Frontiers in Engineering ISSN Print: 3104-4298 ISSN Online: 3104-4301 CD ISSN: 3104-431X
Design of a Precision Automatic Aiming System Based on K230 Visual Feedback and FOC Vector Control
To address the stringent requirements for dynamic response and positioning accuracy in simple automatic targeting systems, this paper presents a precision automatic targeting system based on an STM32F4 microcontroller and a K230 peripheral vision processor, overcoming limitations inherent in traditional servo control such as significant mechanical backlash, motor vibration at low speeds, and insufficient response bandwidth. The visual perception module, centered around the K230, employs a lightweight recognition algorithm utilizing geometric features and adaptive thresholds to achieve high-frame-rate target tracking exceeding 50 frames per second. The motion control module implements FOC control via the STM32F4, employing a cascaded control architecture and optimized PD strategy to eliminate motor torque pulsation at low speeds and suppress mechanical overshoot; the outer loop provides real-time angular correction through UART feedback. Tests demonstrate excellent system stability with a static targeting error of ≤1.5 cm, rapid dynamic tracking response, and smooth operation, fully meeting the demands for high precision and fast dynamic performance.
Copyright (c) 2026 by author(s) and Erytis Publishing Limited https://creativecommons.org/licenses/by-sa/4.0
Evolution Characteristics and Influencing Factors of Air Quality in Xining City from 2021 to 2025
Focusing on the atmospheric environmental conditions of Xining City from 2021 to 2025, this study systematically analyzes the evolution characteristics and influencing factors of air quality based on monitoring data released by the Qinghai Provincial Meteorological Bureau. Results show that over the past five years, Xining's air quality has steadily improved, with annual average good-quality days ranging between 88.21% and 94.52%, exceeding 340 days per year from 2023 to 2025. SO2 and CO concentrations have remained consistently low, while NO2, PM10, and PM2.5 levels have continuously declined by 18.3%, 22.5%, and 24.7%, respectively. O3 concentration showed slight fluctuations but remained overall stable, with all indicators meeting national standards. Air quality follows a pattern of lower in winter, higher in summer, and moderate in spring and autumn. Winter sees elevated concentrations of CO, NO2, SO2, PM10, and PM2.5, whereas O3 peaks in summer—patterns closely related to local climatic conditions, energy consumption, and pollutant dispersion dynamics. This research provides scientific support for optimizing air pollution control strategies in Xining and consolidating the ecological achievement of “Xining Blue”, offering a reference model for ecological protection in plateau cities.
Review on Microstructure and Properties of 45 Steel under High-Temperature Tempering
As the most widely used medium-carbon structural steel in the machinery manufacturing industry, 45 steel exhibits service performance of components that is decisively governed by the selection of process parameters for high-temperature tempering. This paper summarizes the microstructural evolution and mechanical properties of the aforementioned two materials under high-temperature tempering conditions. For 45 steel, research findings and mainstream conclusions from existing literature are elaborated from five perspectives: heat treatment surface effects, fatigue behavior regulation, high-temperature mechanical characteristics, innovative process exploration, and hardness degradation laws.
Analysis of Freeze Damage in Drainage Pipe Networks in Cold High-Altitude Regions and Engineering Mitigation Practices
Drainage pipe networks in cold high-altitude regions are continuously affected by low temperatures, frozen ground, and freeze–thaw cycles, making them susceptible to ice blockage, frost-heave deformation, joint cracking, and manhole freezing, which compromise the safe and stable operation of drainage systems. Existing studies have primarily focused on frozen-soil mechanisms or individual anti-freezing measures, while systematic research on freeze-damage diagnosis, integrated mitigation strategies, and effectiveness verification throughout the entire engineering process remains limited. Therefore, based on the operational characteristics of drainage systems in cold high-altitude regions, this study adopts an integrated approach combining field investigation, risk identification, indicator-based evaluation, and engineering validation to systematically analyze the characteristics and causes of freeze damage in drainage pipe networks. A freeze-damage risk identification framework consisting of environmental, engineering, and operational factors is established. Furthermore, a whole-process anti-freezing technical system featuring “source prevention–process control–operation assurance” is proposed, together with a hierarchical and integrated mitigation scheme. Engineering practice demonstrates that, after implementing zoned and graded anti-freezing measures, the number of freeze-damage incidents during the freezing period in the treated area decreased from 12 to 2, achieving a freeze-damage improvement rate of 83.3%. The internal temperature of high-risk pipeline sections was maintained above 0°C, and the winter operational stability of the drainage system was significantly enhanced. The research establishes a closed-loop framework integrating freeze-damage risk diagnosis, mitigation measure selection, and operational performance evaluation, providing practical guidance for the planning, design, rehabilitation, operation, and maintenance of drainage pipe networks in cold high-altitude regions.
Treatment Technology and Engineering Application of Settlement Distress in Permafrost Subgrades in Alpine Regions of Tibet
Permafrost and seasonal frozen soils are widely distributed in the alpine regions of Tibet. Under the combined effects of climate warming and engineering disturbances, the thermal stability of frozen ground has continuously deteriorated, resulting in increasingly severe pavement and subgrade distresses, including subgrade settlement, pavement cracking, and shoulder deformation, which significantly threaten highway operational safety and service performance. Existing studies have primarily focused on the mechanisms of frozen-subgrade distress formation and individual treatment measures, whereas research on distress diagnosis systems and integrated treatment technologies for engineering maintenance applications remains relatively limited. Based on a settlement remediation project for a highway permafrost subgrade in an alpine region of Tibet, this study established a diagnostic and decision-making framework for settlement distress in frozen-soil subgrades and proposed a synergistic treatment technology integrating thermal insulation, drainage improvement, and foundation reinforcement. By developing a distress classification standard and a comprehensive evaluation index system, accurate matching between distress types and treatment schemes was achieved. Combined with insulation layer installation, drainage system optimization, and grouting reinforcement, field implementation and long-term monitoring were conducted to evaluate treatment effectiveness. The results indicate that the maximum settlement of the distressed section decreased from 168 mm to 42 mm, while the annual settlement rate was reduced from 56 mm·a⁻¹ to 12 mm·a⁻¹, corresponding to a settlement control efficiency of 75%. The proposed synergistic treatment technology effectively improved the thermal regime, moisture condition, and structural stability of the subgrade, thereby significantly mitigating the development of settlement distress. The study establishes a comprehensive technical framework for the treatment of settlement distress in frozen-soil subgrades in the alpine regions of Tibet and provides valuable engineering references for highway maintenance and distress remediation in similar cold-region permafrost areas.
A Review of 4D Millimeter-Wave Radar-Based Automotive Perception Technology Research
4D millimeter-wave radar, with its four-dimensional measurement capabilities encompassing range, azimuth, elevation, and Doppler velocity, has overcome the elevation perception limitations of traditional 3D millimeter-wave radar. Owing to its all-weather operation, high robustness, and cost advantages, it has emerged as a core sensor in the field of automotive intelligent perception. This paper systematically reviews the latest research progress in 4D millimeter-wave radar automotive perception technology, introduces common detection and semantic occupancy methods from two perspectives—raw tensor data and point cloud data—and discusses future development trends.
Optimization and Engineering Application of Mountain Highway Alignment Schemes Based on Topographic and Geological Constraints
This study establishes a multi-source constraint factor system for mountain highway alignment selection based on “topography–geology–engineering” considerations. Elevation, slope, terrain relief, valley incision density, hazard susceptibility, distance to fault fracture zones, and engineering design indicators are uniformly transformed into spatial constraint intensities. Furthermore, a geological hazard risk penalty mechanism is introduced, and an alignment optimization method integrating “risk assessment–constraint transformation–path search–scheme verification” is developed. The A* algorithm is employed for path searching. The proposed method is applied and validated in a county road reconstruction project in Tibet. The results show that, compared with the traditional river-following scheme, the recommended scheme reduces the route length by approximately 8.0%, decreases the length traversing high-risk areas by about 83.3%, lowers the average constraint intensity by approximately 33.9%, and achieves the optimal comprehensive evaluation value. The study demonstrates that the proposed method can transform geological hazard risk from a qualitative avoidance condition into a quantitative optimization constraint, thereby enabling proactive disaster avoidance and comprehensive optimization of mountain highway alignment schemes. The results can provide technical support for route selection decision-making in complex mountainous areas.
Copyright (c) 2026 by author(s) and Erytis Publishing Limited. https://creativecommons.org/licenses/by/4.0/
Analysis of Fault Diagnosis and Safety Protection Technologies for New Energy Vehicle Battery Systems
With the rapid growth in the number of new energy vehicles on the road, the safety and reliability of lithium-ion power battery systems have become a major focus of attention. This paper systematically analyzes typical failure modes in power battery systems, summarizes their multi-source, coupled, and progressive characteristics, and identifies internal short circuits as the core factor triggering thermal runaway. Building on this, the paper reviews three categories of fault diagnosis methods-based on parameter monitoring, mathematical-physical models, and data-driven approaches-and compares their respective application scenarios and limitations. It then elaborates on comprehensive protection strategies covering graded early warning, thermal runaway suppression, high-voltage electrical safety, and regulatory compliance. Finally, the paper discusses technical bottlenecks such as the trade-off between diagnostic real-time performance and accuracy, a0s well as the scarcity of fault samples, and outlines future development directions including vehicle-cloud collaboration and digital twins. This paper aims to provide a technical reference for fault diagnosis and safety protection in power battery systems.
Comparison of Monofractal and Multifractal Methods in Characterizing Coal Pore Structures
Coal pore structures commonly exhibit significant heterogeneity, and fractal theory provides an effective tool for the quantitative characterization of such complex structures. Regarding multi-scale pore data acquired by CO2 adsorption (micropores), N2 adsorption (mesopores), and mercury intrusion porosimetry (macropores), monofractal and multifractal methods differ fundamentally in their computational principles and characterization approaches.This review discusses three classic models for monofractal dimension: the Sierpinski model based on CO2 adsorption data, the Frenkel–Halsey–Hill (FHH) model based on N2 adsorption data, and the Menger sponge model based on mercury intrusion porosimetry (MIP) data. It also introduces the calculation methods for multifractal spectral parameters derived from the box-counting method, including the generalized dimension spectrum D(q), the multifractal singularity spectrum f(α), and the spectral width Δα. On this basis, a systematic comparison of the two approaches is conducted from multiple perspectives. The monofractal dimension quantifies the overall average complexity of coal pore structures as a single scalar value, offering computational simplicity and high efficiency, which renders it suitable for rapid screening of large sample sets and global evaluation of pore complexity. In contrast, the multifractal approach enables a detailed characterization of pore size distribution heterogeneity across different scale intervals and local domains, and is particularly well-suited for high-resolution microstructural analysis of strongly heterogeneous samples, such as tectonically deformed coal. This study provides a theoretical foundation for the rational selection of fractal methods in the characterization of coal reservoir pore structures.
Application of Curtain Grouting Technology in Soft Coal Seam
In order to solve the problems of serious air leakage and easy hole collapse in the process of gas extraction from bedding boreholes in soft coal seams under deep mining conditions, an advanced curtain grouting method for pre-blocking cracks and pre-reinforcement of soft coal bodies was proposed and applied in the field. In this paper, the 38021 working face of Xinzhuang Coal Mine is taken as the engineering background, and the thickness of curtain grouting is determined by drilling cuttings method. The vertical strip grouting curtain body is constructed by the arrangement of oblique plum-shaped grouting holes and the grouting method of low pressure and slow permeability, so as to realize coal body strengthening and efficient sealing of fracture network. The application results show that the initial extraction concentration of borehole gas is increased by 30 %, the attenuation rate of extraction efficiency is reduced to less than 15 %, and the effective extraction time of borehole is extended to 3 months.
Research on Automatic Pressure-Holding and Flow-Limiting Device for Sealing Bladder Based on Embedded Platform
Gas drainage is a key measure to guarantee underground operation and miners' safety, while grouting hole sealing, as the principal technical method for gas drainage, still exists many technical problems. This paper develops an automatic pressure-holding and flow-limiting system based on an embedded platform, consisting of hardware and software designs. The hardware comprises a core control module based on STC12C5A60S2, an LCD1602 display module, a relay module, a pressure sensor, a flow sensor, a two-position three-way solenoid valve, and a check valve. For software design, C-language programming in the Keil uVision5 environment is adopted to realize communication with pressure and flow sensors and control of the relay module. Taking the "two-seal one-injection" pressurized bladder sealing process as an example, in the grouting and expansion stage of the sealing bladder, when the detected pressure and flow values are lower than the set thresholds, the STC12C5A60S2 chip outputs a low-level signal to the relay module, keeping the relay inactive; the circuit of the two-position three-way solenoid valve is disconnected, and the outlet of the solenoid valve is connected to the sealing bladder for normal grouting. When the detected pressure or flow value exceeds the set thresholds, the STC12C5A60S2 chip outputs a high-level signal to activate the relay module, connecting the solenoid valve circuit and linking the solenoid valve outlet to the atmosphere, thus shutting down the grouting pump. Similarly, in the stage of sealing fractures in the middle section of the bladder with non-coagulating flexible gel, grouting continues when the pressure is below the set threshold and stops when the pressure exceeds the threshold. The system automatically regulates grouting pressure within a certain range, enabling "secondary sealing" and "tertiary sealing". This system improves the reliability of grouting hole sealing by means of pressure maintaining and flow limiting, thereby effectively increasing the gas drainage concentration.
A Dynamic Power Management Strategy for Robotic Space Debris Capture Systems in Orbit Recycler Satellites
The accumulation of space debris in low Earth orbit has become a critical challenge for current and future space missions. Although various active debris removal concepts have been proposed, most existing studies focus on capture mechanisms while overlooking onboard power limitations. In practical satellite systems, debris capture operations often introduce transient high-power loads that may exceed available energy capacity. This paper proposes a dynamic power management strategy for an orbit recycler satellite equipped with a robotic capture module. The approach incorporates real-time power awareness into the control process by considering battery state-of-charge and instantaneous power margin when determining capture actions. In addition, a peak power mitigation method is introduced to reduce transient load spikes during actuator operation. Simulation results show that the proposed strategy effectively limits peak power within system constraints and improves battery utilization, while maintaining capture performance. The study highlights the importance of integrating power constraints into system-level design for reliable debris removal missions.
Caustic-Based Modulation of Structured Light Fields along Arbitrary Trajectories
This paper presents an English course report on the caustic-based modulation of structured light fields. Starting from the angular-spectrum description of non-diffracting beams, an inverse design strategy is introduced to map a prescribed transverse intensity contour into an annular spectral phase. In this way, the optical caustic becomes the geometric skeleton that governs both the beam profile and its subsequent propagation. The method enables sharply confined structured beams with arbitrary shapes, while an additional synthesized phase term translates the structure along user-defined trajectories in three-dimensional space. Elliptic and heart-shaped beams are discussed as representative examples, showing that the same framework supports both straight and accelerating propagation. Experimental observations reported in the source material verify the numerical predictions and confirm the robustness of the generated beams. Because these structured non-diffracting fields exhibit strong intensity gradients and structured orbital angular momentum, they are promising for optical trapping, particle transport, beam shaping, wavefront control, and deep imaging. The study demonstrates that inverse caustic engineering offers a flexible and physically intuitive route for designing advanced structured light fields beyond conventional Bessel, Mathieu, Weber, and Airy beam families.
An Investigation into Sustainable Concrete Production Using Glass Powder and Sawdust as Fine Aggregate Substitutes
The construction industry faces significant environmental challenges due to the over-extraction of natural sand and the accumulation of industrial waste. To address this, this study investigates the partial replacement of fine aggregates in concrete with two industrial byproducts: glass powder (GP) and sawdust (SD). The research aims to mitigate ecological damage by diverting these materials from landfills, with a specific focus on replacing 35% of the natural sand volume in its optimal mix. The experimental program involved creating four concrete mixes with a constant 5% SD replacement and varying GP contents of 10%, 20%, and 30% by volume of fine aggregates. These were compared to a conventional control mix. Results demonstrated that the combination of 30% GP and 5% SD yielded the most favorable balance, achieving 85% of the control's compressive strength (25.7 MPa) while improving workability and reducing density by 7%. The increased GP content enhanced the matrix density through pozzolanic reactions, counteracting the porosity introduced by the sawdust. In conclusion, the integration of 30% glass powder and 5% sawdust as a replacement for fine aggregates is technically viable for producing sustainable concrete. This optimal mix not only delivers adequate mechanical properties for non-structural applications but also offers substantial environmental and economic benefits, including reduced raw material consumption and lower CO₂ emissions. Thus, this approach presents a promising pathway towards a more circular economy in the construction sector.
A Real-Time Trajectory Estimation Algorithm for the Virtual Side of an AGV Digital Twin Based on UKF
To address the insufficient trajectory estimation accuracy of the virtual side in AGV digital twins under intermittent measurements, a real-time trajectory estimation algorithm that integrates the Unscented Kalman Filter (UKF) with periodic station-based correction is proposed. Nonlinear state and measurement equations adapted to AGV motion characteristics are constructed. The UKF is employed to realize real-time position recursion based on intermittent velocity and heading information, while high-precision position information from fixed stations is used to correct accumulated errors. Simulation results demonstrate that the proposed algorithm can effectively suppress error accumulation and achieve accurate tracking of the physical trajectory by the virtual side, providing technical support for precise trajectory replication in AGV digital twin systems.
From Reactive to Proactive: Integrating Agentic AI and Automated Workflows for Intelligent Project Management (AI-PMP)
The Project Management Body of Knowledge (PMBOK® Guide) has always been the go-to resource for project lifecycles. Modern projects require a holistic approach with the need to move from static manual, reactive ways of working to proactive, intelligent systems, owing to the interconnected, data-driven and dynamic nature of today. While project management tools now come equipped with data aggregation and simple analytics tools, it mostly stays in a passive repository and puts the overall cognitive load of synthesizing and deciding decisions back on the project manager. The aim of this paper is to examine the new paradigm, AI-PMP — which is a merging of PMP with Artificial Intelligence. It is particularly concerned with Agentic AI and automatically performed workflows. We argue that intelligent agents such as those based on autonomy, proactivity, and social competency change fundamental aspects of the project such as the execution, monitoring, communication, and knowledge management. By deploying a multi-agent system (MAS) architecture, in which advanced and specialized agents (e.g., for risk, schedule, or quality) have access to semantically rich, automated workflows project management can reach unprecedented levels of efficiency, predictive accuracy, and even stakeholder satisfaction. In this paper a theoretical perspective will be presented for this integration, as well as an analysis, regarding challenges in the traditional PMP process groups, major limitations as well as major future research, both technical, human and ethical issues. The study's results indicate that Agentic AI is more than a simple assistive technology, but the core of the upcoming generations of autonomous PMP systems and a key to achieving a fully human-supervised transition in project execution.
Copyright (c) 2025 by author(s) and Erytis Publishing Limited. https://creativecommons.org/licenses/by/4.0/
Wearable Parkinson’s Tremor Monitoring Using a PNC Based Flexible Capacitive Sensor with an AC Bridge and Two-Step Calibration
Wearable monitoring of Parkinson’s Disease (PD) tremor demands sensors that combine high low-pressure sensitivity with readouts robust to lead and parasitic capacitances. We present a flexible Porous-Nanocomposite (PNC) capacitive pressure sensor that’s integrated into an Alternating Current (AC) De-Sauty bridge, along with a two-step calibration process that effectively cancels out lead and parasitic effects. This innovation allows for picofarad-level resolution in a wearable design. The device features a carbon nanotube (CNT)-doped porous dielectric paired with Ag/PI electrodes, and it utilizes a guarded bridge front end that connects to an instrumentation amplifier and Micro Controller Unit (MCU) equipped with an Analogue to Digital Converter (ADC). Onboard Digital Signal Processing (DSP) handles band-pass filtering (around 3-8 Hz) and Welch spectral estimation for detecting tremors. In our benchtop calibration and tests with consenting volunteers, the system demonstrated an absolute sensitivity of about 2.2pF·kPa⁻¹, with a detection limit close to 14-16 Pa, and it showed a reliable dynamic response within the 4-6 Hz tremor range while keeping baseline noise low and ensuring repeatability under cyclic loading. These findings highlight a compact, low-power solution ideal for continuous fingertip tremor monitoring, paving the way for further IRB-approved clinical validation to explore its potential for diagnosis, symptom tracking, and personalized therapy assessment.
Design of intelligent wardrobe control system
Addressing the issue of traditional wardrobes having limited functionality and being unable to meet the management needs of modern clothing storage environments, this paper designs an intelligent wardrobe system based on the microcontroller STM32F103C8T6. This system incorporates functions such as environmental monitoring, voice interaction, automatic adjustment, and WiFi remote control. By integrating core components such as temperature and humidity sensors, photoresistors, ESP8266 modules, and ASRPRO voice chips, it achieves real-time monitoring and intelligent regulation of the internal environment of the wardrobe, providing a feasible solution for smart home applications.
Research Status of Laser Cutting Technology
With the highly advanced development, high performanceof integrated circuit manufacturing, and rapid advancement of optoel-ectronic technology, hard and brittle transparent materials such as s-ilicon wafers and quartz glass have been widely used in fields incl-uding integrated circuits, micro-electromechanical systems, and aero-space, thanks to their excellent physicochemical properties. The dici-ng quality of silicon wafers plays a decisive role in the final produ-ct quality and economic benefits; similarly, quartz glass also requir-es high-quality dicing to prevent stress from propagating along the defective parts of the glass edges and thus causing cracking.This st-udy investigated the current status of dicing from three aspects:tradi-tional dicing, assisted dicing, and dicing after spatial light modulati-on (SLM). Meanwhile, the factors influencing dicing were studiedfr-om the perspectives of laser types, laser polarization states, process-ing parameters, and processing technologies.
Solving Strategy for Silicon Carbide Epitaxial Layer Thickness Based on Nonlinear Least Squares Method
Silicon Carbide (SiC) is a pivotal semiconductor material for next-generation high-power and high-frequency electronics, where precise measurement of its epitaxial layer thickness is crucial. This paper presents a robust method for determining this thickness using infrared interference and a nonlinear least squares optimization framework. We first establish a dual-beam interference model based on the Fresnel equations and Snell's law, deriving reflectivity as a function of thickness and wavelength. The Drude model is incorporated to account for the refractive index dispersion influenced by carrier concentration. For thickness inversion, experimental reflectivity data from SiC wafers is processed by excluding the anomalous "reststrahlen band" (700-1000 cm⁻¹). A hybrid algorithm combining differential evolution for global initial guess generation and nonlinear least squares for local refinement is implemented, yielding a thickness of 7.921 μm with a high goodness-of-fit (R² ≈ 0.94). Furthermore, we analyze multi-beam interference, deriving its necessary conditions: high interface reflectivity, sufficient coherence length, and layer stability. An adaptive hybrid interference model is developed, dynamically applying dual or multi-beam theory based on local optical conditions. Applied to silicon wafer data, it identifies multi-beam regions and calculates a thickness of 3.765 μm. Re-evaluating the SiC data with this model and a region-weighted strategy to mitigate multi-beam effects in the 399.7-666.3 cm⁻¹ band yields an optimized thickness of 7.049 μm. This work provides a reliable and adaptable framework for high-precision thickness characterization in semiconductor engineering.
Iterative improvement of light curing printing all-in-one machine
As photopolymerization 3D printing technology matures and finds increasing applications in the manufacturing of everyday goods, with an expanding market, numerous equipment manufacturers are enhancing printer performance to boost printing efficiency and improve the quality and yield of photopolymerization prints. However, among the various factors affecting the quality of printed products, many manufacturers still rely on manual transportation to connect the post-processing steps for newly printed parts, such as part removal, cleaning, and curing. This approach has a impact on the quality, yield rate, and working environment of the final products. This article will delve into the processes and post-optimization strategies for post-processing integrated machines.
photopolymerization printing post-processing
Study on the Interface Reaction and Properties of Carboxynitrile Rubber/Blended Polyurethane
Millable polyurethane (MPU) is widely used in the field of sealing and wear-resistant components due to its excellent solvent resistance and dimensional stability. However, its inherent drawbacks of high rigidity and low elasticity limit its application in complex working conditions. Carboxylated nitrile butadiene rubber (XNBR) contains reactive carboxyl groups (-COOH) in its molecular chain, which can chemically interact with the isocyanate groups (-NCO) of MPU, providing a new approach to improve the mechanical properties of MPU. At present, research on the blending of XNBR with thermoplastic polyurethane (TPU) has been reported, but studies on the interfacial reaction mechanism, process regulation, and mechanical property synergy rules of the XNBR/MPU system are rarely conducted. In this study, an integrated technical route of "molecular simulation - experimental verification - performance characterization" was adopted, focusing on the correlation between the interfacial reaction and mechanical properties of the XNBR/MPU system: 1) Molecular dynamics simulations were used to confirm that the amidation reaction between XNBR and MPU proceeds spontaneously at 80°C, and the interfacial cross-linking mechanism of amide bonds was revealed; 2) The optimal formula was determined through orthogonal experiments, and mechanical property tests were carried out. This study provides theoretical support for the development of high-performance XNBR/MPU blended materials and has application value in the fields of automotive sealing and shock absorption.
Research on process parameters of composite components based on Simulation
This study systematically investigates the effects of process parameters (mold temperature, curing pressure, resin flow rate, curing time) on composite molding quality via simulation analysis, orthogonal experiments, and simulation-driven genetic algorithm optimization. Physical mechanism modeling reveals key processes (resin flow, curing reaction, fiber impregnation), supporting defect prediction and parameter optimization. Orthogonal experiments clarify parameter interactions, while optimization using genetic algorithms significantly enhances molding quality (reducing defects, improving curing uniformity and mechanical properties), validated by experiments. Results confirm these parameters are critical for quality, with the proposed method improving production efficiency and product reliability. Future work will extend to other composites, refine multi-physics coupling models, and develop smarter algorithms to advance industrial applications.
Research Status of Laser Cladding crack Suppression Technology
As a new type of micro-nano additive technology, laser cladding technology melts powder through a high-power laser beam to form a metallurgically bonded molten pool on the coating surface, which can provide excellent modification functions such as enhancing hardness, wear resistance and corrosion resistance on the workpiece surface. Due to the increase in hardness, the cladding layer is prone to fracture defects. The appearance of cracks seriously affects the service life of the workpiece, poses a great safety hazard to the safe production of enterprises, and greatly limits the application of nickel-based alloy powders. Therefore, this paper summarizes the existing effective technical measures for suppressing crack generation, laying a theoretical foundation for the latter research.
Hydrodynamic Lubrication Mechanism and CFD Analysis of Tesla-Valve Microtextures
Titanium alloys are widely used in aerospace and medical industries owing to their high strength, low thermal conductivity and excellent corrosion resistance. However, their high chemical reactivity and poor heat dissipation cause severe tool wear during cutting. Surface microtexturing has been proven to significantly improve the lubrication performance of friction pairs and extend service life. To explore the lubrication mechanism of Tesla-valve microtextures, femtosecond laser machining was employed to fabricate micrometer-scale Tesla-valve structures on YG8N cemented carbide surfaces. A three-dimensional model was established in Fluent, and the velocity and pressure distributions at various inlet flow rates were simulated. The results show that at low speeds (v ≤ 2 m/s), the microtexture exhibits higher reverse than forward flow velocity, with superior reverse hydrodynamic lubrication performance; whereas at high speeds (v ≥ 3 m/s), the forward flow velocity exceeds the reverse, leading to improved forward hydrodynamic lubrication performance. As flow rate increases, the vortex region and pressure potential inside the microtexture expand significantly, enhancing the load-carrying capacity of the oil film.