Applied Sciences

11 pages, 3707 KiB

Open AccessArticle

Infill Pattern and Density of 3D-Printed Insoles Alter Energy and Pressure Distribution in Gait

by Surapong Chatpun, Tulaya Dissaneewate, Atichart Kwanyuang, Muhammad Nouman, Satta Srewaradachpisal and Dejan Movrin

Appl. Sci. 2025, 15(7), 3916; https://doi.org/10.3390/app15073916 (registering DOI) - 2 Apr 2025

Abstract

Diabetic foot ulcer patients are usually unaware of excessive pressure on their feet due to lost pressure sensitivity. Offloading insoles are used to alleviate foot pain. This study investigated the effect of infill pattern and infill density on plantar pressure reduction for 3D-printed [...] Read more.

Diabetic foot ulcer patients are usually unaware of excessive pressure on their feet due to lost pressure sensitivity. Offloading insoles are used to alleviate foot pain. This study investigated the effect of infill pattern and infill density on plantar pressure reduction for 3D-printed insoles while walking. The study involves five infill patterns: grid, honeycomb, triangle, cubic, and gyroid, along with several infill densities ranging from 14% to 20%. The test 3D-printed thermoplastic polyurethane specimens were assessed for mechanical properties to identify suitable infill patterns for creating prototypes of insoles. The results indicated that the honeycomb infill pattern exhibited the highest maximum compression load at 50% compressive strain and has a significant area under the loading-unloading curve, signifying high energy absorption. Conversely, the gyroid infill pattern exhibited the lowest maximum compression load at 50% compressive strain and minimal energy absorption. Both infill patterns with 20% infill density were applied in 3D-printed insoles and tested on the foot plantar pressure of healthy male volunteers during walking. No statistically significant differences in plantar pressure were observed between the two infill patterns compared to walking without insoles. A reduction in plantar pressure at hindfoot was observed when using the insoles, although this change was not statistically significant. Full article

(This article belongs to the Section Biomedical Engineering)

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15 pages, 3386 KiB

Open AccessArticle

Maintenance Method for Rail Corrugation Considering Wheel–Rail Interaction Force

by Jung-Youl Choi, Cheon Man Jeong and Sun-Hee Kim

Appl. Sci. 2025, 15(7), 3915; https://doi.org/10.3390/app15073915 - 2 Apr 2025

Abstract

Rail corrugation causes various problems such as a decrease in ride comfort due to aggravation of train noise and vibration, and an increase in the amount of track component maintenance due to the amplification of the track impact. Most of the preceding research [...] Read more.

Rail corrugation causes various problems such as a decrease in ride comfort due to aggravation of train noise and vibration, and an increase in the amount of track component maintenance due to the amplification of the track impact. Most of the preceding research on rail corrugation has been conducted on the causes and characteristics of rail corrugation, but there are no countermeasures or management plans for existing rail corrugation. In this study, dynamic track response measurement results are analyzed. The dynamic wheel load, rail acceleration, and displacement of the rails and sleepers due to rail grinding were reduced by approximately 48%, 18%, and 12%, respectively. The analysis model was confirmed to be appropriate by comparing the measured and analyzed values of the dynamic wheel load before and after rail grinding in the section where rail corrugation occurred. Additionally, a maintenance method for rail corrugation was proposed considering the wheel–rail interaction force by calculating the appropriate grinding amount (upper and lower limit) for each train speed. Full article

(This article belongs to the Special Issue Advances in Railway Infrastructure Engineering)

23 pages, 1093 KiB

Open AccessArticle

Valorization of Tomato By-Products: Advanced Extraction Methods and Bioprocessing of Bioactive Compounds and Functional Products

by Christina Drosou, Konstantina Theodora Laina, Maria Dimoula, Panagiota Maria Eleni, Christos J. Boukouvalas, Evangelos Topakas and Magdalini Krokida

Appl. Sci. 2025, 15(7), 3914; https://doi.org/10.3390/app15073914 - 2 Apr 2025

Abstract

This study investigates the valorization of tomato by-products—peels, seeds, and juice—through innovative extraction and bioprocessing techniques. Lycopene recovery from tomato peels was optimized using ultrasound- and microwave-assisted extraction (UAE-MAE) with ethyl lactate as the solvent. The optimal conditions (0.03 g/mL, 500 W microwave [...] Read more.

This study investigates the valorization of tomato by-products—peels, seeds, and juice—through innovative extraction and bioprocessing techniques. Lycopene recovery from tomato peels was optimized using ultrasound- and microwave-assisted extraction (UAE-MAE) with ethyl lactate as the solvent. The optimal conditions (0.03 g/mL, 500 W microwave power, 600 W ultrasound power) yielded a lycopene content of 37.08 mg/100 g of peels and an extraction yield (EY) of 91.20%. For tomato seeds, oil extraction methods, including conventional stirring, UAE-MAE, Soxhlet extraction, and pressurized liquid extraction (PLE), were evaluated. Conventional stirring achieved the highest oil yield (19.66%), followed closely by UAE-MAE (19.53%). However, PLE produced the highest lycopene content (44.0 mg/100 g oil) and significant levels of linoleic acid (544.7 mg/g oil), though Soxhlet extraction yielded slightly more (608.9 mg/g oil). Tomato juice was processed into high-nutritional value vinegar via a two-stage fermentation process. The final product had 5.42% acidity, a pH of 2.85, and retained a high lycopene content (9.19 mg/100 g). This study underscores the potential of innovative extraction and bioprocessing strategies for the valorization of tomato by-products, promoting waste reduction and the development of high-value functional products in alignment with principles of the circular bioeconomy. Full article

(This article belongs to the Special Issue Recent Advances in the Improvement of Food Quality and Safety)

18 pages, 5579 KiB

Open AccessArticle

Optimization of Sensor Targeting Configuration for Intelligent Tire Force Estimation Based on Global Sensitivity Analysis and RBF Neural Networks

by Yu Zhang, Guolin Wang, Haichao Zhou, Jintao Zhang, Xiangliang Li and Xin Wang

Appl. Sci. 2025, 15(7), 3913; https://doi.org/10.3390/app15073913 - 2 Apr 2025

Abstract

Tire force is a critical state parameter for vehicle dynamics control systems during vehicle operation. Compared with tire force estimation methods relying on vehicle dynamics or tire models, intelligent tire technology can provide real-time feedback regarding tire–road interactions to the vehicle control system. [...] Read more.

Tire force is a critical state parameter for vehicle dynamics control systems during vehicle operation. Compared with tire force estimation methods relying on vehicle dynamics or tire models, intelligent tire technology can provide real-time feedback regarding tire–road interactions to the vehicle control system. To address the demand for accurate tire force prediction in active safety control systems under various operating conditions, this paper proposes an intelligent tire force estimation method, integrating sensor-measured dynamic response parameters and machine learning techniques. A 205/55 R16 radial tire was selected as the research object, and a finite element model was established using the parameterized modeling approach with the ABAQUS finite element simulation software. The validity of the finite element model was verified through indoor static contact and stiffness tests. To investigate the sensitive response areas and variables associated with tire force, the ground deformation area of the inner liner was refined along the transverse and circumferential directions. Variance-based global sensitivity analysis combined with dimensional reduction methods was used to evaluate the sensitivity of acceleration, strain, and displacement responses to variations in longitudinal and lateral forces. Based on the results of the global sensitivity analysis, the influence of longitudinal and lateral forces on sensitive response variables in their respective sensitive response areas was examined, and characteristic values of the corresponding response signal curves were analyzed and extracted. Three intelligent tire force estimation models with different sensor-targeting configurations were established using radial basis function (RBF) neural networks. The mean relative error (MRE) of intelligent tire force estimation for these models remained within 10%, with Model 3 demonstrating an MRE of less than 2% and estimation errors of 1.42% and 1.10% for longitudinal and lateral forces, respectively, indicating strong generalization performance. The results show that tire forces exhibit high sensitivity to acceleration and displacement responses in the crown and sidewall areas, providing methodological guidance for the targeted sensor configuration in intelligent tires. The intelligent tire force estimation method based on the RBF neural network effectively achieves accurate estimation, laying a theoretical foundation for the advancement of vehicle intelligence and technological innovation. Full article

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32 pages, 3621 KiB

Open AccessArticle

Methodological Validation of Machine Learning Models for Non-Technical Loss Detection in Electric Power Systems: A Case Study in an Ecuadorian Electricity Distributor

by Carlos Arias-Marín, Antonio Barragán-Escandón, Marco Toledo-Orozco and Xavier Serrano-Guerrero

Appl. Sci. 2025, 15(7), 3912; https://doi.org/10.3390/app15073912 - 2 Apr 2025

Abstract

Detecting fraudulent behaviors in electricity consumption is a significant challenge for electric utility companies due to the lack of information and the complexity of both constructing patterns and distinguishing between regular and fraudulent consumers. This study proposes a methodology based on data analytics [...] Read more.

Detecting fraudulent behaviors in electricity consumption is a significant challenge for electric utility companies due to the lack of information and the complexity of both constructing patterns and distinguishing between regular and fraudulent consumers. This study proposes a methodology based on data analytics that, through the processing of information, generates lists of suspicious metering systems for fraud. The database provided by the electrical distribution company contains 266,298 records, of which 15,013 have observations for possible frauds. One of the challenges lies in managing the different variables in the training data and choosing appropriate evaluation metrics. To address this, a balanced database of 27,374 records was used, with an equitable division between fraud and non-fraud cases. The features used in the identification and construction of patterns for non-technical losses were crucial, although additional techniques could be applied to determine the most relevant variables. Following the process, several popular classification models were trained. Hyperparameter optimization was performed by using grid search, and the models were validated by using cross-validation techniques, finding that the ensemble methods Categorical Boosting (CGB), Light Gradient Boosting Machine (LGB) and Extreme Gradient Boosting (EGB) are the most suitable for identifying losses, achieving high performance and reasonable computational cost. The best performance was compared by measuring accuracy (Acc) and F1 score, which allows for the evaluation of various techniques and is a combination of two metrics: detection rate and precision. Although CGB achieved the best performance in terms of accuracy (Acc = 0.897) and F1 (0.894), it was slower than LGB, so it is considered the ideal classifier for the data provided by the electrical distribution company. This research study highlights the importance of the techniques used for fraud detection in electricity metering systems, although the results may vary depending on the characteristics of the training, the number of variables, and the available hardware resources. Full article

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14 pages, 1090 KiB

Open AccessArticle

Study on the Design of the Gear Pair and Flow Characteristics of Circular-Arc Gear Pumps

by Geqiang Li, Yunda Liu, Weifeng Han, Donglin Li, Shuai Wang and Zhenchao Hao

Appl. Sci. 2025, 15(7), 3911; https://doi.org/10.3390/app15073911 - 2 Apr 2025

Abstract

Compared with traditional gear pumps, circular-arc gear pumps have the advantages of silence and small flow pulsation, but the theory of design is underdeveloped. This paper presents a design method for gear pumps with circular-arc helical gear pairs, and the influence mechanism of [...] Read more.

Compared with traditional gear pumps, circular-arc gear pumps have the advantages of silence and small flow pulsation, but the theory of design is underdeveloped. This paper presents a design method for gear pumps with circular-arc helical gear pairs, and the influence mechanism of flow characteristics is studied. First, a model of the gear pair is established, and a design method for the gear pair is proposed. Second, a CFD model is demonstrated, and the influences of the tooth profile parameters (tooth number, modules, and pressure angle) on the flow characteristics are analyzed. Finally, the significance of the influencing factors is analyzed. The results show that when the stagger angle of the two ends of the arc helical gear pair is an integral multiple of π/Z, there is no flow pulsation, and there is little noise. The tooth number and modules are positively correlated with the flow rate and flow pulsation, among which the modules have the most significant influence. The flow rate of the gear pump increases by 4–5 L/min for every 0.2 increase in the modules. The pressure angle and flow rate show a negative correlation trend, but the influence is insignificant. The flow rate is less than 1 L/min for every 2° change in the pressure angle. This paper provides a theoretical basis and reference value for the gear pair design of gear pumps. Full article

(This article belongs to the Section Mechanical Engineering)

16 pages, 5033 KiB

Open AccessArticle

GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8

by Qiang Hu and Yunhua Zhang

Appl. Sci. 2025, 15(7), 3910; https://doi.org/10.3390/app15073910 - 2 Apr 2025

Abstract

In view of the issues of high complexity, significant computational resource consumption, and slow inference speed in the detection algorithm for grape leaf diseases, this paper proposes GCS-YOLO, a lightweight detection algorithm based on an improved YOLOv8. The lightweight feature extraction module C2f-GR [...] Read more.

In view of the issues of high complexity, significant computational resource consumption, and slow inference speed in the detection algorithm for grape leaf diseases, this paper proposes GCS-YOLO, a lightweight detection algorithm based on an improved YOLOv8. The lightweight feature extraction module C2f-GR is proposed to replace the C2f module. C2f-GR achieves lightweight design while effectively capturing detailed features of multi-scale information by replacing partial convolutions in C2f with Ghost Modules. Additionally, RepConv is incorporated into C2f-GR to avoid the complexity of multi-branch structures and enhance gradient flow capability. The CBAM attention mechanism is added to the model to improve the extraction of subtle features of lesions in complex environments. Cross-scale shared convolution parameters and separated batch normalization techniques are used to optimize the detection head, achieving a lightweight design and improving the detection efficiency of the algorithm. Experimental results indicate that the improved model has a number of parameters and computational load of 1.63 M and 4.5 G, respectively, with a mean average precision (mAP@0.5) of 96.2% and a model size of only 3.5 MB. The number of parameters and computational load of the improved model have been reduced by 45.7% and 45.1%, respectively, compared to the baseline model, while the mAP has increased by 1.3%. This lightweight design not only ensures detection accuracy to meet the real-time detection needs of grape leaf diseases but is also more suitable for edge deployment, demonstrating broad application prospects. Full article

(This article belongs to the Section Agricultural Science and Technology)

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20 pages, 3362 KiB

Open AccessArticle

Research on Active Anti-Slip Control of High-Speed Trains Based on High-Order Sliding Mode

by Song Wang, Buzou Zhang, Yixuan Wang and Shuai Cao

Appl. Sci. 2025, 15(7), 3909; https://doi.org/10.3390/app15073909 - 2 Apr 2025

Abstract

This paper addresses the issue of wheelset slip in trains caused by low-adhesion track surfaces and proposes an active anti-slip tracking control strategy. Considering the wide operational range of trains and the complex adhesion conditions between wheels and rails, a comprehensive model of [...] Read more.

This paper addresses the issue of wheelset slip in trains caused by low-adhesion track surfaces and proposes an active anti-slip tracking control strategy. Considering the wide operational range of trains and the complex adhesion conditions between wheels and rails, a comprehensive model of the train, incorporating adhesion effects, is developed and then transformed into a mathematical model with perturbations. To tackle the slip phenomenon on low-adhesion track surfaces, a robust adhesion observer with high dynamic accuracy is designed. Building on this, an active anti-slip strategy is proposed to ensure that the control command does not exceed the maximum traction force available from the track surface. To further enhance controller performance, higher-order sliding mode control is integrated with a saturation compensation law. Finally, a Hardware-in-the-Loop (HIL) platform is constructed using a Digital Signal Processor (DSP) controller and a Modular Test (MT) PXI real-time simulator. The simulator loads the adhesion model, while the DSP controller executes the designed anti-slip control algorithm. Experimental results demonstrate that the proposed controller effectively prevents wheelset slip under low-adhesion conditions and significantly reduces tracking errors along the target speed-displacement curve. Full article

23 pages, 1976 KiB

Open AccessArticle

Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting

by Yumeng Zhu and Qi Zhu

Appl. Sci. 2025, 15(7), 3908; https://doi.org/10.3390/app15073908 - 2 Apr 2025

Abstract

The proliferation of mobile terminal applications and the increasing energy consumption of chips have raised concerns about insufficient power in mobile user terminals. In response to this issue, this paper proposes a joint optimization algorithm for UAV-assisted caching and charging based on non-orthogonal [...] Read more.

The proliferation of mobile terminal applications and the increasing energy consumption of chips have raised concerns about insufficient power in mobile user terminals. In response to this issue, this paper proposes a joint optimization algorithm for UAV-assisted caching and charging based on non-orthogonal multiple access (NOMA) within the context of mobile edge caching scenarios. The proposed algorithm considers the revenue generated from UAVs providing caching and charging services to users, as well as the cost associated with leasing cache files and the UAV energy consumption. The optimization problem aimed at maximizing UAV utility is established under constraints related to power and cache capacity. To address this mixed-integer programming problem, we divided it into two parts. The first part uses the Stackelberg–Bertrand game to optimize file pricing and the UAV cache strategy. In the second part, the block coordinate descent (BCD) method is used to optimize the UAV transmission power distribution, positioning, and user pairing. The joint optimization problem is divided into three subproblems, which use the Lagrange multiplier method, a simulated annealing algorithm, and a particle swarm optimization algorithm. Simulation results demonstrate that the proposed algorithm effectively reduces user transmission delay while also improving overall revenue generated by UAVs. Full article

(This article belongs to the Special Issue Wireless Networking: Application and Development)

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17 pages, 1713 KiB

Open AccessArticle

A Quantitative-Qualitative Classification for Igneous Building Stones Based on Brazilian Tensile Strength: Application to the Stone Durability

by Amin Jamshidi and Luís Sousa

Appl. Sci. 2025, 15(7), 3907; https://doi.org/10.3390/app15073907 - 2 Apr 2025

Abstract

Building stones are among the most widely used construction materials in building. The Brazilian tensile strength (BTS) is a key indicator for evaluating the durability of building stone against deterioration processes. To date, no quantitative–qualitative classification for the BTS of building stones has [...] Read more.

Building stones are among the most widely used construction materials in building. The Brazilian tensile strength (BTS) is a key indicator for evaluating the durability of building stone against deterioration processes. To date, no quantitative–qualitative classification for the BTS of building stones has been introduced in the literature. This poses a serious challenge for building engineers and architects in selecting the most durable building stone in terms of BTS. In the present study, a novel classification for igneous building stones based on BTS was proposed. In this classification, stones fall into the seven BTS classes: weak (BTS < 1.3 MPa), moderately weak (BTS 1.3–4.2 MPa), strong (BTS 4.2–10.1 MPa), very strong (BTS 10.1–19.3 MPa), and extremely strong (BTS > 19.3 MPa). The applicability of the BTS classification was confirmed using data published on the BTS values of the building stones subjected to deterioration processes. Based on data analysis, it was found that a stone classified into a BTS class with a higher strength can exhibit better quality in terms of its durability against deterioration processes. Consequently, BTS classification has significant advantages as an efficient and practical tool in selecting the most durable building stone for use in a building. Full article

(This article belongs to the Section Materials Science and Engineering)

17 pages, 536 KiB

Open AccessReview

An Overview of Commercial Virtual Reality Providers in Education: Mapping the Current Market Landscape

by Dominik Evangelou, Miriam Mulders and Bünyamin Sekerci

Appl. Sci. 2025, 15(7), 3906; https://doi.org/10.3390/app15073906 - 2 Apr 2025

Abstract

In recent years, virtual reality (VR) has emerged as a pivotal technology in the field of education, offering immersive and interactive experiences that have the potential to significantly enhance teaching and learning processes. However, for educational designers, teachers, and lecturers who lack advanced [...] Read more.

In recent years, virtual reality (VR) has emerged as a pivotal technology in the field of education, offering immersive and interactive experiences that have the potential to significantly enhance teaching and learning processes. However, for educational designers, teachers, and lecturers who lack advanced information technology skills, identifying and evaluating suitable VR applications can be a complex and labour-intensive endeavour. This article provides a non-technical, action-oriented overview of commercially available VR solutions designed for social skills training in education. To identify relevant providers, we conducted a four-phase snowball search from April to October 2024, combining academic literature reviews, expert interviews, web searches, and demo testing. This process led to the identification of ten VR providers suitable for social and communication skills development. The selected applications were analyzed across ten key criteria, including communication style, avatar design and customization, technological requirements, language support, and the availability of content libraries and authoring tools. The results reveal significant variation among providers in terms of pedagogical flexibility, technical accessibility, and degrees of user customization. By mapping these differences, the article offers a practical starting point for educational stakeholders seeking VR solutions that align with their instructional goals. Rather than offering an exhaustive review, the study presents a structured orientation to facilitate informed decision-making in selecting and implementing VR tools for social skills training. Full article

(This article belongs to the Special Issue Applications of Digital Technology and AI in Educational Settings)

34 pages, 11375 KiB

Open AccessReview

Advanced Financial Fraud Malware Detection Method in the Android Environment

by Jaeho Shin, Daehyun Kim and Kyungho Lee

Appl. Sci. 2025, 15(7), 3905; https://doi.org/10.3390/app15073905 - 2 Apr 2025

Abstract

The open-source structure and ease of development in the Android platform are exploited by attackers to develop malicious programs, greatly increasing malicious Android apps aimed at committing financial fraud. This study proposes a machine learning (ML) model based on static analysis to detect [...] Read more.

The open-source structure and ease of development in the Android platform are exploited by attackers to develop malicious programs, greatly increasing malicious Android apps aimed at committing financial fraud. This study proposes a machine learning (ML) model based on static analysis to detect malware. We validated the significance of private datasets collected from Bank A, comprising 183,938,730 and 11,986 samples of benign and malicious apps, respectively. Undersampling was performed to adjust the proportion of benign applications in the training data because the data on benign and malicious apps were unbalanced. Moreover, 92 datasets were compiled through daily training to evaluate the proposed approach, with benign app data updated over 70 days (D-70 to D-1) and malware app data cumulatively aggregated to address the imbalance. Five ML algorithms were used to evaluate the proposed approach, and the optimal hyperparameter values for each algorithm were obtained using a grid search method. We then evaluated the models using common evaluation metrics, such as accuracy, precision, recall, F1-Score, etc. The LightGBM model was selected for its superior performance, achieving high accuracy and effectiveness. The optimal decision threshold for determining whether an application was malicious was 0.5. Following re-evaluation, the LightGBM model obtained accuracy and F1-Score values of 99.99% and 97.04%, respectively, highlighting the potential of using the proposed model for real-world financial fraud detection. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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20 pages, 4970 KiB

Open AccessArticle

A Unified Denoising Framework for Restoring the LiDAR Point Cloud Geometry of Reflective Targets

by Tianpeng Xie, Jingguo Zhu, Chunxiao Wang, Feng Li and Zhe Meng

Appl. Sci. 2025, 15(7), 3904; https://doi.org/10.3390/app15073904 - 2 Apr 2025

Abstract

LiDAR point clouds of reflective targets often contain significant noise, which severely impacts the feature extraction accuracy and performance of object detection algorithms. These challenges present substantial obstacles to point cloud processing and its applications. In this paper, we propose a Unified Denoising [...] Read more.

LiDAR point clouds of reflective targets often contain significant noise, which severely impacts the feature extraction accuracy and performance of object detection algorithms. These challenges present substantial obstacles to point cloud processing and its applications. In this paper, we propose a Unified Denoising Framework (UDF) aimed at removing noise and restoring the geometry of reflective targets. The proposed method consists of three steps: veiling effect denoising using an improved pass-through filter, range anomalies correction through M-estimator Sample Consensus (MSAC) plane fitting and ray projection, and blooming effect denoising based on an adaptive error ellipse. The parameters of the error ellipse are automatically determined using the divergence angle of the laser beam, blooming factors, and the normal vector along the boundary of the point cloud. The proposed method was validated on a self-constructed traffic sign point cloud dataset. The experimental results showed that the method achieved a mean square error (MSE) of 0.15 cm², a mean city-block distance (MCD) of 0.05 cm, and relative height and width errors of 1.92% and 1.91%, respectively. Compared to five representative algorithms, the proposed method demonstrated superior performance in both denoising accuracy and the restoration of target geometric features. Full article

20 pages, 4878 KiB

Open AccessArticle

Ultrasonic Evaluation Method for Mechanical Performance Degradation of Fluororubber Used in Nuclear Power Facility

by Lu Wu, Liwen Zhu, Tong Wu, Chengliang Zhang, Anyu Sun and Bingfeng Ju

Appl. Sci. 2025, 15(7), 3903; https://doi.org/10.3390/app15073903 - 2 Apr 2025

Abstract

Fluororubber sealing products are widely used in nuclear power equipment, and the degree of degradation of their mechanical properties directly affects the sealing performance, which in turn affects the overall safety of nuclear power units. In order to quantitatively evaluate the degradation of [...] Read more.

Fluororubber sealing products are widely used in nuclear power equipment, and the degree of degradation of their mechanical properties directly affects the sealing performance, which in turn affects the overall safety of nuclear power units. In order to quantitatively evaluate the degradation of the mechanical properties of fluororubber, the theory of ultrasonic propagation in fluororubber was studied. A second-order generalized Maxwell viscoelastic model was constructed in a small strain scenario of high-frequency harmonic vibration to describe the correlation between the mechanical properties and acoustic parameters. A nondestructive evaluation method for mechanical performance degradation using ultrasonic waves based on the nonlinear fitting of the model parameters was proposed. A control experiment was designed using O-rings that had been in service and those that had not yet been used in nuclear power, and mechanical tensile tests and electron microscopy microscopic analyses were conducted. The results showed that the overall elastic modulus of the used sealing ring (2.97 ± 0.15 GPa) was significantly higher than that of the unused sealing ring (2.75 ± 0.22 GPa), consistent with the results of the mechanical tensile tests. However, the sound attenuation coefficient of the unused sealing ring was significantly higher than that of the used sealing ring. Therefore, the ultrasonic evaluation of the mechanical performance degradation of fluororubber based on the viscoelastic model is a nondestructive testing method with engineering application potential. Full article

(This article belongs to the Section Applied Physics General)

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21 pages, 7365 KiB

Open AccessArticle

Analysis of Wind-Induced Vibration Response of Transmission Wire Under Crosswind in Canyon Terrain

by Jianhui Chen and Chaohui Zhou

Appl. Sci. 2025, 15(7), 3902; https://doi.org/10.3390/app15073902 - 2 Apr 2025

Abstract

The conventional unidirectional coupling method, which separates the flow field from the solid, is generally used for calculations to study the wind-induced response of overhead transmission wires in complex micro-terrain conditions. This study constructed a calculation method for the strong bidirectional coupling of [...] Read more.

The conventional unidirectional coupling method, which separates the flow field from the solid, is generally used for calculations to study the wind-induced response of overhead transmission wires in complex micro-terrain conditions. This study constructed a calculation method for the strong bidirectional coupling of vibrations in canyon terrain based on the bidirectional coupling theory and analyzed the vibration characteristics of a transmission wire under step and pulse wind speed conditions. The simulation results show that the wire’s displacement trend was basically the same and the oscillation period was the same under different step wind speed conditions. The influence of the pulse width on the wire displacement was periodic under pulse wind speed conditions, and the pulse amplitude affected the displacement amplitude. Full article

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18 pages, 8524 KiB

Open AccessArticle

Pull-Out Test and Mechanical Properties Analysis Based on Intelligent Bolt and Internet of Things

by Zengle Li, Huimei Zhang, Xin Li and Junliang He

Appl. Sci. 2025, 15(7), 3901; https://doi.org/10.3390/app15073901 - 2 Apr 2025

Abstract

The disadvantages of traditional bolt support technology relying too much on engineering experience in slope engineering in China are becoming more and more obvious. Aiming at this problem, this paper establishes an intelligent bolt pull-out test system based on the Internet of Things, [...] Read more.

The disadvantages of traditional bolt support technology relying too much on engineering experience in slope engineering in China are becoming more and more obvious. Aiming at this problem, this paper establishes an intelligent bolt pull-out test system based on the Internet of Things, monitors the whole process of a bolt pull-out test, determines the ultimate pull-out bearing capacity, and grasps the friction of a bolt in real time. Based on the local common deformation theory, the force of the bolt is analyzed theoretically. The results show that the stress process of bolt rod end tension–rod end displacement is divided into quasi-elastic stage, strengthening stage and failure stage. The stress history of bolts with different anchorage lengths is the same, but the curve shape changes from steep to slow with the increase in anchorage length. Increasing the length of the long bolt can increase the ultimate pull-out bearing capacity of the bolt. Full article

(This article belongs to the Special Issue Development, Reliability, Maintenance and Control of Cyber-Physical Systems)

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17 pages, 21270 KiB

Open AccessArticle

Enhancing the Anti-Interference Capability of Orbital Angular Momentum Beams Generated by an Ultra-Large-Scale Metasurface

by Boli Su, Ke Guan and An Qian

Appl. Sci. 2025, 15(7), 3900; https://doi.org/10.3390/app15073900 - 2 Apr 2025

Abstract

Orbital angular momentum beams have been extensively researched due to their ability to enhance the channel capacity of microwave systems. Metasurface near-field calculations of different sizes have been completed. Near-field calculations with Gaussian noise for metasurfaces of different sizes were also completed. The [...] Read more.

Orbital angular momentum beams have been extensively researched due to their ability to enhance the channel capacity of microwave systems. Metasurface near-field calculations of different sizes have been completed. Near-field calculations with Gaussian noise for metasurfaces of different sizes were also completed. The presence of noise suggests that the vortex electric field generated by the small metasurface of the vortex wave may experience disturbance and be overwhelmed by strong noise. On the other hand, the large vortex wave metasurface exhibits superior anti-noise capability. Its anti-interference characteristic was verified by conducting full-wave simulations on metasurfaces of l = −3 and l = −5. Based on the OAM spectral analysis, the mode purity of the generated vortex waves was calculated in detail. Simulation results indicated that a large-scale metasurface exhibits stronger anti-interference capability, which may inspire the design and research of vortex wave metasurfaces in the future. Full article

(This article belongs to the Section Electrical, Electronics and Communications Engineering)

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34 pages, 20653 KiB

Open AccessArticle

A Numerical Study of the Sealing and Interstage Pressure Drop Characteristics of a Four-Tooth Three-Stage Brush Combination Seal

by Chao Gu, Yingqun Ma, Wei Zhao, Xiuming Sui, Bin Hu and Qingjun Zhao

Appl. Sci. 2025, 15(7), 3899; https://doi.org/10.3390/app15073899 - 2 Apr 2025

Abstract

Premature seal failure induced by the unevenness of interstage pressure distribution in multi-stage brush seals significantly compromises the sealing efficiency of Air-Turbo Rocket (ATR) engines operating under high-pressure (megapascal-level) differential conditions. Conventional pressure equalization designs for such seals often result in significant leakage [...] Read more.

Premature seal failure induced by the unevenness of interstage pressure distribution in multi-stage brush seals significantly compromises the sealing efficiency of Air-Turbo Rocket (ATR) engines operating under high-pressure (megapascal-level) differential conditions. Conventional pressure equalization designs for such seals often result in significant leakage rate increases. This study addresses the pressure imbalance phenomenon in four-tooth three-stage brush composite seals through a novel fractal–geometric porous-media model, rigorously validated against experimental data. Systematic investigations were conducted to elucidate the effects of structural parameters and operational conditions on both sealing performance and pressure distribution characteristics. Key findings reveal that, under the prototype structure parameter, the first-, second-, and third-stage brush bundles account for 18.3%, 30.0%, and 43.3% of the total pressure drop, respectively, with grate teeth contributing 8.4%, demonstrating an inherent pressure imbalance. Axial brush spacing exhibits a minimal impact on the pressure distribution, while the gradient thickness settings of the brush bundles show limited influence. Radial clearance optimization and gradient backplate height adjustment effectively regulate pressure distribution, albeit with associated leakage rate increases. Structural modifications based on these principles achieved only a 5.8% leakage increment while reducing the maximum bundle pressure drop by 23%, demonstrating effective pressure balancing. A simplified analysis of entropy reveals that the fundamental mechanism governing the pressure imbalance stems from non-uniform entropy generation caused by aerodynamic damping dissipation across sequential brush stages. These findings establish a dampened dissipation-based theoretical framework for designing high-performance multistage brush seals in aerospace applications, providing critical insights for achieving an optimal balance between leakage control and pressure equalization in extreme-pressure environments. Full article

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45 pages, 5583 KiB

Open AccessReview

From Tweets to Threats: A Survey of Cybersecurity Threat Detection Challenges, AI-Based Solutions and Potential Opportunities in X

by Omar Alsodi, Xujuan Zhou, Raj Gururajan, Anup Shrestha and Eyad Btoush

Appl. Sci. 2025, 15(7), 3898; https://doi.org/10.3390/app15073898 - 2 Apr 2025

Abstract

The pervasive use of social media platforms, such as X (formerly Twitter), has become a part of our daily lives, simultaneously increasing the threat of cyber attacks. To address this risk, numerous studies have explored methods to detect and predict cyber attacks by [...] Read more.

The pervasive use of social media platforms, such as X (formerly Twitter), has become a part of our daily lives, simultaneously increasing the threat of cyber attacks. To address this risk, numerous studies have explored methods to detect and predict cyber attacks by analyzing X data. This study specifically examines the application of AI techniques for predicting potential cyber threats on X. DeepNN consistently outperforms competing methods in terms of overall and average figure of merit. While character-level feature extraction methods are abundant, we contend that a semantic focus is more beneficial for this stage of the process. The findings indicate that current studies often lack comprehensive evaluations of critical aspects such as prediction scope, types of cybersecurity threats, feature extraction techniques, algorithm complexity, information summarization levels, scalability over time, and performance measurements. This review primarily focuses on identifying AI methods used to detect cyber threats on X and investigates existing gaps and trends in this area. Notably, over the past few years, limited review articles have been published on detecting cyber threats on X, especially those concentrating on recent journal articles rather than conference papers. Full article

(This article belongs to the Special Issue Data and Text Mining: New Approaches, Achievements and Applications)

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