Journal of Electronic Research and Application

Design and Impact Resistance Analysis of Express Cushioning Materials Based on Biomimetic Gradient Structure

2026-08-13T17:27:43+08:00

With the rapid development of the logistics industry, the contradiction between green packaging and cargo safety has become increasingly prominent. Inspired by the lightweight, high-strength, and graded energy-absorbing microstructure of pomelo peel, this study proposes a novel biomimetic gradient porous cushioning structure. Using the ANSYS Explicit Dynamics module under a constant velocity crushing condition of 4.4 m/s, the impact resistance of three topologies, namely uniform circular holes (U-C), gradient circular holes (G-C), and gradient square holes (G-S), is compared. The simulation results indicate that, compared with the conventional uniform structure, the biomimetic gradient design successfully induces a controllable deformation mode characterized by layer‑by‑layer collapse, effectively reducing the initial impact peak. Among the three structures, G-C exhibits the best overall performance. Its peak contact reaction force is reduced by 16.2% compared with that of the uniform structure, and it avoids the mechanical instability due to stress concentration that occurs in the square-hole structure. Cross-checking the three simulation reports further indicates that the foam masses of the three models are all about 8.76g with only negligible differences. Therefore, the advantage of G-C should be interpreted as better overall cushioning performance under nearly equal-mass conditions, rather than as a direct proof of significantly reduced mass or the highest specific energy absorption. The study demonstrates that the biomimetic gradient circular hole structure has clear potential for impact protection, structural stability, and engineering feasibility in express packaging design.

Research Progress on Liquid Explosive Dispersion

2026-08-14T17:55:33+08:00

Liquid explosive dispersal refers to the process in which the instantaneous high pressure generated by explosive detonation drives the liquid within the device. This paper reviews domestic and international research on liquid explosive dispersal, categorizing it into core directions including dispersal mechanism, influencing factors, and numerical simulation, and systematically summarizes the research progress of key parameters during the liquid explosive dispersal process.

Design of Optimized Recognition Algorithm for Degraded Facial Images in Wireless Channels

2026-08-13T17:27:48+08:00

The Design of the wireless channel-degraded face image optimization recognition algorithm aims to solve the problem of reduced image quality due to wireless transmission and thus reduce the drop in recognition accuracy. A new optimization recognition algorithm has been put forward, and at the same time, a way to preprocess the degraded image, enhance its features, and improve the clarity of the image has also been introduced. Many attributes and a combination of local and global features will be employed to increase the accuracy and robustness of the recognition. Based on the experiment, it can be seen that this algorithm has improved the recognition rate of all kinds of degraded face images and has good application prospects; thus, it offers a new solution for face image recognition in wireless communication.

A Study on the Enhancement of PM2.5 Air Purification Capability in Cyclone Separators with Curved Structures Based on CFD Simulation

2026-08-13T17:27:45+08:00

Driven by the demand for purifying indoor air from particulate matter, this study has carried out systematic numerical research on the effect of cyclone separator geometry on the performance of PM_2.5 filtration. A comprehensive CFD analysis system is constructed based on three cone segments generatrices: straight, concave, and convex. The continuous phase in the simulation adopts the Reynolds Stress Model (RSM) due to its high ability to predict the strong anisotropic turbulent flow inside the cyclone separator. The particle phase in the present study is simulated through the Discrete Phase Model (DPM) by the Lagrangian method and considers the effects of drag force, centrifugal force, and turbulence diffusion to predict the migration and deposition process of particles with various diameters. From the results, the convex generatrix shows great superiority in capturing fine particles, obtaining a high efficiency of PM_2.5 separation up to 82.4% and a small cut-off diameter down to 2.1 μm. In comparison, the concave generatrix outperforms in reducing the pressure drop and optimizing the energy efficiency ratio, while the straight generatrix ranks in between. The results show that the reasonable control of geometric curvature can significantly improve the flow field stability and particle distribution characteristics.

A Review of Reactive Power Optimization in Distribution Networks with High Penetration of Renewable Energy

2026-08-13T17:27:39+08:00

The global energy mix is undergoing an accelerated transition towards cleaner, lower-carbon sources. As a result, the large-scale integration of a high proportion of renewable energy into distribution networks is an irreversible trend. However, since the output of renewable energy sources is highly random, intermittent, and fluctuating, and given that the high r/x parameter characteristics of distribution grids result in a pronounced active-reactive power coupling, the traditional unidirectional voltage regulation mode in distribution grids is unable to effectively address issues such as bidirectional power flows and frequent voltage overshoots. Consequently, reactive power and voltage control face significant challenges. To this end, this paper provides a systematic and logically coherent review of the problem of reactive power optimization in distribution networks with a high proportion of renewable energy. First, we clarify the mechanisms by which the grid integration of renewable energy sources affects distribution network voltages. This study then systematically summarizes methods for active power regulation, reactive power compensation, tap-changer voltage regulation, and multi-device coordinated control. Subsequently, this study proposes an approach to multi-timescale, hierarchical, and zoned modeling that coordinates active and reactive power. This study then conducted a comparative analysis of uncertainty management techniques, including stochastic optimization, robust optimization, and fuzzy theory. Finally, this study summarizes the application characteristics of traditional mathematical methods, intelligent algorithms, and data-driven methods. This naturally and appropriately leads to the conclusion that the coordination of generation, grid, load and storage, combined with multi-timescale optimization, represents the current mainstream control framework, and that data-driven methods hold immense potential for application. However, it also objectively and cautiously highlights various issues in existing research, including uncertainties that are difficult to address, multi-scale collaborative complexity, communication and privacy constraints, and a lack of interpretability in AI models. Consequently, the future direction of development should focus on collaboration, intelligence and decentralization, whilst the refinement of relevant technologies will directly and effectively underpin the safe and efficient operation of distribution networks with a high proportion of renewable energy.

Beyond Direct AI Assistance: The Mediating Role of AI Crafting in Converting Employee–AI Collaboration into Incremental and Radical Creativity

2026-08-13T17:27:40+08:00

Artificial intelligence is becoming a routine partner in enterprise work, but its creative value depends on how employees reconfigure their work around AI. Using 138 valid survey responses from Chinese employees with AI-use experience, this study examines whether employee-AI collaboration promotes incremental and radical creativity through AI crafting. Results show that employee-AI collaboration significantly predicts AI crafting and both creativity outcomes. AI crafting further mediates these relationships. The findings highlight AI crafting as a behavioral mechanism linking human-AI collaboration with dual creativity.

Optimization of Artificial Immune Algorithms and Research on Key Issues

2026-08-13T17:27:40+08:00

The artificial immune algorithm is an intelligent optimization algorithm derived from the working mechanism of biological immune systems. It simulates immune response processes including biological antigen recognition, antibody generation, clonal selection, immune memory, and immune suppression, and searches for optimal solutions through iterative population evolution. In recent years, artificial immune algorithms have been gradually applied in various fields such as industrial optimization, artificial intelligence, smart cities, and automatic control, showing favorable application value in scenarios including multi-objective constrained optimization, dynamic system scheduling, fault feature identification, and adaptive parameter tuning. However, with the continuous increase in the complexity of application scenarios, the inherent defects of classic artificial immune algorithms have become prominent. On this basis, based on the basic framework of artificial immune algorithms, this paper comprehensively analyzes the core key problems in algorithm operation and constructs a multi-dimensional and highly adaptive algorithm optimization system, aiming to provide comprehensive support for iterative optimization and scenario-based implementation of artificial immune algorithms.

Design of a High-Voltage Constant-Voltage/Constant-Current Power Supply Based on a PSFB Topology and an Automatic Frequency-Conversion Strategy

2026-08-13T17:27:41+08:00

To meet the requirements for wide-range output, current-limit protection, and stable closed-loop control in high-voltage capacitor charging, laboratory high-voltage sources, and pulse-power preamplifier systems, this paper presents a high-voltage constant-voltage/constant-current power supply based on a phase-shifted full-bridge (PSFB) topology. The supply operates from a typical 24 V low-voltage DC input and uses a 1:100 high-frequency transformer for isolated step-up conversion. Its output control range is 0–2200 V and 0–200 mA, with a rated power limit of 400 W. The controller uses an STM32G474CBT6, which generates four complementary phase-shifted gate-drive signals through the HRTIM module and samples secondary-side voltage, secondary-side current, primary-side current, auxiliary-supply status, and temperature feedback with an ADC synchronized to the switching cycle. The control algorithm calculates the constant-voltage, constant-current, and constant-power PI loops in parallel and selects the actual phase-shift duty cycle through minimum-duty-cycle arbitration. To reduce the efficiency fluctuation of fixed-frequency PSFB operation at very low and very high duty cycles, an automatic frequency-conversion strategy is introduced. Frequency increase or reduction within 11–45 kHz is selected according to the duty-cycle state, while score-counter hysteresis, a lockout window, and feedforward duty-cycle correction reduce the disturbance caused by frequency changes. Simulation and experimental results show that the prototype provides stable high-voltage output, constant-current charging, constant-voltage load operation, and ZVS turn-on, confirming its practical engineering value.

Research on the Construction of a Digital Credit Bank System for Vocational Education Students Based on Blockchain Technology

2026-08-13T17:27:41+08:00

Against the backdrop of building a country strong in education, promoting high-quality development of vocational education stands as a core task. The credit bank serves as a critical institutional carrier linking academic education, non-academic training, and lifelong learning. China has completed the construction of basic platforms and pilot promotion for vocational education credits, yet practical operation is still plagued by inconsistent credit recognition standards, security risks of student information and credit data, and cumbersome cross-institutional credit mutual recognition procedures. Featuring distributed ledgers, cryptographic protection, consensus verification, and automatic execution via smart contracts, blockchain technology can target the operational drawbacks of traditional credit banks. On this basis, grounded in the national strategy for digital education development, this paper defines core concepts, sorts out the current status and dilemmas of credit bank construction, and explores the establishment of a blockchain-based digital credit bank system for vocational education students, aiming to provide valuable references for the development of vocational education credit banks.

Post-Grasp Pose Adjustment of a Tendon-Driven Underactuated Robotic Hand Using Finite-Action-Set Receding-Horizon Planning

2026-08-13T17:27:42+08:00

This paper addresses local post-grasp pose adjustment for a tendon-driven underactuated robotic hand. A finite-action-set receding-horizon motor reference planning method is proposed, in which the continuous motor reference increment is discretized into representative actions and an action-effect table predicts local object pose changes. At each decision instant, candidate action sequences are evaluated using pose error, action magnitude, motor limits, grasp margin, and action switching, while only the first action of the optimal sequence is executed. Simulations show that the method generates feasible commands for single-axis and two-dimensional pose adjustment, drives the object pose toward the target, and keeps motor references within the allowable range. Compared with one-step planning, a longer prediction horizon reduces action switching in the two-dimensional coupled task and improves action sequence smoothness.

Research on High-P Precision Match Drilling Method for Reaming Mounting Holes When Replacing Sintering Machine Sprocket Tooth Plates

2026-08-13T17:27:43+08:00

The operational stability and service life of sintering machines are critically dependent on the machining precision of reaming mounting holes in their sprocket tooth plates. To address the limitations of existing match-drilling techniques, this paper proposes a novel high-precision match-drilling method aimed at enhancing assembly accuracy, installation efficiency, and overall operational stability. Through a systematic analysis of current match-drilling processes, this study identifies the alignment accuracy between the reaming holes of the tooth plates and the web plates as the decisive factor in the assembly procedure. To resolve this issue, a custom-designed measuring and positioning tool, in conjunction with an innovative match-drilling workflow, is developed to form a complete reaming scheme. Experimental validation, including positioning tests on multiple tooth plates, confirms the effectiveness and repeatability of the proposed method. The results demonstrate that this approach significantly improves assembly precision and operational stability, reduces installation errors, and lowers both the failure rate and maintenance costs of sintering machines. Beyond its practical contributions, this research enriches the theoretical framework of mechanical processing and assembly, offering robust technical support for on-site applications. Moreover, the standardization of the new match-drilling process provides a comprehensive maintenance solution for routine overhauls of sintering machine sprockets and tooth plates, thereby promoting continuous innovation and advancement in related maintenance strategies.

The Peak Regulation Role and Application Prospects of Pumped Storage in the Construction of a New Power System

2026-08-13T17:27:48+08:00

Against the background of the dual-carbon goals and sustainable development, renewable energy, as a substitute for traditional energy, accounts for an increasing proportion in the new power system. With the advantages of sustainability, low-carbon and environmentally friendly characteristics, it has become an important branch of the new power system. However, new energy power generation has caused a large waste of energy and electricity due to geographical, climatic, demographic, and economic factors. More seriously, extreme changes in climate are extremely detrimental to the stability of the power grid and the safety of generators. Based on domestic and foreign literature, this article reviews the role and application prospects of pumped storage technology in peak regulation in new power systems. Research shows that pumped storage technology can use water, a clean energy source, to store and release the electricity generated by new energy as a “natural battery” in a timely manner, so as to play the role of storing electricity during low-load periods and supplying electricity during peak-load periods. This research can provide theoretical reference for the study of solving the problem of power grid instability in new power systems.

Implementation and Project Management Strategy of Black Start Function in Utility‑Scale Energy Storage Systems

2026-08-14T17:19:17+08:00

As renewable penetration deepens, power system inertia and black‑start capability decline, raising concerns about grid resilience. Utility‑scale battery energy storage systems (BESS)with grid‑forming (GFM)inverters offer a promising solution. This paper examines the technical principles, implementation bottlenecks, and project management strategies for deploying black‑start functionality in large BESS. Two critical challenges are identified: (i) dispatch coordination and restoration path planning and (ii) grid‑connection compatibility and seamless mode switching. Drawing on recent demonstration projects, including Mongolia’s 80 MW/200 MWh BESS (2025), China’s Dalian 200 MW/800 MWh station (2023–2024 black‑start trials), and the Qinghai multi‑GFM collaborative test (2026), this paper proposes a dual management framework: (1) a joint‑drill and protocol‑solidification mechanism for dispatch coordination, and (2) a three‑level interface management system with clear delivery standards to resolve integration bottlenecks. The findings offer actionable guidelines for project managers, system integrators, and grid operators worldwide.

Polynomial Mitigation of the Fermionic Sign Problem via Topological Neural Flows and Generalized Complex Manifold Deformations

2026-08-13T17:27:45+08:00

Since the discovery of the sign problem in the 1980s, all unbiased numerical methods have failed to avoid the exponential growth of computational complexity when simulating strongly correlated fermions at finite densities. This paper proves that by analytically continuing the path integral to a continuous complex manifold and transforming it into an unsupervised geometric optimization problem, this exponential wall can be systematically mitigated. We introduce the Topological Neural Flow (TNF) framework, utilizing Equivariant Continuous Normalizing Flows constrained by Cauchy’s integral theorem to dynamically learn a deformation contour that minimizes the imaginary phase variance of the effective action. Focusing on the highly challenging 2D hole-doped repulsive Hubbard model, we demonstrate exponential sign mitigation on lattices up to 10 × 10, reducing the required number of Monte-Carlo samples by up to 8 orders of magnitude. We explicitly map the critical breakdown point of the method at the 12 × 12 scale, establishing a rigorous mathematical and physical foundation for AI-assisted path integral contour deformations.

Simulation Study on the Crashworthiness of a Bridge Crane Anti-Collision Mechanism

2026-08-13T17:27:38+08:00

A bridge-crane trolley may strike the end anti-collision device after overtravel, braking failure, or control delay; therefore, the collision resistance of the device directly affects operational safety. In this study, a shell-based finite-element model of a bridge-crane anti-collision mechanism was developed in HyperMesh, and explicit impact simulations were conducted in LS-DYNA at trolley speeds of 25 and 35 m/min. Each simulation covered 80 ms, and sliding energy, hourglass energy, added mass, stress, and displacement were examined. The sliding- and hourglass-energy ratios remained below 5%, and the added mass stayed below 1% in both cases. At 25 m/min, the maximum von Mises stress was 342.294 MPa, slightly below the 345 MPa yield strength of Q345 steel. At 35 m/min, the maximum stress increased to 429.190 MPa and exceeded the yield strength. These findings provide a basis for strength verification, end-zone speed limitation, and structural improvement of bridge-crane anti-collision mechanisms.

A Risk-Adaptive TOPSIS Method for Electronic Decision Support in Vulnerable-Pedestrian Crossings

2026-08-14T09:52:57+08:00

Electronic decision support for vulnerable-pedestrian crossings requires heterogeneous factors, including crossing intention, individual vulnerability, traffic conditions, and roadside facilities, to be represented on a common scale. Fixed-weight multicriteria ranking cannot adapt its evaluation priorities to changes in scenario risk. This study proposes an electronic decision-support method that combines an intention-probability-driven risk model with risk-adaptive TOPSIS. The model integrates crossing-intention probability, vulnerability coefficient, traffic density, environmental adversity, and facility deficiency. A convex combination of baseline and scenario-dependent exponential weights produces a composite risk score, which continuously interpolates the TOPSIS criterion weights. The method ranks three intervention options and provides traceable intermediate results for human confirmation. In six reproducible simulated scenarios, the proposed method achieved a policy-level consistency rate of 100.0%, exceeding equal-weight and fixed-weight TOPSIS by 66.7 and 83.3 percentage points, respectively. Under ±10% weight perturbations, the mean preferred-option retention rate was 92.3%, and one risk evaluation and ranking required 31.8 ± 0.7 microseconds. The results show that the method adjusts evaluation priorities with scenario risk and generates intervention recommendations consistent with the predefined response level.

Data Privacy and Patient Consent in Smart Hospitals over the Past Decade

2026-08-13T17:27:48+08:00

Over the past decade, the construction of data-driven smart hospitals has profoundly changed the medical service model and has also made data privacy and patient informed consent core ethical and legal issues. This study systematically sorts out the practical evolution of data privacy protection and informed consent in smart hospitals from 2016 to 2026, reveals the structural tension of “advanced technology and lagging system”, and finds that informed consent is falling into the dilemma of scene generalization and formalization, data ownership is still pending in the legal ambiguity zone, and technical governance brings privacy risks while improving efficiency, forming a “double-edged sword” effect. On this basis, the study puts forward that the key to break through the dilemma lies in the transition from “one-time authorization” to “dynamic informed consent” mechanism, the construction of a three-dimensional protection framework of “legal regulation-technical guarantee-collaborative governance”, and the promotion of institutional innovation in data rights confirmation and benefit distribution; only by putting patients at the center of data governance can we maintain the ethical bottom line in the digital transformation of medical care.

Design and Implementation of a Dual-Layer Decoupled Gimbal Electronic Control System for Mobile Robots

2026-08-13T17:27:46+08:00

This paper proposes a dual-layer decoupled gimbal electronic control system for mobile robots. The hardware platform employs the STM32F407IGH6TR microcontroller with a BMI088 IMU and DaMiao J4310 / DJI GM6020 actuators. A three-layer software architecture running under a preemptive real-time kernel maintains a 1 ms attitude estimation loop and 2 ms motion control loops. A velocity coordinate rotation algorithm is derived to eliminate chassis–gimbal directional coupling inherent to the dual-layer Yaw structure. Angle–velocity cascaded PID controllers are implemented for both gimbal layers, incorporating derivative-on-measurement, conditional integration, and velocity feedforward compensation. Experimental results demonstrate that the inner gimbal Yaw step response rise time is approximately 50 ms with steady-state error below 0.3°; feedforward compensation reduces constant-velocity tracking RMS error by approximately 60% compared to pure PID; all control loops meet their timing requirements at a total CPU utilization of approximately 85%.

Artificial Intelligence Technology and Innovation Path of Government Governance Capability

2026-08-13T17:27:38+08:00

Amid the ongoing Fourth Industrial Revolution, artificial intelligence has taken center stage as the driving force behind the modernization of governmental frameworks and administrative capabilities. This study delves into the innovative approaches for weaving AI technologies into the fabric of public administration while confronting the practical hurdles along this transformative journey. To begin with, the examination unpacks the diverse real-world implementations of AI technologies, ranging from streamlined administrative approvals and precision-crafted public policies to automated risk surveillance in society and the strategic optimization of public resource distribution. Moving forward, the research critically assesses the multifaceted obstacles confronting governmental entities in their AI integration endeavors, encompassing inadequate technological infrastructure, persistent data fragmentation, inflexible administrative structures struggling to accommodate intelligent solutions, latent concerns in algorithmic governance and cybersecurity, and the glaring shortage of digital competencies among public sector employees. To surmount these impediments, the paper puts forward a holistic strategic framework: accelerating digital infrastructure development, fostering seamless cross-departmental data collaboration, constructing adaptive governance frameworks, establishing robust legal and ethical guardrails for AI-driven decision-making, and nurturing digitally adept public leadership. Ultimately, this investigation aims to furnish substantive theoretical underpinnings and actionable guidance for the intelligent metamorphosis of contemporary digital governance.

The Application of an Intelligent Automatic Control System for Wastewater Treatment Containers

2026-08-13T17:27:47+08:00

The sewage treatment system is completed by an upper computer, PLC, and an electric control actuator. The carrier is a container, which is flexible. According to the characteristics of decentralized domestic sewage, we intend to make use of our own advantages in container design and manufacturing, and integrate advanced biological sewage treatment technology into intelligent monitoring technology, such as wind, light, electricity, energy-saving storage technology, container modularization technology, mobile integration technology, etc., to realize the technical subversion of the traditional sewage treatment industry, and upgrade the traditional high-energy, large-scale and centralized sewage treatment mode to a low-carbon, intelligent and decentralized micro-ecological water circulation mode. By designing a new system and a new mode of use and service, the environmental protection industry can be greatly upgraded and eventually industrialized.