Applied Sciences最新文献

{"title":"Experiment on the Tensile Strength of Concrete Joint Surface at Early Ages","authors":"Jingwei Shao, Min Yuan, Yu Chen, Minghao Weng, Fusheng Wang, Sheng Qiang","doi":"10.3390/app14166968","DOIUrl":"https://doi.org/10.3390/app14166968","url":null,"abstract":"Concrete is widely used in large-scale hydraulic structures, which often need to undergo multiple pouring operations due to construction demands, temperature-induced shrinkage phenomena, and structural reinforcement and repair, which in turn creates the bonding surface of old and new concrete. Therefore, it is of great significance to study the strength of the bond between old and new concrete. We designed and completed a split tension test to investigate the evolution of the tensile strength of concrete joint surfaces with age at early ages. The test groups included three sets of matured concrete aged 3 days, 5 days, and 10 days, respectively. Within each group, multiple test specimens were prepared with different ages of the interface, ranging from 1 day to 15 days. The test utilized ready-mixed concrete materials from a commercial batching plant. To ensure uniform and standard roughness of the interface between new and matured concrete, a method employing non-destructive surface roughening tapes was employed. During the test, each specimen was subjected to tensile failure at its corresponding age. The maximum load applied by the testing machine at the point of tensile failure was recorded for each age group. Based on the fundamental principles of material mechanics and relevant formulas, the tensile strength of the interface at different ages was determined for each test group. The obtained data were then used to fit a curve representing the relationship between the early-age tensile strength of concrete and its age, using MATLAB R2020b software. The results show that there is a small increase in the tensile strength of the bonding surface as the age of the old test blocks is increased. This experiment revealed the changing pattern of early-age tensile strength of concrete at the interface with age, providing a basis for accurately simulating the mechanical properties of the interface during numerical simulations. Then, based on the existing temperature-controlled simulation program, a simplified simulation and calculation method of concrete cracking is proposed to make it possible to determine the tensile cracking (vertical cracking) when the stress exceeds the standard. The validity is verified by simulation calculations of a simplified model, using the tensile strength curves obtained from the tests.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"41 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Analysis of Deep Convolutional Neural Network—Bidirectional Long Short-Term Memory and Machine Learning Methods in Intrusion Detection Systems","authors":"Miracle Udurume, Vladimir Shakhov, Insoo Koo","doi":"10.3390/app14166967","DOIUrl":"https://doi.org/10.3390/app14166967","url":null,"abstract":"Particularly in Internet of Things (IoT) scenarios, the rapid growth and diversity of network traffic pose a growing challenge to network intrusion detection systems (NIDs). In this work, we perform a comparative analysis of lightweight machine learning models, such as logistic regression (LR) and k-nearest neighbors (KNNs), alongside other machine learning models, such as decision trees (DTs), support vector machines (SVMs), multilayer perceptron (MLP), and random forests (RFs) with deep learning architectures, specifically a convolutional neural network (CNN) coupled with bidirectional long short-term memory (BiLSTM), for intrusion detection. We assess these models’ scalability, performance, and robustness using the NSL-KDD and UNSW-NB15 benchmark datasets. We evaluate important metrics, such as accuracy, precision, recall, F1-score, and false alarm rate, to offer insights into the effectiveness of each model in securing network systems within IoT deployments. Notably, the study emphasizes the utilization of lightweight machine learning models, highlighting their efficiency in achieving high detection accuracy while maintaining lower computational costs. Furthermore, standard deviation metrics have been incorporated into the accuracy evaluations, enhancing the reliability and comprehensiveness of our results. Using the CNN-BiLSTM model, we achieved noteworthy accuracies of 99.89% and 98.95% on the NSL-KDD and UNSW-NB15 datasets, respectively. However, the CNN-BiLSTM model outperforms lightweight traditional machine learning methods by a margin ranging from 1.5% to 3.5%. This study contributes to the ongoing efforts to enhance network security in IoT scenarios by exploring a trade-off between traditional machine learning and deep learning techniques.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"33 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Damage Assessment Method for the Efficient Maintenance of Aging Small- to Medium-Sized Reinforced Concrete Slab Bridge Decks","authors":"Han-Min Cho, Kyu-San Jung, Ki-Tae Park","doi":"10.3390/app14166962","DOIUrl":"https://doi.org/10.3390/app14166962","url":null,"abstract":"Bridges are a crucial component of social infrastructure, playing a vital role in transportation, logistics and transit. Several bridges in South Korea were constructed during the rapid development period of the 1990s and 2000s, with RC slab bridges making up a significant portion of these structures. Over time, many of these bridges have aged considerably. To address this, the “Special Act on the Safety Control and Maintenance of Establishments” was enacted in South Korea to improve bridge maintenance. However, maintenance for aging small- to medium-sized bridges, except for Type 1 bridges, remains inadequate due to budget and personnel shortages. In this study, we developed a damage assessment method to evaluate the deterioration and analyze the current state of small- to medium-sized RC slab bridges. We derived the correlation between the deflection response ratio and the stiffness reduction rate of a bridge through structural analysis. This correlation data were then used to assess the damage to actual in-service bridges. Finally, we analyzed the current state of the target bridge and validated the damage assessment method.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"48 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141929457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Route Optimization for Open Vehicle Routing Problem (OVRP): A Mathematical and Solution Approach","authors":"Diego Gasset, Felipe Paillalef, Sebastián Payacán, G. Gatica, Germán Herrera-Vidal, R. Linfati, J. Coronado-Hernández","doi":"10.3390/app14166931","DOIUrl":"https://doi.org/10.3390/app14166931","url":null,"abstract":"In the everchanging landscape of human mobility and commerce, efficient route planning has become paramount. This paper addresses the open vehicle routing problem (OVRP), a major logistical challenge in route optimization for a fleet of vehicles serving geographically dispersed customers. Using a heuristic approach, we explore the complexities of OVRP, comparing the results with advanced optimization methods. This study not only highlights the effectiveness of mathematical modeling, but also explores the practicality of heuristic algorithms such as Greedy, Nearest Neighbor and 2-opt to provide quality solutions. The findings highlight the nuanced interplay between solution quality and computational efficiency, providing valuable insights for addressing real-world logistics challenges. Recommendations delve into optimization opportunities and the integration of emerging technologies, ensuring adaptable solutions to the intricate the problem of open vehicle routing.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"67 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence Software Adoption in Manufacturing Companies","authors":"Klemen Kovic, P. Tominc, Jasna Prester, I. Palčič","doi":"10.3390/app14166959","DOIUrl":"https://doi.org/10.3390/app14166959","url":null,"abstract":"This study investigates the adoption of artificial intelligence (AI) software in manufacturing companies in Slovenia, Slovakia and Croatia, and across six production areas. This research ad-dresses a gap in the literature regarding AI software implementation in relation to company size, technology intensity and supply chain role, and examines whether Industry 4.0 (I4.0) readiness influences AI adoption. Data from the European Manufacturing Survey 2022 were analyzed, and showed that the use of AI is still relatively low. On average only 18.4% of companies use AI software in at least one production area. Logistic regression analysis revealed that neither company size nor role in the supply chain or technology intensity are statistically significantly related to AI usage. However, a significant positive relationship was found between I4.0 readiness and AI adoption, suggesting that companies with advanced digital infrastructures and integrated cyber-physical systems are more likely to adopt AI. This finding underlines the importance of digital transformation for the integration of AI software. The study concludes that while company characteristics such as size and the role of the company in the supply chain are not statistically significantly related to the use of AI, the level of digital readiness is crucial.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"24 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Operationalisation of Building Inspections and Repair: Systematisation-Based Approach","authors":"Clara Pereira, Ana Silva","doi":"10.3390/app14166947","DOIUrl":"https://doi.org/10.3390/app14166947","url":null,"abstract":"The possibility of diagnosing and repairing specific sets of defects (those with more severe consequences and impact on the degradation of building components) with the same means is considered. It is important to optimise the planning and kick-off of building inspections by using, from the start, a predetermined set of equipment and to optimise the maintenance and rehabilitation of the building envelope in terms of funds invested and resources. An existing methodology is used to create inter-defect correlation matrices, taking into account an expert knowledge-based building inspection system. The main results include a set of essential diagnosis methods—crack measuring and monitoring; temperature and moisture measurement; infrared thermography; and water absorption tests—and the identification of the most transversal repair techniques—cleaning; protection coating; replacement/reapplication of claddings/glazing; re-application of finishing coats or more adequate claddings—which were also analysed in terms of resource consumption, as a preliminary approach to their life-cycle assessment. The main conclusions indicate that there is still a long path to cover in the field of life-cycle assessment of repair techniques, which can be extended to the application of diagnosis methods.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"114 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and Experimental Study of a Down-Drive Piezoelectric High-Frequency Fatigue Testing Machine","authors":"Sida Zhang, Zhigang Yang, Jiangwei Liu","doi":"10.3390/app14166961","DOIUrl":"https://doi.org/10.3390/app14166961","url":null,"abstract":"In order to solve the problem of large dynamic load and low loading accuracy prevailing in traditional fatigue testing machines, and to meet the fatigue test loading demand of alternating small-load microelectromechanical devices and bionic devices, a high-frequency resonant piezoelectric fatigue tester that can apply alternating small loads in the range of 0.1 N~100 N was designed and manufactured, with a piezoelectric oscillator as the driving source of the system. Firstly, the structure of this fatigue testing machine is designed, and a dynamic model is established for the fatigue testing machine to theoretically study the influence of the system mass and stiffness on the change in the resonance frequency of the fatigue testing machine. Then, numerical calculations and experiments are carried out to verify the effect of system mass and stiffness changes on the intrinsic frequency of the fatigue testing machine. Finally, the fatigue testing machine was used to carry out fatigue test on the dog-bone-shaped specimens, and the failure process of specimen fatigue was verified by analysing the load applied to the specimen by the fatigue testing machine, and at the same time, it was proved that the performance of the present fatigue testing machine complied with the requirements. It provides a new technical means to meet the fatigue test loading demand of small-load electromechanical devices and bionic devices.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"6 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141929100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"E-GTN: Advanced Terrain Sensing Framework for Enhancing Intelligent Decision Making of Excavators","authors":"Qianyou Zhao, Le Gao, Duidi Wu, Xinyao Meng, Jin Qi, Jie Hu","doi":"10.3390/app14166974","DOIUrl":"https://doi.org/10.3390/app14166974","url":null,"abstract":"The shift towards autonomous excavators in construction and mining is a significant leap towards enhancing operational efficiency and ensuring worker safety. However, it presents challenges, such as the need for sophisticated decision making and environmental perception due to complex terrains and diverse conditions. Our study introduces the E-GTN framework, a novel approach tailored for autonomous excavation that leverages advanced multisensor fusion and a custom-designed convolutional neural network to address these challenges. Results demonstrate that GridNet effectively processes grid data, enabling the reinforcement learning algorithm to make informed decisions, thereby ensuring efficient and intelligent autonomous excavator performance. The study concludes that the E-GTN framework offers a robust solution for the challenges in unmanned excavator operations, providing a valuable platform for future advancements in the field.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"8 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Parallel Algorithm Based on Regularized Lattice Boltzmann Method for Multi-Layer Grids","authors":"Zhixiang Liu, Yunhao Zhao, Wenhao Zhu, Yang Wang","doi":"10.3390/app14166976","DOIUrl":"https://doi.org/10.3390/app14166976","url":null,"abstract":"The regularized lattice Boltzmann method (RLBM) is an improvement of the lattice Boltzmann method (LBM). The advantage of RLBM is improved accuracy without increasing computational overheads. The paper introduces the method of multi-layer grids, the multi-layer grids have different resolutions which can accurately solve problems in computational fluid dynamics (CFD) without destroying the parallelism of RLBM. Simulating fluid flow usually requires a large number of grid simulations. Therefore, it is necessary to design a parallel algorithm for RLBM based on multi-layer grids. In this paper, a load-balancing-based grid dividing algorithm and an MPI-based parallel algorithm for RLBM on multi-layer grids are proposed. The load balancing-based grid dividing algorithm ensures that the workload is evenly distributed across processes, minimizing the discrepancies in computational load. The MPI-based parallel algorithm for RLBM on multi-layer grids ensures accurate and efficient numerical simulation. Numerical simulations have verified that the proposed algorithms exhibit excellent performance in both 2D and 3D experiments, maintaining high stability and accuracy. The multi-layer grids method is significantly better than single-layer grids in terms of CPU runtime and number of grids required. Comparative analysis with the OpenMP multi-threading method on the multi-layer grid RLBM shows that the proposed algorithm in this paper achieves superior speedup and efficiency.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"46 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reinforcement-Learning-Based Trajectory Learning in Frenet Frame for Autonomous Driving","authors":"Sangho Yoon, Youngjoon Kwon, Jaesung Ryu, Sungkwan Kim, Sungwoo Choi, Kyungjae Lee","doi":"10.3390/app14166977","DOIUrl":"https://doi.org/10.3390/app14166977","url":null,"abstract":"Autonomous driving is a complex problem that requires intelligent decision making, and it has recently garnered significant interest due to its potential advantages in convenience and safety. In autonomous driving, conventional path planning to reach a destination is a time-consuming challenge. Therefore, learning-based approaches have been successfully applied to the controller or decision-making aspects of autonomous driving. However, these methods often lack explainability, as passengers cannot discern where the vehicle is headed. Additionally, most experiments primarily focus on highway scenarios, which do not effectively represent road curvature. To address these issues, we propose a reinforcement-learning-based trajectory learning in the Frenet frame (RLTF), which involves learning trajectories in the Frenet frame. Learning trajectories enable the consideration of future states and enhance explainability. We demonstrate that RLTF achieves a 100% success rate in the simulation environment, considering future states on curvy roads with continuous obstacles while overcoming issues associated with the Frenet frame.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"58 28","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141929166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}