Journal Description
Applied Sciences
Applied Sciences
is an international, peer-reviewed, open access journal on all aspects of applied natural sciences published semimonthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Multidisciplinary) / CiteScore - Q1 (General Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 2.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our authors say about Applied Sciences.
- Companion journals for Applied Sciences include: Applied Nano, AppliedChem, Applied Biosciences, Virtual Worlds, Spectroscopy Journal and JETA.
Impact Factor:
2.7 (2022);
5-Year Impact Factor:
2.9 (2022)
Latest Articles
The Remaining Life Prediction of Rails Based on Convolutional Bi-Directional Long and Short-Term Memory Neural Network with Residual Self-Attention Mechanism
Appl. Sci. 2024, 14(9), 3781; https://doi.org/10.3390/app14093781 (registering DOI) - 28 Apr 2024
Abstract
In the railway industry, the rail is the basic load-bearing structure of railway tracks. The prediction of the remaining useful life (RUL) for rails is important to avoid unexpected system failures and reduce the cost of maintaining the system. However, the existing detection
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In the railway industry, the rail is the basic load-bearing structure of railway tracks. The prediction of the remaining useful life (RUL) for rails is important to avoid unexpected system failures and reduce the cost of maintaining the system. However, the existing detection of rail flaws is difficult, the rail deterioration mechanisms are diverse, and the traditional data-driven methods have insufficient feature extraction. This causes low prediction accuracy. With objectives set in relation to the problems outlined above, a rail RUL prediction approach based on a convolutional bidirectional long- and short-term memory neural network with a residual self-attention (CNNBiLSTM-RSA) mechanism is designed. Firstly, the pre-processed vibration data are taken as the input for the convolutional bi-directional long- and short-term memory neural network (CNNBiLSTM) to extract the forward and backward dependencies and features of the rail data. Secondly, the RSA mechanism is introduced in order to obtain the contributions of the features at different moments during the degradation process of the rail. Finally, an end-to-end RUL prediction implementation based on the convolutional bi-directional long- and short-term memory neural network with the residual self-attention mechanism is established. The experiments were carried out using the full life-cycle data of rails collected at the railway site. The results show that the method achieves a higher accuracy in the RUL prediction of rails.
Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Open AccessArticle
Enhancing Security in Industrial Application Development: Case Study on Self-Generating Artificial Intelligence Tools
by
Tomás de J. Mateo Sanguino
Appl. Sci. 2024, 14(9), 3780; https://doi.org/10.3390/app14093780 (registering DOI) - 28 Apr 2024
Abstract
The emergence of security vulnerabilities and risks in software development assisted by self-generated tools, particularly with regard to the generation of code that lacks due consideration of security measures, could have significant consequences for industry and its organizations. This manuscript aims to demonstrate
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The emergence of security vulnerabilities and risks in software development assisted by self-generated tools, particularly with regard to the generation of code that lacks due consideration of security measures, could have significant consequences for industry and its organizations. This manuscript aims to demonstrate how such self-generative vulnerabilities manifest in software programming, through a case study. To this end, this work undertakes a methodology that illustrates a practical example of vulnerability existing in the code generated using an AI model such as ChatGPT, showcasing the creation of a web application database, SQL queries, and PHP server-side. At the same time, the experimentation details a step-by-step SQL injection attack process, highlighting the hacker’s actions to exploit the vulnerability in the website’s database structure, through iterative testing and executing SQL commands to gain access to sensitive data. Recommendations on effective prevention strategies include training programs, error analysis, responsible attitude, integration of tools and audits in software development, and collaboration with third parties. As a result, this manuscript discusses compliance with regulatory frameworks such as GDPR and HIPAA, along with the adoption of standards such as ISO/IEC 27002 or ISA/IEC 62443, for industrial applications. Such measures lead to the conclusion that incorporating secure coding standards and guideline—from organizations such as OWASP and CERT training programs—further strengthens defenses against vulnerabilities introduced by AI-generated code and novice programming errors, ultimately improving overall security and regulatory compliance.
Full article
(This article belongs to the Special Issue Artificial Intelligence Applications in Industry)
Open AccessArticle
Development and Characterization of High-Fiber, Gluten-Free Pasta for Celiac Disease Patients
by
Sofyan Maghaydah, Mahmoud Abu-Ghoush, Waed Hayajneh and Sehar Iqbal
Appl. Sci. 2024, 14(9), 3779; https://doi.org/10.3390/app14093779 (registering DOI) - 28 Apr 2024
Abstract
Celiac disease (CD) is a multi-organ complex autoimmune disorder triggered by a gluten-containing diet in genetically predisposed individuals. The only effective treatment for people with CD is strict, lifelong adherence to a gluten-free diet to reduce severe disease outcomes. Therefore, this study aimed
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Celiac disease (CD) is a multi-organ complex autoimmune disorder triggered by a gluten-containing diet in genetically predisposed individuals. The only effective treatment for people with CD is strict, lifelong adherence to a gluten-free diet to reduce severe disease outcomes. Therefore, this study aimed to produce high-nutrition gluten-free pasta by substituting wheat flour with lupin flour, flaxseed flour, rice flour, and corn starch. For this purpose, six gluten-free pasta treatments (T1–T6) were produced with different flour compositions. In addition, inulin, xanthan gum, beta-glucan, and Moringa leaf powder in fixed amounts were added to all treatments. For the proximate analysis, color measurements and sensory evaluation were determined for all treatments. Proximate analysis of our results showed that substituting wheat flour with composite flour blends was satisfactory for producing nutritious pasta products without affecting their quality. Compared to the control group, T6 had a significant increase in fiber (4.68 ± 0.25 vs. 1.24 ± 0.28), lipid (21.99 ± 0.38 vs. 9.32 ± 0.25), protein (13.84 ± 0.30 vs. 13.45 ± 0.51), and ash content (1.65 ± 0.07 vs. 1.28 ± 0.06) of gluten-free pasta. However, the carbohydrate content decreased compared to the control treatment (46.10 ± 0.69 vs. 60.84 ± 0.75). The color measurement evaluation found a significant difference in the lightness (L*), redness (a*), and yellowness (b*) values between the control and all gluten-free pasta treatments. The sensory evaluation of the finished gluten-free pasta treatments and control sample indicated that the quality score for overall acceptability varied widely for different treatments due to individual preferences. Our study concluded that gluten-free pasta with high nutritional value from gluten-free flour is a good alternative product for celiac patients.
Full article
(This article belongs to the Section Food Science and Technology)
Open AccessArticle
Surface Tension Estimation of Steel above Boiling Temperature
by
Joerg Volpp
Appl. Sci. 2024, 14(9), 3778; https://doi.org/10.3390/app14093778 (registering DOI) - 28 Apr 2024
Abstract
Surface tension is an important characteristic of materials. In particular at high temperatures, surface tension values are often unknown. However, for metals, these values are highly relevant in order to enable efficient industrial processing or simulation of material behavior. Plasma, electron or laser
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Surface tension is an important characteristic of materials. In particular at high temperatures, surface tension values are often unknown. However, for metals, these values are highly relevant in order to enable efficient industrial processing or simulation of material behavior. Plasma, electron or laser beam processes can induce such high energy inputs, which increase the metal temperatures to, and even above, boiling temperatures, e.g., during deep penetration welding or remote cutting. Unfortunately, both theoretical and experimental methods experience challenges in deriving surface tension values at high temperatures. Material models of metals have limitations in explaining complex ion interactions, and experimentally measuring temperature and surface tension at high temperatures is a challenge for methods and equipment. Therefore, surface wave analysis was conducted in this work to derive surface tension values around the boiling temperature of steel and identify trends. In addition, a simple ion interaction calculation was used to simulate the impacting parameters that define the surface tension. Since both the experimental values and simulation results indicate an increasing trend in surface tension above the boiling temperature, it is concluded that the dominating attractive forces above this temperature should increase with increasing temperature and lead to increasing surface tension forces in the surface layers of liquid metal.
Full article
Open AccessArticle
A Cobot in the Vineyard: Computer Vision for Smart Chemicals Spraying
by
Claudio Tomazzoli, Andrea Ponza, Matteo Cristani, Francesco Olivieri and Simone Scannapieco
Appl. Sci. 2024, 14(9), 3777; https://doi.org/10.3390/app14093777 (registering DOI) - 28 Apr 2024
Abstract
Precision agriculture (PA) is a management concept that makes use of digital techniques to monitor and optimise agricultural production processes and represents a field of growing economic and social importance. Within this area of knowledge, there is a topic not yet fully explored:
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Precision agriculture (PA) is a management concept that makes use of digital techniques to monitor and optimise agricultural production processes and represents a field of growing economic and social importance. Within this area of knowledge, there is a topic not yet fully explored: outlining a road map towards the definition of an affordable cobot solution (i.e., a low-cost robot able to safely coexist with humans) able to perform automatic chemical treatments. The present study narrows its scope to viticulture technologies, and targets small/medium-sized winemakers and producers, for whom innovative technological advancements in the production chain are often precluded by financial factors. The aim is to detail the realization of such an integrated solution and to discuss the promising results achieved. The results of this study are: (i) The definition of a methodology for integrating a cobot in the process of grape chemicals spraying under the constraints of a low-cost apparatus; (ii) the realization of a proof-of-concept of such a cobotic system; (iii) the experimental analysis of the visual apparatus of this system in an indoor and outdoor controlled environment as well as in the field.
Full article
(This article belongs to the Special Issue Application of Machine Learning in Industry 4.0)
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Open AccessArticle
Lateral Heat Distribution Characteristics of CLP S275 Using Gaussian FFT Algorithm in Optical Thermographic Testing
by
Seungju Lee, Yoonjae Chung, Wontae Kim and Hyunkyu Suh
Appl. Sci. 2024, 14(9), 3776; https://doi.org/10.3390/app14093776 (registering DOI) - 28 Apr 2024
Abstract
In general, when using infrared thermography (IRT) techniques to excite a heat source on the surface of an inspection object, the heat source is focused on the center of the image of the infrared (IR) camera. If the object to be inspected is
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In general, when using infrared thermography (IRT) techniques to excite a heat source on the surface of an inspection object, the heat source is focused on the center of the image of the infrared (IR) camera. If the object to be inspected is small, uniform excitation of the heat source is possible, but if the area is large, the heat source is concentrated locally, resulting in uneven heat distribution. Therefore, in this study, heat distribution was analyzed after inducing a non-uniform heat source by exciting the heat source at different locations. Additionally, the fast Fourier transform (FFT) algorithm with Gaussian filtering was applied to resolve the non-uniform distribution of the heat sources. Excellent results were obtained from the amplitude image, and the effectiveness of the FFT algorithm was verified using the Otsu algorithm. Finally, the signal-to-noise ratio (SNR) was calculated, and the detection ability according to each thinning rate was analyzed.
Full article
(This article belongs to the Special Issue Progress in Nondestructive Testing and Evaluation (NDT&E))
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Open AccessArticle
Analysis of Seismic Response Characteristics of Fractured Carbonate Reservoirs Based on Physical Model (Tarim Basin)
by
Li Wei, Bangrang Di and Jianxin Wei
Appl. Sci. 2024, 14(9), 3775; https://doi.org/10.3390/app14093775 (registering DOI) - 28 Apr 2024
Abstract
Anomalous bright spots, called the string of bead-like response, are typical seismic migration profile features in carbonate fractured reservoirs in the Tarim Basin, and they are indicators of high-quality oil and gas reservoirs. Correctly recognizing the correspondence between fractures and the SBLR can
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Anomalous bright spots, called the string of bead-like response, are typical seismic migration profile features in carbonate fractured reservoirs in the Tarim Basin, and they are indicators of high-quality oil and gas reservoirs. Correctly recognizing the correspondence between fractures and the SBLR can contribute to the efficient drilling of target carbonate fractured reservoirs. Physical models can describe fractured reservoirs more directly and efficiently than real situations and have obvious advantages in accurately and quantitatively designing parameters such as dipping angles and the number of layers of fractured reservoirs. Under such a background, according to the real tectonic characteristics of the Tarim Basin, among the main hydrocarbon reservoirs, fractured reservoirs with various parameters were designed and a physical model was constructed according to the real stratigraphic parameters. After seismic data acquisition and processing, the response characteristics of the string of bead-like response were extracted and summarized from seismic migration profiles for all fractured reservoirs, which provided targeted analyses and discussions on the fracture dipping angle, number of fracture layers, overlying stratigraphic influences, and planar attributes of the fractured reservoirs. In general, the larger the fracture dip, the more difficult it is to identify, while the slope of reflection strength and maximum absolute amplitude attributes can be important markers for fractured reservoir identification. The physical modeling study of fractured reservoirs in this paper can provide a basis for the analysis and prediction of carbonate fractured reservoirs in the Tarim Basin.
Full article
(This article belongs to the Special Issue State-of-the-Art Earth Sciences and Geography in China)
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Open AccessArticle
Research on a Classification Method of Goaf Stability Based on CMS Measurement and the Cloud Matter–Element Model
by
Jiazhao Chen, Yuye Tan, Xu Huang and Jianxin Fu
Appl. Sci. 2024, 14(9), 3774; https://doi.org/10.3390/app14093774 (registering DOI) - 28 Apr 2024
Abstract
The evaluation and classification of goaf stability are fuzzy and random. To address this problem, a new classification method is proposed. A cavity monitoring system is used to detect the goaf, 3DMine and FLAC3D software are used to conduct the 3D visual modeling
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The evaluation and classification of goaf stability are fuzzy and random. To address this problem, a new classification method is proposed. A cavity monitoring system is used to detect the goaf, 3DMine and FLAC3D software are used to conduct the 3D visual modeling of the scanning results, and numerical simulation analysis is performed on the goaf. According to the analysis results, the stability classification standard of the goaf is constructed, and the characteristics of each classification are described. The evaluation indicator system of goaf stability is constructed in accordance with similar engineering experience, and the evaluation indicator is weighted by using the analytic hierarchy process. The cloud–element coupling evaluation model is built, the field measured values of indicators are collected, the cloud correlation degree of goafs belonging to each stability level is calculated, the stability level is evaluated according to the principle of maximum membership degree, and the results are compared with the numerical simulation to analyze the reasons for the differences in the stability evaluation results obtained by the two methods and to improve the accuracy of the evaluation of goaf stability. The pillar stress and surrounding rock deformation are monitored in Room 1# of the inclined mining area of Shirengou Iron Mine. The monitoring results are consistent with the evaluation results, which proves the accuracy of the proposed goaf stability classification method.
Full article
Open AccessArticle
Numerical Simulation and Experimental Verification of Quality Detection of Grouting in Pre-Stressed Pipelines Based on Transmission Wave Method
by
Qingshan Wang, Yun Luo, Yang Liu, Minghao Song, Heng Liu and Xiaoge Liu
Appl. Sci. 2024, 14(9), 3773; https://doi.org/10.3390/app14093773 (registering DOI) - 28 Apr 2024
Abstract
The quality of grouting in pre-stressed pipelines plays a critical role in ensuring the safety and durability of pre-stressed concrete bridges. In this study, the transmission wave method was proposed as a means to assess the quality of grouting in pre-stressed pipelines. The
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The quality of grouting in pre-stressed pipelines plays a critical role in ensuring the safety and durability of pre-stressed concrete bridges. In this study, the transmission wave method was proposed as a means to assess the quality of grouting in pre-stressed pipelines. The ABAQUS finite element simulation (FE simulation) method was used to study the propagation of hammer stress waves in pre-stressed pipes. A full-scale test was conducted to verify the numerical simulation using the AGI-BWG instrument system developed to detect the quality of grouting. The results show that the propagation speed of transmitted waves increases and the frequency shifts towards higher frequencies with an increase in void length within pre-stressed pipelines. This research suggests that the propagation velocity of elastic waves in pre-stressed pipelines serves as a key indicator of grouting quality. The transmission wave method, based on hammer signals, proves to be an effective tool for detecting the quality of grouting in pre-stressed pipelines.
Full article
(This article belongs to the Special Issue Advances in Civil Structural Damage Detection and Health Monitoring)
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Open AccessArticle
Interpretable Recurrent Variational State-Space Model for Fault Detection of Complex Systems Based on Multisensory Signals
by
Meng Ma and Junjie Zhu
Appl. Sci. 2024, 14(9), 3772; https://doi.org/10.3390/app14093772 (registering DOI) - 28 Apr 2024
Abstract
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It is necessary to develop a health monitoring system (HMS) for complex systems to improve safety and reliability and prevent potential failures. Time-series signals are collected from multiple sensors installed on the equipment that can reflect the health condition of them. In this
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It is necessary to develop a health monitoring system (HMS) for complex systems to improve safety and reliability and prevent potential failures. Time-series signals are collected from multiple sensors installed on the equipment that can reflect the health condition of them. In this study, a novel interpretable recurrent variational state-space model (IRVSSM) is proposed for time-series modeling and anomaly detection. To be specific, the deterministic hidden state of a recursive neural network is used to capture the latent structure of sensor data, while the stochastic latent variables of a nonlinear deep state-space model capture the diversity of sensor data. Temporal dependencies are modeled through a nonlinear transition matrix; an automatic relevance determination network is introduced to selectively emphasize important sensor data. Experimental results demonstrate that the proposed algorithm effectively captures vital information within the sensor data and provides accurate and reliable fault diagnosis during the steady-state phase of liquid rocket engine operation.
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Open AccessReview
Key Insights from Preflight Planning for Safety Improvement in General Aviation: A Systematic Literature Review
by
Nuno Moura Lopes, Fátima Trindade Neves and Manuela Aparicio
Appl. Sci. 2024, 14(9), 3771; https://doi.org/10.3390/app14093771 (registering DOI) - 28 Apr 2024
Abstract
This study highlights the disproportionate number of fatal and non-fatal accidents in general aviation (GA) compared to airline carriers, emphasizing the need to investigate the contributing factors to these incidents. It identifies poor decision-making and a lack of situational awareness as key issues
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This study highlights the disproportionate number of fatal and non-fatal accidents in general aviation (GA) compared to airline carriers, emphasizing the need to investigate the contributing factors to these incidents. It identifies poor decision-making and a lack of situational awareness as key issues and presents a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to analyze preflight information used by GA pilots. The findings underscore the significance of operational factors in ensuring a successful flight and suggest modifications to pilot license renewal processes, with an emphasis on the adoption of digital preflight tools. A new theoretical framework based on the operational factors identified is also introduced, which could serve as a foundation for future studies and interventions aimed at enhancing safety in general aviation.
Full article
Open AccessArticle
Oil-Air Distribution Prediction Inside Ball Bearing with Under-Race Lubrication Based on Numerical Simulation
by
Yaguo Lyu, Yuanhao Li, Can Li, Le Jiang and Zhenxia Liu
Appl. Sci. 2024, 14(9), 3770; https://doi.org/10.3390/app14093770 (registering DOI) - 28 Apr 2024
Abstract
Oil/air two-phase flow distribution in the bearings is the basis for bearing lubrication status identification and precise thermal analysis of the bearing. In order to understand the fluid behavior inside the under-race lubrication ball bearing and obtain an accurate oil volume fraction prediction
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Oil/air two-phase flow distribution in the bearings is the basis for bearing lubrication status identification and precise thermal analysis of the bearing. In order to understand the fluid behavior inside the under-race lubrication ball bearing and obtain an accurate oil volume fraction prediction model. A numerical study of ball bearing with under-race lubrication is carried out to study oil-gas two-phase distribution inside the bearing, and the influence of several parameters is quantified, like bearing rotating speed, oil flow rate, oil viscosity, and oil density. The results indicate that the oil fraction in the bearing cavity between the inner and outer ring shows a periodic distribution along the circumference direction, and the period is the same as the number of under-race oil supply holes. Oil distribution alone radial direction is affected by the outer-ring-guiding cage and centrifugal force, leading to oil accumulation near the outer ring. Different bearing running conditions and oil characteristics do not change the oil distribution trend alone in circumference and radial direction, but the difference ratio. Finally, based on the numerical simulation results, a formula for the average oil volume fraction prediction in the bearing ring cavity is constructed.
Full article
(This article belongs to the Special Issue Research on Friction and Lubrication: Surfaces, Bearings and Gears)
Open AccessArticle
Enriching User-Visitor Experiences in Digital Museology: Combining Social and Virtual Interaction within a Metaverse Environment
by
Alba Alabau, Lidia Fabra, Ana Martí-Testón, Adolfo Muñoz, J. Ernesto Solanes and Luis Gracia
Appl. Sci. 2024, 14(9), 3769; https://doi.org/10.3390/app14093769 (registering DOI) - 28 Apr 2024
Abstract
This study investigates the potential of integrating multilayer animations and sophisticated shader technologies to enhance visitor social interactions within metaverse exhibition spaces. It is part of a broader initiative aimed at developing innovative digital museology strategies that foster social engagement through virtual reality
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This study investigates the potential of integrating multilayer animations and sophisticated shader technologies to enhance visitor social interactions within metaverse exhibition spaces. It is part of a broader initiative aimed at developing innovative digital museology strategies that foster social engagement through virtual reality (VR) experiences. The methodology adopted seeks to provide a more immersive and human-centric exploration of 3D digital environments by blending elements of physical spaces with the interactive dynamics common in video games. A virtual exhibition space themed around Mars was created as a testbed to facilitate social interactions among users, who navigate the environment via avatars. This digital space was developed using a specialized Unity template designed by the metaverse platform Spatial.io. Overcoming the programming constraints imposed by Spatial.io, which limits the use of external scripts for security and stability, posed a significant challenge. Nonetheless, by leveraging the ability to modify shader codes used for material creation and employing advanced animation techniques with layered effects, the authors of this work achieved dynamic material responses to lighting changes and initiated complex asset interactions beyond simple linear animations.
Full article
(This article belongs to the Special Issue Virtual Reality Technology: Current Applications, Challenges and Its Future)
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Open AccessArticle
Investigation of Car following and Lane Changing Behavior in Diverging Areas of Tunnel–Interchange Connecting Sections Based on Driving Simulation
by
Zhenhua Sun, Jinliang Xu, Chenwei Gu, Tian Xin and Wei Zhang
Appl. Sci. 2024, 14(9), 3768; https://doi.org/10.3390/app14093768 (registering DOI) - 28 Apr 2024
Abstract
Tunnel–interchange connecting sections pose significant safety challenges on mountainous expressways due to their high incidence of accidents. Improving road safety necessitates a comprehensive understanding of driver behavior in such areas. This study explores the influences of road characteristics, signage information volume, and traffic
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Tunnel–interchange connecting sections pose significant safety challenges on mountainous expressways due to their high incidence of accidents. Improving road safety necessitates a comprehensive understanding of driver behavior in such areas. This study explores the influences of road characteristics, signage information volume, and traffic conditions on drivers’ car-following and lane-changing behavior in tunnel–interchange diverging areas. Utilizing driving data from 25 subjects of 72 simulated road models, driving performance is assessed using the Friedman rank test and multivariate variance analysis. The results highlight the significant influence of both connection distance and signage information load on driving behavior. In tunnel–interchange scenarios, the reduction in velocity increased by 62.61%, and speed variability surged by 61.11%, indicating potential adverse effects on driving stability due to the environmental transitions. Decreased connection distances are associated with reduced lane-changing durations, larger steering angles, and increased failure rates. Furthermore, every two units of increase in signage information leads to a 13.16% rise in maximum deceleration and a 5% increase in time headway. Notably, the signage information volume shows a significant interaction with connection distance (F > 1.60, p < 0.045) for most car-following indicators. Hence, the study recommends a maximum connection distance of 700 m and signage information not exceeding nine units for optimal safety and stability.
Full article
(This article belongs to the Section Transportation and Future Mobility)
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Open AccessArticle
Natural Ventilation to Manage Ammonia Concentration and Temperature in a Rabbit Barn in Central Mexico
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David Vargas Cano, Jorge Flores-Velazquez and Agustín Ruiz Garcia
Appl. Sci. 2024, 14(9), 3767; https://doi.org/10.3390/app14093767 (registering DOI) - 28 Apr 2024
Abstract
The concentration of ammonia (NH3) and the temperature of the air surrounding the rabbit habitat in the farm condition basic health processes such as breathing and feeding. The indoor climate in a rabbit farm is largely conditioned by the ventilation system
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The concentration of ammonia (NH3) and the temperature of the air surrounding the rabbit habitat in the farm condition basic health processes such as breathing and feeding. The indoor climate in a rabbit farm is largely conditioned by the ventilation system (air conditioning). The objective of this study was to build a numerical model based on computational fluid dynamics (CFD) in order to evaluate, by numerical simulations, the air dynamics of a rustic farm. After the validation of the computational model, the thermal gradient and ammonia concentration were analyzed under three wind incidence angles (0°, 45°, and 90° with respect to the horizontal Z axis of the facility). The results of the simulations showed that, in the area occupied by the rabbits (AOR), the concentration of ammonia with respect to the source was reduced by 37.3% in the most favorable case (wind direction at 45°), and 21.2% in the least favorable case (wind direction at 0°), and the indoor temperature presented a maximum difference of 2 °C with respect to the outside temperature. Climate control is a more expensive cost in rabbit farm exploitation; dynamics modulation can serve as an auxiliary tool for reducing health risks in rabbits. The use of models based on fluid dynamics allowed us to understand the efficiency of the ventilation system, which must be increased to reduce the found temperature gradient. Through numerical simulation it will be possible to find alternatives to increase the ventilation rate.
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(This article belongs to the Topic Advanced Heat and Mass Transfer Technologies)
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Open AccessArticle
Study of Rock Damage Constitutive Model Considering Temperature Effect Based on Weibull Distribution
by
Tianci Lu, Hao Wu, Shuiming Yin and Xiaoli Xu
Appl. Sci. 2024, 14(9), 3766; https://doi.org/10.3390/app14093766 (registering DOI) - 28 Apr 2024
Abstract
The deformation and damage process of rocks is accompanied by crack extension and penetration. The rock strength criterion, as a macroscopic characterization of the rock strength microelement, is the basis for establishing the damage constitutive modeling of rock. Aiming at the problem of
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The deformation and damage process of rocks is accompanied by crack extension and penetration. The rock strength criterion, as a macroscopic characterization of the rock strength microelement, is the basis for establishing the damage constitutive modeling of rock. Aiming at the problem of the Hoek–Brown (H–B) strength criterion having a large strength prediction value under high confining pressure, the H–B strength criterion is corrected by considering the influence of the initial cracks on the development of the rock strength, and its applicability is verified. Based on the damage theory, assuming that the rock strength microelement obeys the Weibull distribution and considering the influence of residual strength, the damage correction coefficient is introduced, and a thermal damage statistical constitutive model that can reflect the whole process of the development of initial cracks inside the rock is established. The degree of penetration up to the damage is established, and the method of determining the parameters of the model is given. The theoretical curves of the established model are compared and analyzed with the curves of a conventional triaxial compression test of rock samples, and the study shows that the statistical constitutive model of the thermal damage of rock, established based on the modified H–B strength criterion, can better simulate the stress–strain relationship of rock under a conventional triaxial test. It also verifies the reasonableness and applicability of the model, which is expected to provide a basis for the exploitation of deep resources and the safety assessment of underground engineering.
Full article
(This article belongs to the Section Civil Engineering)
Open AccessArticle
High-Sensitivity Detection of Carbon Fiber-Reinforced Polymer Delamination Using a Novel Eddy Current Probe
by
Yingni Zhou, Bo Ye, Honggui Cao, Yangkun Zou, Zhizhen Zhu and Hongbin Xing
Appl. Sci. 2024, 14(9), 3765; https://doi.org/10.3390/app14093765 (registering DOI) - 28 Apr 2024
Abstract
The demand for non-destructive testing of carbon fiber-reinforced polymer (CFRP) is becoming increasingly pressing to ensure its safety and reliability across different fields of use. However, the complex structural characteristics and anisotropic bulk conductivity of CFRP make achieving high sensitivity in detecting internal
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The demand for non-destructive testing of carbon fiber-reinforced polymer (CFRP) is becoming increasingly pressing to ensure its safety and reliability across different fields of use. However, the complex structural characteristics and anisotropic bulk conductivity of CFRP make achieving high sensitivity in detecting internal defects such as delamination extremely challenging. To address this issue, a novel triple rectangular coil probe with high sensitivity developed for detecting delamination in CFRP is presented in this paper. A finite element model using COMSOL Multiphysics was developed for CFRP delamination eddy current testing with the designed probe. Based on this model, the probe parameters were determined through orthogonal experiments. By analyzing the eddy current distribution in CFRP samples, the scanning mode was defined. Following this, the detection voltage was evaluated for various delamination parameters, and the sensitivity of different probes was compared. Results indicate that, under the same excitation coil parameters, for a 5 mm delamination lateral dimension change, the single pancake and single rectangular coil probes exhibit sensitivities of 88.24% and 72.55%, respectively, compared with the designed probe. For a 0.5 mm delamination thickness change, their sensitivities are 49.04% and 56.69% of those of the designed probe. The designed probe meets the demand for high-sensitivity detection.
Full article
(This article belongs to the Special Issue Non-destructive Testing of Materials and Structures - Volume II)
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Open AccessArticle
A Method for Measuring Spatial Information of Area Maps Considering the Diversity of Node–Edge and Gestalt Principles
by
Qiankun Kang, Xiaoguang Zhou and Dongyang Hou
Appl. Sci. 2024, 14(9), 3764; https://doi.org/10.3390/app14093764 (registering DOI) - 28 Apr 2024
Abstract
Existing methods for measuring the spatial information of area maps fail to take into account the diversity of adjacency relations and the heterogeneity of adjacency distances among area objects, resulting in insufficient measurement information. This article proposes a method for measuring area map
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Existing methods for measuring the spatial information of area maps fail to take into account the diversity of adjacency relations and the heterogeneity of adjacency distances among area objects, resulting in insufficient measurement information. This article proposes a method for measuring area map information that considers the diversity of the node–edge and Gestalt principles. Firstly, this method utilizes the adjacency relations between the Voronoi diagram of area objects to construct an adjacency graph that characterizes the spatial distribution of area objects in area maps. This adjacency graph serves as the information representation of area maps. Secondly, the method selects four characteristic indicators, namely geometric information, node degree, adjacency distance, and adjacency strength, to represent the diversity of nodes and edges in the graph that affect spatial information. Finally, nodes in the adjacency graph are taken as the basic units, and the spatial information of area maps is comprehensively calculated by integrating the four characteristics that represent spatial information. To verify the validity and rationality of the proposed method, a dataset of continuously simplified area maps and a dataset of artificially simulated degrees of randomness were designed to evaluate the performance of the existing method and the method proposed in this paper. The results indicate that the correlation between the measurement results obtained by the method proposed in this paper and the degree of disorder is as high as 0.94, outperforming the existing representative methods. Additionally, the correlation between the measurement results of this method and the degree of simplification reaches 1, indicating that the variation range of the measured values is more consistent with the cognitive assumptions based on artificial simulations compared to the existing methods. The experimental results show that the method proposed in this paper is an effective metric approach for representing spatial information in area maps.
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(This article belongs to the Special Issue Crowd-Sourced Data and Deep Learning in Remote Sensing: Methods and Applications)
Open AccessArticle
Numerical Investigations of the Kinetic Behavior of Adhering Droplets on the Inclined Windshield in Airflows
by
Fei Dong, Xing Xu and Li Xin
Appl. Sci. 2024, 14(9), 3763; https://doi.org/10.3390/app14093763 (registering DOI) - 28 Apr 2024
Abstract
A theoretical foundation for implementing surface self-cleaning can be provided by analyzing the motion of adhering droplets in airflow. When driving in rainy circumstances, self-cleaning windshield technology can efficiently guarantee driver safety. In this study, the CLSVOF method is employed to simulate a
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A theoretical foundation for implementing surface self-cleaning can be provided by analyzing the motion of adhering droplets in airflow. When driving in rainy circumstances, self-cleaning windshield technology can efficiently guarantee driver safety. In this study, the CLSVOF method is employed to simulate a three-dimensional wind tunnel model, enabling an investigation into the dynamics of droplets adhering to a windshield under the influence of airflow. Subsequent analysis mainly focuses on the impacts of wind velocity and droplet size on the motion patterns and morphological characteristics of the droplets. The temporal evolution of the forces acting on the droplets is examined, along with a comparative analysis of the predominant forces driving droplet motion against other forms of resistance. The results demonstrate that the motion patterns of the droplets can be broadly categorized into three phases: accelerated decline, forces equilibrium, and accelerated climb. As wind speed increases, there is a noticeable reduction in the wetting length Ld, while the height of the droplets H and the dominant force influencing their motion shift from gravitational component Fgsinα to wind traction force Fwind. Moreover, an increase in droplet size accentuates the lag in changes to wetting length, droplet height, and the contact angle.
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(This article belongs to the Section Applied Physics General)
Open AccessArticle
Neuromuscular Capabilities in Top-Level Weightlifters and Their Association with Weightlifting Performance
by
Marcos A. Soriano, Francisco J. Flores, Juan Lama-Arenales, Miguel Fernández-del-Olmo and Paul Comfort
Appl. Sci. 2024, 14(9), 3762; https://doi.org/10.3390/app14093762 (registering DOI) - 28 Apr 2024
Abstract
The aim of this study was to determine the associations between the front and back squat, countermovement jump (CMJ) and deep squat jump (DSJ) force–time metrics, and weightlifting performance in top-level weightlifters. Thirteen top-level weightlifters who classified for the World Championship 2023 participated.
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The aim of this study was to determine the associations between the front and back squat, countermovement jump (CMJ) and deep squat jump (DSJ) force–time metrics, and weightlifting performance in top-level weightlifters. Thirteen top-level weightlifters who classified for the World Championship 2023 participated. The heaviest successful snatch and clean and jerk were recorded within a preparation session as performance indicators. The front and back squat one-repetition maximums (1RMs) were evaluated in separate training sessions. The average of three maximum CMJs and DSJs were recorded using a force plate, and jump height, propulsive net impulse, and peak power were calculated for further analysis. Pearson’s correlation coefficients were used to determine the associations between variables. Statistical significance was set at p ≤ 0.05. The front and back squat 1RMs were significant and nearly perfectly associated with weightlifting performance (p < 0.001, r = 0.98–0.99). CMJ and DSJ propulsive net impulse displayed nearly perfect associations with weightlifting performance (p < 0.001, r = 0.96–0.99), while jump height is a less promising metric to assess the weightlifters’ ballistic capabilities. This study reinforces that lower body maximum strength and ballistic capabilities are closely associated with top-level weightlifters’ performance and are of practical importance to monitor their neuromuscular function.
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(This article belongs to the Special Issue Advances in the Biomechanical Analysis of Human Movement)
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