Academic Journal of Science and Technology
Academic Journal of Science and Technology (AJST) is a peer-reviewed journal published by Darcy & Roy Press. The mission of the journal is to provide an academic forum for discussing the issues of science, engineering, and technology across the world. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Ordos Basin, Dingbian Brick Well Block, Chang 7 Member: High-resolution Sequence Stratigraphic Division Using INPEFA
The tuff marker bed of Chang 7 Member of Yanchang Formation in the Ordos Basin is superimposed in multiple periods, and the shale layer system has significant time-crossing filling characteristics. There is great uncertainty in the isochronous comparison of the sub-members of the traditional lithostratigraphic method. Based on the natural gamma logging curve of drilling in Dingbianzhuan well block, the comprehensive prediction error filtering analysis ( INPEFA ) technology is used, supplemented by the constraint of tuff marker layer, and the high-resolution sequence division is carried out for the sub-members of Chang 71, Chang 72and Chang 73. The results show that the Chang 7 oil layer group belongs to a long-term base level descending half cycle as a whole, and two fourth-order sequences can be divided inside. The lower fourth-order sequence consists of a complete symmetrical cycle composed of the Chang 73 progradational sequence group and the Chang 72 regressive sequence group, with the maximum regressive surface located in the interior of Chang 72. The upper fourth-order sequence corresponds to Chang 71, and only the ascending half cycle is retained. The fifth-order sequence is divided into : 1 progradational parasequence developed in Chang 73, 2 parasequence developed in Chang 72, and 2 regressive parasequence developed in Chang 71. The INPEFA trend curve quantitatively reveals differences in cyclic structure among the three sub-members: a continuous negative trend in Chang 7₃ indicates progradation, with a positive trend shift at the top marking the terminal flooding surface; in Chang 7₂, the lower part continues the negative trend while the upper part shifts to positive, with the minimum at the trend transition pinpointing the maximum regressive surface; Chang 7₁ is dominated by a positive trend, with stepwise rise interrupted by two negative deflections, each corresponding to two brief provenance progradation events during the lake transgression. Sequence boundaries at all levels can be traced and correlated across the study area. This division scheme provides a quantitative basis for isochronous stratigraphic correlation in deep-water fine-grained sedimentary areas that does not rely on static lithological boundaries.
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Countermeasures against Elevated C3 Content in Feedstock during High-Purity Isobutane Production
Aiming at the practical problem of increased C3+ content in the feedstock for industrial isobutane production at the Butane Plant of Zhongyuan Oilfield Natural Gas Treatment Plant, this paper investigates the effects of C3+ content fluctuation on key process parameters, and further optimizes the regulation methods for production parameters. When light components in the process materials for industrial isobutane production rise significantly, key control parameters including the overhead temperature of the isobutane column, the overhead temperature of the purification column and the C3+ content in No.1 reflux drum are kept within the standard ranges. This prevents the accumulation of C3+ components and unplanned shutdown reflux of the unit, improves the adaptability of the industrial isobutane production process to variations in feedstock composition, and ensures continuous and stable production of qualified industrial isobutane products.
Research and Application of Multi-dimensional Feasibility Evaluation Method for Protective Layer Decision-Making in Coal and Gas Outburst Seam Groups
Coal and gas outbursts are prone to triggering cascading disasters and rank among the most severe dynamic hazards in coal mines. Mining protective seams is a fundamental measure for achieving regional gas control. Based on the theory of mining-induced pressure relief and the effective mechanical criteria for protective seams, and following the logic of "necessary threshold–core constraints–practical selection," this study constructs a multi-dimensional feasibility evaluation method for protective seam selection in outburst coal seam groups, comprising "three levels and ten indicators." Taking a mine in Yangquan, Shanxi Province as the engineering background, the method is applied to conduct layer-by-layer evaluation and quantitative analysis of six potential protective seams: No.6, 8, 9, 12, 13 and 15. The results show that: (1) Seams No.6, 8 and 9 fail to meet the spatial position conditions and do not satisfy the requirements for protective seam selection. (2) Seams No.12 and 13 meet the theoretical feasibility but exhibit issues in safety feasibility, including discontinuous pressure relief and high disaster coupling risks, as well as constraints in technical-economic feasibility, such as high mining difficulty and poor economic viability. (3) Seam No.15 performs well across all dimensions and indicators and is identified as the preferred protective seam. This method successfully identifies the hidden risks of using thin and unminable seams as protective seams, addressing the limitations of traditional single-parameter verification, and can serve as a reference for scientific decision-making on protective seam selection in outburst coal seam groups under similar complex conditions.
Dynamic Response and Diagnosis of Wear Fault in Plunger Pump Crosshead Guide Plate Based on Multibody Dynamics and Hydraulic Co-simulation
In the high-pressure process systems of the petrochemical industry, piston pumps are continuously used under extremely harsh conditions such as ultra-high pressure, large flow rate, long-term continuous heavy load, and media containing corrosive particles. The key friction pairs at the power end are prone to wear failure. This paper takes a new type of five-cylinder piston pump as the research object. Based on the multi-body dynamics theory and the L-N nonlinear spring-damping contact force model, a combined simulation of the hydraulic system and multi-body dynamics is established to study the vibration response of the crosshead guide plate wear fault under hydraulic conditions. The results show that when the liquid pressure exists, the maximum collision force between the crosshead and the guide plate increases with the continuous increase of the gap. When the gap is greater than 0.6mm, the collision force increases significantly; the vibration energy is concentrated near the second-order natural frequency of the housing (about 325 Hz), and the spectral peak increases with the increase of the gap. The study reveals the characteristic parameter variation rules of the crosshead guide plate wear fault, providing a theoretical basis for online monitoring and fault diagnosis of piston pumps in the petrochemical industry.
Research on Casing Damage Prevention and Remediation Techniques in the a Oilfield
The HSJ Oilfield faces increasing casing damage due to geological factors, sand production, stimulation measures, and corrosive environments, particularly in blocks with produced water reinjection and saltwater intrusion. Casing damage disrupts injection-production balance, reduces water drive efficiency, increases operational costs, and hinders stable production. This paper proposes a systematic methodology integrating prevention, accurate identification, graded treatment, and daily management for casing damage wells. A "prevention-oriented" strategy is emphasized, including cathodic protection via deep-well anodes, DPC internal coating with non-metallic wear protection, sacrificial anode short sections, and regular corrosion inhibitor injection. Accurate identification combines engineering logging with dynamic analysis, revising key indicators such as liquid volume, salt content, water cut, and dynamic fluid level. Notably, casing damage does not always cause water breakthrough, and water breakthrough may originate from sources other than the damaged section. Treatment follows a graded approach: for effective seating positions, LEP long-term packers are preferred; for damaged sections, chemical sealing (<100 m), alloy composite patching (100–400 m), or small casing cementing (>400 m) are applied; well pattern reconfiguration via sidetracking is used for challenging cases. Daily management includes comprehensive wellbore treatment (anti-corrosion, anti-scaling, anti-wear), 2-hour performance graph monitoring, ten-day fluid level tests, and strict construction quality control. Application in the HSJ Oilfield has significantly reduced the casing damage rate from 13.6% to 2.1% in water injection wells and decreased the annual number of new casing damage cases, supporting stable production and economic benefits. This integrated approach provides a practical reference for similar mature oilfields facing casing integrity issues.
Identifying Key Drivers of Natural Gas Demand in Sichuan Province Using a Hierarchical Analysis Framework
Natural gas plays a critical role in the low-carbon energy transition, yet its demand drivers remain insufficiently understood due to complex factor interactions. This study aims to identify and hierarchically classify the key drivers of natural gas demand to better forecasting natural gas demand. Taking Sichuan Province as a case study, we develop an integrated framework combining grey relational analysis, fuzzy DEMATEL, interpretive structural modeling, and MICMAC to examine fourteen candidate factors using data from 2008 to 2023. Results show that all candidate factors have grey relational degrees above 0.82. However, fuzzy DEMATEL reveals that only five factors—population size, technological level, economic development, urbanization, and carbon constraint—are causal drivers, while highly correlated variables such as gas-using population and pipeline length are effect factors. ISM further decomposes the driver system into five hierarchical levels, with population size identified as the root driver, validated by MICMAC. We conclude that statistical association does not equate to causal dominance, and correlation-based variable selection alone is insufficient for natural gas demand forecasting.
Interpretable Dynamic Prediction and Risk Assessment of Filtered-Water Turbidity in a Drinking Water Treatment Plant
Filtered-water turbidity at the study plant was usually low during 2025, but several short excursions coincided with changes in raw-water and hydraulic conditions. The practical problem was not simply to predict those values: operators also needed to know which measurements were driving a warning and whether the predicted value represented a meaningful operational risk. We analysed 4,380 records from January to December 2025 and used observations from January to March 2026 as a separate follow-up set. The available signals covered raw-water turbidity, pH and flow, alum dose, river level, clear-water well level and filtered-water turbidity. Missing entries were handled according to their frequency, while extreme observations were retained and flagged because they could represent genuine plant events. Predictor relevance was examined with Pearson correlation, mutual information, LASSO and randossm-forest importance. XGBoost and LightGBM were then combined in a weighted model, with SHAP values used to inspect individual contributions. An ARX formulation was fitted separately to examine delayed responses, and entropy-weighted fuzzy grading was used to express risk. Clear-water well level, river level and lagged raw-water flow emerged as the leading variables. The ensemble obtained R2 = 0.834 on the training data, whereas the extended ARX model obtained R2 = 0.800. Of the 2025 observations, 90.6% fell in the safe class; every follow-up observation was also classified as safe. The framework therefore links a turbidity estimate to both an explanation and an operational risk label.
Winding Parameter Optimization and Static Strength Analysis of Type IV Hydrogen Storage Cylinders Based on Abaqus-WCM
This study focuses on a 70 MPa Type IV hydrogen storage cylinder and investigates optimization of the fiber-winding process and static-strength behavior through finite element simulation. Based on composite laminate design theory, the thickness distribution of the winding layer in the dome region was predicted. A finite element model consisting of a plastic liner, a metal boss, a carbon-fiber winding layer, and a glass-fiber protective layer was established. The stress distribution of each component under the rated high-pressure condition was systematically analyzed. The results show that the components exhibit good cooperative load-bearing behavior. The stress of the metal boss basically satisfies the strength requirement, and the composite winding layer demonstrates favorable load-bearing capacity.
Mechanical Properties and Chloride Penetration Resistance of UHPC Incorporating Tunnel Spoil and Nano-SiO₂
Using tunnel spoil in ultra-high-performance concrete (UHPC) is attractive for reducing aggregate consumption, yet its porous nature raises concern when the material is exposed to chloride wet–dry action. In this work, quartz sand was partially replaced by tunnel spoil at 0%, 10%, 20%, and 30%, and nano-SiO₂ was incorporated at 0%, 1%, 2%, and 3%. Compressive strength, electric flux, mass variation, SEM, and XRD were used to examine performance changes at different curing ages and exposure durations. Compressive performance and chloride penetration resistance declined under repeated chloride wetting and drying, whereas longer curing and a moderate combination of tunnel spoil and nano-SiO₂ were associated with lower electric flux, smaller mass variation, and a denser matrix. Within the tested mixtures, 2% nano-SiO₂ + 20% tunnel spoil (N2C2) showed the most favorable overall balance.
Application Research of Embedded Systems in Smart Home Control
In the last ten years smart home technology has progressed rapidly due to advancements in embedded system wireless communication and AI. In this article we would be talking about the complete knowledge on the embedded system in smart home control like hardware architecture, comunication protocol,software frameworks,security mechanism and also few of the practical applications. How do we see MCUs and SoC Platform stuff such as the ESP32, STM32, nRF52840 and ARM Cortex-M series being computational backbone of intelligent home node. And then try out 6 most commonly used Wireless Protocols like Zigbee, Z-Wave, Wi-Fi,BLE(Bluetooth Low Energy) Thread,NB – IOT on their range and data - rate at Power Consumption while doing any home Automation Task. And this is what I am going to use for the Device Security Model in my work. It’s Device Auth, AES - 256/WPA3, Access Contro1 and Ota Firmw are verificat. on an Embedded - System Smart Home experiment results shows that they have a contol latency mostlY under 100mS and packet lose rate less than 1% and successful command execute rate more than 99%. Those all experiment show that our embedded system can meet every requirements like performance, save energy and be safe for building up a smart house.
Characteristics of Greenhouse Gas Emission Factors in Sewer Networks, Key Influencing Factors, and Responses to Network Defects
Drainage networks, long treated as passive conduits, are now recognized as GHG sources, yet controls on their emission factors (EFs) remain unclear. We synthesized 138 EFs (111 CH₄, 27 N₂O) from 24 studies (1994–2024), deploying Spearman, Random-Forest-SHAP, and GAMs to pinpoint drivers and nonlinear responses, alongside defect scenarios mimicking illicit flows and rainfall intrusion. Pressurized mains exhibited the highest dissolved CH₄, whereas N₂O partitioned predominantly into the dissolved phase across systems. CH₄ EFs responded chiefly to hydraulics and organics (A/V ratio, COD, depth, temperature), while N₂O EFs shifted toward nitrogen pathways (NH₄⁺-N, NO₃⁻-N, conductivity). Simulations revealed opposing trends: defect severity suppressed CH₄ but elevated N₂O, with rainfall amplifying this divergence. These findings argue against static EFs—emission factors are context-sensitive, varying with hydraulics, chemistry, and pipe integrity. Incorporating such dynamic dependencies would sharpen urban GHG inventories and targeted abatement strategies.
The Application of Large Language Models in Vertical Domains: learning assistance
Although the performance of many large language models (LLMs) is excellent in the general field, with the popularity of LLMs, more and more people find that the performance of LLMs in vertical domains is not satisfactory. Therefore, this paper decided to study the application of LLM in a vertical domains and use LLM to assist volunteer learning. This research plan uses the general LLM in combination with learning methodology, the knowledge enhancement of Skills and Retrieval-augmented Generation (RAG) along with structured guidance of the teaching process, to build a learning assistance AI. This study recruited 10 volunteers to use learning assistance AI to learn new textbooks, and most of them reported that they had improved through the learning of this system, could quickly get started, and quickly gained a preliminary understanding of new knowledge. Therefore, this study concludes that learning assistance AI is effective.
Research on Internal Flow Field Simulation and Structural Optimization of Mesh Belt Dryer
In order to solve the problem that the internal airflow and temperature field distribution of the belt dryer are uneven, resulting in poor drying quality, this paper conducts 3D modeling and flow field simulation analysis of the drying chamber of the three-layer belt dryer based on computational fluid dynamics (CFD). The velocity and temperature fields of the original drying chamber were numerically simulated by using the Realizable k-ε turbulence model and the porous medium model. The results show that in the original structure, the average velocities on the three-layer mesh belts are 0.93 m/s, 1.09 m/s, and 0.88 m/s, with non-uniformity coefficients of 78.36%, 56.95%, and 47.53%, respectively; the average temperatures are 60.18°C, 58.34°C, and 57.51°C, with non-uniformity coefficients of 14.84%, 24.79%, and 15.03%. By adding an air distributor below the air inlet and comparing different perforation sizes, it was found that the optimal optimization effect is achieved when the perforation diameter is 40 mm: the average velocities on the three-layer mesh belts increase by 0.55 m/s, 0.27 m/s, and 0.27 m/s, while the non-uniformity coefficients decrease by 35.85%, 21.09%, and 27.06%; the average temperatures rise by 4.34°C, 5.49°C, and 5.64°C, and the non-uniformity coefficients drop by 9.87%, 14.92%, and 6.67%. This research provides a theoretical basis for the structural optimization of mesh belt dryers.
Study on Laser Additive Joining Process of Stainless Steel and Copper Alloy
This study achieved the joining of 316 stainless steel and T3 copper using a laser additive joining method. The process feasibility of using pure 316 stainless steel powder and pure copper powder as filler materials for additive joining was investigated, and the influence of different joining processes on the microstructure evolution and mechanical properties of the joints was analyzed. The research indicates that when pure 316 powder is used as the filler material, with a laser heating power of 1.8 kW on the steel side and 2.2 kW on the copper side, the joint formation is optimal, and the tensile strength of the joint reaches 250.3 MPa. When pure copper powder is used as the joining material, the internal stress within the joint is relatively large, and aging fracture occurs in the transition zone on the copper side.
First-principles and Experimental Study on Structure and Properties of Fe20Co20Cr20Ni25AlxTi(15-x) High Entropy Alloy Coatings
In this study, based on DFT-based first-principles calculations and the design philosophy of multi-component alloy segmented design, a high-entropy alloy system of Fe20Co20Cr20Ni25AlxTi(15-x) (x = 0, 5, 10, 15) was designed to investigate the synergistic effects of Al and Ti on phase stability, electronic properties, and elastic properties. The designed Fe20Co20Cr20Ni25AlxTi(15-x) high-entropy alloy exhibits good stability; there are no significant differences in the band density among the various high-entropy alloys, and all exhibit metallic properties. The addition of Al and Ti did not compromise the stability of the high-entropy alloy system. Under optimal conditions, defect-free, well-formed high-entropy alloy coatings were successfully prepared. Under optimal conditions, defect-free, well-formed high-entropy alloy coatings were successfully prepared. The basic mechanical properties of the high-entropy alloy coatings were investigated, resulting in a Fe20Co20Cr20Ni25Al5Ti10 high-entropy alloy coating with excellent mechanical properties.
Research on the Impact Effect of Data Factor Agglomeration Empowering Industrial Chain Resilience
This study examines how data factor agglomeration empowers industrial chain resilience, using the establishment of national big data comprehensive pilot zones as a quasi-natural experiment. Based on panel data of 266 Chinese cities from 2009 to 2022, we apply the multi-period difference-in-differences (DID) and double machine learning (DDML) methods. Results show that data factor agglomeration significantly improves industrial chain resilience, mainly through technological innovation, digital infrastructure construction, and industrial structure rationalization. The positive effects are more pronounced in eastern coastal regions, areas with high market, and developed digital economies. These findings provide empirical support for big data policy optimization and industrial chain upgrading.
Spatiotemporal Dynamics of Cropland Non-agriculturalization in Zhengzhou City Using Deep Learning-Based Interpretation
Traditional monitoring of cropland non-agriculturalization heavily relies on land use/cover change data, which is constrained by long update cycles and the difficulty of accurately isolating the unidirectional conversion from cropland to non-agricultural uses. To address these limitations, this study utilizes a semantic change detection network with GaoFen-2 (GF-2) high-resolution time-series remote sensing imagery of Zhengzhou City from 2021 to 2025 as the primary data source. Integrating a land-use transfer matrix, grid cell analysis, spatial autocorrelation analysis, and the Geographic Detector model, we systematically analyze the spatiotemporal evolution dynamics and driving mechanisms of cropland non-agriculturalization in the region. The results demonstrate that: (1) Temporally, the intensity of cropland conversion in Zhengzhou City exhibits an unbalanced fluctuating pattern characterized by "initial intensity, subsequent stabilization, and localized rebound," with construction land being the absolute dominant destination of cropland outflow, resulting in a cumulative converted area exceeding 80 km² over the five-year period. (2) Spatially, cropland non-agriculturalization exhibits a distinct gradient pattern described as "commencing in the central urban core, highly aggregating in near suburbs, and dispersedly distributing with low intensity in far suburbs." Hot spot zones are heavily clustered in the near-suburb plains (e.g., Zhongmu County and Xinzheng City), whereas cold spot zones remain long-term stable in the western and southern hilly and mountainous regions (e.g., Dengfeng and Xinmi). The Global Moran's I indices are consistently positive and statistically significant, revealing pronounced spatial polarization and clustering features. (3) Regarding the driving mechanisms, cropland non-agriculturalization in Zhengzhou City is generally characterized by "transportation location dominance, industrial economic support, and topographical constraints."
Design of Separation Method for Floccules in Condensate Oil from Tight Gas Reservoirs
Floccule contamination in condensate oil is a widespread and severe problem. Conventional separation processes fail to achieve thorough separation and cannot meet industrial requirements. To address this issue, this paper designs a separation scheme tailored for floccules in condensate oil, thereby solving the critical problems of substandard condensate oil quality and frequent product returns. By investigating and comparing various separation schemes, this study determines the use of a decanter centrifuge as the separation equipment and completes the design of the separation scheme and device. Through principle experiments, the influences of material properties and rotating speed on centrifugal separation performance are analyzed. The flow field of the centrifuge is investigated using the finite element method. This research not only improves the separation efficiency of condensate oil and oil product quality but also holds great significance for enhancing the economic benefits of oil and gas fields.
An Automated Annotation and Lightweight Detection Framework for Rice Leaf Disease Based on Color Space Analysis and YOLOv11
Accurate and timely detection of rice leaf diseases is essential for precision agriculture and food security. However, existing object detection approaches heavily rely on labor-intensive manual bounding box annotations, which limits their scalability and practical deployment. In this paper, we propose an automated annotation and detection framework that combines color space analysis-based lesion localization with the lightweight YOLOv11n model for rice leaf disease detection. Our automated annotation method leverages disease-specific HSV color space characteristics and morphological processing to generate bounding box labels without human intervention, achieving a 98.6% successful annotation rate across 5,932 images. The annotated dataset is then used to train YOLOv11n, which achieves a mean Average Precision (mAP@0.5) of 93.36% and mAP@0.5:0.95 of 77.53% on the test set, with only 2.58M parameters and 1.0ms inference time per image. Experimental results on four rice disease categories (Bacterial Blight, Blast, Brown Spot, andTungro) demonstrate that the proposed framework provides an effective and efficient solution for rice disease detection with minimal annotation cost, making it suitable for real-time deployment on edge devices in agricultural settings.
Literature Review on the Construction of the Kill Chain of the Informationized and Intelligentized Combat System
Currently, modern technologies centered on artificial intelligence are driving the evolution of warfare from informatization to intelligentization at an accelerated pace. The construction of informationized and intelligentized combat system kill chains has become a hot topic in military research in recent years. This paper adopts a multi-perspective approach, integrating various research methods to analyze and summarize existing literature on kill chain studies. It focuses on aspects such as conceptual essence, winning mechanisms, design philosophies, model construction, effectiveness evaluation, scenario applications, and research on foreign militaries. Furthermore, by examining the current status of kill chain research and application among the world's major military powers and considering the demands of military struggle preparations, the paper looks ahead to future research directions.
Research on Bearing Mechanism and Key Construction Technologies of Bag-Encased Cast-in-Place Pile Foundations for Overhead Transmission Lines in Hard Rock and Highly Corrosive Regions
Overhead collector line projects for renewable energy frequently encounter special geological conditions where hard rock strata coexist with highly corrosive environments. Traditional foundation solutions exhibit significant limitations in construction efficiency, anti-corrosion durability, and economic viability. This paper systematically presents the technological principles of bag-encased cast-in-place pile foundations, revealing the bearing capacity and durability mechanisms arising from the synergistic integration of physical isolation anti-corrosion and efficient hole-forming and grouting. By analyzing the hydraulic expansion principle of the "water (slurry) injection and slurry discharge method," the key controlling factors for uniform expansion and tight adherence of the anti-corrosion bag against the borehole wall are elucidated. Based on engineering measurement data, pile bearing performance was verified through self-balanced load tests and low-strain integrity testing, with the ultimate vertical compressive capacity of single piles satisfying design requirements and all tested piles classified as Class I. Comparative economic analysis demonstrates that, compared with large open-cut foundations with anti-corrosion coating, rock-anchored pile foundations, and driven steel pipe pile solutions, the comprehensive cost of the proposed method is reduced by approximately 25%–39%, 35%–44%, and 72%, respectively, while the earthwork volume per foundation is reduced by over 90%. The research results indicate that bag-encased cast-in-place pile foundation technology effectively resolves the dual technical challenges of rapid hole-forming in hard rock strata and foundation anti-corrosion in highly corrosive environments, offering significant economic and environmental benefits. This technology provides a reliable technical solution for transmission line foundation engineering under similar geological conditions.
One-Click Quotation System and Method for Online Customization of Door Furniture
Aiming at the problems of complex wiring, significant voltage drop, uneven brightness and insufficient intelligent adjustment of low-voltage LED lamps in customized home scenes, this paper proposes a customized home lighting adaptive adjustment management method based on artificial intelligence and big data, and designs a complete implementation system. The system takes the user 's house decoration map and the lamp belt installation parameters as input, constructs the lighting demand analysis model and the lamp belt wiring optimization model, and completes the lighting strength area determination, converter number optimization and installation position planning through the artificial intelligence algorithm. Under the premise of significantly reducing the influence of voltage drop, the number of converters used is minimized. In addition, the system is also equipped with an environment-aware sensor, and a periodic closed-loop brightness adjustment algorithm is used to achieve adaptive matching of light brightness and illumination in different scenarios. The simulation results show that the proposed method can improve the brightness uniformity of the lamp belt by 28.7 %, reduce the number of converter configurations by 32.4 % on average, and the adaptive adjustment response time is less than 0.6 s. It can effectively solve the pain points of low-voltage lamp belt engineering application and improve the intelligence and practicability of customized home lighting system.
Application and Progress of Nanotechnology in Oil and Gas Fields
Nanotechnology, which emerged as a novel scientific and technological field in the 1990s, has gradually permeated the petroleum industry by virtue of its unique size and surface effects, as well as its excellent optical, electrical, thermal, and magnetic properties. It offers a new technical pathway to address development challenges in onshore oilfields, such as high water cut, strong heterogeneity, and low waterflooding recovery factor. This article reviews the origin and evolution of nanotechnology and summarizes relevant research findings and field application cases across six key areas: downhole nanosensors, drilling engineering, enhanced oil recovery, oil displacement operations, secondary development of mature oilfields, and reservoir nanorobots. The study indicates that nanomaterials and nanodevices exhibit distinct advantages in improving drilling fluid performance, reducing fluid loss, plugging high-permeability layers, altering reservoir wettability, lowering oil–water interfacial tension, and reducing injection pressure to enhance water injectivity. The research and field testing of reservoir nanorobots have achieved milestone-level progress, opening new possibilities for fine reservoir characterization and residual oil recovery. At the same time, this article identifies the technical challenges currently facing nanotechnology in petroleum industry applications and discusses future development directions, providing a reference for the large-scale deployment of nanotechnology in the petroleum sector.
Optimization of Asphalt Mixture Mix Proportion Based on Bayesian Optimization Algorithm Combined with Marshall Test
This study presents an optimization framework that integrates physical testing with intelligent algorithms. With the amount of asphalt and the passing rates of key sieves aggregate gradation as design variables, and Marshall stability, flow value, void ratio, mineral aggregate void ratio, and asphalt saturation as optimization goals, a high-performance prediction model constructed. First, an initial data set is obtained through a small number of carefully designed Marshall tests (such as orthogonal tests, Latin hypercube sampling). Then, a Gaussian model is constructed to replace the complex “variables-performance” black box function. Finally, the Bayesian optimization algorithm is used, with the expected improvement as the acquisition function, to iter recommend the “most potential” mixture ratio for the next round of Marshall test verification until convergence. The results show that this method can quickly locate the Pareto optimal combination frontier that all technical specifications under the premise of significantly reducing the number of tests (expected to reduce by 40%-60%), and can quantify the contribution of each variable to the index. This study provides a new paradigm of data-driven and intelligent efficient for asphalt mixture design, which has important reference value for promoting the intelligent design of road engineering materials.
Foundational Study on Magnetic-Chain-Based Magnetic Flux Leakage Detection for High-Throughput Screening of Under-Magnetized Small Permanent Magnets
Small permanent magnets are indispensable functional components in smart electronic products, where the stability of magnetization directly influences actuation, positioning, sensing, acoustic output, and overall system reliability. In industrial production, however, the final magnetic performance of a small magnet is sensitive to raw-material fluctuations, local field nonuniformity, fixture tolerance, and process disturbance during magnetization. The dominant failure mode is insufficient magnetization intensity, which creates under-magnetized or “NG” parts. Existing commercial inspection equipment usually adopts a discrete strategy in which each magnet is measured independently. Although this approach offers high accuracy, its serial nature limits throughput and is increasingly incompatible with large-scale manufacturing. To support high-speed screening, this work develops a foundational study of magnetic-chain-based magnetic flux leakage (MFL) detection using Hall sensing and finite-element analysis. Rather than treating each magnet as an isolated inspection target, the method organizes multiple magnets into a chain and evaluates whether the leakage-field distribution along the chain can preserve sufficient contrast for reliable NG identification. A three-dimensional Ansys Maxwell model is established using NdFe36 permanent magnets, with a single under-magnetized magnet embedded at the center of the chain. The study first constructs the batch-detection framework, then investigates the signal morphology obtained along vertical and horizontal sensing directions, and finally introduces direction-dependent threshold metrics for quantitative discrimination. For magnet lengths of 10, 8, and 6 mm, the vertical-direction thresholds are 40.35, 37.95, and 31.71, respectively, whereas the horizontal-direction thresholds are 27.99, 29.35, and 28.35. The results show that each magnet produces a quasi-N-shaped leakage signature in the vertical direction and a quasi-parabolic signature in the horizontal direction. More importantly, the vertical arrangement consistently provides stronger NG contrast and clearer waveform separation. This work therefore solves a key early-stage problem for magnetic-chain inspection: how to preserve both throughput and signal distinguishability in a batch-screening configuration. The study provides a physically interpretable detection metric, identifies the more favorable sensing direction, and offers direct guidance for subsequent equipment design, algorithm development, and extension toward more complex magnetic-chain inspection scenarios.
Red-Burnt Clay and Early Chinese Architectural Technology: Archaeological Significance and Scientific Approaches to Firing Temperature Reconstruction
Red-burnt clay remains (hongshaotu) are clayey architectural and occupation deposits that were reddened, hardened, and mineralogically altered by intentional firing or incidental heating. These materials document the transition from unfired earth-and-timber construction to fired ceramic architecture in Neolithic and early Bronze Age China, yet their archaeological value has been limited by reliance on macroscopic description for temperature reconstruction. This narrative review examines published cases — including Guanmiaoshan red-burnt house remains (~600 °C), Lingjiatan red ceramic blocks (>950 °C), Sujiacun burnt soil deposits (~500–600 °C), and Qiaocun composite roof tiles — and compares archaeometric methods for estimating firing temperature, heating temperature, and thermal history. The methods reviewed include magnetic susceptibility and thermal demagnetization, colorimetry, X-ray diffraction, petrography, Fourier-transform infrared spectroscopy, differential thermal analysis, thermal expansion, and physical property testing. Each method responds to different parts of the heating process and operates within a limited temperature range; no single technique covers the full spectrum from low-temperature occupation deposits to high-fired ceramic building materials. The review proposes a multi-method workflow that begins with field screening and contextual classification, matches analytical methods to the likely temperature range, and returns temperature evidence to questions of building practice, site formation, production organization, and the diffusion of firing techniques. Future work should build regional calibration databases from local raw materials, standardize the reporting of temperature estimates, and connect thermal data with architectural and technological history.
Research on the Influence Characteristics of Pitting Damage on the Stress of Downhole Tubular Columns
Production gas well tubing is long-term exposed to harsh corrosive environments, and pitting damage has become one of the main forms of tubing failure, seriously threatening the safe production of oil and gas fields. In response to the failure problems of tubing surface multi-pitting damage and under the action of complex loads in actual working conditions, this paper adopts a method combining finite element numerical simulation and fracture mechanics theory analysis to systematically study the influence of pitting damage on the stress distribution, load-bearing characteristics and failure mechanism of downhole tubing. The research shows that the depth of a single pitting pit is significantly positively correlated with stress concentration, while the hole diameter is negatively correlated with equivalent stress when the depth remains unchanged. For multi-point overlapping damage, the smaller the axial distance between the two holes, the more significant the stress concentration, while the radial distance has a smaller impact on the equivalent stress. In addition, under various loading conditions such as tension, internal pressure and external pressure, the increase in the number of pits will significantly intensify the stress concentration phenomenon and greatly reduce the ultimate load-bearing capacity of the tubing. Theoretical analysis further reveals that pitting damage leads to tubing failure through inducing crack initiation and propagation as well as weakening the effective load-bearing cross-section, ultimately resulting in tensile fracture and collapse. The results of this study provide important theoretical basis for the corrosion protection, remaining life assessment and structural safety design of gas well tubing.
A Study on Improving the Rapid Assembly of Prefabricated Container-Type Substations in Cold, High-Altitude Regions
With the development of China’s power industry, the government has been vigorously promoting the sector since the start of the 15th Five-Year Plan. There has been a significant increase in demand for prefabricated modular substations, which can shorten the construction and installation cycle of substation projects. The Nyingchi Construction Power Supply Package I project is located in Milin City at an altitude of 3,027 meters. Due to its high-altitude setting, the project faces harsh conditions such as extremely cold weather, underdeveloped infrastructure, and difficult transportation, which have posed numerous challenges to the construction of the substation. This paper primarily explores the rapid construction of prefabricated container-type substations in high-altitude areas of Tibet. Focusing on prefabricated container-type modular construction, the study analyzes the advantages of this approach in high-altitude regions, reduces on-site fabrication work, and facilitates modular manufacturing and installation. This method is environmentally friendly in the Tibetan region, minimizes the need for post-construction environmental and water restoration, and thus provides a reference for subsequent prefabricated container installation and application projects.
Lightweight Design and Manufacturing of High-Pressure Die-Cast Magnesium Alloy Components for Automotive Applications: A Comprehensive Review
The imperative for vehicle mass reduction, driven by increasingly stringent greenhouse gas emission regulations and the rapid proliferation of electric vehicles, has positioned magnesium (Mg) alloys as compelling candidates for structural automotive applications. With a density of merely 1.74 g/cm3 — approximately two-thirds that of aluminium and one-quarter that of steel — Mg alloys offer an unparalleled weight advantage among engineering metals. High-pressure die casting (HPDC) remains the dominant manufacturing route for automotive Mg components, accounting for approximately 90% of total production volume. This review systematically synthesizes findings from peer-reviewed publications to establish a comprehensive knowledge framework encompassing alloy systems, vehicular applications, and original equipment manufacturer (OEM) development practices. In the domain of alloy selection, the Mg-Al-Zn system (principally AZ91) provides superior castability and strength for non-safety-critical components, whereas the Mg-Al-Mn system (AM50/AM60) delivers the requisite balance of strength and ductility for crash-relevant structures such as seat frames and instrument panel beams. Recent advances in Mg-Al-Sn (AT72) and Mg-Al-Zn-Mn alloy families demonstrate promising avenues for tailored strength–ductility combinations. With respect to vehicular deployment, Mg die castings have been successfully implemented across body systems (door inners, front-end carriers, closure panels), achieving mass reductions of 40–50%, and chassis systems (wheels, steering columns, subframes). A detailed case study of the Mg alloy seat frame (MASF) forward-development programme at Changan Automobile illustrates the complete design–simulation–process–verification chain, yielding a 9.88 kg seat frame representing a 24.6% mass reduction with process yields exceeding 90%. The challenges and future prospects for expanded automotive Mg adoption are critically assessed.
The Impact of ESG Practices on Corporate Performance: An Empirical Analysis
The impact of ESG performance on corporate financial outcomes was examined using panel data from A-share listed companies in China spanning 2014-2024, with 2020 excluded due to exceptional circumstances. A mediation model was employed to explore the underlying mechanisms. The results indicated that strong ESG performance positively affected financial performance, with financing constraints and agency costs acting as partial mediators. Additionally, the effect of ESG performance was found to be more pronounced among low-pollution firms and small- and medium-sized enterprises. These findings provided important insights for strengthening ESG integration and advancing corporate sustainability.