International Core Journal of Engineering
International Core Journal of Engineering is an international journal to promote all fields of Engineering, it considers original and timely contributions containing new results in mechanical engineering, electrical engineering, civil engineering, chemical engineering, etc. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Status of Organic Carbon Pollution in Chinese Waters based on Meta-Analysis Method
In this paper, we used Meta-analysis to systematically assess the ecological status of organic carbon pollutants in China's aquatic environments between 1980 and 2024. The study was based on relevant literature from the China Knowledge Network (CNKI) and Web of Science (WOS) databases, focusing on the spatial and temporal distribution characteristics of persistent organic pollutants (POPs), perfluorinated compounds (PFCs), plastic particles (MPs), pharmaceuticals and personal care products (PPCPs), and volatile organic compounds (VOCs). Through Meta-analysis, this paper integrates a large amount of research data to reveal the distribution patterns of these pollutants in Chinese waters and their impacts on the ecological environment. The results show that the problem of organic carbon pollution in Chinese waters is becoming more and more serious, especially in the Yangtze and Pearl River basins. This paper not only provides a scientific basis for a comprehensive understanding of the current status of organic carbon pollution in Chinese waters, but also provides an important reference for the development of targeted pollution management strategies.
Meta-analysis; Status of Water Pollution; Organic Carbon Contaminants; Ecological Status.
Copyright (c) 2025 https://creativecommons.org/licenses/by-nc/4.0
Hydrogen Storage Potential in Natural Gas Infrastructure: Material Compatibility and System Integrity Assessment
With the advancement of global energy transition, hydrogen, as a clean energy source, is gradually gaining attention for its storage potential in natural gas infrastructure. Hydrogen storage technology can not only address the volatility of renewable energy but also provide a new solution for reducing carbon emissions. However, the compatibility of hydrogen with natural gas infrastructure, particularly the hydrogen resistance of materials and system integrity, has become a key challenge in achieving large-scale hydrogen storage and transportation. This paper focuses on the hydrogen storage potential in natural gas infrastructure, analyzing the impact of hydrogen on both metallic and non-metallic materials, with a particular emphasis on the threat of hydrogen embrittlement to the safety of pipelines and storage equipment. System integrity evaluation is also included, with a comprehensive analysis of the safety risks, material adaptability, and operational standards of hydrogen storage systems. Through case studies of domestic and international hydrogen storage projects, combined with the experience of natural gas infrastructure modification, this paper summarizes successful experiences and challenges, and outlines the future development directions of hydrogen storage technology. The research shows that with the emergence of new materials and technological advancements, hydrogen storage will play an increasingly important role in future energy systems, driving the development of a low-carbon economy.
Hydrogen Storage; Natural Gas Infrastructure; Material Compatibility; Hydrogen Embrittlement; System Integrity; Energy Transition.
Study on Smart Retrofit Program for Non-Intelligent Cantilever Roller Shutters
In response to the pain points of the cantilever roller shutters used in agricultural greenhouses in vast rural areas, a low - cost and high - benefit intelligent upgrade solution is proposed. This solution is based on retrofitting the existing roller shutters, eliminating the need to purchase new ones and without altering the structure of the existing agricultural greenhouses. The aim of this paper is to transform the cantilever roller shutters by adding functions such as remote control, anti - over - rolling protection, and automatic rolling curtain retraction and deployment. These improvements can reduce curtain - rolling failures and farmers' losses, safeguard the safety of farmers' lives and property, and achieve a highly - efficient intelligent upgrade of the agricultural greenhouse roller shutters with relatively low economic input.
Smart Agriculture; Cantilever Rollers; Infrared Sensors; Automation.
Social Network Analysis of Risks in Prefabricated Building Projects
As a new construction method, prefabricated buildings are gradually changing the traditional construction model with their advantages of high efficiency and environmental friendliness. However, there are still many challenges in the process of its promotion, which requires the collaborative cooperation of various stakeholders. Social network analysis (SNA) provides an effective tool for studying the complex relationships among stakeholders. This study aims to use the social network analysis method to identify the key stakeholders in prefabricated building projects, analyze the characteristics of their relationship network, and provide a theoretical basis for optimizing project management and promoting cooperation. The main stakeholders in prefabricated building projects, such as the government, developers, design units, construction units, prefabricated component manufacturers, etc., are identified through literature research, expert interviews and other methods. Relationship data such as the interaction frequency, cooperation degree, and information exchange among stakeholders are collected through questionnaires, interviews, and other means. Social network analysis software (such as UCINET, Gephi, etc.) is used to construct the stakeholder relationship network model and conduct visual analysis.
Prefabricated Building; Social Network Analysis Method; Stakeholders.
Optimization of Control Strategy and Dynamic Response Performance Analysis of Surface-mounted Permanent Magnet Synchronous Motor
In this paper, the control strategy of Surface-mounted permanent magnet synchronous motor (SPMSM) is optimized, and its dynamic response performance is deeply analyzed. SPMSM is widely used in many fields because of its advantages of high efficiency, energy saving and high power density, but the traditional control strategy has shortcomings in complex working conditions. Therefore, an optimization method based on model predictive control (MPC) is proposed in this paper, which aims at accelerating dynamic response, reducing steady-state error and enhancing system robustness. By establishing the mathematical model of SPMSM, designing the prediction model and cost function, the quadratic programming algorithm is used to optimize the control input in each control cycle, and the rolling optimization is realized. The simulation results show that compared with traditional PI control, MPC control strategy significantly reduces the overshoot in step response (from 12% to 2%), shortens the adjustment time (from 0.25 seconds to 0.12 seconds), and shows higher accuracy and stability in dynamic tracking performance, and the root mean square error (RMSE) is reduced by 68%. This proves the superiority of MPC in improving the dynamic response performance and system stability of SPMSM, provides strong support for the reliable operation of the motor under complex working conditions, and also provides theoretical basis for the technical progress in related fields.
Surface-Mounted Permanent Magnet Synchronous Motor; Control Strategy; Dynamic Response Performance; Model Predictive Control.
Analysis of Influencing Factors for the Layout of Prefabricated Building Construction Sites based on Bayesian Networks
To enhance the scientific and rational layout of prefabricated building construction sites, this study is based on the Systematic Layout Planning (SLP) theory. Through logistics and non-logistics analysis, key factors influencing construction site layout are identified, and a Bayesian network model is constructed for reverse reasoning analysis of these factors. The research results indicate that when the construction site layout achieves a high level, the posterior probabilities of material flow, safety risks, and the convenience of prefabricated component hoisting increase significantly, suggesting that these factors have a substantial impact on site layout, while the influence of other factors is relatively minor. Based on diagnostic analysis, it is recommended to prioritize optimizing logistics paths, strengthening safety management, and improving hoisting efficiency in the planning of prefabricated building construction sites to enhance overall layout quality. This study provides a quantitative decision-making basis for the layout of prefabricated building construction sites, offering both theoretical and practical guidance.
Prefabricated Building; Construction Site Layout; Bayesian Network; Influencing Factor Analysis.
Study on the Method of Detecting Voids Behind Subway Tunnel Lining
When using the impact echo method to detect the void behind the tunnel lining, the continuous impact detection scheme helps to improve the detection efficiency, but it also brings a new challenge: multiple impact echo signals are superimposed and mixed during the recording process, which makes it difficult to independently process each impact event in the subsequent time-frequency analysis. In order to improve the accuracy and efficiency of signal processing, this paper proposes and develops a signal segmentation algorithm based on peak feature extraction, and introduces time window constraints to divide the entire signal into several independent sub-segments, thereby effectively reducing the degree of signal mixing. In practical applications, the data processing time of this segmentation method at the same measuring point is about 10 minutes, which is only 30%~50% of the processing time of the entire data segment; and the segmented multiple signal segments can be processed in parallel, and its segmentation processing efficiency is about 2 to 3 times that of the entire signal segment. By independently analyzing each segment of the signal, not only the subsequent time-frequency conversion and other processing procedures are simplified, the signal processing efficiency is improved, but also the accuracy of signal analysis is significantly improved, which provides theoretical and technical support for the application of the impact echo method in the analysis of tunnel segment void inspection data in the future.
Void Behind Tunnel Lining; Impact Echo Method; Signal Segmentation; Peak Feature Extraction; Time Window Constraints.
Construction and Practice of Operation and Maintenance Quality Management System of Township Sewage Treatment Facilities based on PDCA Cycle
In view of the unstable operation and maintenance quality of township sewage treatment facilities and the imperfect supervision system, combined with the management requirements of the technical specification for intelligent operation and maintenance management of township domestic sewage treatment facilities, an operation and maintenance quality management system based on PDCA cycle is proposed. Through the establishment of standard operating procedures (SOP), digital single system and three-level quality inspection mechanism, the practice was carried out in 32 village level sewage treatment stations in a county of G province. After one year of implementation, the equipment failure rate decreased by 42%, the integrity rate of operation and maintenance records increased from 58% to 96%, and the effluent compliance rate increased by 11.7%, providing a replicable mode for the long-term management of township sewage facilities.
PDCA Cycle; Township Sewage Treatment; Operation and Maintenance Management; Quality Management System; Standardization.
3D Printing Applications and Development of PLLA: A Review
Poly(L-lactic acid) (PLLA), a biodegradable and biocompatible polymer, has emerged as a cornerstone material in additive manufacturing for biomedical applications. This review examines recent advancements in 3D-printed PLLA-based scaffolds and devices, focusing on bone regeneration, infection control, drug delivery, and multifunctional tissue engineering. We analyze innovations in material modifications (e.g., plasticizers, nanocomposites), printing techniques (FDM, SLS, DLP), and structural design strategies (gradient porosity, auxetic architectures). Critical challenges such as degradation control, mechanical optimization, and clinical translation are discussed, along with future directions in 4D printing and personalized medicine.
PLLA; 3D-Printing; Additive Manufacturing.
Static Analysis and Optimization of the Cabin Structure of the Safety Refuge Device
Aiming at the technical problems of pressure resistance, explosion resistance and structural optimization of the safety refuge device, the cabin structure of the safety refuge device was parametrically modeled, and a new triangular cabin structure model was established. Loads were applied to the established triangular cabin, and static analysis was performed using ANSYS Workbench to observe the stress and deformation distribution of the cabin. Taking the quasi-triangular cabin structure as the research object, the optimized mathematical model of the cabin is established, and the equivalent stress, total deformation and quality of the quasi-triangular cabin are multi-objective optimized by using Creo and AWE joint simulation. The optimal solution of the quasi-triangular cabin structure is found through DOE optimization method. The analysis results show that: under the premise of unchanged cabin mass, the optimized cabin stress and total deformation are relatively reduced a lot, achieving the purpose of cabin optimization design, meeting the overall design requirements of the safety refuge device, and providing effective theoretical basis and technical support for the design and manufacture of the safety refuge device.
The Safety Refuge Device; Quasi-Triangular Cabin; Static Analysis; Optimization Design.
Synthesis of Two-dimensional SnS Nanosheets by Vacuum Thermal Evaporation
In this paper, two-dimensional SnS nanosheets of different sizes and morphology were synthesised by a facile vacuum thermal evaporation method. We systematically investigated the effects of growth time, evaporation source temperature, substrate temperature and substrate source distance on the size and morphology of nanosheets during the growth process. Two-dimensional SnS nanosheets with a lateral size of about 100 nm were prepared. The results will help to extend and deepen the basic and applied research on SnS two-dimensional materials.
SnS; Nanosheet; Vacuum Thermal Evaporation.
A Low-Cost, Highly Deployable Traffic Infrastructure Monitoring Solution based on Machine Vision
This study presents an innovative machine vision-based solution to address the challenges of traffic infrastructure monitoring. The proposed system integrates multiple modules to create a low-cost, highly deployable monitoring device and system. It significantly enhances monitoring efficiency and accuracy, offering a new perspective for the development of traffic monitoring technologies. Traditional methods, which mainly rely on manual inspections and fixed sensor networks, suffer from issues such as high costs, limited flexibility, and low timeliness. By introducing machine vision technology and deep learning algorithms, the system enables automatic crack detection and provides a cost-effective, highly deployable monitoring solution. The study provides a new path for advancing traffic infrastructure monitoring technologies.
Machine Vision; Traffic Infrastructure Monitoring; Low-Cost; High Deployability; Intelligent Early Warning.
Optimization Study of Fluctuation Prediction and Standby Unit Dispatch for Wind and Solar Power Generation
With the growing use of renewable energy sources worldwide, the volatility problem of wind and solar power generation challenges the stability of power systems. In this paper, the problem of predicting the volatility of wind and solar power generation and optimizing the dispatch of standby units based on historical data is investigated. First, support vector regression (SVR) and random forest regression (RF) models are used for short-term volatility prediction of wind and solar power generation. The prediction accuracy of the models is improved by optimizing the thresholds, in which the RMSE of the SVR model is 7.49 and that of the RF model is 6.72, which are superior to the traditional methods. Next, a two-objective optimization model is proposed to optimize the standby unit scheduling with particle swarm optimization (PSO) algorithm to balance the stability of the power plant and the cost of the standby unit. The experimental results show that the optimized scheduling strategy can effectively reduce the start-stop frequency of the standby unit and improve the economy and reliability of the power system. The research in this paper provides an effective solution for the fluctuation prediction and scheduling optimization of wind and solar power generation, which has important application value.
Wind Power; Solar Power; Volatility Prediction; Standby Unit Scheduling; Machine Learning; Optimization Algorithms.
Exploration of Safety and Energy Saving Measures in the Process of Oil and Gas Storage and Transportation
Under the background of continuous growth of global energy demand and intensified pressure of environmental protection, the safety risk and high energy consumption in oil and gas storage and transportation have become the key factors restricting the sustainable development of the industry. This paper systematically analyzes the safety and energy saving problems in oil and gas storage and transportation, and proposes comprehensive solutions by combining theoretical discussions and practical cases. It is found that safety risks mainly include physical (e.g., pipeline corrosion, equipment failure), chemical (e.g., fire and explosion caused by leakage), operational (human error), environmental (ecological pollution), and legal (violation of responsibility) dimensions; while energy consumption problems are focused on steam, electricity and fuel consumption, and technological lag and insufficient management are the main constraints; through the comprehensive application of safety and energy-saving technologies and the enhancement of the whole-process management, it is possible to significantly enhance the safety and energy-saving performance of oil and gas storage and transportation. Through the comprehensive application of safety and energy-saving technologies and strengthening the management of the whole process, the safety and energy efficiency of oil and gas storage and transportation can be significantly improved, taking into account the economic and environmental benefits. Future research needs to further focus on technological innovation and policy support in order to promote the sustainable development of the industry.
Oil and Gas; Storage and Transportation; Safety and Energy Saving Measures.
Research on the Strength of Cost-Effective UHPC Material based on Size Effect
Conventional concrete exhibits a size effect in compressive strength testing, whereas ultra-high-performance concrete (UHPC) shares a closer composition with ordinary mortar. This study investigates the compressive strength of cubic specimens with dimensions of 70.7 mm × 70.7 mm × 70.7 mm and 100 mm × 100 mm × 100 mm, analyzing their strength at different curing ages and deriving a 28-day strength ratio coefficient. The findings provide detailed performance data for UHPC, supporting both engineering applications and experimental research.
Size Effect; Compressive Strength; UHPC; Strength Ratio Coefficient; Engineering Applications.
Solid State-Hydrothermal Synthesis and Photoluminescence of ZnS
This study reports a novel solid-state-hydrothermal hybrid strategy for synthesizing phase-pure cubic ZnS. Starting with the high-temperature solid-state synthesis of K2Zn3S4 precursor, subsequent hydrothermal deintercalation yielded ZnS powders with cubic zinc-blende structure. Optical characterization revealed a direct bandgap of 3.50 eV and prominent red emission at 620 nm (2.0 eV) under 365 nm excitation, which can be attributed to de-trapping recombination between sulfur vacancies and zinc vacancies. This work establishes a dopant-free pathway for engineering ZnS luminescence through intrinsic defect control.
Zinc Sulfide; Vacancy Defect; Photoluminescence Spectroscopy.
Application of Long Range Airborne LiDAR in Mapping High-density Vegetation Terrain in Mountainous Areas
In the field of surveying and mapping, the accurate measurement of dense vegetation in mountainous areas is always a challenge. First of all, the use of conventional GNSS technology and total station operation, it is faced with more labor and resource investment, heavy economic burden, high safety risk and long operation cycle drawbacks. Secondly, the use of satellite remote sensing images and UAV aerial photography technology, due to the cover of surface vegetation, often can not clearly capture the surface condition covered by dense vegetation, and it is difficult to ensure the accuracy of measurement results. With the continuous development of LiDAR technology, airborne LiDAR measurement technology has gradually become a mature measurement means, combined with point cloud data processing, optimize the point cloud classification algorithm, can maximize the accuracy of height measurement in dense vegetation areas. Therefore, the use of airborne LiDAR to obtain the elevation data of the measuring area is a more ideal measurement method. The long range and multi-echo airborne LiDARis used to obtain terrain data with point cloud density of 21 points /m2, which solves the problem of terrain mapping under such terrain conditions.
LiDAR; Point Cloud; Drones; Topographic Survey.
Multimodal Bird Monitoring System Integrating Micro-Motion Detection and Gimbal Control YOLOv8 Optimization and Laser Deterrence System
To mitigate aviation safety risks, agricultural damage, and power outages caused by bird activities, this study introduces a bird recognition and dynamic deterrence system that combines You Only Look Once version 8 (YOLOv8) object detection, advanced micro-motion detection algorithms, and intelligent gimbal control. Traditional bird deterrent methods are often inefficient and lack adaptability, while current detection systems struggle with accuracy and real-time tracking of small, fast-moving targets. By integrating the Lucas-Kanade optical flow technique with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm, this research develops a multiscale, adaptive micro-motion detection model that effectively captures subtle bird movements while minimizing noise interference. This model is further enhanced by YOLOv8, utilizing an upgraded Cross-Stage Partial Network to 2-Stage FPN (C2f) architecture, the TaskAlignedAssigner for more accurate sample allocation, and dynamic Mosaic data augmentation for improved detection precision and speed. In addition, a gimbal control algorithm based on spatial registration and adaptive zoom adjustment ensures precise target localization and laser deterrence, employing a two-degree-of-freedom coordinate transformation and a 30x optical zoom field-of-view fitting function.
YOLOv8 Object Detection; Micro-Motion Detection; DBSCAN; Gimbal Camera Control Algorithm.
Research on Simulation and Structural Optimization of the Anchoring Force of Multiple Packers in the Stage Fracturing String
The multi-packer staged fracturing string is a key tool for the staged fracturing and exploitation of "three-low" oil and gas reservoirs in the Changqing Gas Field. The magnitude of the packer's anchoring force is closely related to the stability of the staged fracturing string, and directly affects the on - site fracturing operation effect. In response to the problems such as the lack of a quantitative design basis for packer anchoring during the staged fracturing process in the Changqing Oilfield and the difficulty in ensuring the service safety of the staged fracturing string, this paper selects the Y241 compression - type packer and the K344 expansion - type packer. Through theoretical mechanical analysis and finite - element numerical simulation, the distribution characteristics and variation laws of the anchoring force of the compression - type/expansion - type multi - packers in the staged fracturing string are studied. And combined with the on - site fracturing operation technology, the structure of the multi - packer string is optimized. The research results show that: during the first - stage, second - stage, and third - stage fracturing processes, the Y241 packer provides anchoring forces of 640.64 KN, 566.42 KN, and 566.72 KN respectively. The anchoring forces are all insufficient and cannot meet the requirements of staged fracturing. A hydraulic anchor with a pressure capacity of 300 KN needs to be configured throughout the process. For the K344 packer, during the first - stage fracturing, when the operating pressure is greater than 55 MPa, the packer's anchoring force meets the requirements; during the second - stage and third - stage fracturing processes, when the operating pressure is greater than 50 MPa, there is no need to connect a hydraulic anchor. Through the linear interpolation method, the critical values for connecting the hydraulic anchor of the K344 packer during staged fracturing are calculated to be 53.43 MPa, 46.47 MPa, and 46.17 MPa respectively.
Staged Fracturing; K344 Type Packer; Y241 Type Packer; Anchoring Force; Hydraulic Anchor.
Progress in Phosphorus Removal and Utilization from Converter Slag
Phosphorus, an irreplaceable non-renewable resource essential for agriculture and industry, holds significant economic value. However, global reserves of high-grade phosphate ores are rapidly depleting, making the search for suitable alternatives an urgent priority. Concurrently, the surging demand for steel driven by rapid global industrialization has positioned converter steelmaking-a pivotal process in steel production-as a critical industrial activity. Currently, converter steelmaking accounts for 80% of global steel production, with developed nations generating approximately 200 million tons of steel slag byproducts annually. This massive slag output not only occupies vast land resources but also poses environmental risks. Yet, steel slag is rich in phosphorus, representing a valuable secondary phosphorus resource. Thus, the effective recovery of phosphorus from converter slag is key to addressing phosphorus scarcity.This paper focuses on advanced technologies for efficient phosphorus recovery from converter slag, systematically summarizing global innovations in phosphorus removal from phosphorus-containing steel slag. It reviews metallurgical processes for phosphorus extraction via pyrometallurgical and hydrometallurgical methods, providing a critical research foundation and directional guidance for achieving high-efficiency phosphorus recovery in industrial applications.
Converter Steelmaking; Dephosphorization; Pyrometallurgical Dephosphorization.
Literature Review on Autonomous Navigation of Drones
This paper reviews the research progress in the field of autonomous navigation of drones, with a particular focus on navigation and positioning issues in environments where satellite signals are limited. It begins by introducing the potential applications of drones in civilian, military, and scientific research fields, as well as the importance of drone navigation systems for the quality of task completion. The paper then discusses the current state of research both domestically and internationally on navigation based on multi-agent reinforcement learning for visual navigation, deep reinforcement learning navigation algorithms, and navigation using the fusion of multiple sensors. The application of Ultra-Wideband (UWB) technology in the field of drone autonomous navigation is also explored, including its positioning principles and potential in drone swarm intelligence. Additionally, the paper analyzes the current state of development of drone autonomous landing systems in both civilian and military fields. Finally, the paper discusses the research progress in drone detection and recognition technology based on deep learning, as well as radar detection and recognition technology for drones.
Drones; Autonomous Navigation; Visual Navigation; Ultra-Wideband (UWB) Technology; Deep Learning.
3D Geometric Segmentation Method based on the Point-normal Form Equation of a Plane
Under the background of rapid development of computer technology, mature 3D modeling technology and extensive application of 3 D model, the research of 3 D geometry cutting is of great significance. In this paper, the surface cutting method is adopted to determine the cutting plane based on the point method of the surface, the 3D geometric figure center is selected as the point, and the cutting plane equation is obtained by calculating the normal vector at a given Angle. Using the VTK function library, 3D geometry reading, cutting, after cutting graph data retention and translation separation are realized in Python, and then the cutting plane is displayed. Taking the planning of impacted third molar cutting path in dental medical images as an example, we verify the practicability and flexibility of the algorithm, which has application potential in many fields such as medical treatment and relic restoration.
3D Model; VTK; Geometric Center; Normal Vector; Plane Cutting.
YOLOv8-CDD: A Salient Target Detection Model for Underwater Cultural Heritage in Complex Environments
Existing object detection methods often experience a decline in accuracy when directly applied to underwater scenarios, making it difficult to meet the precision and reliability requirements of practical cultural heritage detection tasks. To address common challenges in underwater heritage detection-such as low image contrast, severe target occlusion, and insufficient detection accuracy-this paper proposes a novel detection model, YOLOv8-CDD. The model is designed to improve the recognition of salient target regions in complex underwater conditions, thereby enhancing the automation and efficiency of archaeological detection. YOLOv8-CDD is developed by deeply optimizing the backbone and detection head of the original YOLOv8 architecture. It integrates a C2f-DCNv4 structure, the CBAM attention mechanism, and the Dynamic4 detection head to significantly enhance feature extraction and the perception of small or occluded objects, while maintaining high computational efficiency. The model is systematically evaluated on both the public DUO dataset and a self-constructed underwater archaeological image dataset. Experimental results show that YOLOv8-CDD achieves an mAP@0.5 of 84.9% and an mAP@0.5:0.95 of 63.8% on the DUO dataset, representing improvements of 4.0% and 3.4%, respectively, over the baseline. On the self-constructed dataset, it attains an mAP@0.5 of 70.4%, with a gain of 4.1%.
Underwater Object Detection; Cultural Heritage; Salient Region Recognition.
Architecture Design of a Smart Logistics Warehouse Management System based on Multi-modal AI
Addressing the inefficiency and poor real-time performance of traditional warehouse management systems, this paper proposes a design scheme for a smart warehouse management system based on multi-modal AI. The system achieves intelligent management of the entire logistics process through the collaborative decision-making of multi-modal AI (DeepSeek-R1 language model and GLM-4V visual model). Combining a modular micro-services architecture (SpringCloud) and distributed technology, it constructs a closed-loop system of "perception-decision-monitoring." The design integrates two-factor authentication and edge-cloud collaborative computing, supporting dynamic inventory optimization and real-time data analysis, providing a lightweight and scalable solution for the intelligent upgrade of logistics warehousing. Future work will further explore the deep integration application of digital twin technology.
Smart Warehouse; Multi-modal AI; Micro-services; Internet of Things.
Heterogeneous Catalytic Degradation of Methyl Orange by H2O2 with FeS Micro-flakes
Organic dyes are common water pollutants that harm both the environment and human health. This study addressed this issue by synthesizing FeS as a heterogeneous catalyst, using methyl orange (MO) as the target pollutant and H2O2 as the oxidant. The degradation performance of FeS was examined. Experimental results demonstrated that, without pH adjustment and at 30 °C, the synergistic effect of 0.8 g/L FeS and 20 mM H2O2 achieved over 90% degradation of MO within 10 minutes and nearly complete removal of MO within 20 minutes. Moreover, high degradation efficiency was achieved over a wide pH range (2 ~ 7.5). This work offers a new and efficient approach for treating dye-containing wastewater.
FeS Micro-flakes; Fenton Reaction; Degradation; MO.
Design of the V-shaped Lower Tower Column Support for Tuojiang Bridge on Jinjianren Expressway
Tuojiang Bridge on Jinjianren Expressway is a single-tower double-plane cable-stayed bridge with the space curve and hexagonal section steel inclined tower. As the urban landscape bridge, it is an important channel connecting the north and south directions of Chengdu city area. Based on the structural characteristics of the main tower of Tuojiang Bridge and the construction process, the design and optimization of the V-shaped lower tower column bracing schemes of the main tower were carried out. Ultimately, the design scheme of less point supporting system was determined by comparison. In the scheme, the foundation of the nearby existing structure is used or the existing structure was avoid through setting template beams and brackets, which brings out lower costs. By welding steel cushion blocks on the V-shaped leg segment, it is conducive to segment hoisting and the structure alignment. Meanwhile, by using finite element software to simulate the construction process, the reaction forces acting on the bracket are analyzed during the construction of the V-shaped lower tower column, which are used as the loads in the calculation of the V-shaped lower tower column support to ensure the reliability of the finite element analysis and the economical efficiency of the support. The less point supporting system program can not only meet the functional requirements of hoisting, assembling and adjusting the shape of the main structure, but also reduce the construction difficulty and cost of the structure, and enable the successful implementation of this project, which can provide a reference for the design of similar projects.
Tuojiang Bridge; Main Tower; V-shaped Lower Tower Column; Support.
Research on Road Surface Inspection System for Lightweight Design
Given the problems of low efficiency, heavy workload, and hidden safety problems associated with manual inspection, this paper proposes a multi-sensor fusion road inspection system for lightweight design. The system adopts a high-definition industrial camera and GNSS / IMU joint positioning terminal to realize the accurate acquisition of high-definition images of roads and real-time location data. At the same time, this study uses the lightweight disease detection model to optimize the inspection process and improve coordination efficiency. Acquisition application results show that the system in common cracks, pits, and other pavement disease detection realizes the rapid, precise data acquisition and, through the task management function, significantly improves the inspection efficiency and data accuracy for the road management department and maintenance unit provides timely and accurate maintenance data support, promote the road maintenance of intelligent management level. Given the problems of low efficiency, heavy workload, and hidden safety problems associated with manual inspection, this paper proposes a multi-sensor fusion road inspection system for lightweight design. The system adopts a high-definition industrial camera and GNSS / IMU joint positioning terminal to realize the accurate acquisition of high-definition images of roads and real-time location data. At the same time, this study uses the lightweight disease detection model to optimize the inspection process and improve coordination efficiency. Acquisition application results show that the system in common cracks, pits, and other pavement disease detection realizes the rapid, precise data acquisition and, through the task management function, significantly improves the inspection efficiency and data accuracy for the road management department and maintenance unit provides timely and accurate maintenance data support, promote the road maintenance of intelligent management level. Given the problems of low efficiency, heavy workload, and hidden safety problems associated with manual inspection, this paper proposes a multi-sensor fusion road inspection system for lightweight design. The system adopts a high-definition industrial camera and GNSS / IMU joint positioning terminal to realize the accurate acquisition of high-definition images of roads and real-time location data. At the same time, this study uses the lightweight disease detection model to optimize the inspection process and improve coordination efficiency. Acquisition application results show that the system in common cracks, pits, and other pavement disease detection realizes the rapid, precise data acquisition and, through the task management function, significantly improves the inspection efficiency and data accuracy for the road management department and maintenance unit provides timely and accurate maintenance data support, promote the road maintenance of intelligent management level. Given the problems of low efficiency, heavy workload, and hidden safety problems associated with manual inspection, this paper proposes a multi-sensor fusion road inspection system for lightweight design. The system adopts a high-definition industrial camera and GNSS / IMU joint positioning terminal to realize the accurate acquisition of high-definition images of roads and real-time location data. At the same time, this study uses the lightweight disease detection model to optimize the inspection process and improve coordination efficiency. Acquisition application results show that the system in common cracks, pits, and other pavement disease detection realizes the rapid, precise data acquisition and, through the task management function, significantly improves the inspection efficiency and data accuracy for the road management department and maintenance unit provides timely and accurate maintenance data support, promote the road maintenance of intelligent management level.
Lightweight Design; Road Surface Disease; Industrial Camera; Satellite Positioning; YOLOv8n; Road Surface Maintenance.
Research on Improved 2D SLAM Algorithm based on Gmapping
In the traditional Gmapping algorithm, particle filtering is susceptible to motion noise, and particles may degrade or fall into local optima, leading to decreased mapping accuracy. This paper proposes an improved Gmapping method that integrates Extended Kalman Filter (EKF) prediction with Adaptive Particle Swarm Optimization (APSO) to enhance SLAM accuracy and robustness. First, EKF is used to fuse IMU and wheeled odometry information for pose prediction, ensuring more precise particle initialization and reducing the impact of motion noise on particle sampling. Second, APSO dynamically adjusts particle velocity and pose to improve global search capability, preventing premature convergence. Finally, APSO is introduced in the resampling process to optimize particle diversity and mitigate particle degradation. Experimental results demonstrate that the proposed algorithm achieves higher localization accuracy and mapping quality in long corridors and low-feature areas while reducing computational cost and enhancing SLAM system robustness.
Investigation of the Morphology of PCL-Based Electrospun Nanofibers under Different Experimental Parameters
This research examines how changes in concentration, flow rate, and the inclusion of various additives impact the morphological characteristics of electrospun nanofibers derived from polycaprolactone (PCL). These factors play a critical role in determining fiber diameter, surface features, and overall quality. The study systematically assesses the effects of these variables on the size, shape, and consistency of the nanofibers. Findings reveal that fine-tuning these parameters allows for the tailored design of fiber properties to meet specific requirements. For example, adjustments in concentration significantly alter fiber formation and structural integrity, whereas flow rate is closely linked to the diameter and uniformity of the fibers. Incorporating certain additives further improves the functional performance of the nanofibers. The outcomes of this work contribute essential knowledge for refining the electrospinning process of PCL-based nanofibers, establishing both a theoretical framework and practical evidence for their use in biomedical applications, filtration technologies, and packaging solutions.
Core-Shell Structure; Coaxial Electrospinning; Polycaprolactone; Nanoparticles.
Design of Intelligent Vehicle Virtual Reality Integration based on Unity3D
Aiming at the problems of high operation risk and lack of interest in the intelligent vehicle control experiment, a set of practical training equipment system is constructed by using the design based on Unity 3D and STM 32 to realize the combination of virtual and real to control the movement of the intelligent vehicle. By simulating the real application of intelligent vehicles, building virtual scenes, according to the experimental data, writing the corresponding processing code, combining the virtual and real, real-time feedback of some parameters in the operation of the intelligent vehicle information situation, to provide users with a safe and reliable operating platform, effectively reduce the risk of operation at the same time to enhance the user's interactivity and interest in the learning process. This innovation not only greatly improves the safety and reliability of the intelligent vehicle in the experimental process, but also lays a solid theoretical and technological foundation for the application of virtual reality technology, simulation testing and other areas of development, and promotes the further innovation and development of the combination of virtual and real technology.
Unity 3D; STM 32; Intelligent Vehicles; Virtual Reality.