International Journal of Advanced Engineering and Technology Research
International Journal of Advanced Engineering and Technology Research (IJAETR) is an international, peer-reviewed journal. The mission of the journal is to provide an academic platform for scholars and practitioners to discuss the issues of engineering and technology across the world. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
From "Drawing" to "Model": Research on the Reconstruction of Landscape Architecture Teachers' BIM Teaching Competence under the Background of New Engineering Education: A Case Study of Zhaoqing University
The development of new engineering disciplines has imposed new requirements for digitalization and interdisciplinary integration in landscape architecture talent cultivation, with BIM technology proficiency becoming a critical competency for industry transformation. However, current BIM education in landscape architecture programs faces the persistent challenge of "teacher preparation lag" —teachers 'BIM knowledge reserves, technical capabilities, and instructional adaptation skills remain core bottlenecks constraining educational quality. Using Zhaoqing University's landscape architecture program as a case study, this research systematically diagnoses three pedagogical dilemmas through questionnaire surveys, in-depth interviews, and teaching action research: knowledge fragmentation, tool instrumentalization, and formalized teaching approaches. Based on these findings, we propose a teacher development pathway encompassing "cognitive restructuring, competency reconstruction, and instructional redesign," while establishing a tripartite competency enhancement mechanism integrating project immersion, workshop empowerment, and interdisciplinary collaboration. The study reveals that the essence of teachers' BIM instructional competence lies not in software proficiency but in cognitive transformation—recognizing BIM as an "information carrier" rather than a "drawing tool" —alongside corresponding curriculum restructuring capabilities and industry-academia collaboration skills. This research provides actionable frameworks for teacher development in landscape architecture programs at regional universities within the context of new engineering education.
Industry-Academia-Research Collaboration
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Feasibility Study on Application of Electric Stove in Civil Kitchen
As urban gas adoption approaches saturation and electrification of household appliances accelerates, electric cooktops—a novel plasma cooking device—are gaining traction in residential kitchens. This study systematically evaluates thermal efficiency, heat load stability, and operational safety of two electric cooktop models (Xingyu YN-XY-0001-A and Huahuo HH-DTQP5 Pro) through comparative tests with traditional gas stoves. Results reveal that electric cooktops demonstrate lower thermal efficiency (57.4%) at low power levels compared to gas stoves (64.6%), though significant efficiency improvements occur in medium-to-high power ranges. Actual heat load measurements consistently fall below rated power output, indicating energy conversion losses. Notably, ozone emissions generated by corona discharge during operation can now be effectively mitigated through electrode structure optimization and UV decomposition systems. Comprehensive techno-economic analysis indicates potential for electric cooktops in gas-free areas, newly electrified communities, and scenarios requiring open flame cooking. However, ozone control mechanisms and thermal efficiency enhancement remain critical barriers to large-scale commercial adoption.
Toward Equitable Access to Technical Training via Multilingual Conversational Agents
The global technical skills gap disproportionately affects non-English-speaking populations who encounter substantial language barriers when attempting to access digital training resources. Multilingual conversational agents (MCAs), powered by advanced natural language processing (NLP) technologies, offer a promising pathway toward democratizing technical education across linguistic communities. This paper presents a mixed-methods investigation into the design, deployment, and evaluation of an MCA system tailored for vocational and technical skill acquisition in multilingual environments. Drawing on transformer-based multilingual language models, recurrent encoder-decoder architectures, and adaptive task-oriented dialogue management frameworks, the proposed system was assessed across four language groups — Spanish, Arabic, Mandarin Chinese, and Hindi — in simulated technical training scenarios covering information technology fundamentals and industrial safety protocols. Quantitative results indicate statistically significant improvements in learning outcomes, task completion rates, and user engagement compared to English-only baseline systems. Qualitative findings further reveal that language alignment between learner and agent substantially reduces cognitive load and increases perceived system credibility. This research contributes a validated architecture and evaluation framework for practitioners and policymakers committed to equitable access to technical education through intelligent conversational systems.
Theoretical Research on Hopf Insulators and Model Construction in One-Dimensional Phononic Crystals
In this Letter, a theoretical model of the Hopf insulator is constructed to realize topologically protected boundary states and higher-order corner states via parameter-space modulation. The nontrivial topological order is characterized by the Hopf mapping; by tuning the Hamiltonian coupling parameters, phase transitions are induced, and the localized stability of the boundary and corner states is theoretically verified. Subsequently, this framework is mapped onto a phononic crystal platform, leveraging the tunability of artificial bands to construct a one-dimensional equivalent physical model of the Hopf insulator. Through the precise design of resonator geometries and coupling parameters, an effective correspondence of the topological bands is achieved. Analytical calculations and finite-element simulations exhibit excellent agreement in both band dispersions and eigenstate distributions, confirming the feasibility of this model in acoustic systems and the robustness of its topological states.
Application of Automated Data Extraction Technologies in Ophthalmic Electronic Health Records
Now that the healthcare industry is increasingly using digital technology, there is a lot of useful unstructured data in the electronic health record of the eye, but it is easy to make mistakes when it takes time to process it manually. In order to solve this problem, this paper carefully examines the application of optical character recognition and natural language processing in ophthalmic electronic medical records, and also pays special attention to the large language models that have recently been very hot. We checked a lot of data through Google Scholar, and after careful screening, we selected 30 good quality articles to study. From the results, these technologies have their own advantages and disadvantages: optical character recognition processing standardized equipment reporting accuracy is very high, but it is not very good when it comes to handwriting. Natural language processing can find vision data and disease characteristics from the medical record text, but if the medical record format is not uniform, the effect will be reduced. The latest large-scale language models are really powerful, they can directly handle words and pictures, and change the entire workflow, but they also have their own problems, such as data security, high operating costs, and possible hallucinations. In general, these automated technologies have deepened the use of data on electronic medical records of ophthalmology. Later research can focus more on how to better combine different types of data, and to develop some language models that are specific to ophthalmology, smaller, and can operate safely locally.
Research Status of Advanced Prediction for Water and Mud Inrush in Karst Tunnels
In the construction of tunnel engineering, adverse geological disasters such as water and mud inrush are frequently encountered, which tend to cause severe consequences including construction delay, casualties and economic losses. Therefore, it is crucial to conduct advanced prediction of water and mud inrush disasters. This paper summarizes the failure mechanism of water and mud inrush in tunnels and analyzes its influencing factors. Commonly used advanced prediction technologies and methods for tunnel water and mud inrush are introduced in detail, including the TSP geological prediction method, ground penetrating radar (GPR), infrared water detection, terrestrial sonar method, and transient electromagnetic method. According to the applicability and accuracy of these advanced prediction technologies, their specific applicable engineering conditions are summarized. Based on the latest theories and methods for water and mud inrush testing, cutting-edge achievements in water and mud inrush prediction are presented. New detection methods such as CT technology, nuclear magnetic resonance (NMR), and multi-homogeneous source array resistivity detection are elaborated in detail.
Fabrication and Performance Tuning of Silica/Silicone Rubber Composites for High-Permittivity Low-Modulus Dielectric Elastomers
Dielectric elastomers (DEs) are promising electroactive polymers owing to their low modulus, large actuation strain, and fast response. Silicone rubber, particularly polymethylvinylsiloxane (PMVS), is highly attractive due to its excellent flexibility and fatigue resistance. However, its low dielectric constant limits electromechanical performance. Here, we report a synergistic strategy that combines KH570-modified SiO₂ nanoparticles with tunable liquid-to-solid PMVS ratios. By optimizing the matrix composition, the SiO₂@3L7S composite (liquid:solid = 3:7) achieves an optimal balance of high dielectric constant and low modulus. The dielectric constant reaches 4.0 (46% higher than pure PMVS), while the maximum actuation strain increases to 45.4%—50% higher than the solid PMVS baseline—delivering a high energy density of 20.5 mJ/g. This approach, integrating covalent interfacial bonding and homologous plasticization, offers a simple yet effective route to high-performance silicone-based dielectric elastomer actuators for soft robotics and artificial muscles.
Development of a Lateral Flow Assays Sensing Platform Based on Aptamer-Modified Pt@Au Nanozymes for The Detection of Kanamycin
Thanks to its ease of use, speed, efficiency, and the ability to visually identify detection signals without the need for specialized equipment, lateral flow assay (LFA) technology has become a key analytical method in fields such as pharmaceutical safety testing and biomedicine. Traditional lateral flow assays use colloidal gold as a signal label; however, due to the limited intensity of its colorimetric signal, conventional LFA technology suffers from insufficient sensitivity and fails to meet detection requirements. Based on this, this study synthesized platinum-based bimetallic nanozymes (Pt@Au). Through the synergistic interaction of multiple metal elements, these nanozymes exhibit high enzyme-like catalytic activity. They were then applied to lateral flow assay technology to enable sensitive detection in biosensing. The Pt@Au nanozyme possesses high peroxidase-like catalytic activity, enabling it to catalyze the color-forming substrate TMB within an extremely short time to amplify the signal and achieve sensitive color development. By using an aptamer as an intermediate competitive molecule, streptavidin was conjugated to biotin-DNA molecules on the surface of the Pt@Au nanozyme to competitively detect kanamycin in LFA test strips. The detection linear range is 100 ng/mL to 800 ng/mL. Within the spiked concentration range of 50 to 250 ng/mL, the recovery rates of this method range from 95.1% to 105.2%, with relative standard deviations (RSD) of 3.4% to 8.5%, providing a new technical approach for the rapid on-site detection of antibiotic residues.
Overview of the YOLO Object Detection Algorithm
The YOLO (You Only Look Once) object detection algorithm, proposed in 2015, has now evolved to YOLOv12, boasting improved detection speed and accuracy, and is currently a hot research topic. This article focuses on introducing the basic network structure of the YOLO series algorithms, summarizing the innovations, advantages, and limitations of the YOLOv1~YOLOv12 algorithms, reviewing the applications of YOLO detection algorithms and their improved versions in industrial, agricultural, and security fields, and based on this, looking ahead to the possible future development trends of the YOLO algorithm.
Wheat LAI Inversion and Yield Estimation under T-MLP
To address the limited accuracy and poor generalization capabilities of existing winter wheat Leaf Area Index (LAI) inversion methods, such as the NDVI vegetation index model and support vector machine (SVM), this paper proposes a hybrid modeling approach that integrates a radiative transfer model with deep learning. This method uses the PROSAIL model to generate simulated samples, optimizes the input parameter configuration through local and global sensitivity analysis, constructs a lookup table (LUT) to assist in the generation of training sets, and designs a T-MLP network that integrates Transformer and Multilayer Perceptron (MLP). This approach leverages the cross-band global dependencies in Landsat 8multispectral data and enhances LAI modeling capabilities through nonlinear regression. Using ground-truth data from the main wheat-producing region of Shangqiu City, Henan Province, this model's performance is validated and compared with the NDVI, PROSAIL and CNN models. Winter wheat yield estimation is then performed using the LAI inverted by the T-MLP model in combination with the EC-LUE model. Results showed that T-MLP achieved superior inversion accuracy across multiple growth stages (R²=0.83, RMSE=1.04), outperforming the NDVI model (R²=0.55, RMSE=1.58), the PROSAIL model (R²=0.76, RMSE=1.36) and CNN model (R²=0.78, RMSE=1.12). Comparison of the inversion results with the MODIS LAI product revealed that T-MLP demonstrated greater robustness in terms of temporal consistency and cross-plot stability, accurately reflecting the dynamic trends of wheat LAI. The relative error of yield predictions was below 10%. This study provides a practical approach for high-precision LAI inversion and yield estimation that integrates physical constraints with the advantages of deep learning.
Research Progress of Inorganic Solid Electrolytes in All-Solid-State Lithium Metal Batteries
All-solid-state lithium metal batteries have become an important development direction for next-generation battery technologies due to their high energy density and high safety. As a core component, inorganic solid electrolytes demonstrate great potential in suppressing lithium dendrite growth and reducing the risk of internal short circuits because of their high ionic conductivity, wide electrochemical stability window, good thermal stability, and strong mechanical properties. This paper reviews recent research progress on inorganic solid electrolytes, especially oxide, sulfide, and halide solid electrolytes. The characteristics and interfacial issues of oxide solid electrolytes, including perovskite-type and LISICON-type materials, are discussed in detail, along with the advantages and challenges of sulfide and halide solid electrolytes in terms of high ionic conductivity and interfacial stability. Finally, the future prospects of inorganic solid electrolytes in all-solid-state lithium metal batteries are discussed.
Temperature Field Prediction of Polypropylene Yarns in Fabric-Based Evaporators for Solar Seawater Desalination
To accurately predict the temperature field in the horizontal segment of polypropylene yarns for solar-driven seawater desalination fabrics, this study performed experimental tests and modeling analysis. 900D polypropylene yarns were prepared to build a temperature test system, with data measured by an infrared thermal imager. A multiphysics coupling temperature field prediction model was developed as the core work: the unsteady conduction-convection coupled heat transfer control equation of yarns was derived, the 1D Richards equation was adopted for capillary liquid transport characterization, and the interfacial evaporation rate quantification model was coupled. The governing equations were iteratively solved after steady-state transformation, spatial discretization and second-order central difference discretization. Experimental verification showed high consistency between model predictions and measured data (RMSE= 0.92, average relative error=2.01%), which accurately reveals the gradual rise of yarn temperature from the water supply end to the evaporation far end. The study also analyzed model limitations such as idealized assumptions and parameter source issues, and proposed optimization directions including multi-dimensional modeling and experimental measurement of key parameters. It clarifies the essence of heat transfer before constructing the temperature field model, accurately reveals the heat and mass transfer correlation at the yarn scale, and provides a theoretical basis for the performance improvement of fabric-based evaporators.
Broadband Low-Frequency Sound Absorption Based on Helmholtz Resonators Embedded with Microperforated Panel
This study proposes a novel Helmholtz resonator embedded with a microperforated panel (HREMPP) for broadband low-frequency sound absorption. A theoretical model was validated by simulations. The 50-mm-thick HREMPP unit achieves near-perfect absorption at 250 Hz with a bandwidth 50% wider than a conventional Helmholtz resonator. Parameter analysis reveals how neck radius, neck length, and micro-perforation radius tune the performance. By parallel coupling two units with different neck radii (2 mm and 3 mm) while maintaining a 50 mm total thickness, a broadband metamaterial is created. It exhibits two absorption peaks at 208 Hz and 284 Hz, forming a continuous broad absorption band from 176 Hz to 358 Hz. This work provides a design for ultra-thin, broadband, low-frequency acoustic absorbers.
Research on the Operational Reliability of the Crankshaft Rotation Device of the Compressor Unit
This paper conducts a structural safety optimization study on the gear strength of the automatic cranking device for natural gas reciprocating compressor units, aiming to enhance their overall reliability. By replacing the gear material with 20Cr and optimizing the radius of the fillet at the tooth root, the contact stress on the tooth surface was reduced by 46.3%, and the bending stress at the tooth root decreased by 31%. Both of these indicators fell below the allowable stress threshold after optimization. The research results show that the reliability of the optimized cranking device has been significantly improved, providing an effective solution for the safe and efficient operation of natural gas compressor units.
Natural gas reciprocating compressor unit
Parameter Optimization of Pre-stage CO₂ Fracturing
As a core technology for the efficient and green stimulation of unconventional oil and gas reservoirs, pre-stage carbon dioxide (CO₂) fracturing relies on the unique properties of CO₂ including low viscosity, high diffusivity, easy phase transition, and energy enhancement for flowback improvement. It can effectively reduce reservoir breakdown pressure, activate natural fractures, mitigate water-sensitive formation damage, and facilitate carbon sequestration. However, current field applications are constrained by several critical issues, such as poor matching of injection parameters, insufficient accuracy in fracture network regulation, difficult wellbore phase-state control, and an imbalance between cost and benefit, which severely restrict its stimulation potential. Based on the fundamental mechanisms of pre-stage CO₂ fracturing, this paper systematically analyzes the key influencing factors for process optimization. Combined with the petrophysical properties of shale oil reservoirs in Sichuan, the CO₂ injection volume and rate are optimized, providing theoretical support for the efficient development of this block.
Geometric Reinforcement Over Material Upgrading: Integrated Modal–Static–Fatigue Assessment of Large-Scale Hydrogen Cylinder Mounting Systems for Heavy-Duty Commercial Vehicles
When a hydrogen cylinder mounting frame shows signs of inadequate strength, the conventional engineering response is to specify stronger steel. This paper argues that is the wrong diagnosis. Two Q345 frames for a dual-cylinder 510 L hydrogen storage system (1,149 kg total loaded mass) were analysed in Altair OptiStruct and nCode DesignLife under the full ECE R110 inertial load envelope and the ISO 16750-3 road vibration spectrum. The only difference between the two frames was bracket geometry. The baseline frame failed on both counts that matter. Under 6.6g forward loading, stress at the bracket–frame junction reached 396.4 MPa—a yield exceedance of 14.9% for Q345 steel (SF = 0.87). Under road vibration, the longitudinal fatigue damage index reached D = 4.424, more than four times the Palmgren–Miner limit. The two failures share a cause: flat vertical support plates force load transfer through bending rather than axial tension, concentrating stress at a poorly transitioned junction (Kt ≈ 2.8) whose first natural frequency sits uncomfortably close to the dominant road excitation range. Adding diagonal bracing along the forward load axis and widening fillet radii from R = 5 mm to R = 12 mm resolved both issues without touching the steel specification. Forward stress fell to 214.8 MPa (SF = 1.61); fatigue damage fell to D = 0.004, a reduction of roughly three orders of magnitude. The scale of that improvement may initially look implausible, but it follows directly from IIW FAT 90 weld mechanics: mean stress, RMS amplitude, and stress concentration all fell together, and under the cubic S–N damage law those effects compound multiplicatively rather than adding. For this class of structure, bracket geometry appears to govern fatigue durability more decisively than the steel grade ever could.
An Optimization Model and Computational Framework for UAV Smoke Deployment Using Simulated Annealing and Genetic Algorithms
This paper addresses the issue of smoke screen formation for drone-deployed missiles by proposing a computational method integrating geometric modeling and intelligent optimization algorithms. Kinematic models for the drone, missile, smoke grenade, and smoke cloud are established within a three-dimensional coordinate system. By constructing a geometric occlusion criterion between the missile's line of sight and the spherical smoke cloud, the shielding process is transformed into a spatial intersection problem between a line and a sphere, enabling the calculation of effective shielding duration. Building upon this foundation, a nonlinear optimization model is established with maximum effective concealment duration as the objective function. This model incorporates variables such as flight direction, flight velocity, smoke grenade release time, and detonation time. For single-UAV deployment, parameter optimization is achieved using the simulated annealing algorithm. For multi-UAV coordinated deployment, a genetic algorithm is employed to ensure seamless coordination between multiple smoke screen coverage intervals. Simulation results demonstrate that this method effectively extends concealment duration while exhibiting excellent stability and adaptability.
An Electro-Thermal Battery Runtime Prediction Framework Based on Markov Chain and Monte Carlo Simulation
This paper proposes an electrothermal coupling modeling and stochastic simulation method for predicting battery runtime in mobile devices. An electrical model of lithium-ion batteries is constructed based on Thevenin equivalent circuits, combined with SOC dynamics and polarization voltage evolution to establish a continuous-time state-space model. Concurrently, thermal equilibrium equations describe Joule heating generation and convective heat dissipation, forming an electro-thermal coupled kinetic model to characterize the coupling relationships among temperature, current, and internal resistance. For load modeling, a Markov chain describes the random switching of device operating states, overlaid with Gaussian perturbations to construct a stochastic power model. Based on this, Monte Carlo simulations generate multiple load sequences, iteratively updating SOC, voltage, and temperature states to derive the statistical distribution of the device's remaining operational time. Results demonstrate that this method effectively reflects the impact of multiple factors on battery endurance performance, exhibiting good applicability and potential for broader implementation.
Research on the Evolution Mechanism and Risk Prevention and Control of Leakage Accidents in Depleted Oil and Gas Reservoir-Type Underground Gas Storages
With the acceleration of the global low-carbon energy transition, the demand for natural gas continues to grow. As core infrastructure for ensuring a stable natural gas supply, the safety issues of underground gas storages (UGS) are becoming increasingly prominent. In China, depleted oil and gas reservoir-type UGS account for 76%, making them the main type in this field. However, frequent leakage accidents pose a serious threat to the safe operation of UGS. This study takes depleted oil and gas reservoir-type UGS as the research object to systematically investigate the evolution mechanism and risk prevention and control of leakage accidents. Firstly, through statistical analysis of accident cases and expert interviews, the main influencing factors of leakage accidents were identified, including three categories: geological body leakage, injection-production well leakage, and surface facility leakage. Secondly, using the Grounded Theory method, the core categories in the driving stage of leakage accident evolution were extracted, and a conceptual model of driving factors for leakage accident evolution based on the four elements of "Human, Machine, Environment, and Management (H-M-E-M)" was constructed. Thirdly, through system dynamics modeling and numerical simulation, the dynamic evolution law of leakage accidents from initial evolution to secondary disasters was revealed. Finally, from the three dimensions of source prevention, process control, and emergency response, precise whole-process prevention and control measures were proposed targeting the four categories of factors: human, equipment, environment, and management. The research indicates that injection-production well leakage is the main form of UGS leakage, accounting for 57%, followed by geological body leakage (28%). The evolution of leakage accidents is influenced by the coupling effect of the four elements: Human, Machine, Environment, and Management. The constructed evolution mechanism model can effectively reflect the structural characteristics of the leakage accident system. The research results provide a theoretical basis and technical support for the precise identification and efficient prevention and control of leakage risks in depleted oil and gas reservoir-type underground gas storages.
The FiBSR Method for Face Super-Resolution Reconstruction in Power Systems
This paper proposes a blind face super-resolution reconstruction method called FiBSR, aiming to solve the complex spatial-temporal degradation problems in real scenarios. The core innovations of this method include: A physical modeling system based on anisotropic Gaussian kernels is constructed, and the degradation prior of spatial changes is explicitly regressed through the degradation kernel parameter estimation network (SV_KEN).a multi-scale discriminator, and a progressive two-stage training strategy, FiBSR provides a robust and systematic solution that outperforms existing mainstream methods in both subjective and objective evaluations, laying a solid foundation for practical applications in complex degradation scenarios.
Diagnosis-Driven Stage-Wise Trajectory Planning for a Mobile Dual-Arm Robot in Confined Derrick Pin Disassembly
Derrick pin disassembly in drilling structures is a typical confined-space maintenance task that requires dual-arm cooperation, multi-stage motion transition, and strict safety control. Although a fixed workstation may satisfy pose-level reachability and collision-free requirements, executable full-process motion generation remains difficult because local safety-margin degradation, inter-arm interference, and blocked stage transitions may still occur during continuous planning. To address this problem, this paper proposes a diagnosis-driven stage-wise trajectory planning method for a mobile dual-arm robotic system operating under a fixed workstation input. The method first formulates the task as an ordered sequence of stage targets under unified safety constraints. A trajectory-risk diagnosis mechanism is then introduced to identify the minimum safety margin, bottleneck location, and dominant constraint relation of each stage trajectory. Based on the diagnosis result, a cascade repair framework is constructed by integrating local segment repair, endpoint-neighborhood repair, and global recovery with adaptive step size. After the geometric trajectory has been repaired and verified, piecewise quintic polynomial time parameterization is applied to generate smoother executable output. The proposed method is intended to bridge the gap between pose-level feasibility and full-process executability in confined dual-arm derrick operations. It provides a practical planning framework for converting fixed-workstation feasible results into continuous and task-consistent dual-arm motions under multiple geometric safety constraints.
Green Mining-The Only Way for Sustainable Development of Coal Mine
As the main energy in China, coal is an important guarantee for China 's energy security and economic development. In the face of the goal and fall of a modern powerful country In order to meet the requirements of carbon peak and carbon neutralization, the traditional coal mining technology in the past has been backward, and coal enterprises must be green and ecological protection. To develop, green mining has become the only way for sustainable development of coal mines. This paper first analyzes the requirements of coal mining under the background of the new era. This paper introduces the connotation of green coal mining, and then analyzes several main green mining technologies, including water-preserved coal mining, coal and tile. Co-mining, gangue emission reduction, subsidence reduction mining, underground coal gasification, etc. Finally, the significance of green coal mining to the development of coal mines is expounded. The future of color mining technology is prospected.
Study on the Influence of Anti-Slip Pile on the Mechanical Response of Pipeline Under Landslide
In the process of laying anti-slip piles, by adjusting their number, spacing, shape, size and other parameters to analyze the changes of landslide morphology and pipeline stress under different working conditions, the reinforcement effect can be optimized and provide a basis for landslide control in actual engineering. Based on the strength reduction method, the finite element software ABAQUS was used to establish a numerical model of the sliding slope impact gas pipeline under the reinforcement effect of anti-slip pile, realize the pile-soil interaction analysis, and study the mechanical response of the gas pipeline under different reinforcement methods. The results show that when the number of anti-slip piles increases, the overall displacement of the sliding body decreases, and for the gas pipeline, the displacement decreases with the increase of the number of anti-slip piles, and the decrease range reaches 168.1mm, a year-on-year decrease of 35.89%, while the maximum effective stress of the pipeline increases first and then decreases with the increase of the number of anti-slip piles. When the size of the anti-slip pile increases, the maximum displacement of the sliding body gradually decreases, and the anti-slip effect of the soil directly above the slip pile and at the perimeter of the landslide slope is particularly obvious, indicating that the anti-slip pile size increases significantly to enhance its anti-slip effect on the slope. Although the construction of cylindrical anti-slip pile is smaller than that of square anti-slip pile, its anti-slip ability to resist slope is worse and its own anti-deformation ability is weaker.
Experimental Study on Engineering Properties of Expansive Soil Improved by Coal Gangue with Different Particle Sizes
In order to investigate the effects of coal gangue particle size and content on the properties of expansive soil, a series of laboratory tests including compaction test, swelling test, direct shear test, and unconfined compressive strength test were carried out. Three particle size groups of coal gangue (0–2 mm, 2–5 mm, and 5–10 mm) and six content levels (0%, 5%, 10%, 15%, 20%, and 25%) were selected. The results show that, for the same particle size, the maximum dry density of the mixture increases with increasing coal gangue content, while the optimum moisture content decreases. All particle sizes of coal gangue can effectively inhibit the swelling behavior of expansive soil, and the inhibition effect becomes more significant with increasing content, particularly at 15%. Under the same content, larger particle sizes exhibit better swelling suppression effects. For shear strength, the internal friction angle and cohesion fluctuate significantly when small (<2 mm) or large (>5 mm) particles are added, while the optimal improvement is achieved at a particle size of 2–5 mm and a content of 15%–20%. The unconfined compressive strength increases first and then decreases with increasing content, reaching a peak at 15%. Meanwhile, under the same content, the strength decreases with increasing particle size, and the optimal combination for compressive strength is 0–2 mm particle size with 15% content.
Study on Mechanical Properties of Aerogel Concrete at High Temperatures
In this paper, uniaxial compression tests were carried out on aerogel concrete at room temperature and after exposure to high temperatures. The influence of different aerogel contents on the degradation law of mechanical properties of concrete at room temperature and high temperature was investigated. The results show that at room temperature, the strength of concrete first decreases, then increases, and then decreases with the increase of aerogel content. When the aerogel content is controlled at 5%–15%, the strength reduction of the specimens is relatively gentle. After high-temperature treatment, the compressive strength of aerogel concrete exhibits an obvious temperature effect. Before 500℃, the strength increases slightly and then decreases gradually, indicating that hydration products are still formed and strength develops to a certain extent inside the concrete at this stage. However, the microcracks induced by temperature rise propagate continuously and gradually offset the strengthening effect caused by hydration. After 500℃, the compressive strength drops sharply, revealing that high temperature significantly aggravates the internal structural damage of concrete. When the temperature rises to 900℃, the strength loss can reach up to 0.886, and the specimens basically lose their bearing capacity. This reflects that continuous high temperature has caused serious damage to the internal structure of concrete, making it difficult to maintain the original mechanical performance.
Additively Manufactured Auxetic Structures: A Review
Auxetic structures exhibit mechanical behaviors that are significantly different from those of conventional materials. They expand laterally under tensile loading and contract laterally under compressive loading, which provides advantages in energy absorption, impact resistance, indentation resistance, and structural stability. In recent years, the rapid development of additive manufacturing, particularly 3D printing, has enabled the precise fabrication of complex auxetic structures that are difficult to achieve using traditional manufacturing methods, thereby greatly promoting related research and applications. This paper reviews the research progress of 3D printed auxetic structures. First, common 3D printing technologies used for fabricating complex structures, including fused deposition modeling (FDM), stereolithography (SLA), and selective laser sintering (SLS), are introduced. Then, the development history and structural types of auxetic structures are summarized. Furthermore, recent advances in the structural design and mechanical performance of 3D printed auxetic structures are reviewed, along with their applications in impact protection, aerospace, biomedical engineering, and vibration isolation. Finally, the main challenges and future development trends of 3D printed auxetic structures are discussed. The integration of advanced manufacturing technologies with structural optimization is expected to further expand the application potential of auxetic structures.
The Significance of Fluid Inclusions' Characteristics in Indicating the Evolution of Ore-Forming Fluids
Objective: Fluid inclusions are microfluids trapped within mineral crystals during their growth. These fluid droplets are the only direct observational samples which can invert the physicochemical condition and trace back its source as well as reveal the origin of mineral deposit. In order to comprehensively understand the petrographical, thermodynamic data on and compositional characteristics of the included fluids and what they imply for the history of mineralizing fluid evolution. Methods: To make a systematic and detailed division of fluids, use the petrographic division; analyze various microscopic thermometric data. Use laser Raman spectrum detection technology for detection, follow isotope tracing to track its movement, precipitation, etc., with the mass balance method, thermodynamic state equation method; Results: Temperature, Salinity Evolution of Inclusions has the same trend of uniform evolution, it is very accurate to display the mineralization dynamics process such as cooling, boiling (non-miscible), fluid mixing etc. in the fluid system; Volatile Components and Trace Element Composition can reflect the transport and precipitation way of metal complex. Concusions: Fluid inclusion can play an important role of divide the stage of mineralizing, it also can be called "Mineralization Phaze indicator" which give its microfluric Dynamic evidence to prove at mining deep drilling when build a regional scale model of mineralized zone: It is inevitable that the site multiple scale andmultiple methodanalyses of fluid inclusions, if we wantto know about how these minerals form fluids evolvesin the future.
Unstructured Grid-Based Finite Element Forward Modeling Method for Electromagnetic Fields
In complex terrain modern day geophysical electromagnetic work or microwave engineering needs a good model of the electro magnetic field to succeed. The outdated numerical calculations relying equally distributed reguar grid finite diff, and un-even grounds like waves, faults, all sorts of messed up 3D anomalous distortions, it would greatly warp the local EM field response data points in ALL but maybe some last steps before 'inverted', and trying to interpret that result. In order to solve the bottleneck problem, we explore and realize a 3D vector finite element forward modeling method of electromagnetism field with unstructured tetrahedron grids. Utilizes very closely conformed unstructured grids to closely approximate complicated geological model and also has vector basic function based on edge element to remove these kinds of pseudo solution that you have when you do normal node FEM method. This article describes how to obtain the weak form integral equation of Maxwell’s equation of the electric field curl and introduces a pre-process Krylov subspace iteration solution strategy for solving big sparse complex linear equations. It is also the proof for truth of both its accuracy and strength in converging, it has experienced a lot of easy numerical check upon simple halfspace, roughest terrain and even most complicated bodies with deeply buried 3D high conductivity targets. The article can be considered true 3dfoward Model Theory Support and algorithm Basis To Get True Data Refinements And Exact Location Of Any Complex Geologic Body Within China while carrying out an Electromagnetic Investigation.
Earth System Significance Environmental Response and Morphological Evolution of Neoproterozoic Stromatolites
The oproterozoic (1000–541 Ma) constitutes a critical transitional period in Earth's evolutionary history. As microbial-dominated biosedimentary structures, stromatolites faithfully record the coevolutionary processes of biological evolution and environmental changes during this era. This study systematically combs the global distribution pattern and spatiotemporal evolutionary characteristics of Neoproterozoic stromatolites. Integrating sedimentological, geochemical, and paleontological evidence from typical sections, it deeply analyzes the controlling factors of their morphological diversity, reveals the response mechanisms of stromatolites to major geological events such as Snowball Earth events and the Second Great Oxidation Event (NOE), and explores the intrinsic connection between microbial community evolution and stromatolite construction. Research indicates that Neoproterozoic stromatolites underwent a transformation from the Mesoproterozoic giant conical-columnar assemblages to diverse small-scale morphologies. The microstructural mutation event at 850–800 Ma marks a revolution in cyanobacterial calcification, while the morphological turnover around glacial periods records microbial adaptation strategies under extreme environments. Geochemical indicators confirm that the carbon, oxygen, and chromium isotope compositions of stromatolites are highly coupled with the evolution of marine redox conditions, and their microbially induced manganese deposits provide key empirical evidence for the biological mineralization theory. In the future, it is necessary to further clarify the impact mechanism of eukaryote rise on stromatolite decline through the combination of high-precision isotope analysis and molecular fossil technology, so as to establish a more comprehensive cognitive framework for reconstructing Neoproterozoic Earth system evolution.
Distribution Characteristics and Ecological Risk Assessment of Microplastic Pollution in the Water Body of Dasha River in Jiaozuo City
Microplastic is one of the new pollutants, with a wide range of sources and distributions, and it can also be used as a carrier to adsorb heavy metals, persistent organic pollutants, and other hazardous substances in the environment, which constitutes a potential threat to the health of biological human beings. However, there is only one study on microplastic water pollution in Jiaozuo City, Qin River. In this study, 19 sampling stations in Dasha River in Jiaozuo City were sampled in March 2025, and microplastic abundance, shape, color, and particle size were analyzed by body-view microscopy, and the results showed that microplastics were detected at 100% in all sampling stations, with an abundance range of 0.9-10.6 n-L-1 and an average abundance of 3.90 ± 2.83 n-L The average abundance was 3.90 ± 2.83 n-L-1. Fibers were the main form of microplastics in the Dasha River, with black and transparent colors and particle sizes ranging from 0.3 to 1.0 mm. The polymer types were further identified with the help of micro Fourier transform infrared (FTIR) instrument, and it was found that polyethylene terephthalate (PEGT), polyamide, and polypropylene were the main microplastic species in the study area. The results of the ecological risk assessment showed that the microplastic pollution load of the Dasha River in Jiaozuo City was at low risk (level I), while the polymer risk index of the sampling stations with high hazard scores of PVC and PAN was high, and even reached very high risk in the S19 sampling station. The results of this study can provide a reference for Jiaozuo City to recognize the microplastic pollution situation in rivers and to prevent and control the risk.