Scientific Journal of Technology is a monthly online, international, peer-reviewed journal, dedicated to publish empirical, academic, theoretical and review research articles that contribute to the practice in science, technology, and related topics. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Research on Production Prediction of Shale Gas Wells Based on Grey Relation Analysis and Typical Decline Models
Against the backdrop of increasingly constrained global conventional oil and gas resources, the efficient development of shale gas, as a crucial unconventional alternative, is of paramount importance. Shale gas wells, particularly horizontal wells, exhibit a production decline behavior distinctly different from conventional gas wells, characterized by high initial rates followed by rapid decline, and ultimately transitioning to a long period of low-yield stabilization. This paper systematically investigates the production decline behavior of shale gas wells and the analytical methods of typical decline models. Firstly, it elaborates on the principles, formulas, and applicability of various models, ranging from the classical Arps decline model to modern models tailored for shale gas characteristics, such as the Duong, Power Law Exponential (PLE), Stretched Exponential Production Decline (SEPD), and Logistic Growth Model (LGM). Secondly, to address the insufficient analysis of factors influencing production decline, the Grey Relation Analysis (GRA) method is introduced. A complete analytical process—from determining analysis sequences and dimensionless processing to calculating the correlation degree—is established to quantify the impact of geological and engineering factors on the decline behavior. Finally, a comparative evaluation of the main analytical methods, including the Wattenbarger linear flow method, PLE, SEPD, Duong, and LGM, is conducted, highlighting their respective advantages, disadvantages, and application conditions. The comparison reveals differences among these models in terms of fitting accuracy, data sensitivity, flow regime identification, and early-time prediction capability. The research demonstrates that integrating grey relation analysis with appropriately selected decline models based on specific production stages and reservoir characteristics can more accurately elucidate the decline behavior of shale gas wells. This integrated approach provides a scientific basis for production forecasting, recoverable reserves estimation, and development plan optimization.
Shale Gas Wells; Production Decline; Grey Relation Analysis.
Copyright (c) 2025 Scientific Journal of Technology https://creativecommons.org/licenses/by-nc/4.0
Lithology Identification Method for Sandstone and Mudstone Based on the ADASYN-IRMO-CatBoost Combined Model
Accurate lithology identification is a crucial prerequisite for sedimentary environment analysis, oil and gas exploration, and development. Traditional identification methods have problems such as low efficiency, high cost, or limited applicability. This paper proposes an ADASYN-IRMO-CatBoost combined model. Firstly, the ADASYN algorithm is used to perform adaptive sampling on the logging datasets of three wells in the southern Ordos Basin to solve the problem of data imbalance. Then, the Improved Radial Movement Optimization (IRMO) algorithm is utilized to optimize the hyperparameters of the CatBoost model. Finally, CatBoost is used as the core classifier for lithology identification. Experimental results show that the overall accuracy of the combined model on the test set reaches 92%, which is 13% higher than that of the single CatBoost model. The F1 scores of various lithologies and the AUC values of the ROC curves are significantly better than those of the single model, demonstrating stronger classification performance and robustness. It provides an efficient and accurate new method for lithology identification of sandstone and mudstone reservoirs and has good application prospects in the field of geological exploration.
Lithology Identification; Logging Curves; Sample Imbalance; LightGBM Model; IRMO Algorithm.
Study on the Lower Bound of Reservoir Properties in the L Member of the Lower White Poplar River Formation, Tertiary System, Yaxia Oilfield
Addressing the ambiguity surrounding the lower limits of effective reservoir properties in the L Member of the Biaoyanghe Formation, Tertiary System, in the Yaxia area, this study employs a multidisciplinary approach integrating property data, logging interpretation results, sedimentary facies analysis, and cast thin sections. It investigates the lower limits of effective reservoir properties and analyzes the primary factors governing their development. The study indicates that the lower limits for the L Member in the study area are: , porosity 8.2%, and permeability 1.5×10⁻³μm².
Effective Reservoir; Minimum Physical Properties; Controlling Factors; Baiyanghe Formation; Yaxia Area.
Study on Reservoir Characteristics and Main Controlling Factors of Chang-7 Reservoir in the Southwest of Wuqi Oilfield
This paper focuses on the problems of unclear oil and gas enrichment laws and difficult prediction of favorable zones in the tight reservoir of the Chang-7 member in the southwest of Wuqi Oilfield. It conducts research on reservoir characteristics and main controlling factors to provide a geological basis for efficient exploration in this area. By comprehensively applying technical methods such as detailed core observation, cast thin sections, scanning electron microscopy, high-pressure mercury intrusion, and basin simulation, the petrology, pore structure, and physical properties of the reservoir are systematically analyzed, and the controlling mechanisms of tectonism, sedimentation, and diagenesis are deeply discussed. The results show that the Chang-7 reservoir in the study area is an ultra-low porosity and ultra-low permeability lithic arkose sandstone, with intergranular pores and feldspar dissolution pores as the main pore types. The reservoir quality is controlled by multiple factors: sedimentary facies zones control the distribution of high-quality reservoirs such as sandy debris flows and turbidite sand bodies; in diagenesis, strong compaction and cementation lead to reservoir densification, while dissolution effectively improves the reservoir space; most importantly, the tectonic uplift and denudation since the Late Cretaceous have significantly improved the seepage capacity of the reservoir through elastic rebound and pressure reduction expansion mechanisms. Tectonic uplift is the key acquired constructive factor for improving the physical properties of the reservoir in the study area, and the paleotectonic high areas and areas with strong uplift and denudation are the favorable targets for further oil and gas exploration.
Southwest of Wuqi Oilfield; Chang-7 Reservoir; Tectonism; Sedimentation; Diagenesis.
Current Research Status and Development Trends of Mine Ventilation Technology in China
Mine ventilation is a crucial safeguard for safety in mine production. This paper provides an in-depth analysis of the current development status and future trends of mine ventilation technology in China. By reviewing the technological evolution, intelligent transformation practices, breakthroughs in key technologies, and the effectiveness of industry applications, it reveals the core values of mine ventilation systems in ensuring safety, enhancing energy efficiency, and promoting green development. Combining policy guidance, market demands, and directions of technological innovation, the paper indicates that future mine ventilation technology will evolve towards deep intelligence, full-factor digitization, and green and low-carbon development. Furthermore, it proposes development suggestions such as strengthening basic research, improving standard systems, and cultivating interdisciplinary talents, providing theoretical support for promoting safe and efficient mining operations in China.
Mine Ventilation; Technological Status; Development Trends; Intelligence; Digitization; Green Mine.
Analysis of the Influence of Structural Parameters of Coupling-Type Casing Threads on Joint Connection Strength
Casing drilling technology originates from mining wire-line coring technology. It uses casing as the drill string to perform drilling and casing running simultaneously without the need for pulling out. This technology can solve downhole accidents in complex formations and is suitable for large-sized boreholes. However, due to the characteristics of the casing, the joint connection strength is weak, the performance is poor, and the thread stress is complex and uneven, making it the weakest link of the pipe string. To fill the gap in the existing research on the influence of thread structure on joint strength, this paper establishes a mechanical analysis model for casing joint threads, explores the influence laws of two factors, namely variable tooth width and shoulder clearance, on the torsional resistance performance of casing threads, and provides a reference for the research on the structural optimization of casing joint threads. The research results show that reducing the tooth width at the small end of the male thread and increasing the tooth width at the small end of the female thread can balance the maximum stress of the male and female threads and improve the load-bearing capacity of the threads. However, a further increase in the tooth width ratio will lead to excessive stress at the small end of the male thread, making it the main failure part. With the increase of shoulder clearance, the stress begins to decrease, and the maximum stress shifts from the female shoulder to the first thread turn. However, an excessively large clearance will reduce the load shared by the shoulder and cause an increase in the overall stress of the thread.
Casing Drilling Technology; Special Thread; Torsional Resistance Performance; Stress Distribution; Finite Element Analysis.
Recent Advances in Characterizing the Interfacial Mechanical Properties of Composites based on Ultrasonic Inversion
In response to the growing demand for composite materials with high specific strength, high specific stiffness, and lightweight structural characteristics, this paper systematically reviews the development and research progress of ultrasonic characterization techniques for fiber–matrix interfaces. The mechanical and durability properties of composites are largely governed by the interfacial bonding quality and its evolution mechanisms. However, interfacial damage is often concealed within the material, highlighting the urgent need for quantitative and nondestructive monitoring approaches. First, the paper reviews the emergence and development of the Scanning Acoustic Microscope in the 1970s and elaborates on its pioneering role in revealing interfacial microstructures and early-stage debonding phenomena. Subsequently, it focuses on the quantitative studies since the 1990s based on the imperfect interface spring model, including the introduction of normal and tangential stiffness parameters (KN and KT), the development of reflection/transmission inversion methods, and the establishment of spectrum–angular spectrum analysis techniques. These advances enabled a paradigm shift in interfacial characterization—from mere visualization to quantitative evaluation. In the 21st century, research has further evolved toward refined modeling, optimized inversion algorithms, and engineering-oriented applications, leading to the formation of multi-angle, multi-frequency, and multimodal integrated detection frameworks. By integrating signal processing, finite element simulation, and machine learning, the accuracy and stability of interface parameter inversion have been significantly enhanced. Finally, the paper summarizes the major challenges in this field, including model ill-posedness, adaptability under complex environments, and difficulties in data fusion. It also envisions future developments toward intelligent, real-time, and multi-physics-coupled characterization approaches.
Composites; Fiber–Matrix Interface; Ultrasonic Characterization; Inversion Algorithms; Nondestructive Testing.
Discrete Fracture Network Simulation of Shale Reservoir
Shale reservoirs are characterized by low porosity, low permeability, and extensive natural fractures, where fluid migration and storage primarily depend on complex fracture networks. As the primary flow channels in shale reservoirs, natural fractures not only directly govern hydrocarbon migration and distribution but also significantly influence the expansion of hydraulic fracturing fracture networks and fracturing effectiveness. Given the pronounced heterogeneity, anisotropy, and fractal characteristics of shale fractures, traditional equivalent continuum models struggle to accurately describe their intricate geometry and flow behavior. This study employs a discrete fracture network (DFN) simulation method to model spatial parameters including fracture orientation, inclination angles, and lengths. The results provide a realistic representation of natural fracture distribution in shale reservoirs, offering enhanced structural foundations for reservoir evaluation, fracturing design, and flow simulation. Therefore, DFN modeling of natural fracture systems in shale reservoirs serves dual purposes: it provides crucial insights into storage mechanisms and flow processes, while also constituting a pivotal element for optimizing shale hydrocarbon development efficiency and fracturing operations.
Shale Reservoir; Geometric Parameters; Natural Fractures; Discrete Fracture Network.
Parameter Optimization of the Critical Liquid-Carrying Flow Model based on The Field
The critical liquid-carrying flow rate is a core parameter for the dynamic regulation and reasonable production capacity assessment of gas Wells. The accuracy of its calculation formula directly affects the early warning of liquid accumulation in gas Wells, the optimization of production systems and the development benefits. The critical liquid-carrying flow calculation formulas widely used at home and abroad (such as Turner model, Min Li model, etc.) often have significant deviations from the on-site measured values under complex working conditions (high sulfur content, high pressure, low production, etc.) due to the failure to fully consider the flow state changes of gas-liquid two-phase, the coupling effect of fluid physical property parameters, and the actual structural differences of the wellbore. It is difficult to meet the precise development requirements. To enhance the applicability of the formula and the calculation accuracy, based on the theory of gas-liquid two-phase flow and combined with the on-site measured data of 325 production Wells in a certain gas field, this paper optimizes the critical liquid-carrying flow model.
Critical Liquid-carrying Flow Rate; Gas Reservoir Development; Dynamic Analysis.
Distribution and Genesis of Permian Overpressure in the Eastern Fukang Sag, Junggar Basin
Overpressure is widely distributed in the Permian strata of the eastern Central Depression in the Junggar Basin and is closely related to hydrocarbon reservoirs. However, its genesis, evolution process, and controlling effects on reservoir formation remain unclear. Using comprehensive mudstone compaction curves and vertical effective stress-density crossplots, the formation mechanisms of abnormal high pressure in the Permian strata of the study area were analyzed. On this basis, the basin modeling method was applied to reconstruct the overpressure evolution for different lithologies in the Permian strata, summarize its planar distribution patterns, analyze the impact of overpressure on hydrocarbon reservoirs within the area, and further summarize the hydrocarbon accumulation models under the control of Permian overpressure in the study area. The results indicate: (1) The Permian strata in the study area develop weak to strong overpressure, with significant differences in the magnitude of overpressure developed in different structural locations. The overpressure is strongest in the sag area, followed by the slope zone, and relatively weak in the uplift area. (2) The genesis of overpressure varies significantly among different lithologies. The overpressure in the source rocks of the Lucaogou Formation is attributed to hydrocarbon generation and undercompaction; the overpressure in the reservoir of the Upper Wuerhe Formation is attributed to overpressure transfer and undercompaction; the overpressure in the mudstone caprock of the Upper Wuerhe Formation is attributed to undercompaction.
Junggar Basin; Fukang Sag; Permian; Overpressure Genesis.
Experimental Study on the Thermal Response Characteristics of Porosity in Sandstone
The pore structure of sandstone directly influences its physical and mechanical properties as well as its fluid seepage capacity, with temperature being a key factor in altering this structure. This study simulates thermal effects by heating sandstone samples in a muffle furnace to explore the evolution patterns of sandstone porosity under different temperatures. Standard sandstone samples were primarily selected, prepared, and then heated isothermally at various temperatures. Porosity was measured based on the physical process where non-wetting liquid, driven by pressure, overcomes surface tension to infiltrate pores. This research provides crucial experimental evidence for understanding the damage mechanisms in sandstone reservoirs under thermal stress and offers guiding significance for engineering practices such as oil-type gas management.
Sandstone; Heat Treatment; Porosity; Thermal Damage; Temperature Effect; Muffle Furnace.
Research on the Digital Transformation Path in Engineering Education Based on AI and VR
Under the backdrop of the Ministry of Education's "Education Digitalization Strategy Action," this study uses the Shanghai municipal key course Tolerance, Fit and Technical Measurement as a practical vehicle to construct a new four-dimensional integrated teaching paradigm: "AI Empowerment + Knowledge Graph + Virtual Simulation + Curriculum-based Ideological Education." By integrating the Tencent IMA smart teaching platform, the DeepSeek large model, and VR experimental technology, a smart teaching closed-loop covering the entire "pre-class-in-class-post-class" process was formed. Empirical data shows that this model increased course participation to 98%, improved experiment operation accuracy by 32%, and elevated students' overall scores by an average of 18.7%. This research provides replicable technological pathways and practical case studies for the digital transformation of engineering education.
Educational Digitalization; Artificial Intelligence; Knowledge Graph; Virtual Simulation; Tolerance and Fit; Curriculum-based Ideological and Political Education.
Investigation on the Current Status of Functional Movement Screen(FMS) for Male Specialized Football Athletes in Colleges and Universities
Football is a high-intensity competitive sport that involves the shoulders, torso, and lower limbs of the body. During movement, various parts of the body engage in complex coordination to achieve movements such as footwork, foot frequency, sprinting, turning, and jumping. This sport requires athletes to have highly developed physical fitness and is often accompanied by sports injuries. The seven test movements in Functional Movement Screening (FMS) include the basic movement patterns of the human body. It is a measurement tool used to evaluate the quality of athletes' movements and exercise risks. Based on the results, the training plan can be adjusted accordingly, and corrective training can be carried out to reduce exercise risks and improve athletic performance. At present, the application of this measurement tool in college football special athletes is relatively limited. Therefore, this article selects this group for research, with two research objectives: firstly, to understand the overall and sub scoring characteristics of FMS for male specialized football players in universities through testing, and secondly, to explore the relationship between FMS test results and athletes' sports injuries. This study focuses on 18 male football students majoring in physical education from Lvliang University who participated in the Shanxi Province Campus Football League. Firstly, before the test, the subjects filled in a survey questionnaire about their training time and sports injury history within one year. Then, the functional movement quality of the subjects was tested using a functional movement screening kit. After the test, the distribution characteristics of the overall and sub item scores of the subjects' functional movements were analyzed based on the data, and the relationship between the athlete's FMS test score and sports injury was explored. (1) According to the FMS test results of 18 participants, it was found that the athlete's total score was the highest at 17 points, with only one person; The minimum score is 7 points, and there is only one person, each accounting for 5% of the total sample size. The highest number of people scored between 11-14, with a total of 13 people, accounting for 72.2% of the total sample size. According to the gold standard for FMS scores, subjects with a total score below 14 are prone to sports injuries, with a total of 9 people, accounting for half of the football team. This indicates that the overall testing level of the team is not high, and the quality of the movements completed in FMS is poor, making the possibility of sports injuries very high. (2) After analyzing the scores of each sub item in the test, it was found that the athletes' scores in each event were mainly concentrated in 1 and 2 points. The test with the highest score of 3 points was the over the top squat event, which may be due to the fact that this event can reach the standard testing ability after a short period of training. The athletes who scored 2 points in the shoulder flexibility test were the most, which may be due to the fact that team members often engage in shoulder exercises during regular classes, training, and competitions, which improves shoulder flexibility. The test with the highest score of 1 is the trunk rotation stability project, because this test requires particularly high coordination ability, and athletes who have not undergone systematic training find it difficult to maintain limb coordination stability. After investigation, it was found that the functional movement screening scores of male football special athletes from Lvliang College were relatively low. The core stability and control ability of the body, as well as the flexibility of the ankle joint, need to be strengthened. The strength of the quadriceps and rectus femoris muscles needs to be strengthened. Pelvic stability and the flexibility and coordination ability of the lower limb muscles are poor, and the risk of sports injuries is high. In the training after the football team, targeted corrective training should be strengthened, and FMS testing should be used in regular training to reflect the risk of sports injuries and performance of athletes, and to continuously improve the team's sports level based on this indicator level.
Campus Football; Football-specific; Functional Movement Screening; FMS Test.
Accessibility Analysis of Urban Park Green Spaces in Nanning City Based on Network Analysis and G2SFCA
The accessibility of urban park green spaces holds significant importance for the daily lives of city dwellers and for evaluating urban liveability. This study integrates the Gaussian two-step floating catchment area method (G2SFCA) and network analysis to assess the accessibility distribution characteristics of park green spaces in Nanning City. The G2SFCA accounts for population density and park area to quantify per capita service capacity, while network analysis simulates real transport networks to evaluate distance- based and time-based accessibility. Results indicate significant disparities in accessibility across Nanning's districts: Qingxiu and Liangqing District exhibit the highest accessibility with average proportions of 65.84% and 45.54% respectively, while Xixiangtang and Xingning District record the lowest at 18.01% and 16.61%. Spatial Autocorrelation Analysis (Moran’s I = 0.928) further indicates pronounced clustering, with high–high clusters concentrated in the southeast and low–low clusters in the northern and western areas. The comparative analysis highlights the methodological complementarity between supply–demand based and distance–cost based evaluations, providing a more robust understanding of green space accessibility. Policy recommendations suggest prioritising the addition of community parks and green corridors in low-accessibility and high-density areas such as northern Xixiangtang and western Jiangnan, while consolidating the “large core–small node” layout along the Yongjiang River. This research offers scientific support for ecological spatial planning and contributes to advancing the development of a liveable and sustainable urban environment in Nanning.
Urban Park Green Spaces; Accessibility; Network Analysis; Gaussian Two-Step Floating Catchment Area Method (G2SFCA); Nanning City.
Study on Energy Conversion Performance and Transmission Mechanism of New Thermoelectric Materials under High Temperature Gradient
This study focuses on the energy conversion performance and transmission mechanism of new thermoelectric materials under high temperature gradient. Aiming at the problems of poor thermal stability and low figure of merit (ZT) of traditional thermoelectric materials in high temperature environment, a gradient composite structure (STBT) based on SrTiO₃ with high melting point and Bi₂Te₃ with chalcogenide was designed and constructed. Continuous transition of composition is achieved through spark plasma sintering (SPS) technology, forming an interface diffusion layer with good metallurgical bonding. By combining in-situ high-temperature characterization and multiscale simulation, the electrical thermal transport operation of materials under high-temperature gradients was systematically studied in relation to their microscopic mechanisms. The results show that the STBT material has a Seebeck coefficient of -520 μ V K⁻¹ at 700 K, a power factor of 130μW m⁻¹ K⁻², and a lattice thermal conductivity reduced to 1.6 W m⁻¹ K⁻¹, ultimately achieving a ZT value of about 0.57, an order of magnitude increase compared to a single component. The performance improvement is attributed to the enhanced Seebeck coefficient due to the interface energy filtering effect, as well as the significant suppression of thermal conductivity by phonon scattering induced by thermal stress. This study provides new ideas for the design of high-temperature thermoelectric materials and demonstrates the enormous potential of gradient structures in synergistically optimizing the electrical and thermal transport performance.
Energy Conversion; Transmission Mechanism; Thermoelectric Materials; High Temperature; SrTiO₃; Bi₂Te₃; Energy Filtering; Non-harmonic Vibration; Gradient Composite Structure.
MOF-Based Solid-State Batteries: An Ideal Choice for High Safety and Environmental Protection
With the widespread application of lithium-ion batteries in fields such as power, energy storage, and consumer electronics, the environmental pollution and resource waste issues caused during their manufacturing and recycling processes have increasingly drawn the attention of all sectors of society. To address the above problems, the research on environmentally friendly battery systems has been put on the agenda. Among them, solid- state batteries have received significant attention from both the academic and industrial communities due to their characteristics of having no organic electrolyte, high safety, and high energy density. In this study, a ZIF-8-PVDF- HFP-IL composite solid electrolyte was prepared by compounding a metal- organic framework (MOF) ZIF-8, a polymer matrix PVDF-HFP, and an ionic liquid (IL). Through various performance tests, it was demonstrated that the ZIF-8-PVDF-HFP-IL composite solid electrolyte exhibits good mechanical strength and thermal stability, and can maintain its shape even at high temperatures (300 °C). Moreover, it self-extinguishes within 1.5 s after combustion, indicating excellent flame retardancy. In addition, the room- temperature ionic conductivity of the ZIF-8-PVDF-HFP-IL composite solid electrolyte reaches 0.36 mS cm⁻¹ , which is 2 - 3 orders of magnitude higher than that of conventional polymer solid electrolytes. Finally, when the ZIF-8- PVDF-HFP-IL composite solid electrolyte was assembled into a pouch battery, the battery could still operate normally after being physically damaged, demonstrating extremely high safety performance. This research verifies the feasibility of the proposed solid electrolyte preparation strategy, has the potential to replace existing liquid lithium-ion batteries, and thus provides a new technical solution to address the environmental pollution and resource waste issues caused by the preparation and recycling of liquid lithium-ion batteries.
ZIF-8-PVDF-HFP-IL Composite Solid Electrolyte; Anti-thermal Shrinkage; Flame Retardancy; High Safety; Environmental Pollution Caused By Battery Leakage.
Configuration Design and Performance Evaluation of Deep-Sea Self-Powered Power Generation Devices based on High-Voltage Thermoelectric Materials
Aiming at the energy bottleneck of long-term operation of deep-sea equipment, this paper proposes a high-voltage self-powered power generation device with new Ag₁.₉₉₅Au₀.₀₀₅Te₀.₇S₀.₃ nano-thermoelectric materials as the core. Through Au doping and Te/S ratio control, the ZT value of the material reaches 1.2 at 300 K, and the thermal conductivity of the lattice decreases below 0.4 W/m·K; Adopt TA32 titanium alloy shell+vacuum potting +Inconel 718 metal seal to realize 30 MPa pressure resistance. Trapezoidal array layout and micro-channel water cooling design make the thermal efficiency of the system reach 85%, and the output power density is 320 W/m² and the conversion efficiency is 8.5% under the temperature difference of 10 K deep sea, which is 407% and 124% higher than that of the traditional Bi₂Te₃ system respectively. Integrating 1850 kWh Ferrous lithium phosphate energy storage and SiC inverter, the end-to-end energy utilization rate of 72 h system is 7.8%. After 500 h aging in 30 MPa and 3.5% NaCl environment, the power attenuation is only 4.7%, which verifies the stability and engineering application potential of the device under extreme conditions in deep sea.
Configuration Design; Performance Evaluation; Power Generation Devices; High-Voltage Thermoelectric Materials; Ag₁.₉₉₅Au₀.₀₀₅Te₀.₇S₀.₃ Nanometer Thermoelectric Material.
A Novel Optimization Method for Electric Capacitated Vehicles Routing Problem Considering Battery Degradation Based on Hybrid Neighborhood Search Algorithm
With the growing adoption of electric vehicles in logistics, the electric capacitated vehicle routing problem has become increasingly important. The battery, as a core component of electric vehicles, directly affects operational costs due to its degradation over time. Therefore, incorporating battery degradation into vehicle routing optimization is essential. This study incorporates battery degradation cost into the objective function, establishing a comprehensive mathematical model that further reduces overall transportation costs. Meanwhile, a hybrid genetic neighborhood search algorithm is developed by introducing the operator mechanism of neighborhood search into the genetic algorithm framework. This integration accelerates convergence and improves solution quality by combining the global search capability of genetic algorithms with the local refinement strength of neighborhood search. Numerical experiments demonstrate the effectiveness of the proposed algorithm, offering valuable insights and guidance for optimizing electric vehicle routing problems under realistic operational conditions.
Electric Capacitated Vehicle Routing Problem; Battery Degradation; Hybrid Genetic Neighborhood Search Algorithm.
A High-Precision Constant Temperature Control System for Microenvironments in Industrial HVAC Systems
In industrial HVAC (Heating, Ventilation, and Air Conditioning) systems, precise temperature control is critical for ensuring process stability, product quality, and equipment reliability. To address the demand for high-precision temperature regulation in localized microenvironments within industrial settings, a high-precision constant temperature control system was developed for industrial HVAC applications. This system utilizes an Arduino Uno microcontroller, integrated with DS18B20 digital temperature sensors and NTC thermistors, and employs a PID algorithm combined with relay feedback tuning to achieve adaptive, high-precision temperature control. Extensive operational testing demonstrates that the system can rapidly respond to and accurately regulate microenvironment temperatures in complex and variable industrial conditions, achieving temperature control accuracies of ±0.2°C for cooling and ±0.4°C for heating. This solution provides an efficient and stable temperature management approach for industrial HVAC systems.
Industrial HVAC; Temperature Control; PID Algorithm; Semiconductor Cooling.
Design of Intelligent Fire Extinguishing Vehicle Based on STM32
Aiming at the problems of high safety risks for personnel in fire rescue and the lagging response of traditional fire-fighting equipment, this paper designs an intelligent fire-extinguishing trolley control system with the STM32F103C8T6 microcontroller as the core. The system integrates a power supply circuit, motor drive circuit, multi-sensor detection modules (flame, temperature, smoke, obstacle avoidance) and a fire-extinguishing actuator to realize functions such as fire source positioning, automatic obstacle avoidance, sound and light alarm, and desiccant spraying for fire extinguishing. In terms of hardware selection, the L298N chip is used to drive the DC motor to realize the trolley's motion control; the DS18B20 sensor is used for temperature measurement, the AC4067 infrared sensor for flame detection, the MQ-2 sensor for smoke detection, and the E18-D80NK sensor for obstacle avoidance, ensuring the coordinated and stable operation of each module. Tests show that the trolley can quickly detect the fire source, accurately avoid obstacles, and start fire extinguishing within 10 seconds after locating the fire source, which can effectively improve the efficiency of initial fire handling and reduce the risk of casualties.
Intelligent Fire-extinguishing Car; STM32F103C8T6; L298N; Multi-sensor Fusion.
Research on Drilling Technology Methods and Application Effects in Geological Engineering Exploration
Drilling technology is one of the core means of geological engineering exploration. This article systematically reviews the commonly used technical methods in geological engineering exploration, such as rotary drilling, impulse drilling, vibratory drilling, hydraulic rotary drilling, and pneumatic drilling. It focuses on analyzing the principles, characteristics, applicable conditions, and existing problems of each type of drilling technology. On this basis, the application status of drilling technology in geotechnical engineering investigation, hydrogeological investigation, mineral resource exploration and other fields was further explored. The exploration accuracy and quality, efficiency and cost, environmental impact, etc. of drilling technology were systematically evaluated, and corresponding optimization countermeasures and suggestions were put forward, with the aim of providing references for improving the level of drilling technology and better serving the practice of geological engineering exploration.
Geological Engineering Exploration; Drilling Technique; Application Effect; Optimizing Strategy.
An Exploration of Enterprise ESG Practice Paths Based on Fintech Innovation
With the deepening global adoption of sustainable development, environmental, social, and governance (ESG) considerations have become core dimensions for measuring a company's overall value. The rapid evolution of Fintech offers new avenues for companies to overcome bottlenecks in ESG practice. This article explores the inherent connection between Fintech innovation and corporate ESG practices. Through literature analysis and logical deduction, it identifies pain points in corporate ESG practices, such as irregular data collection, opaque information disclosure, and inefficient performance evaluation. The article then analyzes these issues from the perspectives of technology, implementation, and risk. The study finds that Fintech tools such as big data, blockchain, and artificial intelligence can play a key role in ESG data integration, credible disclosure, and intelligent assessment, respectively. Companies must integrate Fintech into the entire ESG governance process through a comprehensive approach of "technology adaptation - architecture optimization - collaborative collaboration." At the same time, they must mitigate risks such as data security and insufficient technological adaptability. This article aims to provide theoretical guidance for companies leveraging Fintech to improve the quality of their ESG practices, helping them achieve the dual goals of sustainable development and value enhancement.
Fintech Innovation; Enterprise ESG; Practical Path; Data Governance; Green Finance.
Diagenetic Facies Division of Different Types of Sandstone Reservoirs and Their Differentiation
In response to the increasing proportion of low-porosity, low-permeability, and tight sandstone reservoirs in current oil and gas exploration, this paper conducts a systematic study on diagenetic facies division. First, the development stages and existing problems of diagenetic facies research are reviewed, with an emphasis on the objective of establishing a scientific classification system. The study highlights the core criteria for facies division, including types and intensities of diagenesis, petrographic characteristics, pore and petrophysical features, as well as logging responses and quantitative models. Differentiated emphasis is proposed for reservoirs of different types. Finally, a general methodological framework is constructed, progressing “from micro to macro, from qualitative to quantitative,” providing systematic ideas and methodological support for diagenetic facies research and favorable zone prediction in various types of reservoirs.
Diagenetic Facies Division; Sandstone Reservoirs and Their Differentiation; Different Types of Reservoirs; Quantitative Models; Logging Responses; Overall Methodological Framework.
Research on the Quantitative Evaluation and Methods of Drilling Overflow Risk Based on While-Drilling Information
In order to solve the problems of insufficient generalisation ability and poor interpretability of evaluation results in the complex geological environment of the current data-driven overflow risk assessment model, this paper proposes a quantitative overflow risk assessment method based on the combination of CNN-LSTM data-driven model and fuzzy reasoning system. The data features were extracted, the overflow risk was predicted, the fuzzy comprehensive evaluation method was further adopted, the membership function was generated based on the normal distribution fitting historical data, the risk probability threshold was dynamically calibrated, the risk was refined into low, medium and high levels, and the expert experience was integrated through fuzzy reasoning rules to improve the transparency and flexibility of overflow risk assessment. The experimental results show that the accuracy of the proposed method is 99.95%, and the false alarm rate is only 0.5%, which significantly improves the adaptability and reliability of risk assessment compared with the traditional static threshold method, and enhances the interpretability of the model through feature visualisation and dynamic rules, which provides intelligent decision support with both high precision and strong robustness for drilling safety.
Overflow Risk; Composite Model; CNN-LSTM; Quantitative Evaluation.
TransDeeplab: A Novel Architecture for Medical Image Segmentation
Early and accurate diagnosis of brain tumors plays a critical role in improving patient prognosis. Magnetic Resonance Imaging (MRI) serves as the core diagnostic modality; however, the inherent heterogeneity of brain tumors and the complexity of their morphological boundaries pose significant challenges for traditional segmentation methods, limiting their clinical applicability. To address this issue, we propose the TransDeepLab model, aiming to develop an efficient and precise brain tumor segmentation algorithm. The model integrates DeepLabV1 and Vision Transformer (ViT) within an Encoder–Decoder U-shaped architecture, leveraging the strengths of local feature extraction and global context modeling. Moreover, we introduce two novel components: a Feature Information Exchange Module to enhance feature fusion and a Trainable Gated Selection Module to optimize feature utilization. Using the BraTS2021 dataset and implemented within the PyTorch framework, the proposed approach is rigorously evaluated against state-of-the-art segmentation methods in terms of accuracy, robustness, and computational efficiency. The study aims to provide an automated, high-precision brain tumor segmentation tool to advance intelligent healthcare in the field of neuro-oncology.
Brain Tumor Image Segmentation; Deep Learning; TransDeepLab Model; Vision Transformer (ViT); BraTS2021 Dataset.
Research on Micro Expression Emotion Recognition Algorithm Based on Improved YOLOV8 and ResNet
With the rapid advancement of artificial intelligence, micro-expression recognition has demonstrated significant application value in fields such as criminal investigation and lie detection. However, the extremely short duration of micro-expressions and the scarcity of annotated data pose substantial challenges to accurate recognition. This study proposes a two-stage micro-expression recognition method based on an improved YOLOv8 and ResNet framework. In the first stage, a YOLOv8 model enhanced with StarNet multi-scale feature fusion and the CBAM attention mechanism is employed to achieve high-precision face detection. In the second stage, the detected static facial frames are fed into a ResNet50 network embedded with an SE module to strengthen channel-wise feature representation, thereby enabling micro-expression classification. For experimental validation, the improved models were trained and tested on the WiderFace and RAF-DB datasets. Results indicate that the improved YOLOv8 achieved an mAP of 0.693 on WiderFace, representing an increase of 0.109 over the baseline, while the SE-ResNet50 attained an F1-score of 0.7548 on RAF-DB, with an improvement of 0.2. These findings confirm the effectiveness of the proposed approach in both face detection and micro-expression classification. Moreover, this study provides a feasible solution to address the challenges of capturing micro-expressions and data insufficiency, while also laying the groundwork for future research on end-to-end joint modeling and lightweight network optimization.
Micro-expression Recognition; YOLOv8; ResNet; Attention Mechanism; Two-stage Model.
Literature Analysis of Science and Engineering Journals in Jilin Province's "Double First Class" Construction Universities from 2020 to 2024
Journal of Jilin University (Engineering Edition) (Journal A), Journal of Jilin University (Science Edition) (Journal B), Journal of Northeast Normal University (Natural Science Edition) (Journal C) and Journal of Yanbian University (Natural Science Edition) (Journal D) were taken as research objects, the basic information of journals was introduced, the trend of publication, the proportion of funded articles, the distribution of disciplines, relevant institutions and related keywords in the journals from 2020 to 2024 were analyzed. The results show that with the increase of years, the publication volume of Journal A shows an increasing trend, while the publication volume of Journals B and C shows a decreasing trend, and the publication volume of Journal D first decreases and then increases. In these five years, the average annual publication volume and average publication volume per issue of Journal A and Journal B are relatively high. The proportion of funded articles in Journal A, B and C is higher than 90%. Mathematics, computer software and computer applications , and automation technology account for a larger proportion in journals. The number of articles published by universities in their journals is significantly higher than that of other institutions. The top three keywords in Journal B and Journal C are exactly the same.
Journal; Number of Publication; Trend of Publication; Discipline.
Research Progress of Enhanced Oil Recovery
With the continuous growth of global energy demand and the depletion of conventional oil and gas resources, enhanced oil recovery ( EOR ) technology has become the core direction to ensure energy security and achieve sustainable development of oil fields. This paper systematically reviews the mainstream EOR methods such as chemical flooding, gas flooding, thermal oil recovery, microbial oil recovery, micro-nano technology and improved water flooding, and analyzes them from four aspects : action principle, development process, application cases and limitations. Combined with the current research status, the future development direction is prospected, which provides a reference for the selection and innovation of oilfield development technology.
Oil Recovery; Chemical Flooding; Gas Drive; Thermal Oil Recovery; Micro-nano Technology; Oilfield Development.
Orthogonal Analysis of Shear Capacity of Ultra High Performance Concrete Beams with High Strength Reinforcement and Coarse Aggregate
The influence of seven factors, including shear span ratio, reinforcement grade, reinforcement diameter, reinforcement spacing, section width, section height, and concrete strength, on the shear bearing capacity of Ultra high performance concrete with coarse aggregate (UHPC-CA) beams containing high-strength steel bars was analyzed using orthogonal experimental method. The results show that the influence of various factors on the shear bearing capacity of high-strength steel reinforced UHPC-CA beams, from large to small, is in the order of section width>concrete strength>shear span ratio>section height>hoop diameter>hoop spacing>hoop grade. The shear capacity of high-strength reinforced UHPC-CA beams decreases with the increase of shear span ratio and hoop spacing, and increases with the increase of hoop grade, hoop diameter, section width, section height, and strength of ultra-high performance concrete containing coarse aggregates.
Ultra High Performance Concrete with Coarse Aggregate(UHPC-CA); High Strength Reinforcement; Shear Capacity; Stirrup.
Research on Patent Technology Based on Wireless Charging Patent Pools
With the in-depth transformation of the new energy vehicle industry towards "electrification and intelligence", wireless charging, as a key technology to address the inconvenience of traditional charging, has seen its patent layout and patent pool operation gradually become the core of industrial competition. This paper takes typical global wireless charging patent pools (with the EV Charging Patent Pool under Via Licensing Alliance (Via LA) as the core research object) as samples, and combines data from the AutoPat global automotive patent big data platform (as of December 2024). It systematically analyzes the current status of patent technologies in wireless charging patent pools from four dimensions: patent pool composition, core technology distribution, geographical layout characteristics, and licensing rates. This paper proposes a three-level strategy of "targeted technology R&D - standardized collaborative layout - independent patent pool construction", providing references for China's new energy vehicle wireless charging field to break through patent barriers and enhance technological competitiveness.
Wireless Charging; Patent Pool; Standard-Essential Patents; Patent Technology Layout; Licensing Rate; New Energy Vehicles.