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.
Multi-Objective Location Optimization of Drone Vertiports Considering Hierarchical Economic Feasibility
To address the efficiency bottleneck in urban last-mile delivery and the limitations of existing drone vertiport location models-which neglect the structural cost differences between urban and rural logistics and are sensitive to dimensional disparities in Pareto solution ranking-this paper proposes a multi-objective location optimization model and decision-making method for drone vertiports that considers hierarchical economic feasibility, providing a location decision tool for drone logistics distribution. The model maximizes demand coverage and minimizes total life-cycle cost, introducing a hierarchical economic feasibility threshold based on the distance from each demand point to its nearest logistics node, along with a hard capacity constraint. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) with elitist strategy is employed for solution, and a Nadir-Ideal Point Bidirectional Normalization method is proposed for Pareto solution ranking. The model is validated using real-world data from Caofeidian District, comprising 364 demand points and 10 traditional logistics nodes. After 800 generations, 110 non-dominated solutions are obtained. The recommended scheme constructs 11 vertiports, covering 55.77% of demand points, with a five-year total life-cycle cost of approximately 11.98 million CNY, achieving a 44.87% daily operating cost saving compared to traditional delivery. Sensitivity analysis reveals that the hierarchical threshold improves coverage in remote areas by 13.6 percentage points compared to a uniform threshold. The hierarchical economic feasibility threshold effectively identifies the substitution value of drones in remote areas, and the Nadir-Ideal Point Bidirectional Normalization method effectively eliminates the interference of dimensional differences on Pareto decision-making. The model and algorithm provide valuable support for scientific site selection of drone vertiports.
Drone Logistics; Vertiport Location; Hierarchical Economic Threshold; Pareto Decision-Making.
Copyright (c) 2026 International Core Journal of Engineering https://creativecommons.org/licenses/by-nc/4.0
Defect Detection and Grain Size Evaluation based on Metallographic Images of Long Shafts
Aiming at the difficulties in identifying tiny surface defects and automatic grain size evaluation of long shaft parts, this paper proposes an automatic detection and grading method based on robot visual guidance and adaptive image segmentation. The YOLOv8 algorithm is adopted to identify surface defects on long shafts, and the defect coordinates are mapped to the base coordinate system through the hand-eye calibration matrix with a positioning error within 0.9 mm, which guides the end effector to complete fixed-point grinding and etching. This paper focuses on developing an OpenCV-based grain size calculation algorithm: CLAHE contrast enhancement, adaptive Gaussian threshold segmentation and watershed algorithm are applied to metallographic images after etching to accurately separate adhered grains. Pseudo-boundary interferences are eliminated via contour morphological filtering, and the average grain area method is finally used to calculate and grade grain sizes. Experiments verify that the proposed system realizes integrated operations from defect localization to metallographic grading for long shafts, with a repeatability error of grain size grading less than 0.5 grades, satisfying the high-precision detection requirements of industrial sites.
Long Shaft Inspection; YOLOv8; Grain Size Grading; Watershed Algorithm.
Performance Optimization and Fault-tolerant Control Technology of Drive System
Amid the rapid development of the new energy vehicle sector, the drive system, a pivotal power component of electric vehicles, directly dictates the vehicle’s performance, economic efficiency, safety, and operational reliability. Current pure electric vehicles are confronted with challenges such as limited driving range, uneven power performance and high failure risks in the drive system. Although rotor permanent magnet brushless motors are widely applied in electric vehicle (EV) drive systems due to their high efficiency and power density, they are prone to permanent magnet demagnetization and winding faults, which pose severe threats to vehicle operational safety. Therefore, performance optimization and fault-tolerant control technologies for drive systems have become critical breakthroughs to enhance the overall competitiveness of new energy vehicles. This paper systematically reviews the structural types, performance optimization methods and fault-tolerant control technologies of EV drive systems at home and abroad. It analyzes the advantages and disadvantages of different drive modes, core optimization approaches and key fault-tolerant control technologies, identifies the current research bottlenecks, and outlines the future development trends. The findings of this study serve as a useful reference for enhancing the performance and reliability of new energy vehicle drive systems, bolster the high-quality development of China's new energy vehicle sector, and contribute to realizing the goals of carbon peaking and carbon neutrality.This project focuses on the precise parameter matching of key components in the powertrain of pure electric vehicles, as well as innovative solutions to the existing problems of rotor permanent magnet brushless motors.
Permanent Magnet Synchronous Motor; Fault Diagnosis; Multi-motor Coupling Drive; Parameter Matching; Topology Optimization; Torque Ripple Suppression.
Design of Core Drilling Rig Data Monitoring System based on STM32
To improve the drilling efficiency and intelligence level of core drilling rigs, a local data monitoring system was designed based on the STM32F407VGT6 and the Boke Screen F150E. The system uses Kinco DTools configuration software for interface design and employs CAN bus communication technology to monitor and communicate with the host computer. Test results show that the system can monitor various parameters of the core drilling rig in real time, which can enhance the intelligence level of the rig and has certain practical engineering value.
STM32F407VGT6; Boke Screen; Kinco DTools; Data Monitoring System.
Numerical Analysis on Seismic Response of Buried Pipelines with Defects in Liquefiable Sites
The rapid expansion of long-distance oil and gas pipeline networks has led to increased pipeline crossings of high-seismic-risk regions. Soil liquefaction substantially degrades pipe–soil interaction restraint, triggering significant axial deformation of buried pipelines. In addition, local corrosion defects generated during long-term service reduce pipe wall cross-sectional area and induce severe stress concentration, considerably exacerbating pipeline failure hazards under seismic conditions.In this study, a finite element numerical model is established to investigate the seismic response of buried pressure pipelines with local corrosion defects in liquefiable soils. Solid elements are employed to discretize the pipeline structure, while nonlinear spring elements are adopted to characterize soil confinement effects. The stiffness degradation of soil in liquefied zones is realized by reducing the stiffness of soil springs, which accurately simulates the attenuation of soil bearing capacity during liquefaction. The maximum axial strain is selected as the critical evaluation index to quantify the tensile and compressive deformation of pipelines during liquefaction-induced uplift. By comparing the calculated axial strain with the material yield strain, the plastic development degree and bearing capacity degradation of defective pipelines can be quantitatively identified. Parametric analyses are systematically conducted to explore the effects of liquefied zone length, corrosion defect depth, and internal operating pressure on pipeline axial strain responses.The numerical results demonstrate that the expansion of the liquefied zone weakens pipe–soil constraint stiffness and enlarges pipeline axial deformation, with the maximum axial strain increasing monotonically with liquefied zone length. Deepened corrosion defects significantly reduce the local structural stiffness of the pipe wall and aggravate strain concentration at defect locations. Moreover, elevated internal pressure raises the initial circumferential stress of pipelines, which further amplifies the axial strain of defective sections under seismic excitation. This study provides a reliable theoretical reference for the seismic safety assessment and risk mitigation of defective buried pipelines in liquefaction-prone areas.
Buried Defective Pipeline; Liquefiable Site; Seismic Excitation; Numerical Analysis.
Digital Twin Visualization Design for Intelligent Warehousing and AGV Scheduling System
To address information silos, delayed equipment-state perception, path conflicts among multiple AGVs, and insufficient visual monitoring capability in conventional warehousing systems, this paper proposes a digital-twin-based visualization design method for an intelligent warehousing and AGV scheduling system. First, three-dimensional models of key equipment, including the automated storage warehouse, underride AGVs, racks, inbound/outbound stations, and handling manipulators, are constructed using the three-dimensional modeling platform, and non-critical structures are lightweighted to balance visualization accuracy and simulation efficiency. Second, rigid bodies, collision bodies, motion joints, sensors, actuators, and signal mapping relationships are configured in the NX_MCD mechatronic concept design environment to establish a virtual warehousing system with kinematic constraints and logical response capability. Third, a virtual PLC control system is developed by integrating TIA Portal and PLCSIM Advanced, enabling real-time signal interaction between the PLC control program and the NX_MCD simulation model. On this basis, virtual commissioning of AGV storage and retrieval paths, manipulator handling actions, and inbound/outbound operation processes is realized. Finally, an HMI interface is used to dynamically monitor and visualize rack occupancy, AGV operating status, and inbound/outbound task information. The results show that the proposed method can achieve coordinated mapping among physical objects, control logic, and virtual models in an intelligent warehousing system. It provides a feasible engineering solution for multi-AGV scheduling process verification, warehouse operation monitoring, and early-stage virtual commissioning, and offers practical reference for reducing physical commissioning costs, improving warehouse system design efficiency, and promoting the digital transformation of small- and medium-sized warehousing systems.
Digital Twin; Intelligent Warehousing; AGV Scheduling; NX_MCD; PLC; Virtual Commissioning; Visual Monitoring.
Creep Curve Characteristics Analysis of White Sandstone under Coupled Chemical Corrosion and Temperature Effects
White sandstone in underground structures may be exposed to chemical attack and temperature variation at the same time, but the resulting change in its creep-stage transition has not been clearly quantified. In this work, specimens collected from Zigong, Sichuan Province, were conditioned in H₂SO₄ solution (pH = 1), distilled water, or NaOH solution (pH = 13) at 0 °C, 25 °C, 50 °C, 75 °C, and 100 °C, and were then tested under uniaxial stepwise loading. The complete strain-time records retained the usual sequence of primary, secondary, and tertiary creep in every group. The main difference was the stress at which accelerated deformation began. For specimens treated in distilled water, this threshold was 24 MPa at each temperature. For the acid- and alkali-treated specimens, it remained 24 MPa from 0 °C to 50 °C, decreased to 20 MPa at 75 °C, and reached 16 MPa at 100 °C. Thus, temperature alone did not alter the threshold under neutral conditions within the tested range; its influence became pronounced when a reactive solution was present. The results are consistent with heating-enhanced water-rock reactions that advance internal deterioration and bring forward the transition to unstable creep. These observations provide direct experimental evidence for evaluating chemo-thermal effects on the full creep response of white sandstone.
White Sandstone; Creep Curve; Chemical Corrosion; Temperature Coupling; Accelerated Creep.
Methods for Suppressing Short-Channel Effects in FinFET Process
This paper focuses on the key technologies of FinFET devices for suppressing short-channel effects (SCE). It systematically analyzes their three-dimensional structural characteristics and the mechanisms of SCE, and explores the influence of critical factors such as fin body parameters, material selection, and three-dimensional structure optimization on device performance. Research indicates that FinFET, with its unique three-sided gate-wrapped channel structure and superior gate control efficiency, significantly enhances the electrostatic performance of the device, thereby demonstrating outstanding effectiveness in suppressing leakage currents caused by short-channel effects. This is specifically reflected in the effective mitigation of drain-induced barrier lowering (DIBL) and subthreshold leakage. The paper compares the current development status of FinFET technology domestically and internationally, clarifying the advantages and disadvantages of current technical routes and their industrial maturity. To meet the technical requirements of advanced process nodes such as 7 nm and below 5 nm, this study optimizes key parameters of the fin structure (including fin width and height) and introduces innovative material systems such as high-k dielectrics/metal gates. This lays a theoretical foundation for enhancing device performance and reducing power consumption, while providing a feasible technical path. The paper also looks forward to the future evolution of FinFET toward gate-all-around (GAA) and negative capacitance structures, emphasizing its significant value in extending Moore's Law. This study not only summarizes the core mechanisms of FinFET in suppressing short-channel effects, but also provides a reference for the design and manufacturing of subsequent advanced technology nodes.
FinFET; Short-Channel Effect; Three-Dimensional Structure; Device Performance; Process Optimization.
Stress Analysis of Buried Pipelines with Complex Defects based on ABAQUS
To investigate the influence of complex defects on the mechanical behavior of buried pipelines, a three-dimensional finite element model of buried pipelines was established based on ABAQUS software. Three typical defect models, including single corrosion defects, overlapping defects, and corrosion–crack coupled defects, were developed to analyze the stress response characteristics under different defect configurations. The control variable method was adopted to study the effects of defect length, width, and depth on the maximum equivalent stress of the pipelines. The results show that the maximum equivalent stress increases with the increase of defect length and defect depth, among which defect depth has the most significant influence on the stress response of pipelines. In contrast, the influence of defect width on stress variation is relatively negligible. Under the same geometric parameters, the corrosion–crack coupled defect model exhibits the highest equivalent stress, followed by the overlapping defect model, while the single defect model shows the lowest stress level. This finding indicates that complex defects can further aggravate local stress concentration and reduce the structural safety of buried pipelines. The research results can provide valuable references for the integrity assessment and safety evaluation of buried pipelines with complex defects.
Buried Pipeline; Complex Defects; Finite Element Analysis; Corrosion Defect; Stress Analysis.
Autonomous Wingtip Docking of Fixed-Wing UAVs: Relative Navigation, Closed-Loop Control, and System-Level Challenges
Autonomous wingtip docking of fixed-wing unmanned aerial vehicles offers a potential approach to long-endurance flight, modular mission reconfiguration, and airborne assembly. Unlike conventional formation flight, this task requires two forward-flying aircraft to reduce the relative position, attitude, and closing-velocity errors between their actual docking points while satisfying fixed-wing flight-envelope, visibility, aerodynamic-interaction, and collision-avoidance constraints. This article organizes relevant research around two closely coupled themes: relative navigation and closed-loop docking control. Vision-based relative measurement methods are examined, including cooperative fiducial markers, structure-based non-cooperative perception, monocular and stereo pose estimation, and learning–geometry hybrid approaches; multi-sensor relative-state estimation is then discussed with emphasis on visual–inertial fusion, GNSS/RTK and UWB assistance, dual-moving-platform modeling, asynchronous measurements, lever-arm compensation, observability, and uncertainty representation. The control literature is further analyzed from the perspectives of position-based and image-based visual servoing, robust and prescribed-performance control, model predictive and safety-critical control, and learning-based disturbance compensation. The central technical challenge lies not in improving pose-estimation accuracy or tracking convergence in isolation, but in constructing an uncertainty-aware, constraint-compliant, and contact-transition-capable autonomous closed-loop system. Future research should therefore focus on dual-platform relative observability, confidence-aware closure control, visibility-preserving trajectory planning, real-time near-field aerodynamic modeling, hybrid contact dynamics, navigation–control–mechanism co-design, and progressively structured experimental validation.
Fixed-wing UAV; Wingtip Docking; Relative Navigation; Visual–inertial Fusion; Visual Servoing.
Integrated Diagnostic Model for Leakage and Blockage in Water Distribution Networks based on Multisensor Data Fusion
Together, the diagnosis of leaks and blockages in the water distribution network has been affected by coupled perception, hydraulics, computation and operation uncertainty, so a single deterministic controller or classifier cannot be applied reliably in engineering practice. According to various sensors, a powerful diagnosis and control framework has been proposed in this paper that is biased-aware, employs model predictive reasoning and conservative fallback rules. Instead of field claims for the parameters in this study, Disequations will be used; all indicators are Design Variables and will undergo several engineering evaluations. The five tables are sensor channel information, disturbance cases, diagnostic thresholds, control responses and robustness indices, and the two formulas are the residual score and the weighted stability index. Based on the above results, the proposed framework can reduce false alarms, keep the stability of operation, and provide clear decision support in the case of bias, delay or partial missing data in the input signal. The new one is to integrate the fault evidence, model constraints and practical control measures in a traceable way that can be published in the journal.
Robust Control; Sensor Bias; Multisensor Fusion; Digital Twin; Fault Diagnosis; Engineering Stability.
Heat Recovery Characteristics and Energy Efficiency Analysis of a Heat Pump-Fine Filament Water-Film Sucrose Drying System
Given the problems of high energy consumption, poor utilisation of exhaust heat, and low sugar dust recovery efficiency in traditional sucrose hot-air drying, this paper presents a heat pump-coupled fine-filament water-film sucrose drying system and studies its heat recovery characteristics and energy performance. The condenser side of the heat pump in the proposed system supplies drying heat, and the evaporator side provides low-temperature circulating water to maintain a stable liquid film on the fine filaments for integrated drying, exhaust heat recovery and wet sugar dust capture in a unified process. According to the system's structure, this paper outlines the primary heat-transfer paths, the functional purpose of the recovery unit, and an energy-efficiency assessment system; at the same time, it investigates how to modify operating parameters to increase heating capacity and heat-recovery intensity for the entire system. Based on the above analysis, connecting a heat pump with a fine-filament water-film unit can reduce sensible and latent heat loss in the exhaust stream, improve the utilisation of recirculated air, and enhance cascade use of thermal energy in the system. At the same time, a liquid-film interface can increase the efficiency of particle collection and provide a good environment for the re-absorption and redistribution of exhaust heat. Introduce indicators such as the coefficient of performance, specific moisture extraction rate and heat recovery ratio to assess the energy-saving effect and engineering feasibility of the system in an all-around way. Provide the foundation for the following experiments and numerical simulations of low-carbon sucrose drying equipment: experimental verification and engineering optimisation.
Heat Pump; Fine-Filament Water Film; Sucrose Drying; Heat Recovery; Energy Efficiency; Sugar Dust Recovery.
AQWA-Based Motion Response Analysis of a Suezmax FPSO
To investigate the motion response characteristics of a long-term moored floating production, storage and offloading unit (FPSO) under wave action, a Suezmax FPSO was selected as the research object. Based on three-dimensional linear potential-flow theory and wave radiation/diffraction theory, numerical simulations of the motion responses under wave loading were conducted using AQWA. The six-degree-of-freedom response amplitude operators (RAOs), first-order wave excitation forces, and time-domain motion response characteristics of the platform under different wave directions were systematically analysed. The effects of wave frequency and wave direction on the seakeeping performance of the FPSO were also discussed.The results show that the six-degree-of-freedom motion responses of the FPSO exhibit significant directional dependence. The RAO peaks are mainly concentrated in the low-frequency range, and the motion responses are significantly amplified when the wave frequency approaches the natural frequency of the platform. Moreover, the RAO peaks are not determined solely by the maximum value of any single type of excitation force, but result from the combined effects of the Froude–Krylov force, diffraction force, and other hydrodynamic forces. The time-domain analysis further verifies the frequency-domain results, indicating that the pitch and roll responses increase most significantly under severe sea conditions.
Design of an Intelligent Monitoring Platform for Guide Robot Dogs in High-Speed Railway Stations
Addressing the issues of dense passenger flow, complex circulation routes, high travel risks for visually impaired passengers in high-speed railway stations, as well as the standalone operation, decentralized management, and weak intelligent coordination capabilities of traditional guide robot dogs, this paper designs an intelligent monitoring platform for guide robot dogs in high-speed railway stations based on multi-agent technology. The platform adopts a core architecture consisting of robot dog execution agents, monitoring and dispatching agents, emergency decision-making agents, and operation and maintenance management agents, integrating five functional modules: situational visualization, equipment monitoring, remote dispatching, alarm handling, and data operation and maintenance. It realizes an integrated management and control mode featuring autonomous collaboration among multiple guide robot dogs, intelligent task allocation, proactive risk warning, and closed-loop fault management. This can provide a reference for the cluster management and control of intelligent service robots in transportation hubs.
High-Speed Railway Station; Guide Robot Dog; Multi-Agent; Intelligent Monitoring; Collaborative Scheduling; Emergency Decision-Making.
Flexible Land-Use Control Planning for Bus Terminals at Mega Railway Hubs: An AI-Enabled Approach
In recent years, bus terminals serving mega railway hubs in China’s major cities and megacities have faced a prominent contradiction between declining passenger demand and redundant land provision. This study examines four benchmark railway hubs in China and abroad and shows that three land-use optimization strategies-distributed layout, functional sharing, and three-dimensional integration-can substantially reduce terminal land requirements while maintaining essential feeder-transport functions, thereby providing an alternative to the conventional approach of sizing land solely from peak passenger demand. On this basis, a flexible land-use control model is developed by dividing terminal land into rigid service space and flexible adjustment space. The former is sized against off-peak passenger demand to meet basic operational needs, while the latter accommodates peak-period reserve capacity, mixed-use functions, and long-term development reserves. The study also explores an implementation pathway supported by deep learning and video-image recognition technologies and establishes an operational mechanism that integrates AI-enabled multi-source data acquisition, passenger-flow prediction, dynamic spatial regulation, and closed-loop feedback. This framework shifts bus-terminal land-use control from a static and rigid model toward dynamic and adaptive spatial governance. The findings provide a conceptual and methodological reference for intensive land use and adaptive planning of bus terminals at mega railway hubs.
Railway Hub; Bus Terminal; Land-Use Control Planning; Artificial Intelligence; Image Recognition.
Analysis of Structural Strength and Fatigue Life of Unmanned Aerial Vehicles (UAVs) based on Finite Element Method
The use of Unmanned Aerial Vehicles (UAVs) has seen a rapid rise in the areas of reconnaissance, surveying and mapping, logistics and agriculture. One important factor influencing the operational safety and service life of the structures is the structural fatigue failure under long-term alternating loads. This paper is dedicated to the wing of a fixed-wing UAV with the goal of improving the structural reliability of UAVs. The three-dimensional (3D) model was established by the finite element analysis method, and the typical flight conditions were set to simulate and calculate the stress distribution and structural response. On basis of this, the S-N curve and Miner's damage accumulation theory were combined to finish the fatigue life prediction, find out the key weak areas and put forward the structural optimization schemes. The results show that the finite element analysis can effectively reveal the stress characteristics of UAV structures and accurately evaluate the fatigue life, providing a reliable technical basis for structural design and in-service safety assessment.
Unmanned Aerial Vehicle (UAV); Finite Element Analysis; Fatigue Life.
Failure Mechanism of Airtightness Detection Caused by Corrosion-Induced Clogging in Power Battery Liquid Cooling Plates
Leakage detection of coolant is critical for the safe operation and maintenance of power battery liquid cooling systems. However, a false‑negative phenomenon has frequently been observed in engineering practice: dry‑air airtightness tests indicate acceptable sealing performance even though corrosion-induced perforation has already occurred. To reveal the underlying mechanism, a multi‑physics coupling model integrating electrochemical corrosion, ionic transport, precipitation kinetics, and porous seepage was developed based on an actual field failure case. Accelerated galvanic corrosion experiments were further conducted to validate the corrosion morphology and failure mode. The results demonstrate that galvanic corrosion between the aluminum liquid cooling plate and the steel battery enclosure leads to the formation of an occluded corrosion cell. Hydrolysis of Al3+ ions induces an autocatalytic “dissolution–acidification–accelerated dissolution” cycle, which continuously promotes localized corrosion growth. Meanwhile, Al3+ and OH− ions accumulate near the defect channel and lead to preferential precipitation of Al(OH)3​ corrosion products. The local deposition density reaches approximately 1321 kg/m3 , causing the permeability of the leakage channel to decrease from 10−11 m2 to below 10−15 m2. Consequently, the seepage capacity of the leakage path is essentially lost. To quantitatively evaluate the risk of leakage misdetection, a False‑Negative Index (FNI) is proposed. When FNI exceeds 0.99, conventional dry‑air airtightness testing becomes incapable of identifying existing leakage defects. Furthermore, three‑dimensional airtightness simulations show good agreement with experimental measurements, with pressure‑drop deviations below 8%. The proposed mechanism successfully explains the contradiction between actual corrosion perforation and qualified airtightness test results. The findings provide theoretical support for leakage diagnosis, corrosion prevention, and safety‑oriented design of battery liquid cooling systems.
Liquid Cooling Plate; Galvanic Corrosion; Multi-Physics Simulation; Corrosion Product Deposition; Failure of Airtightness Detection.
Optimal Design of Crankshaft for a Single-cylinder Diesel Engine based on ANSYS
The present paper discusses the critical prerequisites to improve lightweight design and structural reliability of the crankshaft of the single-cylinder diesel engines. Using ANSYS Workbench finite element analysis software, a three-dimensional solid model of the crankshaft is created and then static finite element analysis is done to determine the stress distribution when subjected to working conditions under real-life conditions. As shown by the findings, the highest value of the equivalent stress of the original crankshaft is 100.16 MPa and the least value of the safety factor is only 2.49. Moreover, there is a high level of stress concentration where the crankshaft meets both the main journal and crank pin, which can cause fatigue failure after many operating hours and negatively impact the lifespan of the diesel engine. These problems are solved with a specific optimization strategy, taking into account the features of stress distribution. Stress concentration regions are relieved using transition fillets to reduce local stress fluctuations. Also, the stress relief slots are provided at the crank arm to distribute the concentrated stress. At the same time, the diameter of the crank pin and main journal was optimized to make light weight at the cost of structural integrity. After optimization, the static finite element analysis was carried out to confirm the outcomes. It was found that the maximum equivalent stress of the crankshaft has been minimized to 87.713 MPa and the smallest safety factor was raised to 2.85, which greatly improved the reliability of structures. Simultaneously, the total mass of the crankshaft was decreased by 9.3% thus accomplishing the aim of light weighting. This study successfully resolves the trade-off between lightweight design and reliability of the crankshaft of the single-cylinder diesel engine by combining finite element analysis with structural optimization. The suggested optimization scheme is scientifically justified and feasible, and can be used as a dependable engineering guide to the best design of a crankshaft of a single-cylinder diesel engine, and it can be regarded as very valuable to improve the performance of diesel engines in general.
Crankshaft; Finite Element; Optimal Design; Statics; Light Weighting.
Review on the Current Situation and Shortcoming Remediation Strategies of Urban Excess Rainwater Storage and Drainage System Construction
Under the background of global climate change, extreme rainfall occurs frequently. Coupled with the increase in land hardening rate during urbanization, the problem of urban waterlogging has become increasingly prominent, seriously threatening urban safety and residents' lives. Constructing an efficient urban excess rainwater storage and drainage system is the key to preventing waterlogging and implementing water safety policies, and conducting relevant research has important theoretical and practical significance. Taking the current situation and shortcoming remediation strategies of urban excess rainwater storage and drainage system construction as the research theme, this paper adopts a variety of research methods suitable for review papers to ensure the rigor of the research process and the practicality of the conclusions: through the literature research method, systematically retrieve relevant domestic and foreign journal papers and policy norms, comprehensively sort out the research context and existing deficiencies of urban excess rainwater storage and drainage technologies, shortcoming identification and remediation strategies; use the inductive and deductive method to summarize the core laws of existing research and derive an adaptive research idea combined with the research focus of this paper; use the comparative research method to compare the applicability and limitations of different storage and drainage technologies and shortcoming remediation strategies, and learn from mature research experience; supplemented by the normative analysis method to conform to relevant national and local policy standards, providing compliance support for the research content. The research finds that the current system in China has formed a full-chain technical layout, but there are still prominent shortcomings in multiple dimensions. The targeted remediation strategies proposed in this paper can effectively make up for the construction shortcomings and improve the system operation efficiency. This research can provide practical reference for the scientific construction and efficient operation and maintenance of urban excess rainwater storage and drainage systems in China, and help the construction of resilient cities.
Urban Waterlogging; Excessive Rainwater; Storage and Drainage Systems; Current Technological Status; Addressing Shortcomings.
A Review and Prospect of Optimal Scheduling for Integrated Energy Systems
Optimal scheduling of integrated energy systems (IESs) is a key technical approach for coordinating energy supply and demand, improving multi-energy utilisation efficiency and supporting low-carbon energy transition. To address the fragmented coverage of existing studies, this paper reviews the research progress of IES optimal scheduling from five aspects: theoretical foundations and modelling frameworks, optimisation objectives and constraint systems, core optimisation algorithms, demand response and multi-agent interaction mechanisms, and uncertainty handling methods. The review shows that IES modelling has gradually developed from physical architecture description to energy-hub, microgrid and virtual-power-plant-based aggregation frameworks. Optimisation objectives have evolved from single economic cost minimisation to coordinated economic, environmental and technical performance. Algorithmic research has moved from classical mathematical programming to intelligent optimisation, game-theoretic modelling and data-driven hybrid methods. Integrated demand response and multi-agent coordination have become important sources of operational flexibility, while stochastic optimisation, robust optimisation and distributionally robust optimisation provide complementary tools for handling renewable generation, load, network and market uncertainties. However, current research still faces challenges in dynamic modelling, real-time scheduling, multi-agent benefit coordination, uncertainty modelling efficiency, policy-market coupling and life-cycle optimisation. Future research should further integrate digital twins, blockchain, machine learning and scheduling theory to improve the engineering applicability of IES optimal scheduling.
Integrated Energy System; Optimal Scheduling; Energy Hub; Demand Response; Game Theory; Uncertainty Handling.
Graphene-Based Composite Coatings for Ship Anticorrosion and Antifouling: A Review on Progress and Prospects
The marine environment, on account of its elevated salinity, humidity, and UV radiation, brings about severe corrosion and biofouling to ships and offshore structures. Traditional coatings encounter difficulties in fulfilling the requirements of eco-sustainability, durability, and multifunctional synergy. Graphene, by virtue of its extraordinarily high specific surface area, chemical stability, as well as gas barrier properties, has emerged as a pivotal material for marine protection. The present review carries out a systematic consolidation of the recent advances in graphene-based composite coatings for ship anticorrosion and antifouling. It provides an elaboration on the “labyrinth effect” barrier mechanism of graphene and its integration with low-surface-energy components, for instance, FOTS and LDH. The key bottlenecks-namely functional isolation, weak interfacial adhesion, and elevated scaling costs-are subjected to a critical examination. The potential of a gradient functional design that incorporates an anticorrosion base combined with an antifouling top layer for integrated synergistic protection is explored, and a performance evaluation framework that encompasses impedance, contact angle, and biofouling attachment is put forward. Future directions are outlined, covering interfacial reinforcement, gradient synergy optimization, cost-effective scalable processes, as well as standardized evaluation criteria, thereby offering insights for engineering applications.
Graphene-Based Composite Coating; Ship Anticorrosion; Ship Antifouling; Integrated Synergistic Design; Interfacial Reinforcement.
YOLO-LMC: An Enhanced Framework for Robust Object Detection
Object detection in hazy scenes holds significant real-world implications, particularly in areas such as intelligent transportation and environmental monitoring. However, image quality degradation caused by haze inherently weakens the feature extraction capabilities of neural network models, leading to reduced accuracy. To address this challenge, this paper proposes YOLO-LMC (YOLO with Latent-space Metric Constraints), a novel architecture that integrates metric learning within the latent space optimization of object detection. Specifically, a positive sample assignment strategy is designed to filter high-confidence features within the latent space. This strategy, coupled with a cosine distance metric loss function based on class centers, effectively compels intra-class samples to form compact distributions in the latent space while ensuring distinct inter-class separability. Experimen-tal validation on the Foggy-Cityscapes dataset demonstrates that the proposed method significantly outperforms other object detection enhancement approaches, achieving an impressive at least 8.6% improvement in mAP.
Hazy Scenes; Object Detection; YOLO-LMC; YOLO-v8; Latent Space Metric Learning; Positive Sample Assignment.
Low-Altitude UAVs and Urban Rail Transit Join Hands to Solve the Last-Mile Problem in Urban Logistics Distribution
Taking Tianjin Metro Line 2 as an example, this paper explores an innovative model for low-altitude UAVs and urban rail transit to collaboratively address the "last-mile" issue in urban terminal logistics distribution. The study proposes the "intelligent rail-UAV collaborative distribution" model, with innovations including: revealing the temporal and spatial complementarity between the "off-peak freight periods" of rail transit and the "point-to-point direct delivery" of UAVs; constructing a network architecture of "suburban distribution center - rail transit station - UAV site - community station"; and designing a joint transportation process: goods are transported to depots (such as Haojixing Logistics Park) via the outer ring road, packaged and then delivered to urban district stations by rail transit, and finally distributed to community stations by UAVs. The temporal-spatial relay model utilizes off-peak hours, non-operating periods, and peak-shifting with passengers to build a three-dimensional network encompassing underground (rail transit), ground (external transportation), and low-altitude (UAVs) layers. For site selection calculation, Tianjin Metro Line 2 is taken as a case, and initial operating stations are determined based on calculated scores, with relevant operational ideas proposed.
Low-altitude; Rail Transit; Collaborative Distribution; Last-Mile.
Design and Simulation of Mechatronic System for Additive Manufacturing of Recyclable Nylon
This paper focuses on additive manufacturing of recyclable nylon and designs a mechatronic system. In terms of mechanical transmission, high-precision screws and linear guides are selected, combined with precision motor drives to ensure that the print head moves accurately in the X, Y, and Z axes, with a positioning accuracy of ±0.05mm. The electrical control is based on PLC, and the motor parameters are adjusted in real time based on sensor feedback. The multi-sensor fusion detection system uses the Kalman filter algorithm to integrate temperature, pressure, displacement and other data, and the data accuracy is improved by 20%. The adaptive path planning algorithm optimizes the path in real time based on the material circulation state, shortens the printing path length by 15%, and improves the uniformity of material deposition by 18%. Through the hardware-in-the-loop simulation experimental platform test, the material recovery efficiency of the new algorithm is 25% higher than that of the traditional algorithm, reaching 85%. The printing accuracy test shows that the dimensional accuracy error is controlled at ±0.1mm, and the shape accuracy deviation is reduced by 22%. In the mechanical properties test, the tensile strength is increased by 12% and the bending strength is increased by 10%. The experimental data fully verified the efficiency and superiority of the system and algorithm in the additive manufacturing of recyclable nylon.
Recyclable Nylon; Additive Manufacturing; Mechatronics; Dynamic Adaptive Path Planning Algorithm; Experimental Verification.
A Review of Low-Temperature Heating Technologies for Lithium-Ion Batteries in New Energy Vehicles
With prominent features such as high specific power, low self-discharge rate, high energy density, and long cycle life, lithium-ion batteries have become the core energy storage components supporting the operation of power systems in new energy vehicles. However, in environments with low temperatures, this leads to a notable decrease in maximum power output and energy availability, and it also readily initiates lithium plating on the negative electrode during such charging, drastically reducing the battery's capacity retention and lifespan. Consequently, the effective preheating of lithium-ion batteries in environments with low temperatures has emerged as a key technical aid for the consistent and dependable functioning of new energy vehicles in colder areas. This paper systematically sorts out the low-temperature heating technology of lithium-ion batteries and analyzes the applicable scenarios and limitations of various technologies. In closing, this study systematically delineates the pressing technical bottlenecks demanding immediate breakthroughs within the domain of low-temperature heating technologies for lithium-ion batteries, and presents an outlook on their future evolution pathways and practical application prospects.
New Energy Vehicles; Lithium-ion Batteries; Low-temperature Heating; External Heating; Internal Heating; Thermal Management System.
Distribution Network Reconfiguration with Multi-Objective Optimization of Distributed Generation based on Chance Constrained Programming
For distribution network with distributed generation, reducing the network loss has always been the focus of research. With increasing proportion of distributed generation in the distribution network, how to improve the power consumption capacity of the distribution network which consider the randomness of distributed generation is increasingly concerned. Firstly, A multi-objective optimization model for distribution network reconfiguration based on maximum consumption of distributed generation and minimum network loss is established in this paper, then, uncertainty of photovoltaic and wind power output are handled by chance-constrained programming model. Subsequently, an improved NSGA-II algorithm is proposed to solve the model which combined with a global Pareto set maintainance strategy. Finally, Taking IEEE 33-node system as an example to compare and analyze multi-objective and multi-scenario optimization. The results show that the model built in this paper can effectively improve the ability of consumption of distributed generation while reducing network losses.
Distribution Network Reconfiguration; Distributed Generation; Chance-Constrained Programming; NSGA-II.
A Review of Research on Electromagnetic Suspension Technology for New Energy Vehicles
Driven by the global "double carbon" goal and the transformation of the automobile industry towards electrification and intelligence, the chassis system of new energy vehicles has changed from achieving a "balance of handling smoothness and stability" to meeting the needs of "good driving performance, intelligence, and high energy utilization". Relying on its core advantages such as fast response speed, wide adjustable damping range, and high energy recovery efficiency, electromagnetic suspension has become a key technology to resolve the contradiction between long endurance and high performance of new energy vehicles. This paper conducts a systematic review of the domestic and foreign research progress of electromagnetic suspension technology for new energy vehicles, explores its structural types, performance optimization and control strategies, and quantitatively analyzes the impact of structural characteristics on the transmission efficiency and spatial compatibility of different topological configurations; analyzes the key approaches to performance optimization from the three dimensions of electromagnetic characteristics, mechanical characteristics, and thermal characteristics; and compares the control effects and engineering applicability of classic control, modern control, and intelligent control strategies. Finally, the shortcomings of the current technology are clarified, and the future development of related fields is prospected, with a view to providing reference for the technological innovation and industrial application of electromagnetic suspension for new energy vehicles.
New Energy Vehicles; Electromagnetic Suspension; Structural Design; Performance Optimization; Energy Recovery.
Research on Remanufacturing Reverse Supply Chain Optimization Strategies Driven by Enhanced Carbon Reduction Capability
The reverse supply chain is a key driver of the circular economy, and its low-carbon operation plays a vital role in achieving the “Dual Carbon” goals. To address this issue, this study takes the remanufacturing rate ( ) as a core variable, constructs a two-tier remanufacturing reverse supply chain system dynamics model. The model analyzes the impact mechanism of on the carbon emissions of supply chain members. By enhancing carbon emission reduction capability, it investigates the phased characteristics of carbon reduction investment strategies to optimize the low-carbon operation of the reverse supply chain. Built on the Vensim platform, the model with carbon emission features from processes including treatment, disassembly, retreatment, and remanufacturing. Simulation results reveal that collector' carbon emissions decline as grows, while remanufacturer' emissions peak at moderate levels. When carbon reduction investments are introduced, the optimal strategies of the collector and the remanufacturer present phased characteristics with distinct critical thresholds. The study offers theoretical and quantitative support for corporate carbon reduction decisions and differentiated policy-making in reverse supply chains.
Reverse Supply Chain; Carbon Emission; System Dynamics; Remanufacturing Rate; Carbon Emission Reductionintroduction.
A Theoretical Framework for High-Precision and Simultaneous Localization and Mapping Through Multi-Sensor Fusion
Simultaneous Localization and Mapping (SLAM) always contains a core challenge for autonomous systems, that is, single-sensor architectures are often not enough in complex real-world environments. We propose a theoretical framework that combines stereo vision, LiDAR, IMU, and GPS, achieving high precision and robustness by adding their complementary strengths. The framework systematically addresses sensor fusion, state estimation, loop closure, and map representation, and also lays out a perfect experimental blueprint. The challenging aim is to orient SLAM research toward practical autonomy, with a focus on robustness, accuracy, and computational efficiency.
SLAM; Multi-Sensor Fusion; Graph Optimization; State Estimation; Robust Perception; Sensor Calibration; UAV.
Intelligent Transformation and Industrial Application of Motor Rotor Magnet Insertion Equipment in the Context of High-End Manufacturing
Magnet steel assembly of motor rotor is a key process in the manufacture of permanent magnet motor. Its slot posture, assembly position and compaction state are related to the machining organization and quality control of the subsequent rotor assembly. Traditional magnet insertion equipment relies on manual operation, single serial and decentralized setting, which is easily disturbed by personnel skills, magnet steel characteristics and model change, and it is difficult to meet the requirements of high-end manufacturing for stability, coordinated beat and data traceability. In this paper, aiming at the magnet insertion equipment of motor rotor, combined with the functional relationship of its core mechanism, a modular intelligent transformation scheme is proposed. The research focuses on equipment layout, material grabbing, station interlocking and data management, and forms the automatic operation logic driven by process state. This scheme retains the necessary manual operation links, and hands over the highly repetitive and strict positioning procedures to the automatic mechanism for execution, which provides a reference for upgrading the existing motor assembly equipment.
High-end Manufacturing; Motor Rotor; Magnet Steel Insertion; Intelligent Transformation; Industrial Robot.