Shijie Guo, Xuan He, Hao He, Zhijie Li, Yong Zeng, H. Tan, Jianting Zhou
This study looks into a new composite bridge deck structure that employs a corrugated steel plate as the base. The goal is to address the shortcomings of traditional deck-bearing capacity, stiffness, and stress performance. Specifically, this study investigates the shear performance and slip characteristics of this structure. To achieve this, the study analyzes the shear behavior and slip tendencies of the composite bridge deck. The study focuses on the role of shear studs and PBL (Perfobond Leiste) perforated steel plates as essential components for shear connections. The shear performance of the composite deck is analyzed based on the structure of shear connection keys such as shear studs and PBL perforated steel plates. The advantages of composite decks in terms of stiffness, self-weight, load-bearing capacity, shear resistance, slip resistance, etc., are discussed to provide a theoretical reference for practical engineering applications. The shear resistance of shear stud shear keys is investigated through shear push-out experiments, and the shear resistance of shear studs is investigated through finite element simulations based on the ABAQUS 2020 finite element software. The results showed that the shear load capacity of the shear studs increased with the increase in the height-to-diameter ratio for different diameters of the shear studs, and the range of increases was from 2% to 23%. However, when the diameter of the shear stud exceeded 22 mm, the ultimate shear capacity of the shear stud increased with the increase in the height-to-diameter ratio, and the magnitude of the increase slowed down. For the actual design of the composite deck, it is recommended to maintain a shear stud height-to-diameter ratio within the range of 9 to 12. When using a composite deck with a PBL open-hole steel plate, the maximum longitudinal slip at the plate end and within the span is only 0.28 mm and 0.0158 mm, respectively. These values are 31% and 36% lower than those of the composite deck with a peg shear key. Additionally, the vertical peeling within the span of the PBL open-hole steel plate is merely 0.46 mm, showing a 21% reduction compared to that of the shear studs. It can be seen that the PBL perforated steel plates are more effective than the shear studs in resisting slip and peel.
{"title":"Study on Shear Resistance and Structural Performance of Corrugated Steel–Concrete Composite Deck","authors":"Shijie Guo, Xuan He, Hao He, Zhijie Li, Yong Zeng, H. Tan, Jianting Zhou","doi":"10.3390/app131810112","DOIUrl":"https://doi.org/10.3390/app131810112","url":null,"abstract":"This study looks into a new composite bridge deck structure that employs a corrugated steel plate as the base. The goal is to address the shortcomings of traditional deck-bearing capacity, stiffness, and stress performance. Specifically, this study investigates the shear performance and slip characteristics of this structure. To achieve this, the study analyzes the shear behavior and slip tendencies of the composite bridge deck. The study focuses on the role of shear studs and PBL (Perfobond Leiste) perforated steel plates as essential components for shear connections. The shear performance of the composite deck is analyzed based on the structure of shear connection keys such as shear studs and PBL perforated steel plates. The advantages of composite decks in terms of stiffness, self-weight, load-bearing capacity, shear resistance, slip resistance, etc., are discussed to provide a theoretical reference for practical engineering applications. The shear resistance of shear stud shear keys is investigated through shear push-out experiments, and the shear resistance of shear studs is investigated through finite element simulations based on the ABAQUS 2020 finite element software. The results showed that the shear load capacity of the shear studs increased with the increase in the height-to-diameter ratio for different diameters of the shear studs, and the range of increases was from 2% to 23%. However, when the diameter of the shear stud exceeded 22 mm, the ultimate shear capacity of the shear stud increased with the increase in the height-to-diameter ratio, and the magnitude of the increase slowed down. For the actual design of the composite deck, it is recommended to maintain a shear stud height-to-diameter ratio within the range of 9 to 12. When using a composite deck with a PBL open-hole steel plate, the maximum longitudinal slip at the plate end and within the span is only 0.28 mm and 0.0158 mm, respectively. These values are 31% and 36% lower than those of the composite deck with a peg shear key. Additionally, the vertical peeling within the span of the PBL open-hole steel plate is merely 0.46 mm, showing a 21% reduction compared to that of the shear studs. It can be seen that the PBL perforated steel plates are more effective than the shear studs in resisting slip and peel.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41354041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The statistical modeling with ILR-RPCA-back CLR has two problems when dealing with the closure effect of geochemical data. Firstly, after performing isometric logratio (ilr) transformation, robust principal component analysis (RPCA) is employed for processing. The double-plot diagram illustrates that the element sequence transformation occurs in the first and second principal components, while the unique principal component remains unattainable. Secondly, by transforming both the score and load into the centered logratio (CLR) space using the U matrix, it is possible to obtain a score result that corresponds to the original order of elements according to the CLR = ILR·U formula. However, for obtaining a load result that corresponds to the original order of elements, an alternative formula “CLR = UT·ILR” must be used instead. In order to determine the optimal element assemblage for porphyry copper deposits, this study conducted statistical analysis on mineral assemblages from discovered deposits in the Gangdese metallogenic belt and identified Cu, Mo, Au, Ag, W, and Bi as key elements associated with porphyry copper deposits. Subsequently, by analyzing the singularities of the composite elements, the spatial overlay of the combined element is carried out, and concentration-area (C-A) fractal filtering is applied to identify the anomaly and background areas. To facilitate comparison, we conducted an analysis of various mineral and ore deposit types, revealing the following findings: (1) Combination elements exhibit superior recognition capability than single elements in porphyry copper deposits; (2) Skarn-type copper deposits unrelated to porphyry show a high degree of dissimilarity compared to those related to porphyry; (3) this method offers advantages over the single element method in evaluating porphyry gold deposits by reducing anomaly levels and initial investment during the evaluation stage for porphyry copper anomalies; (4) However, this method has limited ability in distinguishing between porphyry copper and molybdenum deposits.
{"title":"Spatial Overlay Analysis of Geochemical Singularity Index α-Value of Porphyry Cu Deposit in Gangdese Metallogenic Belt, Tibet, Western China","authors":"Shunli Zheng, Xiaojia Jiang, Shunbao Gao","doi":"10.3390/app131810123","DOIUrl":"https://doi.org/10.3390/app131810123","url":null,"abstract":"The statistical modeling with ILR-RPCA-back CLR has two problems when dealing with the closure effect of geochemical data. Firstly, after performing isometric logratio (ilr) transformation, robust principal component analysis (RPCA) is employed for processing. The double-plot diagram illustrates that the element sequence transformation occurs in the first and second principal components, while the unique principal component remains unattainable. Secondly, by transforming both the score and load into the centered logratio (CLR) space using the U matrix, it is possible to obtain a score result that corresponds to the original order of elements according to the CLR = ILR·U formula. However, for obtaining a load result that corresponds to the original order of elements, an alternative formula “CLR = UT·ILR” must be used instead. In order to determine the optimal element assemblage for porphyry copper deposits, this study conducted statistical analysis on mineral assemblages from discovered deposits in the Gangdese metallogenic belt and identified Cu, Mo, Au, Ag, W, and Bi as key elements associated with porphyry copper deposits. Subsequently, by analyzing the singularities of the composite elements, the spatial overlay of the combined element is carried out, and concentration-area (C-A) fractal filtering is applied to identify the anomaly and background areas. To facilitate comparison, we conducted an analysis of various mineral and ore deposit types, revealing the following findings: (1) Combination elements exhibit superior recognition capability than single elements in porphyry copper deposits; (2) Skarn-type copper deposits unrelated to porphyry show a high degree of dissimilarity compared to those related to porphyry; (3) this method offers advantages over the single element method in evaluating porphyry gold deposits by reducing anomaly levels and initial investment during the evaluation stage for porphyry copper anomalies; (4) However, this method has limited ability in distinguishing between porphyry copper and molybdenum deposits.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42755648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fuyang Ke, Xiangxiang Hu, Guan Hong, Lulu Ming, Bao Song
Research concerning the response characteristics of lower atmosphere to volcanic eruption is a key and hot topic in the field of volcanic environment research. Against the background of a submarine volcano in the South Pacific island country of Hunga Tonga–Hunga Ha’apai (HTHH) on 15 January 2022, this paper explores the response characteristics of this volcanic eruption on environmental factors in the lower atmosphere region using a priori data such as ERA5 reanalysis data, water vapor data from GNSS inversion and surface temperature data from Landsat inversion for the Tonga Islands region. Among them, (1) The amount of precipitable water (PWV) in Tonga was abnormally high on 15 January. (2) The water vapor flux was mainly in the lower space below 850 hPa. (3) The average surface temperature in December 2021 was higher. In February 2022, the average surface temperature was lower. (4) There was a low-pressure center near 30° S on the south side of Tonga volcano on 14 January, and a new low-pressure center was formed on the east side of Tonga volcano after the eruption of Tonga volcano on 15 January. Furthermore, the precipitation area of Tonga increased in January and decreased in February 2022. The PWV values, water vapor fluxes, temperature and circulation response characteristics, and precipitation characteristics show that the volcanic eruption affected part of the atmospheric and oceanic circulation, and water vapor was transported to the low-pressure center along the direction of atmospheric circulation. With the continuous water vapor transport, precipitation formed in Tonga, and the intensity and area of precipitation in Tonga increased significantly in January. Thus, the volcanic eruption could have significantly triggered the response between the low-pressure center, PWV, precipitation and surface temperature in the lower atmosphere, which influenced the environmental characteristics of this eruption.
{"title":"Characteristics and Evolution of the Response of the Lower Atmosphere to the Tonga Volcanic Eruption","authors":"Fuyang Ke, Xiangxiang Hu, Guan Hong, Lulu Ming, Bao Song","doi":"10.3390/app131810095","DOIUrl":"https://doi.org/10.3390/app131810095","url":null,"abstract":"Research concerning the response characteristics of lower atmosphere to volcanic eruption is a key and hot topic in the field of volcanic environment research. Against the background of a submarine volcano in the South Pacific island country of Hunga Tonga–Hunga Ha’apai (HTHH) on 15 January 2022, this paper explores the response characteristics of this volcanic eruption on environmental factors in the lower atmosphere region using a priori data such as ERA5 reanalysis data, water vapor data from GNSS inversion and surface temperature data from Landsat inversion for the Tonga Islands region. Among them, (1) The amount of precipitable water (PWV) in Tonga was abnormally high on 15 January. (2) The water vapor flux was mainly in the lower space below 850 hPa. (3) The average surface temperature in December 2021 was higher. In February 2022, the average surface temperature was lower. (4) There was a low-pressure center near 30° S on the south side of Tonga volcano on 14 January, and a new low-pressure center was formed on the east side of Tonga volcano after the eruption of Tonga volcano on 15 January. Furthermore, the precipitation area of Tonga increased in January and decreased in February 2022. The PWV values, water vapor fluxes, temperature and circulation response characteristics, and precipitation characteristics show that the volcanic eruption affected part of the atmospheric and oceanic circulation, and water vapor was transported to the low-pressure center along the direction of atmospheric circulation. With the continuous water vapor transport, precipitation formed in Tonga, and the intensity and area of precipitation in Tonga increased significantly in January. Thus, the volcanic eruption could have significantly triggered the response between the low-pressure center, PWV, precipitation and surface temperature in the lower atmosphere, which influenced the environmental characteristics of this eruption.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49531398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Kumar, V. K. Tewari, A. Chandel, C. Mehta, C. M. Pareek, C. Chethan, B. Nare
Specific energy prediction is critically important to enhance field performance of agricultural implements. It enables optimal utilization of tractor power, reduced inefficiencies, and identification of comprehensive inputs for designing energy-efficient implements. In this study, A 3-5-1 artificial neural network (ANN) model was developed to estimate specific energy requirement of a vertical axis rotor type intra-row weeding tool. The depth of operation in soil bed, soil cone index, and forward/implement speed ratio (u/v) were selected as the input variables. Soil bin investigations were conducted using the vertical axis rotor (RVA), interfaced with draft, torque, speed sensors, and data acquisition system to record dynamic forces employed during soil–tool interaction at ranges of different operating parameters. The depth of operation (DO) had the maximum influence on the specific energy requirement of the RVA, followed by the cone index (CI) and the u/v ratio. The developed ANN model was able to predict the specific energy requirements of RVA at high accuracies as indicated by high R2 (0.91), low RMSE (0.0197) and low MAE (0.0479). Findings highlight the potential of the ANN as an efficient technique for modeling soil–tool interactions under specific experimental conditions. Such estimations will eventually optimize and enhance the performance efficiency of agricultural implements in the field.
{"title":"Modelling Specific Energy Requirement for a Power-Operated Vertical Axis Rotor Type Intra-Row Weeding Tool Using Artificial Neural Network","authors":"S. Kumar, V. K. Tewari, A. Chandel, C. Mehta, C. M. Pareek, C. Chethan, B. Nare","doi":"10.3390/app131810084","DOIUrl":"https://doi.org/10.3390/app131810084","url":null,"abstract":"Specific energy prediction is critically important to enhance field performance of agricultural implements. It enables optimal utilization of tractor power, reduced inefficiencies, and identification of comprehensive inputs for designing energy-efficient implements. In this study, A 3-5-1 artificial neural network (ANN) model was developed to estimate specific energy requirement of a vertical axis rotor type intra-row weeding tool. The depth of operation in soil bed, soil cone index, and forward/implement speed ratio (u/v) were selected as the input variables. Soil bin investigations were conducted using the vertical axis rotor (RVA), interfaced with draft, torque, speed sensors, and data acquisition system to record dynamic forces employed during soil–tool interaction at ranges of different operating parameters. The depth of operation (DO) had the maximum influence on the specific energy requirement of the RVA, followed by the cone index (CI) and the u/v ratio. The developed ANN model was able to predict the specific energy requirements of RVA at high accuracies as indicated by high R2 (0.91), low RMSE (0.0197) and low MAE (0.0479). Findings highlight the potential of the ANN as an efficient technique for modeling soil–tool interactions under specific experimental conditions. Such estimations will eventually optimize and enhance the performance efficiency of agricultural implements in the field.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45236576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In addressing the challenge of tracking moving targets at sea, our focus has been directed towards the development of a reconstruction methodology founded upon satellite orbital manoeuvres. This endeavour has led us to devise a predictive model for manoeuvres within a geographic coordinate system, alongside the creation of a three-phase orbital manoeuvre model. A Non-dominant Sorting Adaptive Memetic (NSAM) algorithm is proposed in this paper, which is a two-layer multi-objective optimization algorithm that retains the advantages of evolutionary algorithms based on the population’s evolution and has an excellent local optimization ability of local search algorithms. The proposed algorithm can be used to solve multi-objective optimization problems. By comparing the target observation results before and after the satellite reconstruction simulation, it can be concluded that the orbital manoeuvring can effectively improve the observation probability and observation duration of the target at a certain speed. The orbital manoeuvre model created in this paper provides a certain methodical support for the tracking problem of moving targets at sea.
{"title":"Research on the Reconfiguration Method of Space-Based Exploration Satellite Constellations for Moving Target Tracking at Sea","authors":"Yao Wang, Junren Luo, Xueqiang Gu, Wanpeng Zhang","doi":"10.3390/app131810103","DOIUrl":"https://doi.org/10.3390/app131810103","url":null,"abstract":"In addressing the challenge of tracking moving targets at sea, our focus has been directed towards the development of a reconstruction methodology founded upon satellite orbital manoeuvres. This endeavour has led us to devise a predictive model for manoeuvres within a geographic coordinate system, alongside the creation of a three-phase orbital manoeuvre model. A Non-dominant Sorting Adaptive Memetic (NSAM) algorithm is proposed in this paper, which is a two-layer multi-objective optimization algorithm that retains the advantages of evolutionary algorithms based on the population’s evolution and has an excellent local optimization ability of local search algorithms. The proposed algorithm can be used to solve multi-objective optimization problems. By comparing the target observation results before and after the satellite reconstruction simulation, it can be concluded that the orbital manoeuvring can effectively improve the observation probability and observation duration of the target at a certain speed. The orbital manoeuvre model created in this paper provides a certain methodical support for the tracking problem of moving targets at sea.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41877310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Clustering, an unsupervised machine learning technique, plays a crucial role in partitioning unlabeled data into meaningful groups. K-means, known for its simplicity, has gained popularity as a clustering method. However, both K-means and the LAC algorithm, which utilize learning automata, are sensitive to the selection of initial points. To overcome this limitation, we propose an enhanced LAC algorithm based on the K-Harmonic means approach. We evaluate its performance on seven datasets and demonstrate its superiority over other representative algorithms. Moreover, we tailor this algorithm to address the controller placement problem in software-defined networks, a critical field in this context. To optimize relevant parameters such as switch–controller delay, intercontroller delay, and load balancing, we leverage learning automata. In our comparative analysis conducted in Python, we benchmark our algorithm against spectral, K-means, and LAC algorithms on four different network topologies. The results unequivocally show that our proposed algorithm outperforms the others, achieving a significant improvement ranging from 3 to 11 percent. This research contributes to the advancement of clustering techniques and their practical application in software-defined networks.
{"title":"Improved Learning-Automata-Based Clustering Method for Controlled Placement Problem in SDN","authors":"Azam Amin, Mohsen Jahanshahi, M. Meybodi","doi":"10.3390/app131810073","DOIUrl":"https://doi.org/10.3390/app131810073","url":null,"abstract":"Clustering, an unsupervised machine learning technique, plays a crucial role in partitioning unlabeled data into meaningful groups. K-means, known for its simplicity, has gained popularity as a clustering method. However, both K-means and the LAC algorithm, which utilize learning automata, are sensitive to the selection of initial points. To overcome this limitation, we propose an enhanced LAC algorithm based on the K-Harmonic means approach. We evaluate its performance on seven datasets and demonstrate its superiority over other representative algorithms. Moreover, we tailor this algorithm to address the controller placement problem in software-defined networks, a critical field in this context. To optimize relevant parameters such as switch–controller delay, intercontroller delay, and load balancing, we leverage learning automata. In our comparative analysis conducted in Python, we benchmark our algorithm against spectral, K-means, and LAC algorithms on four different network topologies. The results unequivocally show that our proposed algorithm outperforms the others, achieving a significant improvement ranging from 3 to 11 percent. This research contributes to the advancement of clustering techniques and their practical application in software-defined networks.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45781854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shengpeng Zheng, Xiaoping Xiao, Xin Ma, Zisheng Li, Yitao Liu, J. Li, Dongyu Wang, Xiang Li
This study investigates the sealing performance of a combined sealing structure under extremely high and low temperature conditions, considering potential issues like high-temperature aging and low-temperature brittle fracture, which can lead to sealing failure. EPDM rubber underwent uniaxial compression tests at high, low, and normal temperatures, then the sealing performance under extreme working conditions was compared with that under normal temperature conditions. Additionally, the influences of gasket parameters and gas pressure on the sealing performance were analyzed. The result shows that compared with the normal temperature conditions, the maximum von Mises stress is reduced by 65% and the effective sealing length and the maximum contact pressure is reduced by 40% under the high temperature conditions, while the maximum von Mises stress is increased by 7 times and the maximum contact pressure is increased by a remarkable 7 times under the low temperature conditions. In the range of 10–100 MPa, the increase in gas pressure aggravates the O-ring stress concentration and improves the sealing performance relatively. When the thickness of gasket is 0.85–1.05 mm, the stress concentration of the O-ring is lighter and the sealing performance is better.
{"title":"Research on Dynamic Sealing Performance of Combined Sealing Structure under Extreme Working Conditions","authors":"Shengpeng Zheng, Xiaoping Xiao, Xin Ma, Zisheng Li, Yitao Liu, J. Li, Dongyu Wang, Xiang Li","doi":"10.3390/app131810100","DOIUrl":"https://doi.org/10.3390/app131810100","url":null,"abstract":"This study investigates the sealing performance of a combined sealing structure under extremely high and low temperature conditions, considering potential issues like high-temperature aging and low-temperature brittle fracture, which can lead to sealing failure. EPDM rubber underwent uniaxial compression tests at high, low, and normal temperatures, then the sealing performance under extreme working conditions was compared with that under normal temperature conditions. Additionally, the influences of gasket parameters and gas pressure on the sealing performance were analyzed. The result shows that compared with the normal temperature conditions, the maximum von Mises stress is reduced by 65% and the effective sealing length and the maximum contact pressure is reduced by 40% under the high temperature conditions, while the maximum von Mises stress is increased by 7 times and the maximum contact pressure is increased by a remarkable 7 times under the low temperature conditions. In the range of 10–100 MPa, the increase in gas pressure aggravates the O-ring stress concentration and improves the sealing performance relatively. When the thickness of gasket is 0.85–1.05 mm, the stress concentration of the O-ring is lighter and the sealing performance is better.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43934302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The entry and exit method is a simple and practical method to decide the critical slip surface of slope. Nevertheless, it has the drawback of sacrificing computational efficiency to improve search accuracy. To solve this problem, this paper proposes an improved entry and exit approach to search for the critical slip surface. On basis of the random fields produced by applying the Karhunen–Loève expansion approach, the simplified Bishop’s method combined with the improved entry and exit method is used to decide the critical slip surface and its relevant minimum factor of security. Then, the failure probability is calculated by conducting Monte Carlo simulation. Two instances are reanalyzed to validate the precision and efficiency of the method. Meaningful comparisons are made to show the calculating precision and calculating efficiency of the improved entry and exit method in searching for the minimum security factor of slope, based on which the effect of the reduced searching range on slope reliability was explored. The outcomes suggest that the approach offers a practical device for assessing the reliability of slopes in spatially variable soils. It can significantly enhance the computational efficiency in relatively high-computational precision of slope reliability analysis.
{"title":"Application of the Improved Entry and Exit Method in Slope Reliability Analysis","authors":"Rong Yang, Boyan Sun, Yukuai Wan, Xinyue Gao","doi":"10.3390/app131810081","DOIUrl":"https://doi.org/10.3390/app131810081","url":null,"abstract":"The entry and exit method is a simple and practical method to decide the critical slip surface of slope. Nevertheless, it has the drawback of sacrificing computational efficiency to improve search accuracy. To solve this problem, this paper proposes an improved entry and exit approach to search for the critical slip surface. On basis of the random fields produced by applying the Karhunen–Loève expansion approach, the simplified Bishop’s method combined with the improved entry and exit method is used to decide the critical slip surface and its relevant minimum factor of security. Then, the failure probability is calculated by conducting Monte Carlo simulation. Two instances are reanalyzed to validate the precision and efficiency of the method. Meaningful comparisons are made to show the calculating precision and calculating efficiency of the improved entry and exit method in searching for the minimum security factor of slope, based on which the effect of the reduced searching range on slope reliability was explored. The outcomes suggest that the approach offers a practical device for assessing the reliability of slopes in spatially variable soils. It can significantly enhance the computational efficiency in relatively high-computational precision of slope reliability analysis.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43431314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maintaining data dependability within wireless sensor network (WSN) systems has significant importance. Nevertheless, the deployment of systems in unattended and hostile areas poses a major challenge in dealing with noise. Consequently, several investigations have been conducted to address the issue of noise-affected data recovery. Nevertheless, previous research has primarily focused on the internal noise of the system. Neglecting to include external factors that impact the WSN system in the study might lead to findings that are not true to reality. Hence, this research takes into account both internal and external noise factors, such as rain, fog, or snow conditions. Moreover, in order to maintain the temporal characteristics and intersensor relationships, the data from multiple sensor nodes are consolidated into a two-dimensional matrix format. The stacked convolutional autoencoder (SCAE) model is proposed, which has the capability to extract data features. The stack design of the SCAE enables it to effectively mitigate the issue of vanishing gradients. Moreover, the weight sharing approach used between the two subnetworks also enhances the efficiency of the weight initialization procedure. Thorough experiments are conducted using both simulated WSN systems and real-world sensing data. Experimental results demonstrate that the SCAE outperforms existing methods for reconstructing noisy data.
{"title":"Noise-Tolerant Data Reconstruction Based on Convolutional Autoencoder for Wireless Sensor Network","authors":"Trinh Thuc Lai, Tuan Phong Tran, Jaehyuk Cho, Myung-Sig Yoo","doi":"10.3390/app131810090","DOIUrl":"https://doi.org/10.3390/app131810090","url":null,"abstract":"Maintaining data dependability within wireless sensor network (WSN) systems has significant importance. Nevertheless, the deployment of systems in unattended and hostile areas poses a major challenge in dealing with noise. Consequently, several investigations have been conducted to address the issue of noise-affected data recovery. Nevertheless, previous research has primarily focused on the internal noise of the system. Neglecting to include external factors that impact the WSN system in the study might lead to findings that are not true to reality. Hence, this research takes into account both internal and external noise factors, such as rain, fog, or snow conditions. Moreover, in order to maintain the temporal characteristics and intersensor relationships, the data from multiple sensor nodes are consolidated into a two-dimensional matrix format. The stacked convolutional autoencoder (SCAE) model is proposed, which has the capability to extract data features. The stack design of the SCAE enables it to effectively mitigate the issue of vanishing gradients. Moreover, the weight sharing approach used between the two subnetworks also enhances the efficiency of the weight initialization procedure. Thorough experiments are conducted using both simulated WSN systems and real-world sensing data. Experimental results demonstrate that the SCAE outperforms existing methods for reconstructing noisy data.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42412591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yang Huang, Shaolei Xu, Xingyu Gao, Chuannen Wei, Yang Zhang, Mingfeng Li
An intelligent, vision-guided welding robot is highly desired in machinery manufacturing, the ship industry, and vehicle engineering. The performance of the system greatly depends on the effective identification of weld seam features and the three-dimensional (3D) reconstruction of the weld seam position in a complex industrial environment. In this paper, a 3D visual sensing system with a structured laser projector and CCD camera is developed to obtain the geometry information of fillet weld seams in robot welding. By accounting for the inclination characteristics of the laser stripe in fillet welding, a Gaussian-weighted PCA-based laser center line extraction method is proposed. Smoother laser centerlines can be obtained at large, inclined angles. Furthermore, an improved chord-to-point distance accumulation (CPDA) method with polygon approximation is proposed to identify the feature corner location in center line images. The proposed method is validated numerically with simulated piece-wise linear laser stripes and experimentally with automated robot welding. By comparing this method with the grayscale gravity method, Hessian-matrix-based method, and conventional CPDA method, the proposed improved CPDA method with PCA center extraction is shown to have high accuracy and robustness in noisy welding environments. The proposed method meets the need for vision-aided automated welding robots by achieving greater than 95% accuracy in corner feature point identification in fillet welding.
{"title":"Feature Point Identification in Fillet Weld Joints Using an Improved CPDA Method","authors":"Yang Huang, Shaolei Xu, Xingyu Gao, Chuannen Wei, Yang Zhang, Mingfeng Li","doi":"10.3390/app131810108","DOIUrl":"https://doi.org/10.3390/app131810108","url":null,"abstract":"An intelligent, vision-guided welding robot is highly desired in machinery manufacturing, the ship industry, and vehicle engineering. The performance of the system greatly depends on the effective identification of weld seam features and the three-dimensional (3D) reconstruction of the weld seam position in a complex industrial environment. In this paper, a 3D visual sensing system with a structured laser projector and CCD camera is developed to obtain the geometry information of fillet weld seams in robot welding. By accounting for the inclination characteristics of the laser stripe in fillet welding, a Gaussian-weighted PCA-based laser center line extraction method is proposed. Smoother laser centerlines can be obtained at large, inclined angles. Furthermore, an improved chord-to-point distance accumulation (CPDA) method with polygon approximation is proposed to identify the feature corner location in center line images. The proposed method is validated numerically with simulated piece-wise linear laser stripes and experimentally with automated robot welding. By comparing this method with the grayscale gravity method, Hessian-matrix-based method, and conventional CPDA method, the proposed improved CPDA method with PCA center extraction is shown to have high accuracy and robustness in noisy welding environments. The proposed method meets the need for vision-aided automated welding robots by achieving greater than 95% accuracy in corner feature point identification in fillet welding.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42880815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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