Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012016
Qiwen Wu, Xi Zhao
In the digitization process of the construction industry, it is frequently necessary to use BIM as a digital model carrier, and the registration between BIM and point cloud is a crucial step in BIM applications. Most existing 3D registration methods, such as the ICP algorithm, are capable of aligning point clouds. However, these classical methods are subject to the influence of numerous points contained within the point cloud, relying heavily on point-to-point correlations. Consequently, it is challenging to extend these algorithms to register with other forms of spatial information, such as BIM models, beyond the point cloud. Considering that planes are basic geometric elements in building BIM models, this paper proposes a novel method for aligning BIM models with point clouds by matching planar features. The method extracts planes from point clouds using an enhanced region growing algorithm, directly parsing the planar geometric information from BIM in IFC format. After completing the matching of plane groups, the optimal solution is calculated using a weighted least squares method. The experimental results indicate that the proposed method can achieve successful registration between the BIM model and point cloud, with a lower RMSE of 5.73mm compared to the registration method using RANSAC+ICP on the same dataset.
{"title":"A Registration Method Based on Planar Features Between BIM Model and Point Cloud","authors":"Qiwen Wu, Xi Zhao","doi":"10.1088/1742-6596/2833/1/012016","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012016","url":null,"abstract":"In the digitization process of the construction industry, it is frequently necessary to use BIM as a digital model carrier, and the registration between BIM and point cloud is a crucial step in BIM applications. Most existing 3D registration methods, such as the ICP algorithm, are capable of aligning point clouds. However, these classical methods are subject to the influence of numerous points contained within the point cloud, relying heavily on point-to-point correlations. Consequently, it is challenging to extend these algorithms to register with other forms of spatial information, such as BIM models, beyond the point cloud. Considering that planes are basic geometric elements in building BIM models, this paper proposes a novel method for aligning BIM models with point clouds by matching planar features. The method extracts planes from point clouds using an enhanced region growing algorithm, directly parsing the planar geometric information from BIM in IFC format. After completing the matching of plane groups, the optimal solution is calculated using a weighted least squares method. The experimental results indicate that the proposed method can achieve successful registration between the BIM model and point cloud, with a lower RMSE of 5.73mm compared to the registration method using RANSAC+ICP on the same dataset.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199372","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}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012007
Sherry J.H Feng, Edmund M-K Lai, Weihua Li
Data augmentation is necessary if the amount of training data is insufficient for supervised learning. For natural language processing tasks, obtaining good quality augmented data is not easy. This paper introduces GATFilter, a novel method for filtering out inappropriate augmented textual data for text classification (TC). Utilizing geometric concepts, more specifically the principle component and convex hull analyses, this method adeptly preserves the semantic integrity of words within augmented texts. GATFilter is versatile and applicable across various types of textual augmentation methods. Experiments using several datasets and augmentation strategies showed that classifiers trained with GATFilter-filtered augmented data sets showed improvements in key performance metrics, including accuracy, precision, recall, and F1 score. The method’s efficacy is notably influenced by the quality of the underlying augmentation techniques, indicating its potential to complement and refine various text augmentation strategies. Furthermore, our analysis showed that GATFilter is particularly able to amplify the effectiveness of methods that generate good quality augmented data. GATFilter is openly available online on Github1, and as a Python package2.
{"title":"A Geometric Approach to Textual Augmented Data Filtering","authors":"Sherry J.H Feng, Edmund M-K Lai, Weihua Li","doi":"10.1088/1742-6596/2833/1/012007","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012007","url":null,"abstract":"Data augmentation is necessary if the amount of training data is insufficient for supervised learning. For natural language processing tasks, obtaining good quality augmented data is not easy. This paper introduces GATFilter, a novel method for filtering out inappropriate augmented textual data for text classification (TC). Utilizing geometric concepts, more specifically the principle component and convex hull analyses, this method adeptly preserves the semantic integrity of words within augmented texts. GATFilter is versatile and applicable across various types of textual augmentation methods. Experiments using several datasets and augmentation strategies showed that classifiers trained with GATFilter-filtered augmented data sets showed improvements in key performance metrics, including accuracy, precision, recall, and F1 score. The method’s efficacy is notably influenced by the quality of the underlying augmentation techniques, indicating its potential to complement and refine various text augmentation strategies. Furthermore, our analysis showed that GATFilter is particularly able to amplify the effectiveness of methods that generate good quality augmented data. GATFilter is openly available online on Github<sup>1</sup>, and as a Python package<sup>2</sup>.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199380","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}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012019
Deng Huiyong, Sun Haitao, Cui Kaibo, Zhao Yulong, Yin Fei
The feeding process of the feeding system in the power transmission chain was a high-speed, high impact, non-stationary process, and easy to detect functional faults, aimed at the problem, based on nonlinear multi-body dynamics and Dubowsky contact modeling theory, a gear transmission modeling method including backlash was proposed. A dynamic simulation model of the feeding system injected with gear wear fault was established, and the system dynamic performance under different wear levels was analyzed. The research results show that due to the wear of the gear teeth, the contact force between the teeth increased by about 70%. When the wear of a single tooth pair increased to 0.2mm, there would be jamming faults caused by delayed chain throwing. The research results provided support for the optimization and improvement of the feeding system.
{"title":"Research on failure simulation of the feeding system considering transmission gear wear","authors":"Deng Huiyong, Sun Haitao, Cui Kaibo, Zhao Yulong, Yin Fei","doi":"10.1088/1742-6596/2833/1/012019","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012019","url":null,"abstract":"The feeding process of the feeding system in the power transmission chain was a high-speed, high impact, non-stationary process, and easy to detect functional faults, aimed at the problem, based on nonlinear multi-body dynamics and Dubowsky contact modeling theory, a gear transmission modeling method including backlash was proposed. A dynamic simulation model of the feeding system injected with gear wear fault was established, and the system dynamic performance under different wear levels was analyzed. The research results show that due to the wear of the gear teeth, the contact force between the teeth increased by about 70%. When the wear of a single tooth pair increased to 0.2mm, there would be jamming faults caused by delayed chain throwing. The research results provided support for the optimization and improvement of the feeding system.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199370","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}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012011
Zhao Feng, Qi Min, Xu Hua
Traditional segmentation methods can only segment grayscale images, which limits their application; The segmentation process often depends on the doctor’s experience, which can lead to subjective factors affecting the results; Therefore, the accuracy and efficiency of segmentation are difficult to achieve practical application results. The deep learning model is a structural model that mimics the neural connections within the human brain. The deep learning model can accurately extract multi-level features of key information in images from low-level to high-level, and provide feedback on data interpretation, thereby achieving accurate and efficient image segmentation results. Introducing deep learning algorithms into medical image segmentation can accurately express the key information at a deeper level in spinal images, achieving better image segmentation results.
{"title":"Research on the Application of Deep Learning in Human Spinal Image Segmentation","authors":"Zhao Feng, Qi Min, Xu Hua","doi":"10.1088/1742-6596/2833/1/012011","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012011","url":null,"abstract":"Traditional segmentation methods can only segment grayscale images, which limits their application; The segmentation process often depends on the doctor’s experience, which can lead to subjective factors affecting the results; Therefore, the accuracy and efficiency of segmentation are difficult to achieve practical application results. The deep learning model is a structural model that mimics the neural connections within the human brain. The deep learning model can accurately extract multi-level features of key information in images from low-level to high-level, and provide feedback on data interpretation, thereby achieving accurate and efficient image segmentation results. Introducing deep learning algorithms into medical image segmentation can accurately express the key information at a deeper level in spinal images, achieving better image segmentation results.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199378","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}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012021
Kaibo Cui, Haitao Sun, Huiyong Deng
UAV poses a serious threat to ground troops and combat personnel in modern operations, and fighting against UAV is called an important task of air defense operations. Taking DJI UAV as the object, this article researches the typical blasting debris of the prefabricated damage effect of drone target through modeling simulation and simulation calculation, which is focused on damage simulation analysis of the drone battery, power plant, camera and other key components, and studies the damage condition of fragments in different direction and at different speeds, which can improve theoretical basis and reference for fighting against the drone and its swarm.
{"title":"Simulation Study of the Damage Effect of Typical Fragment on UAV Target","authors":"Kaibo Cui, Haitao Sun, Huiyong Deng","doi":"10.1088/1742-6596/2833/1/012021","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012021","url":null,"abstract":"UAV poses a serious threat to ground troops and combat personnel in modern operations, and fighting against UAV is called an important task of air defense operations. Taking DJI UAV as the object, this article researches the typical blasting debris of the prefabricated damage effect of drone target through modeling simulation and simulation calculation, which is focused on damage simulation analysis of the drone battery, power plant, camera and other key components, and studies the damage condition of fragments in different direction and at different speeds, which can improve theoretical basis and reference for fighting against the drone and its swarm.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199368","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}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012022
Li Mingxuan, Cui Yanru, Zhu Yifan, Wang Weiping, Li Xiaobo, Wang Xinfeng
Since 2023, local conflicts have intensified and local wars have occurred frequently. The term “order strike” has appeared on the battlefield many times and is one of the hot spots in the study of modern warfare. Order strike has the characteristics of small scale, fast response, low cost, etc. It is a distributed combat mode proposed by the US military on the basis of theories of “Kill Chain” and “Mosaic Warfare”, etc. This paper takes the UAV penetration and strike against large targets as research case, and builds a new type of UAV penetration and strike combat platform based on the theory of “order strike”, combined with the technologies of “ StarLink “ satellite network reconnaissance and intelligent UAV control. This combat platform can continuously monitor the designated area and effectively strike the hostile targets invading the area. Finally, we conducted a preliminary simulation and initial effectiveness evaluation of the method proposed in this paper through multi-agent simulation.
{"title":"Modeling and Simulation of UAV Task Assignment and Execution in Designated Area Based on Order Strike Theory","authors":"Li Mingxuan, Cui Yanru, Zhu Yifan, Wang Weiping, Li Xiaobo, Wang Xinfeng","doi":"10.1088/1742-6596/2833/1/012022","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012022","url":null,"abstract":"Since 2023, local conflicts have intensified and local wars have occurred frequently. The term “order strike” has appeared on the battlefield many times and is one of the hot spots in the study of modern warfare. Order strike has the characteristics of small scale, fast response, low cost, etc. It is a distributed combat mode proposed by the US military on the basis of theories of “Kill Chain” and “Mosaic Warfare”, etc. This paper takes the UAV penetration and strike against large targets as research case, and builds a new type of UAV penetration and strike combat platform based on the theory of “order strike”, combined with the technologies of “ StarLink “ satellite network reconnaissance and intelligent UAV control. This combat platform can continuously monitor the designated area and effectively strike the hostile targets invading the area. Finally, we conducted a preliminary simulation and initial effectiveness evaluation of the method proposed in this paper through multi-agent simulation.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199369","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}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012009
Yuankai Liu, Feng Guo, Qian Zhao, Chuankun Wu
As the utilization of IoT devices becomes more widespread, the variety of attacks targeting these devices is also increasing. Traditional intrusion detection systems in IoT environments often struggle to effectively recognize the diverse types of attacks. Therefore, this study proposes a Residual Memory Convolutional Neural Network (RMCNN) model incorporating an attention mechanism, aimed at improving the accuracy and efficiency of multi-class attack detection in IoT environments. The model begins by extracting spatial features from traffic data through Convolutional Neural Network (CNN) layers, and then captures dynamic changes in time series data using Gated Recurrent Unit (GRU). Subsequently, a multi-head attention mechanism is employed to reinforce focus on critical information. Finally, the outputs from the GRU are combined with those from the multi-head attention mechanism via residual connections, enhancing the model’s learning capabilities and improving the recognition accuracy of various attack types. Verified through experiments on the CICIOT2023 dataset, the model achieved an F1 score of 97.29%, indicating significant improvements in the detection performance of multi-class attacks and confirming its applicability and effectiveness in the field of IoT security.
随着物联网设备的使用越来越广泛，针对这些设备的各种攻击也越来越多。物联网环境中的传统入侵检测系统往往难以有效识别各种类型的攻击。因此，本研究提出了一种包含注意力机制的残差记忆卷积神经网络（RMCNN）模型，旨在提高物联网环境中多类攻击检测的准确性和效率。该模型首先通过卷积神经网络（CNN）层从流量数据中提取空间特征，然后使用门控递归单元（GRU）捕捉时间序列数据的动态变化。随后，采用多头关注机制，加强对关键信息的关注。最后，GRU 的输出通过残差连接与多头注意力机制的输出相结合，从而增强了模型的学习能力，提高了对各种攻击类型的识别准确率。通过在 CICIOT2023 数据集上的实验验证，该模型的 F1 得分为 97.29%，表明多类攻击的检测性能有了显著提高，证实了其在物联网安全领域的适用性和有效性。
{"title":"An Intrusion Detection Model Based on a Residual Memory Convolutional Neural Network with Attention Mechanism","authors":"Yuankai Liu, Feng Guo, Qian Zhao, Chuankun Wu","doi":"10.1088/1742-6596/2833/1/012009","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012009","url":null,"abstract":"As the utilization of IoT devices becomes more widespread, the variety of attacks targeting these devices is also increasing. Traditional intrusion detection systems in IoT environments often struggle to effectively recognize the diverse types of attacks. Therefore, this study proposes a Residual Memory Convolutional Neural Network (RMCNN) model incorporating an attention mechanism, aimed at improving the accuracy and efficiency of multi-class attack detection in IoT environments. The model begins by extracting spatial features from traffic data through Convolutional Neural Network (CNN) layers, and then captures dynamic changes in time series data using Gated Recurrent Unit (GRU). Subsequently, a multi-head attention mechanism is employed to reinforce focus on critical information. Finally, the outputs from the GRU are combined with those from the multi-head attention mechanism via residual connections, enhancing the model’s learning capabilities and improving the recognition accuracy of various attack types. Verified through experiments on the CICIOT2023 dataset, the model achieved an F1 score of 97.29%, indicating significant improvements in the detection performance of multi-class attacks and confirming its applicability and effectiveness in the field of IoT security.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"144 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199379","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}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012020
Sun Haitao, Liang Hui, Deng Huiyong, Cui Kaibo, Jiang Youcai
The automatic gun feeding system is an important mechanism for achieving continuous shooting, but due to its complex structure, there is a lot of contact during firing, and its reliability is lower. To improve the reliability of the feeding system and its dynamic characteristics, a multi rigid body dynamic simulation model of the feeding system considering contact nonlinearity was established based on nonlinear dynamics theory. The dynamic characteristics of the feeding system were analyzed for single and continuous firing. The research results indicate that the presence of contact nonlinearity increases the interaction forces between components and also increases the uncertainty of component motion.
{"title":"Research on non-linear dynamic simulation model of feeding system","authors":"Sun Haitao, Liang Hui, Deng Huiyong, Cui Kaibo, Jiang Youcai","doi":"10.1088/1742-6596/2833/1/012020","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012020","url":null,"abstract":"The automatic gun feeding system is an important mechanism for achieving continuous shooting, but due to its complex structure, there is a lot of contact during firing, and its reliability is lower. To improve the reliability of the feeding system and its dynamic characteristics, a multi rigid body dynamic simulation model of the feeding system considering contact nonlinearity was established based on nonlinear dynamics theory. The dynamic characteristics of the feeding system were analyzed for single and continuous firing. The research results indicate that the presence of contact nonlinearity increases the interaction forces between components and also increases the uncertainty of component motion.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199365","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}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012008
Shuai Xiaoying, Yin Yuxia
Messages in wireless Ad hoc networks may require intermediate multi-hop forwarding from the source to the target node. To find an optimum contend-free time slots scheduling solution in Ad hoc, a TDMA (Time Division Multiple Access) scheduling scheme based on BRKGA (Biased Random-key GA) is proposed. The algorithm divides the population of generation k into elite group and rest group. The elite solutions are copied directly to the next generation. One parent from the elite group and another parent from the rest population are randomly selected to crossover a new solution. The worst Pm solutions of the population of generation k are replaced by the mutants. The simulation results demonstrate that the TDMA based on BRKGA exhibits better performance in terms of lower frame length and higher channel utilization.
无线 Ad hoc 网络中的信息可能需要从源节点到目标节点的中间多跳转发。为了在 Ad hoc 中找到最佳的无竞争时隙调度方案，本文提出了一种基于 BRKGA（有偏随机密钥 GA）的 TDMA（时分多址）调度方案。该算法将第 k 代种群分为精英组和其他组。精英解直接复制到下一代。从精英组中随机选取一个父代，从其他群体中随机选取另一个父代，交叉产生一个新的解。第 k 代群体中最差的 Pm 解决方案被突变体取代。仿真结果表明，基于 BRKGA 的 TDMA 在降低帧长度和提高信道利用率方面表现出更好的性能。
{"title":"Design and Implementation of TDMA Scheduling Based on BRKGA","authors":"Shuai Xiaoying, Yin Yuxia","doi":"10.1088/1742-6596/2833/1/012008","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012008","url":null,"abstract":"Messages in wireless Ad hoc networks may require intermediate multi-hop forwarding from the source to the target node. To find an optimum contend-free time slots scheduling solution in Ad hoc, a TDMA (Time Division Multiple Access) scheduling scheme based on BRKGA (Biased Random-key GA) is proposed. The algorithm divides the population of generation k into elite group and rest group. The elite solutions are copied directly to the next generation. One parent from the elite group and another parent from the rest population are randomly selected to crossover a new solution. The worst P<sub>m</sub> solutions of the population of generation k are replaced by the mutants. The simulation results demonstrate that the TDMA based on BRKGA exhibits better performance in terms of lower frame length and higher channel utilization.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199376","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}
Pub Date : 2024-07-31DOI: 10.1088/1742-6596/2805/1/012008
H Junaedi and T A Sebaey
Carbon-Aramid fiber-reinforced epoxy has been used extensively in the aerospace and automobile industries. The combination of high-strength carbon fiber and the high toughness of aramid fiber is believed to be beneficial to the structural behavior of composites. In the current study, Aramid fiber was sandwiched between carbon fiber layers to maintain high strength and toughness simultaneously. The behavior of the laminate with the presence of an open hole and single-edge notch was investigated. For justification, the response of the hybrid laminate was compared with two other laminates, one is made totally from carbon fiber-reinforced epoxy (CFRP) and the other is made from aramid fiber-reinforced epoxy (AFRP). The effect of an open hole was assessed by a tension test, while the single-edge notch effect was evaluated by the flexural test. Tensile and flexural tests were also performed on the regular samples. As per the current results, the notch sensitivity of hybrid laminate was found to be less than that of CFRP laminate. The CFRP laminate failure type was dominated by delamination. AFRP composite laminate failure was dominated by fiber breakage and crack propagation through the matrix. The hybrid composite laminates were dominated by fiber breakage of the AFRP laminates and delamination of CFRP outer layers. The flexural modulus of hybrid laminate resulted in the greatest value, followed by CFRP and AFRP. The hybrid laminate’s fracture toughness is significantly higher than that of CFRP but lower than that of AFRP.
{"title":"Carbon-Aramid Fiber/Epoxy Hybrid Composite Laminates with the Presence of Defect: An Experimental Study","authors":"H Junaedi and T A Sebaey","doi":"10.1088/1742-6596/2805/1/012008","DOIUrl":"https://doi.org/10.1088/1742-6596/2805/1/012008","url":null,"abstract":"Carbon-Aramid fiber-reinforced epoxy has been used extensively in the aerospace and automobile industries. The combination of high-strength carbon fiber and the high toughness of aramid fiber is believed to be beneficial to the structural behavior of composites. In the current study, Aramid fiber was sandwiched between carbon fiber layers to maintain high strength and toughness simultaneously. The behavior of the laminate with the presence of an open hole and single-edge notch was investigated. For justification, the response of the hybrid laminate was compared with two other laminates, one is made totally from carbon fiber-reinforced epoxy (CFRP) and the other is made from aramid fiber-reinforced epoxy (AFRP). The effect of an open hole was assessed by a tension test, while the single-edge notch effect was evaluated by the flexural test. Tensile and flexural tests were also performed on the regular samples. As per the current results, the notch sensitivity of hybrid laminate was found to be less than that of CFRP laminate. The CFRP laminate failure type was dominated by delamination. AFRP composite laminate failure was dominated by fiber breakage and crack propagation through the matrix. The hybrid composite laminates were dominated by fiber breakage of the AFRP laminates and delamination of CFRP outer layers. The flexural modulus of hybrid laminate resulted in the greatest value, followed by CFRP and AFRP. The hybrid laminate’s fracture toughness is significantly higher than that of CFRP but lower than that of AFRP.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934165","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}
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