutinous rice, wheat, and corn through multigrain co-fermentation. Different sorghum varieties can influence microbial metabolism and flavor formation due to variations in physicochemical properties such as starch, protein, and tannin content. Therefore, a sensomics-based approach was employed in this study. Under the guidance of national-level Baijiu experts, an olfactory panel was selected and systematically trained. By integrating quantitative descriptive analysis (QDA), gas chromatography–olfactometry–mass spectrometry (GC-O-MS), and aroma extract dilution analysis (AEDA), the aroma profiles and key aroma compounds of five-grain strong-flavor Baijiu produced from five different sorghum varieties were comprehensively characterized.
Five-grain strong-flavor Baijiu; Sorghum varieties; Sensory evaluation; Aroma profile; Key aroma compounds.
Advances in Chlorpromazine Detection Technologies: A Review
Chlorpromazine (CPZ) is a representative phenothiazine antipsychotic that needs to be analytically assessed reliably in clinionmental fate and transformation research. Conventional techniques such as high-performance liquid chromatcal therapeutic monitoring of drugs, residue analysis of animal-derived foods, forensic toxicology, and envirography, gas chromatography and enzyme-linked immunosorbent assay have traditionally been employed to analyze CPZ but remain limited in ultra-trace detection, scalability to complex matrices, swift on site screening, and multiplexed multi-analyte analysis. Over the past few years, chromatographic-mass spectrometry-based methodologies, spectroscopic and nano-optical assays, electrochemical sensors, new immunoassays and biosensors have grown at a fast pace offering new lines of analysis of the CPZ quantitation in plasma, oral fluid, tissue and animal samples, food, and environmental samples. The current review presents the advances in CPZ detection technologies in the last few years focusing on selected articles published between 2015 and 2025 on the chromatographic and chromatography-mass spectrometry methods, rapid testing approaches, and up-and-coming sensing technologies. Also considered are sample preparation, method optimization, technical comparison, applications, and future trends. On the whole, chromatography-mass spectrometry remains the most popular platform in confirmatory analysis and high-precision quantification, whereas fast optical, electrochemical, and immunochemical techniques are also promising in field screening, microsample analysis, and point-of-care testing.
Chlorpromazine; chromatography-mass spectrometry; electrochemical sensing; immunoassay; rapid detection; simultaneous multi-analyte detection.
RANSAC-based Point Cloud Calibration Algorithm Accounting for Point Quantity and Distribution
To tackle the challenge of inadequate accuracy in UAV-LiDAR point cloud data, this research introduces a RANSAC calibration algorithm that takes into account both the quantity and spatial distribution of points. Simulation experiments were carried out across four experimental sites to ascertain the optimal point placement strategy under diverse terrain conditions. Initially, control points were established within the experimental zones, and both control point data and point cloud data were collected. Subsequently, calibration strategies incorporating different point counts and distributions were devised. Ultimately, the precision of each calibration approach was evaluated. The experimental findings reveal that: (1) calibration accuracy decreases as terrain complexity increases within the experimental areas; (2) a greater number of points correlates with higher calibration accuracy; (3) given an equal number of points, a diamond-shaped point distribution yields the highest calibration accuracy.
Mechanical Resonance Suppression of Servo System Based on Resonant Frequency Online Identification
This paper analyzes the mechanical resonance of permanent magnet AC servo systems and identifies the main factors that affect resonance. Further use fast Fourier transform for frequency online identification of the resonant system, and finally use a notch filter to filter the resonant frequency of the system. The impact of the notch filter on the system was analyzed and the parameters of the filter were determined, ultimately achieving the digitization of the notch filter. By analyzing the mechanical resonance system and identifying the resonance frequency online, the mechanical resonance of the permanent magnet AC servo system itself has been effectively suppressed. The experimental results have verified the effectiveness of the vibration suppression control algorithm.
Mechanical resonance; Fast Fourier transform; Online identification; Notch filter.
Meteorological Drought Prediction in the Loess Plateau Based on Three Machine Learning Models
Drought, a severe natural hazard, exerts profound impacts on both ecological systems and agricultural productivity. Consequently, advancing drought prediction methodologies is paramount for optimizing regional water resource management and mitigating associated risks. This research centers on the Loess Plateau, leveraging monthly precipitation (P) and potential evapotranspiration (PET) datasets spanning 1960 to 2022 to compute the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) at temporal resolutions of 1-, 3-, 6-, and 12-months. The predictive efficacy of three computational models—Convolutional Long Short-Term Memory (CNN-LSTM), Random Forest (RF), and Support Vector Machine (SVM)—was systematically evaluated across semi-humid, semi-arid, and arid climatic zones. Empirical results elucidate three key findings: (1) CNN-LSTM outperformed its counterparts across all regions and time scales; RF demonstrated superior accuracy relative to SVM at 3- and 6-month lags, whereas SVM yielded stronger predictive power at the 12-month scale. Overall, the performance hierarchy prioritizes CNN-LSTM > RF > SVM for short-to-medium term forecasts, while CNN-LSTM > SVM > RF holds for long-term projections. (2) Model predictive accuracy achieved higher magnitudes when employing SPEI as the predictor compared to SPI within semi-arid and semi-humid domains. Conversely, in arid regions at extended time scales, SPI-12 outperformed SPEI-12, indicating that precipitation-dominated trends exhibit greater relevance for long-term drought forecasting in water-scarce areas. (3) Incorporating SPEI into the predictive framework conferred significantly enhanced performance in semi-arid and arid zones relative to semi-humid regions, further underscoring SPEI’s utility in water-limited landscapes. Collectively, this study elucidates the interrelationships among model architectures, drought indices, and regional climatic characteristics, thereby establishing a scientific basis for developing regional drought early-warning systems and decision-support tools. These outcomes carry practical implications for optimizing agricultural management strategies and regulating water resources.
Loess Plateau; drought prediction; SVM; RF; CNN-LSTM; SPI; SPEI.
Research on the Performance of SiC Particle Reinforced Aluminum Matrix Composite Brake Discs
To meet the performance requirements of wear resistance, energy saving and consumption reduction during operation, as well as speed and noise reduction for rail transit brake discs, a SiCp/A356 composite material with a SiC particle volume fraction of 20% was prepared by liquid stirring casting method using SiC particles as reinforcement and A356 aluminum alloy as matrix. Firstly, experiments were conducted on the thermal cycling characteristics, crack propagation, and fracture performance of the high-speed train brake disc made of this material. Secondly, a brake disc model was established using HYPERMESH software. Then, finite element simulation analysis of the temperature and stress fields under emergency braking conditions at 200km/h was conducted using ANSYS software to study the fracture failure mechanism. Compared with traditional steel brake discs, the results show that the maximum temperature during the braking process of SiCp/A356 reinforced aluminum based composite brake discs is reduced by 29.6% compared to ordinary steel materials; The amplitude of stress changes is small, which can effectively reduce thermal damage to the surface of the brake disc; The fatigue life is increased by about 20% compared to ordinary steel materials, exhibiting excellent mechanical and fatigue properties.
Research on Curvature Adaptive Control Method for ABB Robot Blade Polishing Residuals
To address challenges in traditional blade polishing such as low error control precision, irrational path planning, and poor parameter matching of belt pulleys, error control methods were investigated using ABB industrial robots as execution platforms and belt pulleys as polishing tools, combined with curvature adaptive algorithms. By analyzing blade surface curvature characteristics, a correlation model linking polishing errors to parameters and surface curvature was established. A curvature-adaptive error control algorithm was designed to dynamically adjust polishing parameters across different curvature zones. Simulation environments were built using Robot Studio platform to validate error control through both simulation and experimental testing. Results demonstrate that: In high-curvature zones, polishing errors reach 0.012mm at 1500r/min belt speed and 80N polishing force; In medium-curvature zones, errors minimize to 0.009mm at 1700r/min belt speed and 70N force; In low-curvature zones, errors decrease to 0.007mm at 2000r/min belt speed and 60N force. The curvature-adaptive control strategy achieves an average error of 0.011mm and a maximum error of 0.021mm, both remaining within the target error range of 0.1mm. Compared to traditional fixed-parameter methods, this approach improves allowance control precision by 61.1%. These findings provide theoretical support and technical references for automated high-precision blade polishing.
Research and Practice on Meteorological Data Security Supervision Technology Based on Tianqing·Qinghai
To address the challenges of data circulation security supervision in the meteorological big data environment and enhance the security protection capabilities of meteorological data usage in Qinghai Province, this paper, based on the "Tianqing·Qinghai" meteorological big data cloud platform and the "Tianjing·Qinghai" comprehensive business monitoring system, adopts three core methods: data structure processing, data denoising, and data security usage auditing. It integrates advanced technologies such as distributed collection control, parallel computing, and big data storage to construct a meteorological data security supervision system. The research focuses on three dimensions: the development of meteorological data security supervision technology, analysis of usage situations, and security risk management. It establishes the judgment rules and disposal processes for six types of data security risk events, achieving real-time monitoring of account access behaviors, precise control of key accounts, and collaborative handling of risk events. Practical application shows that this system can effectively reduce data security risks, improve supervision efficiency, and provide a replicable technical solution and practical reference for data security governance in provincial meteorological departments.
Study on the Flow Field Characteristics of a Gas–Liquid–Solid Three-Phase Combined Impeller Agitator Based on CFD
To address the issues of mixing efficiency and impeller configuration in the gas–liquid–solid three-phase system during CO₂ mineralization and sequestration using coal-based solid waste, a numerical investigation of the internal flow characteristics in a three-phase stirred reactor was carried out using computational fluid dynamics (CFD). A reactor model was established using Fluent simulation software. The multiple reference frame (MRF) method was adopted to construct the stirring flow-field model, and the Navier–Stokes equations were employed as the governing equations. The standard k–ε turbulence model was applied to solve the fluid flow in the stirred tank. Under a stirring speed of 100 r/min, the flow-field characteristics of different impeller combination schemes were simulated and analyzed. By examining the axial, radial, and tangential velocity distributions at specific cross-sections of the reactor, and combining velocity contours with the distributions of solid volume fraction and gas volume fraction, the flow characteristics and mixing performance of different impeller combinations were comparatively studied. The results show that different impeller combinations have significant effects on the internal flow-field structure and multiphase distribution in the reactor. Among the investigated configurations, the combination of an upper double-helical ribbon impeller and a lower pitched-blade turbine impeller can generate a more pronounced axial circulation flow, promoting the suspension of solid particles and the dispersion of gas bubbles. This configuration results in a more uniform distribution of the three phases within the reactor and improves the overall mixing efficiency of the system. The findings provide a theoretical reference for the structural optimization of three-phase stirred reactors and the design of impeller combinations in the CO₂ mineralization and sequestration process using coal-based solid waste.
Double helical ribbon and three-pitched blade turbine combined impeller
Hardware-in-the-Loop Simulation of Pressure Measurement Modules in While-Drilling Systems
To address the issues of high cost and low efficiency in traditional testing of pressure measurement modules while drilling—which rely on physical sensors and simulated high-temperature environments—a testing system based on hardware-in-the-loop simulation technology is proposed to achieve efficient and low-cost performance verification of the measurement module. The system consists of a PC host computer, a real-time simulator (PXIe platform), and the measurement module. Simulation models of pressure and temperature sensors are built using Simulink and deployed to the real-time simulator via VeriStand software to emulate voltage and resistance signals consistent with those of actual sensors. A host computer interface is developed using C# to enable parameter configuration, data acquisition, and error analysis. The system validates the effectiveness of the temperature drift compensation algorithm through comparative experiments with and without correction. Test results show that the system can effectively simulate downhole sensor outputs, and after correction, the pressure measurement error is controlled within ±108 psi, significantly suppressing the influence of temperature on measurement accuracy. This verifies the feasibility and superiority of the hardware-in-the-loop simulation method in testing measurement-while-drilling modules.
Permanent Magnet Synchronous Motor Drive Control for High-Temperature Downhole Formation Sampling: Design and Experimental Validation
Downhole formation sampling requires stable motor control under high temperature and strong vibration. This paper presents an integrated permanent magnet synchronous motor (PMSM) control-drive system for a compact downhole sampling tool. The system combines miniaturized hardware, resolver-based feedback, field-oriented control, and an improved fuzzy two-degree-of-freedom PI speed controller to enhance low-speed stability and turn-count accuracy. Experiments were carried out under no-load, load, high-temperature, and vibration conditions. Results show that the system operates reliably at 150 °C and 20 g vibration, with steady-state speed error below 1% full scale and full-scale relative turn-count error below 0.5%. The proposed design provides a practical high-temperature motor-drive solution for downhole formation sampling tools.
Research on Ferromagnetic Resonance of Electromagnetic Voltage Transformers in Shale Gas Field Distribution Network
The shale gas field has vigorously implemented the "electricity replacing oil" extraction method. Promoting the wide application of distribution network automation technology in shale gas distribution networks. Regarding the frequent occurrence of ferromagnetic resonance faults caused by the saturation of electromagnetic voltage transformers. The current research fails to take into account the load characteristics and actual working conditions. This paper, based on the electromagnetic transient simulation software PSCAD, establishes a PT ferromagnetic resonance model for the 10kV non-grounded system of the Changning Shale Gas Field. The simulation analyzed the effects of line length, conductor cross-section and excitation conditions on ferromagnetic resonance, and proposed suppression measures for the PT high-voltage side through a linear resistor connection. The simulation results show that when the length of the line meets the resonance condition, an increase in length will lead to an increase in the amplitude and frequency of the resonant overvoltage. When considering the cross-sectional area of the electrical conductor, the overcurrent on the PT high-voltage side of the fracturing-specific line is greater than that of the conventional line, which is prone to causing the fuse to blow. The influence of excitation conditions on resonant overvoltage varies greatly. The resonant amplitude triggered by arc grounding faults is the highest. Finally, a protective measure is proposed where the neutral point of the primary winding of the PT is connected to a non-linear resistor, in order to prevent the frequent occurrence of resonance accidents.
a series of policies have been introduced
Rheological Characteristics and Engineering Predictive Modeling of Liquid CO₂/Guar Foam Fracturing Fluids
Although CO₂ foam fracturing fluids are partially heated by the formation during injection, the majority of the CO₂ phase remains in a liquid state along the wellbore. Therefore, investigating the rheological behavior of liquid CO₂ foam fracturing fluids is essential for accurate friction prediction and hydraulic parameter optimization. In this study, a high-precision rotational rheometer was employed to characterize the rheological properties of liquid CO₂/guar-based foam fracturing fluids under controlled temperature and pressure conditions. Compared with conventional large-scale pipe rheometers, the present method provides improved measurement accuracy, repeatability, lower experimental cost, and better variable control. Experimental results indicate that under high shear rate conditions (>30 s⁻¹), the power-law model adequately describes the flow behavior of the liquid CO₂/guar foam system, with a coefficient of determination (R²) greater than 0.996. The effects of CO₂ volume fraction, temperature, and pressure on the flow behavior index (n) and consistency coefficient (K) were systematically analyzed. An exponential temperature-dependent correlation model for rheological parameters was established, yielding an average prediction error of only 0.658%. The obtained constitutive relationship provides a reliable theoretical basis for generalized Reynolds number calculation and wellbore friction prediction, offering significant engineering guidance for CO₂ foam fracturing design.
Establishment of Pigging Model for CO2 Long-distance Pipeline Pigging Devices and Research on Pigging Performance
CO2 pipeline transportation is a key link in the development of carbon capture, utilization and storage (CCUS) technology. Due to the presence of impurities in the gas source and the special transportation conditions, hydrates are prone to form during the pipeline transportation of CO2. Therefore, pigging operations need to be carried out to ensure the safe and smooth operation of the pipeline. Based on the CO2 pipeline pigging parameters in the carbon capture and storage process of Kingsnorth, a pigging numerical model with the help of the pigging theory and pigging module of OLGA software was constructed in this study. The model verification results show that under the basic and full transportation volume conditions, the relative errors of the simulated values and the on-site detection values of the pigging time of the supercritical/dense-phase CO2 pipeline and the pigging speed at the pipeline outlet are 4.20%, 4.17%, 3.17%, and 3.86% respectively, all within the acceptable range of the project. Based on this model, a simulation study was conducted on the pigging work of a certain supercritical CO2 long-distance pipeline. The results show that the pigging effect of the intelligent pigging device is superior to that of the polyurethane mechanical pigging device. The pipeline pigging model established in this research can accurately predict the pigging performance of CO2 long-distance pipelines, providing a research method and guidance for the optimization of CO2 pigging devices.
Multidisciplinary Collaborative Treatment for Bilateral Posterior Tooth Loss Based on Occlusal Reconstruction: A Case Report
Objective To evaluate the value of occlusal reconstruction in multidisciplinary treatment for patients with long-standing bilateral posterior tooth loss, providing precise treatment references for complex dental arch defects with severe abrasion. Methods: A 66-year-old patient with long-standing bilateral maxillary posterior tooth loss, combined with severe full-mouth abrasion, deep overbite, and chronic apical periodontitis underwent imaging to assess alveolar bone conditions and temporomandibular joint status. The Gilbach splint precisely determined the vertical dimension of occlusion (elevated by 5 mm). Using impressions andCAD/CAM technology to fabricate a splint for occlusal elevation, establishing the correct vertical dimension. This restored the patient's lower third facial height, chewing function, and aesthetic appearance. Treatment was implemented in four phases: basic therapy, occlusal adjustment, final restoration, and long-term maintenance. Outcomes were evaluated during a 3-year postoperative follow-up. Results: Occlusal reconstruction restored normal lower third facial height with significantly improved masticatory function. Implant osseointegration remained stable throughout follow-up, with no ceramic fractures or prosthetic loosening. Temporomandibular joint function was normal, and patient satisfaction was high. Conclusion Occlusal reconstruction effectively restores masticatory function in patients with long-standing bilateral posterior tooth loss, improves occlusal relationships, and maintains long-term stability.
Multimodal Sensing and Intelligent Disinfection Technology in Indoor Integrated Research and Application of Air Quality Management
This study addresses the practical needs of multi-parameter sensing and dynamic regulation in current indoor air quality management. Targeting the insufficient integration among monitoring, disinfection, and control components in existing purification systems, we adopt a research approach combining multimodal information fusion and closed-loop feedback control. Through theoretical modeling, system integration, and experimental testing, we explore the synergistic integration of multimodal sensing and intelligent disinfection technologies. By constructing a sensing unit incorporating nucleic acid fluorescence detection, laser particle counting, and multi-parameter gas sensors, combined with dynamic control strategies based on real-time sensor data, the system drives adjustable ultraviolet, low-temperature plasma, and photocatalytic modules to achieve adaptive disinfection. The system interconnects with air conditioning equipment via IoT protocols and incorporates power optimization algorithms to balance purification efficacy and energy consumption. Comparative analysis with traditional solutions demonstrates the feasibility of this integrated approach in enhancing comprehensive indoor air quality management. The research indicates that this integrated pathway provides a viable technical solution for collaborative and precise indoor air quality regulation.
Study on Heat Transfer Characteristics of Brush-Type Sealing Labyrinth
This study addresses the significant deviation between actual heat consumption rates and design values caused by inter-stage air leakage in a power plant steam turbine's staggered-tooth labyrinth seal system. Focusing on retrofitting existing labyrinth seals, we implemented brush seals at specific stator sealing tooth positions based on field operational data. The proposed hybrid system demonstrates that maximum temperature serves as the primary thermal performance metric for evaluating structural and operational parameters. Key findings include: 1) Positive correlations exist between brush wire diameter, bundle thickness, brush ring inner diameter, temperature, and rotational speed with maximum temperature, while negative correlations are observed for brush arrangement angle, front/rear plate height, brush ring outer diameter, sealing clearance, and pressure differential. Labyrinth tooth clearance has minimal impact. 2) Temperature variations primarily result from frictional heat generation and leakage variations caused by parameter adjustments.
Coal Series Sedimentary Environment and Coal Accumulation Characteristics of Xinyuan Coal Mine in Qinshui Coalfield
The Xinyuan Coalfield is located in Shouyang County, northwest of the Qinshui Coalfield. The primary coal-bearing strata within the field consist of the Upper Carboniferous Taiyuan Formation and the Lower Permian Shanxi Formation. Distinct coal accumulation environments have resulted in significant differences between these two strata in lithological composition, facies characteristics, and coal-bearing properties. Both formations represent transitional environmental deposits. The Taiyuan Formation features barrier coast and deltaic sedimentary systems, with stable and substantial thickness at coal seams No.8, 9, and 15, constituting stable recoverable coal seams across the region. In contrast, the Shanxi Formation develops deltaic sedimentary systems based on pre-deltaic and deltaic foreland deposits at the top of the Taiyuan Formation. While coal seams No.3 and 6 exhibit relative stability, their thickness varies, making them locally recoverable coal seams. Through systematic analysis of the Xinyuan Coalfield's stratigraphy, age determination of coal-bearing strata, coal seam correlation, and sedimentary environment evolution, this study summarizes the coal accumulation characteristics within the field, providing geological evidence for regional coal resource exploration and development.
Structural Design and Dynamic Sealing Failure Optimization of Metal C-Rings
Targeting the miniaturized static sealing and control valve radial dynamic sealing conditions, this paper constructs an integrated “Design-Verification-Optimization” research framework for metal C-rings. Based on the Inconel X750/718/Ag multilayer composite structure, high-temperature and high-pressure static sealing tests and reciprocating dynamic sealing wear studies were conducted. The results indicate that the helium leak rate of this C-ring at room temperature reaches 6.6×10-9 Pa• m3/s, and it passed the verification of 21.5 MPa water pressure and 40 high-temperature cycles. Dynamic sealing failure is dominated by friction and wear; when the sleeve bore roughness is reduced to Ra=0.8 μm, the life is significantly extended to over 15,000 cycles, with limited benefits from further reducing roughness. Considering both cost and performance, it is recommended to set the roughness threshold for both the dynamic sealing mating surface and the static sealing surface at Ra≈0.8 μm.
Experimental Study on The Mechanical Properties of High Territory-Steel Fiber-Rubber Concrete Under Multi-Component Coupling Effects
In this paper, the effects of multi-component coupled dosages on the compressive strength, splitting tensile strength, and flexural strength of concrete, a three-factor, three-level orthogonal experiment was employed, and the analysis of variance method was used to determine the primary and secondary order of the effects of materials on concrete properties. Results indicate that the single incorporation of rubber particles into traditional concrete optimizes impact resistance via elastic deformation but results in a significant reduction in strength. In contrast, high territory improves strength and durability by generating C-S-H gels through its pozzolanic activity, while steel fibers establish a three-dimensional supporting network that enhances crack resistance and toughness. The combined incorporation of high territory compensates for the strength loss by virtue of its filling effect and pozzolanic reaction, while steel fibers inhibit the propagation of micro-cracks at the rubber interface. SEM analysis results reveal that the hydration products of high territory–steel fiber-rubber concrete exhibit a smoother surface, fewer weak interfacial zones and better bonding between aggregates and cement mortar, which significantly improves the overall performance of the concrete.
Research on the Correlation between Microstructure and Macroscopic Properties of Magnesium Oxysulfide Foamed Lightweight Blocks Based on Proportion Optimization
To address the high carbon emissions and resource consumption of traditional Portland cement, this study prepared lightweight and high-strength magnesium oxysulfide foamed blocks based on magnesium oxysulfide cement by optimizing the raw material ratio, adding composite modifiers and compounding mineral admixtures. The effects of oxygen-sulfur ratio, water-sulfur ratio, citric acid-potassium aluminum sulfate composite modifier, silica-fly ash double admixture system and glass fiber reinforcement on the mechanical properties, water resistance and volume stability of the material were systematically investigated. The intrinsic correlation between macroscopic properties and microscopic structures (hydration product morphology, pore distribution, fiber-matrix interface) was revealed by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results showed that the optimal raw material ratio was MgO: MgSO₄:H₂O = 8:1:20, and the compound modifier (citric acid 1.2wt% + potassium aluminium sulfate 2.0wt%) significantly increased the softening coefficient from 0.41 to 0.91; The double addition of silica fume and fly ash (total dosage 30%, mass ratio 1:2) simultaneously increased compressive strength (66.2 MPa) and flexural strength (13.35 MPa), and significantly improved volume stability (28-day drying shrinkage strain reduced to 2304 µm/m). The lightweight block (with a bulk density of 800 kg/m³) prepared by physical foaming process has a compressive strength of 12.2 MPa and a 28-day volume shrinkage rate of only 1.11%; An addition of 0.6wt% of glass fibre can further enhance early strength and crack resistance. Microscopic analysis indicates that the increased generation of 5·1·7 phase (5 mg (OH)₂·MgSO₄·7H₂O) after modification, optimized crystal morphology, and densification of structure are the keys to the macroscopic performance improvement. The wall mechanics test confirmed that the compressive, shear and flexural strengths of the masonry met the requirements of the code. This study provides theoretical and experimental evidence for the industrial production and application of magnesium oxysulfide foamed lightweight blocks.
Flow Characteristics and Cavitation Behavior of an Industrial Gate Valve Based on CFD and Fluid–Structure Interaction Analysis
To reduce the dependence of small- and medium-sized enterprises on physical experiments during valve research and development, this study employs the SolidWorks Flow Simulation module to visualize and analyze the internal flow field of a DN100 industrial gate valve under different opening conditions. A steady-state computational fluid dynamics (CFD) model is established to systematically investigate the flow characteristics, pressure drop, flow resistance coefficient, and cavitation-sensitive regions at various valve openings. The influence of valve opening reduction on internal flow behavior and cavitation evolution is revealed. The results indicate that, with decreasing valve opening, the internal flow field exhibits pronounced pressure drops, significant velocity variations, and an expansion of cavitation-sensitive regions. At small openings, a distinct negative-pressure zone forms on the leeward side of the gate plate, accompanied by strong vortical structures and high-velocity jet flows. Meanwhile, the cavitation region expands progressively as the opening decreases, indicating an increased cavitation risk. The present study provides a valuable theoretical reference for analyzing valve flow characteristics under complex operating conditions.