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.
Development and Real-Vehicle Validation of an Around View Monitor Evaluation System for Parking Experience
With regard to surround view systems, after they have been broadly applied in mass - produced cars, one must consider them as part of the factors influencing parking safety or satisfaction .Yet at present no full industry evaluation exists — neither theoretical nor practical — that meets driver needs by combining objective data with subjective impressions .The present article is devoted mainly to problems arising in basic parking situations, and by means of user surveys, of the Delphi method, and of hierarchical analysis, a surround-view evaluation plan is proposed—one with four components: viewing angle, activation time, real - scene proportion, and stitching quality .It was applied to 31 common models currently available on the market .The data suggest that stitching quality affects the whole experience more than any other factor .The evaluation idea seems well suited for detecting differences, and it gives carmakers a solid basis for design choices or for standard-setting purposes.
Copyright (c) 2026 Academic Journal of Science and Technology https://creativecommons.org/licenses/by/4.0
A Third-Party Construction Detection Model Incorporating Residual Scaling and Channel-Adaptive Gating
Third-party construction is a leading cause of urban gas pipeline damage. Unregulated digging and drilling frequently rupture pipes, disrupt service, and create safety hazards. To address this, we propose TPC-DETR—an end-to-end detector built on the DETR framework—that identifies risky construction activities near pipelines and helps prevent human-caused damage. Three enhancements improve the baseline. In the backbone, we add a Residual Scaled Block (RSB) that stabilizes deep-network training and strengthens feature representation, with zero extra parameters or FLOPs. Between the backbone and neck, we insert a Channel-Adaptive Cascaded Gating Layer (CACG-Layer) that lowers computational cost while boosting speed and accuracy through fine-grained multi-branch feature modulation. In the feature extraction path, we adopt re-parameterized RefConv, whose kernels adjust dynamically at inference based on learned weights—improving adaptability and generalization at no additional cost. On our self-built dataset, TPC-DETR achieves 97% mAP@0.5 and 81.6% mAP@0.5:0.95. These results show that the model reliably detects a wide range of third-party construction activities in complex pipeline environments, and is practical for real-world deployment.
Research on an Air‑Ground Community Governance System with Wheel‑Leg Composite Chassis and UAV Visual‑Aided Collaboration
To address three prominent challenges prevailing in aging residential districts, including omnipresent three-dimensional sensing blind zones, insufficient traversal capability over unstructured terrains and lagged emergency disposal responses, the proposed "Zhikan-Yunxun" system equips the robot with a wheel-legged composite chassis to achieve stable traversal over steps and diverse ground obstacles. An unmanned aerial vehicle (UAV) is pre-stored inside the roof-mounted cabin and kept in standby mode; upon the occurrence of visual occlusion, the UAV takes off on demand and leverages the lightweight LAF-YOLOv10 detection algorithm to compensate for ground-level sensing blind zones from the aerial viewpoint. The UAV and unmanned ground vehicle (UGV) perform coordinated operation relying on UWB/IMU/vision hierarchical fusion localization and MOCHA opportunistic communication framework, which sustains centimeter-level navigation precision under complete GNSS signal deprivation. Furthermore, a SCARA manipulator is deployed to conduct flexible manipulation tasks such as litter retrieval and on-site emergency support. Benefiting from the integrated air-ground coordination architecture, raw sensing data can be directly converted into executable community governance interventions.
Short-Term Traffic Flow Prediction Method Based on Dung Beetle Optimizer-Optimized LSTM Network
Short-term traffic flow is affected by various factors and usually presents strong nonlinear and stochastic characteristics, which makes accurate prediction difficult. Meanwhile, the selection of LSTM network parameters is often based on manual experience, and an inappropriate parameter setting may affect the prediction performance of the model. Therefore, this study proposes a Dung Beetle Optimizer-based LSTM (DBO-LSTM) model for short-term traffic flow prediction. The LSTM network is used to learn the temporal characteristics of traffic flow, and the DBO algorithm is applied to optimize important parameters of the LSTM network, including the learning rate and the number of hidden-layer neurons. In this way, the parameter selection process can be improved and the dependence on manual parameter adjustment can be reduced. Traffic flow data collected from a real road network are selected for model validation. The proposed DBO-LSTM model is compared with the conventional LSTM, PSO-LSTM, and WOA-LSTM models. The results show that the DBO algorithm can obtain a better parameter combination for the LSTM network. Compared with the three comparison models, the DBO-LSTM model obtains lower RMSE and MAPE values and has better overall prediction performance. The results verify the effectiveness of the proposed model for short-term traffic flow prediction and provide a reference for traffic congestion warning and traffic management in intelligent transportation systems.
Model Reference Adaptive Control for Load Mitigation in Floating Offshore Wind Turbines via Blade Pitch Regulation
Floating offshore wind turbines (FOWTs) face significant challenges in power regulation due to the inherent intermittency and fluctuations of wind resources. To address this issue, this study proposes a novel collective blade pitch controller based on Model Reference Adaptive Control (MRAC) with a constant modification term for precise generator speed regulation. Furthermore, an auxiliary feedback loop incorporating a PID controller is integrated to utilize floating platform pitch angle measurements, thereby enhancing overall system stability. Simulation results demonstrate that the proposed control strategy effectively mitigates load variations and improves power output quality, confirming its superior performance compared to conventional methods.
Spatiotemporal Evolution and Driving Analysis of Carbon Storage in Hebei Province Based on InVEST-CatBoost-MGWR Models
Land use and cover change significantly affects regional carbon cycles. From a multi-model coupling perspective, this study focuses on the mechanisms by which land use change influences carbon storage in Hebei Province. The InVEST model was employed to quantify the spatiotemporal dynamics of carbon storage from 2000 to 2025. The CatBoost machine learning algorithm was used to identify key driving factors, whose contributions were interpreted through SHAP values. Additionally, the multiscale geographically weighted regression (MGWR) model was applied to reveal the spatially non-stationary relationships between these factors and carbon storage. The results indicate that carbon storage in Hebei Province experienced a continuous decline from 2000 to 2025, decreasing from 1.887 billion tons to 1.841 billion tons,a total reduction of 46 million tons, or 2.44%. Notably, the decline accelerated markedly in the later period: the reduction was only 0.23% from 2000 to 2015 but reached 2.23% from 2015 to 2025. NDVI was the most important driving factor during 2000–2015, whereas slope emerged as the dominant factor by 2025, reflecting the increasing control of topographic conditions over carbon storage. The influence of each factor exhibited significant spatial heterogeneity. NDVI had the strongest impact in the Taihang Mountain area, while population density showed a significant negative effect in the urban agglomerations of the central Hebei Plain. These findings provide a scientific basis for low-carbon territorial spatial planning and the realization of carbon peak and carbon neutrality goals in Hebei Province.
Risk-Aware Site Selection of Transshipment Nodes for Low-Altitude Logistics Route Networks
To balance logistics efficiency and ground safety in urban low-altitude logistics, this paper proposes a risk-aware SOM-based transshipment node siting method. A 10 m static ground risk map is built to screen candidate nodes, and risk suppression and risk-gradient repulsion terms are embedded into the SOM weight update so nodes migrate to low-risk areas while fitting demand. In a 5 km x 5 km Tangshan area, at λ = 0.8 and k = 25, the average service distance rises only 1.55% (254.23 m to 258.16 m), while point risk, 50 m buffer risk, and maximum node risk fall by 17.9%, 16.5%, and 17.1%.
Development of a Novel Spring-Reset-Triggered Packaging Wheel Overbridge for ZB417
To address the issue that the original packaging wheel overbridge of the ZB417 packaging unit is a fixed structure incapable of effectively detecting defective cigarette packs during the conveying process of cigarette group packaging and forming, this paper proposes a novel packaging wheel overbridge design scheme. Adopting an integrated design of mechanical and detection components, the scheme realizes elastic lifting of the overbridge plate via reset springs and trigger studs, and achieves automatic detection of defective cigarette packs and shutdown protection with proximity switches. Practical application results show that the device can effectively identify expanded and deformed cigarette packs, significantly reduce the incidence of quality accidents, and adapt to carton papers of varying thicknesses.
A Review of Carbon Nanotubes’ Effects on Plant Growth and Their Environmental Impact
Against the backdrop of global warming and rapid population growth, issues such as limited arable land and soil degradation and water pollution caused by the overuse of traditional chemical fertilizers are becoming increasingly severe. Developing new agricultural technologies to ensure food security has become a global consensus. Carbon nanotubes (CNTs), with their unique physicochemical properties—including high specific surface area, excellent conductivity, and environmental friendliness—offer innovative solutions to these challenges and serve as key materials for promoting sustainable agricultural development. Research indicates that CNTs can optimize plant growth in multiple dimensions, including promoting water transport and nutrient absorption, as well as regulating endogenous plant hormones and antioxidant systems. These beneficial effects can also significantly enhance crop resilience under adverse conditions such as drought and salinity. When faced with heavy metal or pesticide residue contamination, CNTs can alleviate stress by reducing the bioavailability of toxins. Furthermore, as novel carriers for fertilizers and pesticides, CNTs not only enable the slow release of active substances to enhance efficacy but also facilitate the construction of microsensors, supporting precision monitoring and virus control in smart agriculture. However, concerns remain regarding the ecological safety of CNTs. Their environmental degradation mechanisms are unclear, and they are prone to bioaccumulation; moreover, their effects on plants and soil microorganisms vary depending on type, concentration, and exposure duration. Compounding this complexity, CNTs may exhibit synergistic toxicity with environmental pollutants, and their long-term ecological risks urgently require assessment. This research focuses on the microscopic mechanisms by which CNTs promote the growth of major crops, their practical application efficacy, and their potential disruption of soil ecosystems. It aims to systematically evaluate the agricultural application potential of CNTs, providing a theoretical basis for maximizing their agronomic benefits while mitigating ecological risks, ultimately contributing to global food security and the green transformation of agriculture.
Graphene-TMDs Van der Waals Heterojunction Photodetectors: From Mechanisms and Fabrication to Performance and Applications
Photodetectors, as the core devices for photoelectric signal conversion, are widely used in key fields such as optical communication, imaging, and sensing. The rise of two-dimensional materials provides a new idea for solving the material bottleneck of traditional photodetectors. Graphene, with its ultra-high carrier mobility and broad spectral response advantages, has become an ideal platform for constructing high-speed photodetectors. However, its zero-bandgap property leads to problems such as low photoresponsivity and high dark current. Transition metal dichalcogenides (TMDs) have a suitable direct bandgap and strong light-matter interaction, but their carrier mobility is relatively low. By constructing van der Waals heterojunctions of graphene and TMDs, the advantages of both can be fully utilized to achieve efficient separation and transport of photogenerated carriers, significantly improving the photodetection performance.
Synergistic Pathways to Carbon Neutrality in China: Multi-Criteria Evaluation of Urban Metabolism, Ecological Restoration, and Direct Air Capture
China's commitment to carbon neutrality by 2060 cannot be met through emission cuts alone; the residual emissions from hard-to-abate sectors must also be offset by carbon removal. Mitigation and removal, in other words, are two halves of a single strategy. To date, researchers have largely examined urban metabolism optimization, ecological restoration, and direct air capture (DAC) as separate topics, leaving their combined potential and regional variation underexplored. This paper addresses that gap by constructing an evaluation framework that couples the analytic hierarchy process (AHP) with the entropy weight method. Each pathway is scored along four dimensions—carbon reduction potential, cost-effectiveness, technical maturity, and scalability—with weights derived from both expert judgment and data variability. Drawing on IPCC AR6, IEA 2024, and Chinese official statistics, we compare a baseline scenario against an enhanced scenario and disaggregate the results by eastern, central, and western China. Four findings emerge. Urban metabolism regulation dominates, accounting for 42–43% of projected 2030 emission reductions. Ecological restoration offers the lowest unit cost (USD 17–21 per ton of CO₂) and strong life-cycle net benefits. DAC remains supplementary before 2040 but gains importance thereafter as costs fall. Regional heterogeneity is pronounced: the east should prioritize urban metabolism, the center a balanced mix, and the west ecological restoration. Under the enhanced scenario, the three pathways together could deliver 1.5–1.8 Gt of annual CO₂ reduction by 2035. These results provide empirical support for a phased, regionally differentiated decarbonization strategy.
Applications and Countermeasures of Rapid Soil Pollution Detection Technologies in Agricultural Production
As agricultural intensification and industrialization continue to accelerate in China, soil pollution in farmland has become increasingly prominent, posing serious threats to food safety and ecosystem health due to heavy metals, organic pollutants, and microplastics. Although traditional laboratory detection methods feature high accuracy, they suffer from limitations including prolonged detection duration, high costs, and complex operational procedures, rendering them incapable of meeting the demand for real-time, rapid assessment of soil quality in modern agriculture. In this paper, the research progress of rapid detection technology of soil pollution in recent years is systematically reviewed, and the principle and characteristics of mainstream technologies such as visible near infrared spectroscopy, portable X-ray fluorescence spectroscopy, and laser-induced breakdown spectroscopy are analyzed. On this basis, the application value of these technologies in farmland heavy metal screening, sampling optimization, nutrient detection and contaminated site investigation was discussed, the limitations of current technologies were analyzed, and the future development strategy of rapid detection technology was put forward, in order to provide technical support for the prevention and control of agricultural soil pollution and sustainable development.
A Coupled Inductor Coil Z-Source Inverter for Photovoltaic-Assisted Charging of Hilly Electric Agricultural Machinery
The coupled inductor coil Z-source inverter has advantages such as continuous input current and good boost performance. However, the traditional quasi-Z-source inverter not only requires a bulky isolation transformer but also suffers from large high-frequency common-mode leakage current. To address these drawbacks, this paper first proposes a coupled inductor coil Z-source inverter topology for photovoltaic-assisted charging of hilly electric agricultural machinery. Secondly, the high-frequency common-mode leakage current suppression mechanism of the inverter is analysed. Then, a detailed comparison is made between the proposed inverter and the traditional quasi-Z-source inverter. The research shows that the proposed inverter not only effectively suppresses high-frequency common-mode leakage current without the need for a bulky isolation transformer, but also requires only one magnetic core and one capacitor, which can effectively reduce the weight and volume of the inverter and lower its cost. Finally, the correctness of the inverter design and theoretical analysis is verified by circuit simulation.
Research Progress in The Preparation of Graphene by Oxidation-Reduction Method
Graphene represents a monolayer carbon material with a hexagonal honeycomb lattice. It has high conductivity, high specific surface area and excellent thermal and mechanical properties. Such outstanding properties enable its wide-ranging applications in sensing, membrane technology, biomedical engineering, and other advanced fields. In this paper, the research progress of graphene prepared by oxidation-reduction method is systematically reviewed, covering the development from classical oxidation methods to modern improved processes. The effects of different types of reduction methods on the structure and properties of the products are analyzed. Finally, the main problems and future development directions are summarized.
Reforming Auditing Education in the AI Era: A Three-Stage Progressive Teaching Model and Its Policy Implications for Higher Education
As artificial intelligence and digital technologies become deeply embedded in the auditing profession, the structural gap between conventional university curricula and evolving industry demands has grown increasingly pronounced. This paper reports on a systematic teaching reform of an undergraduate Auditing course, validated across multiple academic cycles, which addresses three core pedagogical pain points: fragmented knowledge structures, the failure to integrate AI and digital tools into instruction, and insufficient team-based project experience. Drawing on diagnostic surveys of 225 students, the course was redesigned around a "Three-Stage Progressive" model encompassing two coordinated innovations: a "Three-Module, Five-Dimensional Integration" content restructuring, and a dual-track approach combining AI-driven instructional methods with team-based project learning and portfolio assessment. Post-reform data show significant improvements in student academic performance, digital competency, and professional identity. On this basis, the paper advances five higher education policy recommendations for reforming accounting and auditing programmes in the AI era, addressing curriculum governance, industry-embedded practicum frameworks, and competency-oriented assessment systems.
Inhibition of Return and Refixation in Visual Search
Search is efficient only if observers know when to leave a location and when to inspect it again. Inhibition of return (IOR) is usually inferred from slower responses at a previously cued or inspected location and is often taken as a mechanism that favors novel locations. The inference is incomplete. A cost measured with an experimental probe need not predict the next voluntary fixation, while returns are frequent in natural viewing. This review places classic cueing and visual-search studies alongside work on refixation, virtual and three-dimensional search, and real-world eye movements. The evidence separates three questions that are often conflated: how an old location is processed, whether it is selected again, and whether returning benefits the task. Laboratory results reliably demonstrate conditional costs, but their expression varies with response requirements and scene continuity. Studies of active viewing show that incomplete encoding, comparison demands, environmental change, and movement economy can make a return worthwhile. IOR is thus treated here as one bias in fixation priority, not a ban on looking back. The proposed return-control account predicts that revisiting will be favored when the expected benefit of another look exceeds the recency-related disadvantage and the cost of moving elsewhere.
Geological Investigation and Slope Stability Analysis of the Archaeological Excavation Trench at the Zhouqiao Bridge Site and Bianhe Canal Ruins, Kaifeng
Based on field investigations of the geological structure, stratigraphic lithology, and groundwater depth of the excavation trench slopes at the Zhouqiao bridge site and Bianhe canal ruins, Kaifeng, together with slope deformation monitoring data, the stability of the trench slope was studied by numerical simulation using the FLAC3D model. The results show that under the self-weight condition, the maximum displacement of the trench wall is 3.87 cm and the factor of safety (FOS) is 1.18, indicating a basically stable state; under the combined self-weight and earthquake condition, the maximum displacement reaches 7.23 cm and the FOS is 0.943, indicating an unstable state. These findings provide a data reference for the selection and implementation of reinforcement and protection measures for the slopes of archaeological excavation trenches.
Model Predictive Control for n-Butyl Acetate Distillation Column via Aspen-MATLAB Co-Simulation
To address the issues of significant fluctuations in conventional PID control and the susceptibility of product purity to disturbances in n-butyl acetate production, a steady-state model was first established in Aspen Plus and then imported into Aspen Dynamics to obtain a dynamic simulation model of the process. On the basis of the conventional control structure, a model predictive control (MPC) scheme was designed through a co-simulation platform integrating MATLAB and Aspen Dynamics. Simulation results demonstrate that the MPC scheme can effectively suppress dynamic fluctuations caused by feed flow disturbances, with notably reduced amplitudes of product purity variations. This achieves smooth and efficient operation of the n-butyl acetate production process, along with a significant enhancement in product quality stability.
Review of Vibration Characteristics, Inducing Mechanisms, and Control Strategies for High-Stress Amplitude Fatigue Test Machines Under High and Low Temperature Environments
The device developed for material fatigue assessment is the core to help the development of related equipment fields such as aerospace, nuclear energy systems, and low-temperature storage and transportation. However, when the device encounters extreme temperature range (-100 °C to + 600 °C) and medium and high load amplitude (≥ 0.5 times the yield strength) at the same time, such devices often appear abnormal vibration and sound beyond the ISO 10816-3 standard, which greatly affects the measurement accuracy and shortens the service life. This paper systematically sorts out the common characteristics of the source of vibration generation in such work scenarios, digs into the underlying basic physical laws, evaluates the latest achievements of multi-physical field coupling simulation, and sorts out the current noise reduction methods. Based on the research of SCI / EI related literature content and ASTM / ISO related specifications in the past five years, it is concluded that the resonance frequency shift caused by ambient temperature fluctuation and the wide range frequency stimulation during high temperature operation are the main triggers of such problems. Noise reduction technology is gradually shifting from the traditional isolation method to the intelligent system that anchors the root cause of the problem. This study proposes three noise reduction implementation schemes that adapt to the standardized test framework, and also clarifies the core limitations of the current numerical simulation methods in thermal effects, force-frequency correlation coupling, and time-space field coordination. It is necessary to integrate multiple control strategies to improve. The goal of this paper is to establish a relevant theoretical framework for the design, production, capacity optimization and practical engineering use of devices that perform fatigue problem detection in complex working environments, and give practical guidance.
A Review of Research on Pedestrian Red-Light Running Behavior: Theoretical Frameworks, Influencing Factors and Intervention Strategies
Pedestrian red-light running is one of the most prevalent traffic violations at signal-controlled intersections and a critical contributor to pedestrian-vehicle collision crashes. This review breaks down pedestrian red-light running research into three main areas: theoretical models, key drivers, and prevention methods. It relies heavily on extended Planned Behavior models as the main backbone, while using the Prototype Willingness Model to show how much social pressure actually fuels the behavior. In terms of influencing factors, existing studies have identified multi-level mechanisms of waiting time, traffic flow, distracted behavior, herd effect and other variables, among which waiting time and herd effect are verified as the most influential predictors. For intervention strategies, engineering countermeasures, law enforcement and educational publicity form three major approaches, yet quantitative assessments of their effectiveness remain insufficient. On the basis of commenting on limitations of current research, this paper puts forward several directional suggestions for future studies.
Recent Progress in Process and Mechanical Properties of Ultrasonic-Assisted Friction Stir Welding of Aluminum Alloys: A Review
Aluminum alloys, as pivotal structural materials for lightweight manufacturing, have been extensively applied in cutting-edge industries such as aerospace, rail transit, and automotive engineering. However, the conventional solid-state joining technology, friction stir welding (FSW), often faces critical bottlenecks when processing ultra-high-strength aluminum alloys or dissimilar materials, including non-uniform heat input, excessive tool wear induced by high axial forces, restricted grain refinement, and a high susceptibility to welding defects like tunneling and kissing bonds. As an advanced solid-state hybrid joining technology that deeply integrates a high-frequency acoustic field with a thermal-mechanical coupled field, ultrasonic-assisted friction stir welding (UAFSW) introduces high-frequency ultrasonic vibrations during the welding process. This hybrid process significantly improves the rheological characteristics of plasticized metals, reduces mechanical loads, and refines the joint microstructure. This paper systematically reviews recent research progress in UAFSW for both similar and dissimilar aluminum alloys. Special emphasis is placed on elucidating the underlying mechanisms of microstructural reconstruction and mechanical performance enhancement driven by the acoustic volume and acoustic surface effects. Furthermore, representative process parameters and experimental data are comprehensively deconstructed, followed by an outline of key future research trends in this field.
Experimental Research on Damage Recognition of T-shaped Beam on an Areospacecraft
The paper pre-set some damages in different level in the T-shaped beam test specimen by wire cutting, and obtained modal data of the damaged T-shaped beam by experiment. It adopted two methods, i.e. element modal strain energy change rate and element modal strain energy basis, to recognize damage locationally, and it adopted two methods, i.e. sensitivity matrix and second order generalized flexibility matrix, to recognize damage quantificationally. The result showed that the element modal strain energy basis had better locational recognition result while the second order generalized flexibility matrix had better quantitative recognition result. Therefore, using a combination of the two methods will get good recognition result, i.e., firstly using the element modal strain energy basis to recognize damage locationally, and then using the second order generalized flexibility matrix to recognize damage quantificationally.
Land-use and Fractional Vegetation Cover Changes in Tianshui, China: Spatiotemporal Patterns and Spatial Associations
To clarify the spatial association between land-use change and fractional vegetation cover (FVC) dynamics, we integrated land-use and MODIS NDVI data from 2000, 2007, 2015, and 2022 with land-use dynamic degree, land-use transition matrices, the pixel dichotomy model, FVC transition matrices, and spatial overlay analysis to examine the spatiotemporal evolution of land use and FVC in Tianshui from 2000 to 2022. The results showed that (1) land-use structure changed markedly during the study period. Cropland declined by 1,425.795 km², whereas grassland, forest land, and built-up land generally expanded, with the largest increases occurring in grassland and forest land. Land-use conversions occurred mainly among cropland, grassland, and forest land, and built-up land expansion was driven primarily by the conversion of cropland and grassland. (2) FVC generally increased, with higher values in the southeast and lower values in the northwest. Areas of low and relatively low FVC contracted, whereas moderate- and high-FVC areas expanded, indicating an overall shift towards higher FVC classes. (3) Land-use type was closely associated with the spatial distribution of FVC, and vegetation-cover characteristics differed among land-use types. FVC was generally higher in forest land and grassland than in built-up land and unused land. These findings indicate that ecological restoration and land-use adjustment jointly shaped the surface ecological environment of Tianshui and provide a scientific basis for regional land-resource optimization, ecological conservation, and sustainable development.
Feedforward Periodic Torque Synthesis-Based Precise Control for BLDC Motor with Swashplateless Mechanism
Aiming at the problems of torque response lag and low modulation accuracy existing in traditional throttle modulation modes of unmanned aerial vehicles (UAVs) equipped with Swashplate-less Mechanism (SPLM), a periodic torque SVPWM synthesis control method based on phase feedforward is proposed. Firstly, the dynamic model of the SPLM and the Field-Oriented Control (FOC) model of surface-mounted permanent magnet synchronous motor (SPMSM) are established to reveal the coupling relationship between the instantaneous electromagnetic torque of the motor and the blade pitch angle. Secondly, the action mechanisms of three schemes, namely outer modulation of traditional speed loop, pure feedback current loop tracking and load feedforward periodic torque synthesis, are compared and analyzed. Finally, quantitative evaluation is carried out from three dimensions including total harmonic distortion of torque waveform, amplitude tracking error and phase tracking error via simulation experiments. The results show that under the operating condition of 5000 r/min, the load feedforward periodic torque synthesis method reduces the torque phase error from 8.7° to 1.2°, the amplitude error from 11.3% to 2.1%, and the total harmonic distortion from 18.6% to 4.2%, which significantly improves the torque modulation accuracy and response speed of the SPLM.
A Digital Twin-Driven Multisource Fault Diagnosis System for Smart Water Distribution Networks
Due to the combination of sensing, hydraulics, computation and operation in the digital twin fault diagnosis of smart water distribution networks, there are many sources of uncertainty, and thus a single deterministic controller or classifier cannot be used in engineering practice. The main contents of this paper are a strong diagnosis and control system, multi-sensor fusion, bias-aware residual construction, model-predictive reasoning, conservative fallback rules, etc. Parametric scenario data will be employed in the framework evaluation, and all evaluation indices and threshold parameters will be set to guarantee the repeatability of the engineering test. The five tables present the sensor channel, disturbance case, diagnostic threshold, control response and robustness indicator; the two analytical formulas are the residual score and the weighted stability index. Based on the above tests, it can be seen that the proposed framework has a small false alarm rate and is relatively stable under all circumstances; even when the input signal is biased, delayed or partially missing, the chain of evidence connecting fault data, model constraint derivation and control measures can still meet the audit requirements of standard engineering journals.
Graphene Composites for Lithium-ion Battery Anodes: A Review
New energy technologies are advancing fast, pushing up the demand for higher-energy-density lithium-ion batteries. Graphene composites stand out among anode modification strategies due to their good conductivity and flexibility. They have been applied to silicon, sulfide, and oxide anodes. This review covers recent progress in graphene composite anodes, looks at how graphene works in these systems, and discusses future directions.
Fault Diagnosis and Early Warning of Power Systems Based on Artificial Intelligence
This study attempts to offer a broad picture of where artificial intelligence (AI) currently stands in power system applications, touching on its role in fault diagnosis and early warning, while also weighing the difficulties encountered and possible routes ahead. Through a systematic review and synthesis of the available literature, the paper surveys the existing landscape of AI adoption within power systems, covering, among other things, expert systems and neural network approaches. The findings suggest that AI has indeed improved both the efficiency of fault detection and the overall operational performance of modern power grids. However, certain concerns persist, including data equilibrium reliability and real-time coordination, which remain open for deeper investigation. In response, the paper puts forward several policy-oriented suggestions for upcoming research efforts, and reaffirms the significance and untapped potential of AI applications in the power domain.
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.
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.
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.