Pub Date : 2021-10-15DOI: 10.1109/CCCI52664.2021.9583218
Feilong Du, X. Ban, Yalan Zhang, Z. Dong, H. Duan
To solve the problems of low accuracy in long time series prediction and low generality of network parameter model in the existing data-driven Lagrangian fluid simulation, a light neural network prediction model which is physics-based multi-layer shared perceptron was proposed. Each fluid particle is standardized by searching neighbor particles through the optimized parallel processing module. The neural network is used to predict the effect of each neighbor particle on the central particle. The solid-liquid two-state differentiated aggregation operation is used to predict the acceleration of each fluid particle. The experimental results show that, compared with the existing methods, the method proposed in this paper greatly improves the prediction accuracy with less time overhead, and at the same time maintains more fluid motion details. In addition, we can enables more accurate long-term fluid motion prediction. Compared with PointRNN, PointNet++ and other single-channel data-driven methods, we can better deal with the fluid-solid coupling problem, and has wider network versatility.
{"title":"Solid-liquid dual channel data-driven method for Lagrangian fluid simulation","authors":"Feilong Du, X. Ban, Yalan Zhang, Z. Dong, H. Duan","doi":"10.1109/CCCI52664.2021.9583218","DOIUrl":"https://doi.org/10.1109/CCCI52664.2021.9583218","url":null,"abstract":"To solve the problems of low accuracy in long time series prediction and low generality of network parameter model in the existing data-driven Lagrangian fluid simulation, a light neural network prediction model which is physics-based multi-layer shared perceptron was proposed. Each fluid particle is standardized by searching neighbor particles through the optimized parallel processing module. The neural network is used to predict the effect of each neighbor particle on the central particle. The solid-liquid two-state differentiated aggregation operation is used to predict the acceleration of each fluid particle. The experimental results show that, compared with the existing methods, the method proposed in this paper greatly improves the prediction accuracy with less time overhead, and at the same time maintains more fluid motion details. In addition, we can enables more accurate long-term fluid motion prediction. Compared with PointRNN, PointNet++ and other single-channel data-driven methods, we can better deal with the fluid-solid coupling problem, and has wider network versatility.","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130424820","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 : 2021-10-15DOI: 10.1109/ccci52664.2021.9583216
{"title":"CCCI 2021 Cover Page","authors":"","doi":"10.1109/ccci52664.2021.9583216","DOIUrl":"https://doi.org/10.1109/ccci52664.2021.9583216","url":null,"abstract":"","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"291 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122003555","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 : 2021-10-15DOI: 10.1109/CCCI52664.2021.9583201
Chunli Song, Xin Zhang
In this paper, we investigate the physical layer security (PLS) for reconfigurable intelligent surface (RIS)-assisted non-orthogonal multiple access (NOMA) system over generalized fading channels. Specifically, we assume that the system is based on RIS access point (AP) and RIS is used to improve the secrecy performance of two legitimate users. We adopt the FisherSnedecor F model to characterize the composite fading and shadowing channel. In particular, novel expressions for the outage probability and secrecy outage probability (SOP) are derived. We verify our analytical results through Monte-Carlo simulations. The results indicate that the secrecy performance is affected by the number of RIS reflecting elements and Fisher-Snedecor F composite fading parameters.
{"title":"Physical Layer Security of RIS-assisted NOMA Networks Over Fisher-Snedecor ℱ Composite Fading Channel","authors":"Chunli Song, Xin Zhang","doi":"10.1109/CCCI52664.2021.9583201","DOIUrl":"https://doi.org/10.1109/CCCI52664.2021.9583201","url":null,"abstract":"In this paper, we investigate the physical layer security (PLS) for reconfigurable intelligent surface (RIS)-assisted non-orthogonal multiple access (NOMA) system over generalized fading channels. Specifically, we assume that the system is based on RIS access point (AP) and RIS is used to improve the secrecy performance of two legitimate users. We adopt the FisherSnedecor F model to characterize the composite fading and shadowing channel. In particular, novel expressions for the outage probability and secrecy outage probability (SOP) are derived. We verify our analytical results through Monte-Carlo simulations. The results indicate that the secrecy performance is affected by the number of RIS reflecting elements and Fisher-Snedecor F composite fading parameters.","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122140052","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 : 2021-10-15DOI: 10.1109/CCCI52664.2021.9583186
Yuanyan Xie, Yu Guo, Yue Chen, Zhenqiang Mi
Instance segmentation can enable mobile robots to obtain the environmental semantic information and accomplish more complex interaction with environments, such as navigation, grasping, and virtual reality. However, low-cost mobile robots have limited onboard resources, and can not afford the massive computation of instance segmentation methods. This paper proposes a real-time instance segmentation framework for mobile robot systems based on computation offloading, which offloads part of computation of the instance segmentation network to the cloud, and leverages the powerful computation resources and sufficient memories on the cloud platform to accelerate the network. First, we formulate the instance segmentation network as the directed acyclic graph, and present its time cost model and energy consumption model. Then, a computation offloading strategy is proposed to reduce the time cost of the whole instance segmentation and the energy consumption on the mobile robot. Our framework has been verified on the representative one-stage method, Yolact, and two-stage method, Mask R-CNN. The results show that our framework can accelerate the execution of instance segmentation network on mobile robots, and achieve the speed of around one second per frame.
{"title":"Real-Time Instance Segmentation for Low-Cost Mobile Robot Systems Based on Computation Offloading","authors":"Yuanyan Xie, Yu Guo, Yue Chen, Zhenqiang Mi","doi":"10.1109/CCCI52664.2021.9583186","DOIUrl":"https://doi.org/10.1109/CCCI52664.2021.9583186","url":null,"abstract":"Instance segmentation can enable mobile robots to obtain the environmental semantic information and accomplish more complex interaction with environments, such as navigation, grasping, and virtual reality. However, low-cost mobile robots have limited onboard resources, and can not afford the massive computation of instance segmentation methods. This paper proposes a real-time instance segmentation framework for mobile robot systems based on computation offloading, which offloads part of computation of the instance segmentation network to the cloud, and leverages the powerful computation resources and sufficient memories on the cloud platform to accelerate the network. First, we formulate the instance segmentation network as the directed acyclic graph, and present its time cost model and energy consumption model. Then, a computation offloading strategy is proposed to reduce the time cost of the whole instance segmentation and the energy consumption on the mobile robot. Our framework has been verified on the representative one-stage method, Yolact, and two-stage method, Mask R-CNN. The results show that our framework can accelerate the execution of instance segmentation network on mobile robots, and achieve the speed of around one second per frame.","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131551926","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 : 2021-10-15DOI: 10.1109/CCCI52664.2021.9583187
Georgios L. Stavrinides, H. Karatza
A wide spectrum of applications, ranging from big data analytics to financial risk modeling and genomics, feature a high degree of parallelism, forming bags-of-tasks. Such applications are typically processed on distributed resources and are often prone to transient software failures. Consequently, load balancing and fault tolerance are two crucial aspects of such environments. In this paper, we consider bag-of-tasks jobs that utilize application-directed checkpointing. According to this technique, each component task is responsible for checkpointing its own progress at regular intervals during its execution. When a failure occurs, the affected task is rolled back to its most recent checkpoint and resumes execution. In order to investigate the impact of transient software failures on the performance of the system, we employ four resource allocation strategies, two well-known and two novel ones. The routing policies are compared through simulation experiments, under different task failure probabilities and load cases.
{"title":"Fault-Tolerant Orchestration of Bags-of-Tasks with Application-Directed Checkpointing in a Distributed Environment","authors":"Georgios L. Stavrinides, H. Karatza","doi":"10.1109/CCCI52664.2021.9583187","DOIUrl":"https://doi.org/10.1109/CCCI52664.2021.9583187","url":null,"abstract":"A wide spectrum of applications, ranging from big data analytics to financial risk modeling and genomics, feature a high degree of parallelism, forming bags-of-tasks. Such applications are typically processed on distributed resources and are often prone to transient software failures. Consequently, load balancing and fault tolerance are two crucial aspects of such environments. In this paper, we consider bag-of-tasks jobs that utilize application-directed checkpointing. According to this technique, each component task is responsible for checkpointing its own progress at regular intervals during its execution. When a failure occurs, the affected task is rolled back to its most recent checkpoint and resumes execution. In order to investigate the impact of transient software failures on the performance of the system, we employ four resource allocation strategies, two well-known and two novel ones. The routing policies are compared through simulation experiments, under different task failure probabilities and load cases.","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132509547","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 : 2021-10-15DOI: 10.1109/CCCI52664.2021.9583205
D. Mishra, M. Obaidat, Ankita Mishra
Advancement in network technology provides an opportunity for e-commerce industries to sell digital content. However, multimedia content has the drawback of easy copy and redistribution, which causes rampant piracy. Digital rights management (DRM) systems are developed to address content piracy. Basically, DRM focuses to control content consumption and distribution. In general, to provide copyright protection, DRM system loses flexibility and creates a severe threat to users’ privacy. Moreover, traditional DRM systems are client-server architecture, which cannot handle strategies geographically. These disadvantages discourage the adoption of DRM systems. At the same time, multi-distributor DRM (MD-DRM) system provides a way to facilitate content distribution more effectively. Most of the existing multi-distributor DRM systems are privacy encroaching and do not discuss the useful content distribution framework. To overcome the drawbacks of existing schemes, we propose a privacy-preserving MD-DRM system, which is flexible enough to support location-based content distribution. The proposed scheme maintains a flexible and transparent content distribution without breaching consumer privacy. Besides, the proposed scheme does not violate accountability parameters. This mechanism makes traitor identification possible without violating the privacy rights of authorized consumers.
{"title":"Privacy Preserving Location-based Content Distribution Framework for Digital Rights Management Systems","authors":"D. Mishra, M. Obaidat, Ankita Mishra","doi":"10.1109/CCCI52664.2021.9583205","DOIUrl":"https://doi.org/10.1109/CCCI52664.2021.9583205","url":null,"abstract":"Advancement in network technology provides an opportunity for e-commerce industries to sell digital content. However, multimedia content has the drawback of easy copy and redistribution, which causes rampant piracy. Digital rights management (DRM) systems are developed to address content piracy. Basically, DRM focuses to control content consumption and distribution. In general, to provide copyright protection, DRM system loses flexibility and creates a severe threat to users’ privacy. Moreover, traditional DRM systems are client-server architecture, which cannot handle strategies geographically. These disadvantages discourage the adoption of DRM systems. At the same time, multi-distributor DRM (MD-DRM) system provides a way to facilitate content distribution more effectively. Most of the existing multi-distributor DRM systems are privacy encroaching and do not discuss the useful content distribution framework. To overcome the drawbacks of existing schemes, we propose a privacy-preserving MD-DRM system, which is flexible enough to support location-based content distribution. The proposed scheme maintains a flexible and transparent content distribution without breaching consumer privacy. Besides, the proposed scheme does not violate accountability parameters. This mechanism makes traitor identification possible without violating the privacy rights of authorized consumers.","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133492246","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 : 2021-10-15DOI: 10.1109/CCCI52664.2021.9583206
Dongliang Xuan, Huaping Hu, Bidong Wang, Bo Liu
With the emergence of increasingly growing network threats, network security becomes a major issue which causes huge existing and potential losses, such as WannaCry. Various methods had been adopted to maintain network security, among which Intrusion Detection System (IDS) is one of the most essential parts of cybersecurity to defense against sophisticated and ever-growing network attacks. A number of researchers have studied comprehensive datasets and effective approaches to build IDS. Machine learning models are also applied in IDS and obtained considerable results in building better network security system. In this paper, we proposed a two-stage IDS based on machine learning models RF and SVM optimized with Feature Selection algorithm CFS. We also conducted experiments on NSL-KDD benchmark datasets to evaluate the performance of the two-stage IDS, comparing against RF and SVM models respectively. The results demonstrated that our proposed two-stage IDS outperformed RF and SVM with an increase from 4.31% to 14.62% in Precision and a reduction of 93.84% in time than SVM.
{"title":"Intrusion Detection System Based on RF-SVM Model Optimized with Feature Selection","authors":"Dongliang Xuan, Huaping Hu, Bidong Wang, Bo Liu","doi":"10.1109/CCCI52664.2021.9583206","DOIUrl":"https://doi.org/10.1109/CCCI52664.2021.9583206","url":null,"abstract":"With the emergence of increasingly growing network threats, network security becomes a major issue which causes huge existing and potential losses, such as WannaCry. Various methods had been adopted to maintain network security, among which Intrusion Detection System (IDS) is one of the most essential parts of cybersecurity to defense against sophisticated and ever-growing network attacks. A number of researchers have studied comprehensive datasets and effective approaches to build IDS. Machine learning models are also applied in IDS and obtained considerable results in building better network security system. In this paper, we proposed a two-stage IDS based on machine learning models RF and SVM optimized with Feature Selection algorithm CFS. We also conducted experiments on NSL-KDD benchmark datasets to evaluate the performance of the two-stage IDS, comparing against RF and SVM models respectively. The results demonstrated that our proposed two-stage IDS outperformed RF and SVM with an increase from 4.31% to 14.62% in Precision and a reduction of 93.84% in time than SVM.","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122082293","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}
With more and more encrypted traffic such as HTTPS, encrypted traffic protects not only normal traffic, but also malicious traffic. Identification of encrypted malicious traffic without decryption has become a research hotspot. Combined with deep learning, an important branch of machine learning, encrypted malicious traffic detection has achieved good results. This paper reviews the detection of encrypted malicious traffic in recent years. Firstly, we classify encrypted malicious traffic. Secondly, we sorts out the extraction characteristics of encrypted malicious traffic, the key and difficult problems we are facing at present. Then, with encrypted malicious traffic detection technology as the main line, we summarized the current detection model from the four core aspects of data collection, data processing, model training and evaluation improvement. Finally, we analyze the problems and point out future research directions.
{"title":"A Survey of Encrypted Malicious Traffic Detection*","authors":"Yanmiao Li, Hao Guo, Jiangang Hou, Zhen Zhang, Tong Jiang, Zhi Liu","doi":"10.1109/CCCI52664.2021.9583191","DOIUrl":"https://doi.org/10.1109/CCCI52664.2021.9583191","url":null,"abstract":"With more and more encrypted traffic such as HTTPS, encrypted traffic protects not only normal traffic, but also malicious traffic. Identification of encrypted malicious traffic without decryption has become a research hotspot. Combined with deep learning, an important branch of machine learning, encrypted malicious traffic detection has achieved good results. This paper reviews the detection of encrypted malicious traffic in recent years. Firstly, we classify encrypted malicious traffic. Secondly, we sorts out the extraction characteristics of encrypted malicious traffic, the key and difficult problems we are facing at present. Then, with encrypted malicious traffic detection technology as the main line, we summarized the current detection model from the four core aspects of data collection, data processing, model training and evaluation improvement. Finally, we analyze the problems and point out future research directions.","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122846136","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 : 2021-10-15DOI: 10.1109/CCCI52664.2021.9583215
Jiayu Wang, Lintao Liu, Jia Chen, Xuehu Yan
Secret image sharing (SIS) means to share a secret image into multiple shadow images, and the secret image can be recovered when a sufficient number of shadow images are obtained. SIS has the advantages of loss tolerance, simple encryption and decryption, scattered storage and so on. This paper describes three realization principles(i.e., the polynomial-based SIS, SIS based on the Chinese remainder theorem and visual secret sharing), verifies them with experiments, and calculates the PSNR, SSIM values and the time cost for each scheme to recover the image. Comparing the values of each index and the visual quality of the restored images can more intuitively reflect the advantages and disadvantages of each scheme. Finally, the advantages and disadvantages of each algorithm are analyzed by combining the theory and experimental results of the algorithm.
{"title":"Comparison and analysis of secret image sharing principles","authors":"Jiayu Wang, Lintao Liu, Jia Chen, Xuehu Yan","doi":"10.1109/CCCI52664.2021.9583215","DOIUrl":"https://doi.org/10.1109/CCCI52664.2021.9583215","url":null,"abstract":"Secret image sharing (SIS) means to share a secret image into multiple shadow images, and the secret image can be recovered when a sufficient number of shadow images are obtained. SIS has the advantages of loss tolerance, simple encryption and decryption, scattered storage and so on. This paper describes three realization principles(i.e., the polynomial-based SIS, SIS based on the Chinese remainder theorem and visual secret sharing), verifies them with experiments, and calculates the PSNR, SSIM values and the time cost for each scheme to recover the image. Comparing the values of each index and the visual quality of the restored images can more intuitively reflect the advantages and disadvantages of each scheme. Finally, the advantages and disadvantages of each algorithm are analyzed by combining the theory and experimental results of the algorithm.","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114868387","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 : 2021-10-15DOI: 10.1109/CCCI52664.2021.9583207
Zihao Liu, Yanrui Xu, Xiaokun Wang, X. Ban, Z. Zheng
The simulation and visualization of natural phenomena has been widely studied in computer graphics. But those studies are less involved in complex phenomena, such as solid-liquid interaction and transition. We propose a method for simulation and visualization of solid-liquid heat conduction and phase transition using Smooth Particle Hydrodynamics(SPH) based on Fourier law. To achieve a realistic phase transition, spatio-temporal discretization of solid-liquid two-phase material, we map the temperature field to solid and liquid particles and combining with the heat conduction model. Our method includes heat conduction between solid and liquid, solid and surrounding air, and latent heat caused by phase transition. The experimental results show that our method can realize stable heat conduction and smooth phase transition from solid to liquid with accurate simulation details and visualization effects.
{"title":"Simulation and visualization of solid-liquid phase transition and interactive using particle-based method","authors":"Zihao Liu, Yanrui Xu, Xiaokun Wang, X. Ban, Z. Zheng","doi":"10.1109/CCCI52664.2021.9583207","DOIUrl":"https://doi.org/10.1109/CCCI52664.2021.9583207","url":null,"abstract":"The simulation and visualization of natural phenomena has been widely studied in computer graphics. But those studies are less involved in complex phenomena, such as solid-liquid interaction and transition. We propose a method for simulation and visualization of solid-liquid heat conduction and phase transition using Smooth Particle Hydrodynamics(SPH) based on Fourier law. To achieve a realistic phase transition, spatio-temporal discretization of solid-liquid two-phase material, we map the temperature field to solid and liquid particles and combining with the heat conduction model. Our method includes heat conduction between solid and liquid, solid and surrounding air, and latent heat caused by phase transition. The experimental results show that our method can realize stable heat conduction and smooth phase transition from solid to liquid with accurate simulation details and visualization effects.","PeriodicalId":136382,"journal":{"name":"2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124324837","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：