Pub Date : 2020-09-01DOI: 10.13374/J.ISSN2095-9389.2019.10.03.001
陈庆发, 王少平, 秦世康
To further reveal the internal mechanism of the granular media flow process under the flexible isolation layer, numerical experiments on the evolution characteristics of bulk media flow force chain under the flexible isolation layer were carried out based on the discrete element software PFC. Based on a combination of contact mechanics and statistical mechanics, the evolution characteristics of the force chain length, quantity, strength, direction, and the collimation coefficient of the internal bulk medium system in the multifunnel ore drawing process were quantitatively studied. It is found that the proportions of the strong contact and the force chain contact is found to be relatively stable in the multi-funnel ore drawing process;the proportion of strong contact is stable at about 33%, that of the force chain contact is stable at about 16%, and the fluctuation amplitude is not more than 2%. The total number of force chains decreases with the increase in ore drawing times, and it is stable at 790 strips in the later stage of ore drawing. The probability distribution of the force chain length is almost the same under different ore drawing times, and it decreases exponentially with the increase in the force chain length. The probability distribution of the force chain strength first increases exponentially with the increase in the ore drawing times and then decreases exponentially;it reaches a peak value at 0.7■(■is the average contact force).In the initial ore drawing stage,the force chain is mainly distributed along the vertical direction, and the force chain direction distribution is similar to a peanut shape.After that, with the continuous release of ore particles, the phenomenon of local stress concentration in the granular media system becomes remarkable, and the main direction of the force chain distribution changes to become four(vertical direction, horizontal direction, and angles of ±60° to the horizontal). The force chain collimation coefficient increases exponentially with the increase in drawing times and gradually becomes stable.
{"title":"Discrete element simulation for evolution characteristics of multi-funnel mineral-rock force chain under flexible isolation layer","authors":"陈庆发, 王少平, 秦世康","doi":"10.13374/J.ISSN2095-9389.2019.10.03.001","DOIUrl":"https://doi.org/10.13374/J.ISSN2095-9389.2019.10.03.001","url":null,"abstract":"To further reveal the internal mechanism of the granular media flow process under the flexible isolation layer, numerical experiments on the evolution characteristics of bulk media flow force chain under the flexible isolation layer were carried out based on the discrete element software PFC. Based on a combination of contact mechanics and statistical mechanics, the evolution characteristics of the force chain length, quantity, strength, direction, and the collimation coefficient of the internal bulk medium system in the multifunnel ore drawing process were quantitatively studied. It is found that the proportions of the strong contact and the force chain contact is found to be relatively stable in the multi-funnel ore drawing process;the proportion of strong contact is stable at about 33%, that of the force chain contact is stable at about 16%, and the fluctuation amplitude is not more than 2%. The total number of force chains decreases with the increase in ore drawing times, and it is stable at 790 strips in the later stage of ore drawing. The probability distribution of the force chain length is almost the same under different ore drawing times, and it decreases exponentially with the increase in the force chain length. The probability distribution of the force chain strength first increases exponentially with the increase in the ore drawing times and then decreases exponentially;it reaches a peak value at 0.7■(■is the average contact force).In the initial ore drawing stage,the force chain is mainly distributed along the vertical direction, and the force chain direction distribution is similar to a peanut shape.After that, with the continuous release of ore particles, the phenomenon of local stress concentration in the granular media system becomes remarkable, and the main direction of the force chain distribution changes to become four(vertical direction, horizontal direction, and angles of ±60° to the horizontal). The force chain collimation coefficient increases exponentially with the increase in drawing times and gradually becomes stable.","PeriodicalId":31263,"journal":{"name":"工程设计学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72383284","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}
Artificial intelligence(AI), especially the rapid development of deep learning, has a profound impact on various industries and has continuously changed the traditional production methods and lifestyles. From passive learning with computing power to autonomous learning and enhanced learning, the development of machine intelligence is largely due to the innovation of the AI theory and practice. AI has also had a far-reaching impact on the military field, as it has provided modern warfare with new features such as intelligence, interconnectedness, and destructiveness. Winning in a military confrontation requires not only machine intelligence but also human wisdom. Therefore, human-machine collaboration would combine the strengths and complement the weaknesses of human and machine, which is the key to victory in the increasingly complex war environment. How to achieve a high degree of hybrid human–artificial intelligence to obtain a good result of "1+1>2" is also a problem that needs to be further explored in military confrontation. This paper reviewed the application of AI in military confrontation as the starting point and highlighted the important measures and achievements of representative countries in the use of AI technology in the military development process. Moreover, we analyzed the development status from the two perspectives of confrontation strategy and the three-tier architecture of the Internet of Things,revealed the shortcomings of using AI in the current military field, and analyzed the development trend of hybrid human–artificial intelligence in military confrontation. We also presented three possible technical schemes and detailed explanations and finally proposed future research directions. We believe that the future development trend of intelligent military may be based on the hybrid human–artificial intelligence, which will further improve the adaptability of machines to the combat environment and reveal the merits of the integration of human wisdom and machine intelligence;this integration may be the next step of AI research in military confrontation.
{"title":"Application progress of artificial intelligence in military confrontation","authors":"张智敏, 石飞飞, 万月亮, 1 ，宁焕生, Zhi-min Zhang, ，. Shi, ，. Wan, XU ，, .. Zhang, ，. Ning","doi":"10.13374/J.ISSN2095-9389.2019.11.19.001","DOIUrl":"https://doi.org/10.13374/J.ISSN2095-9389.2019.11.19.001","url":null,"abstract":"Artificial intelligence(AI), especially the rapid development of deep learning, has a profound impact on various industries and has continuously changed the traditional production methods and lifestyles. From passive learning with computing power to autonomous learning and enhanced learning, the development of machine intelligence is largely due to the innovation of the AI theory and practice. AI has also had a far-reaching impact on the military field, as it has provided modern warfare with new features such as intelligence, interconnectedness, and destructiveness. Winning in a military confrontation requires not only machine intelligence but also human wisdom. Therefore, human-machine collaboration would combine the strengths and complement the weaknesses of human and machine, which is the key to victory in the increasingly complex war environment. How to achieve a high degree of hybrid human–artificial intelligence to obtain a good result of \"1+1>2\" is also a problem that needs to be further explored in military confrontation. This paper reviewed the application of AI in military confrontation as the starting point and highlighted the important measures and achievements of representative countries in the use of AI technology in the military development process. Moreover, we analyzed the development status from the two perspectives of confrontation strategy and the three-tier architecture of the Internet of Things,revealed the shortcomings of using AI in the current military field, and analyzed the development trend of hybrid human–artificial intelligence in military confrontation. We also presented three possible technical schemes and detailed explanations and finally proposed future research directions. We believe that the future development trend of intelligent military may be based on the hybrid human–artificial intelligence, which will further improve the adaptability of machines to the combat environment and reveal the merits of the integration of human wisdom and machine intelligence;this integration may be the next step of AI research in military confrontation.","PeriodicalId":31263,"journal":{"name":"工程设计学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77820298","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 : 2020-04-01DOI: 10.13374/J.ISSN2095-9389.2019.09.04.004
龚乐君, 张知菲
As a document recorded by professional medical personnel, electronic medical records contain a large and important clinical resource. How to use a large amount of potential information in electronic medical records has become one of the major research directions. Chinese electronic medical records are knowledge-intensive, in which the data has considerable research value. However,they have more complex entities because of the language features of Chinese, and the composite entity is long. These sentences components in the text are missing. Moreover, the boundaries of clinical entities are often unclear. Labeling corpus is a job that requires a great deal of manpower because of the technical language used in a given text. Therefore, the recognition of Chinese clinical named entities is a hard problem. Considering these characteristics of Chinese electronic medical records, this paper proposed a double-layer annotation model that combined with a domain dictionary and conditional random field(CRF). A medical domain dictionary was constructed by statistical analysis method, and combined with CRF to mark two different granularity labeling operations. The manually constructed medical domain dictionary has extremely high accuracy for the recognition of registered words, and machine learning could automatically recognize unregistered words. This work integrated the two aspects based on these advantages. With the proposed method, diseases, symptoms, drugs, and operations could be recognized from Chinese electronic medical records. Using the test dataset, the Macro-P with 96.7%,the Macro-R with 97.7%and the Macro-F1 with 97.2%were obtained.The recognition performance of the proposed method was greatly improved compared with that of a single-layer model.The recognition effect of deep neural network with attention was also analyzed,which did not perform well due to the size of the domain dataset.The experimental results show the efficiency of the double-layer annotation model for the named entity recognition of Chinese electronic medical records.
{"title":"Clinical named entity recognition from Chinese electronic medical records using a double-layer annotation model combining a domain dictionary with CRF","authors":"龚乐君, 张知菲","doi":"10.13374/J.ISSN2095-9389.2019.09.04.004","DOIUrl":"https://doi.org/10.13374/J.ISSN2095-9389.2019.09.04.004","url":null,"abstract":"As a document recorded by professional medical personnel, electronic medical records contain a large and important clinical resource. How to use a large amount of potential information in electronic medical records has become one of the major research directions. Chinese electronic medical records are knowledge-intensive, in which the data has considerable research value. However,they have more complex entities because of the language features of Chinese, and the composite entity is long. These sentences components in the text are missing. Moreover, the boundaries of clinical entities are often unclear. Labeling corpus is a job that requires a great deal of manpower because of the technical language used in a given text. Therefore, the recognition of Chinese clinical named entities is a hard problem. Considering these characteristics of Chinese electronic medical records, this paper proposed a double-layer annotation model that combined with a domain dictionary and conditional random field(CRF). A medical domain dictionary was constructed by statistical analysis method, and combined with CRF to mark two different granularity labeling operations. The manually constructed medical domain dictionary has extremely high accuracy for the recognition of registered words, and machine learning could automatically recognize unregistered words. This work integrated the two aspects based on these advantages. With the proposed method, diseases, symptoms, drugs, and operations could be recognized from Chinese electronic medical records. Using the test dataset, the Macro-P with 96.7%,the Macro-R with 97.7%and the Macro-F1 with 97.2%were obtained.The recognition performance of the proposed method was greatly improved compared with that of a single-layer model.The recognition effect of deep neural network with attention was also analyzed,which did not perform well due to the size of the domain dataset.The experimental results show the efficiency of the double-layer annotation model for the named entity recognition of Chinese electronic medical records.","PeriodicalId":31263,"journal":{"name":"工程设计学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76945674","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 : 2020-04-01DOI: 10.13374/J.ISSN2095-9389.2019.09.15.008
赵海春, 姚宣霞, 郑雪峰
With the development of cloud computing technology, more individuals and organizations have chosen cloud services to store and maintain their data and reduce the burden on local storage and corresponding maintenance costs. However, although the cloud computing infrastructure is more powerful and reliable than personal computing devices, the cloud storage server is not completely trusted due to various internal and external threats;therefore, users need to regularly check whether their data stored in the cloud server are intact. Therefore, in recent years, researchers have proposed a variety of schemes for data integrity auditing in cloud storage. Among them, in a part of public auditing schemes for cloud storage based on homomorphic authenticators, random sampling of data blocks, and random masking techniques, users need to store and maintain a two-dimensional(2 D) table related to the index information of data blocks in the file. When a user’s outsource data need to be frequently updated to avoid forgery attacks due to the similar index value of data block being reused, the design and maintenance of the 2 D table become cumbersome. In this study, to solve the abovementioned problem, an index–stub table structure was first proposed, which is simple and easy to maintain. On the basis of this structure, a thirdparty auditor auditing scheme with a privacy-preserving property was proposed for cloud storage. This scheme can effectively support various remote dynamic operations for outsource data at the block level. Then, a formal security proof for data integrity guarantee provided by the scheme was given under the random oracle model. A formal security analysis was also given for the privacy-preserving property of the audit protocol. Finally, the performance of the scheme was theoretically analyzed and compared with relevant experiments. Results indicate that the scheme has high efficiency.
{"title":"Cloud storage data integrity audit based on an index–stub table","authors":"赵海春, 姚宣霞, 郑雪峰","doi":"10.13374/J.ISSN2095-9389.2019.09.15.008","DOIUrl":"https://doi.org/10.13374/J.ISSN2095-9389.2019.09.15.008","url":null,"abstract":"With the development of cloud computing technology, more individuals and organizations have chosen cloud services to store and maintain their data and reduce the burden on local storage and corresponding maintenance costs. However, although the cloud computing infrastructure is more powerful and reliable than personal computing devices, the cloud storage server is not completely trusted due to various internal and external threats;therefore, users need to regularly check whether their data stored in the cloud server are intact. Therefore, in recent years, researchers have proposed a variety of schemes for data integrity auditing in cloud storage. Among them, in a part of public auditing schemes for cloud storage based on homomorphic authenticators, random sampling of data blocks, and random masking techniques, users need to store and maintain a two-dimensional(2 D) table related to the index information of data blocks in the file. When a user’s outsource data need to be frequently updated to avoid forgery attacks due to the similar index value of data block being reused, the design and maintenance of the 2 D table become cumbersome. In this study, to solve the abovementioned problem, an index–stub table structure was first proposed, which is simple and easy to maintain. On the basis of this structure, a thirdparty auditor auditing scheme with a privacy-preserving property was proposed for cloud storage. This scheme can effectively support various remote dynamic operations for outsource data at the block level. Then, a formal security proof for data integrity guarantee provided by the scheme was given under the random oracle model. A formal security analysis was also given for the privacy-preserving property of the audit protocol. Finally, the performance of the scheme was theoretically analyzed and compared with relevant experiments. Results indicate that the scheme has high efficiency.","PeriodicalId":31263,"journal":{"name":"工程设计学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72369010","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 : 2020-04-01DOI: 10.13374/J.ISSN2095-9389.2019.09.15.009
刘娅汐, 皇甫伟
The Internet of Things(IoT) has become an essential supporting platform for the present and future cyber-enabled services. Cellular networks is considered as the main channel of the data access for IoT terminals distributed in the region of interest, and they have an irreplaceable value, especially in wide-area coverage. Thus, it has a significant application value to reduce the downlink transmit power consumption of base stations under the restrictions of the coverage requirements for the green communication in heterogeneous cellular networks. A gradient descent algorithm was proposed based on smooth approximation and root mean square propagation. The algorithm could minimize the total downlink power consumption of base stations while satisfying the IoT service coverage. First, the penalty function method was used to simplify such an optimization problem with complicated constraints to a new one with simple constraints. Then, the non-derivative objective function was transformed by an approximation method into a derivable form. We also presented the close-form of the gradient of the objective function with respect to both the azimuths of the antennas installed in the base stations and the downlink transmit power levels related to these antennas. Finally, the gradient descent algorithm with root mean square propagation was used to execute the optimization of the newly approximated but smoothed version of the original objective function. Simulation experiments were conducted, and the results show that the proposed algorithm can significantly reduce the total power consumption of the downlink radio frequency transmit under the restrictions of the coverage ratio requirements in the region of interest. Furthermore, not only is the convergence speed of the proposed algorithm very fast, but also the oscillation phenomenon that occurs during the iterative procedure steps of the optimization is greatly suppressed by the proposed algorithm compared with the meta-heuristic algorithms and ordinary gradient descent method.
{"title":"Heterogeneous cellular network optimization for green access of IoT traffics","authors":"刘娅汐, 皇甫伟","doi":"10.13374/J.ISSN2095-9389.2019.09.15.009","DOIUrl":"https://doi.org/10.13374/J.ISSN2095-9389.2019.09.15.009","url":null,"abstract":"The Internet of Things(IoT) has become an essential supporting platform for the present and future cyber-enabled services. Cellular networks is considered as the main channel of the data access for IoT terminals distributed in the region of interest, and they have an irreplaceable value, especially in wide-area coverage. Thus, it has a significant application value to reduce the downlink transmit power consumption of base stations under the restrictions of the coverage requirements for the green communication in heterogeneous cellular networks. A gradient descent algorithm was proposed based on smooth approximation and root mean square propagation. The algorithm could minimize the total downlink power consumption of base stations while satisfying the IoT service coverage. First, the penalty function method was used to simplify such an optimization problem with complicated constraints to a new one with simple constraints. Then, the non-derivative objective function was transformed by an approximation method into a derivable form. We also presented the close-form of the gradient of the objective function with respect to both the azimuths of the antennas installed in the base stations and the downlink transmit power levels related to these antennas. Finally, the gradient descent algorithm with root mean square propagation was used to execute the optimization of the newly approximated but smoothed version of the original objective function. Simulation experiments were conducted, and the results show that the proposed algorithm can significantly reduce the total power consumption of the downlink radio frequency transmit under the restrictions of the coverage ratio requirements in the region of interest. Furthermore, not only is the convergence speed of the proposed algorithm very fast, but also the oscillation phenomenon that occurs during the iterative procedure steps of the optimization is greatly suppressed by the proposed algorithm compared with the meta-heuristic algorithms and ordinary gradient descent method.","PeriodicalId":31263,"journal":{"name":"工程设计学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80513960","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 : 2020-04-01DOI: 10.13374/J.ISSN2095-9389.2019.09.13.003
曹文斌, 武卓峰, 杨涛, 凡友荣
Affected by complex international factors in recent years, terrorism events are increasingly rampant in many countries,thereby posing a great threat to the gloal community. In addition, with the widespread use of emerging technologies in military and commercial fields, terrorist organizations have begun to use emerging technologies to engage in destructive activities. As the Internet and information technology develop, terrorism has been rapidly spreading in cyberspace. Terrorist organizations have created terrorism websites, established multinational networks of terrorist organizations, released recruitment information and even conducted training activities through various mainstream websites with a worldwide reach. Compared with traditional terrorist activities, cyber terrorist activities have a greater degree of destructiveness. Cybercrime and cyber terrorism have become the most serious challenges for societies. Terrorist organizations take advantage of the Internet in rapid dissemination of extremism ideas, and develop a large number of terrorists and supporters around the world, especially in developed Western countries. Terrorist organizations even use the Internet and"dark net" networks to conduct terrorist training, and their activities are concealed. As a result, the "lone wolf" terrorist attacks in various countries have emerged in an endless stream, which is difficult to prevent. This study proposed a method of extracting entities and attributes of terrorist events based on semantic role analysis, and provided technical support for monitoring and predicting cyberspace terrorism activities. Firstly, a naive Bayesian text classification algorithm is used to identify terrorism events on the cleaned text corpus collected from the Anti-Terrorism Information Site of the Northwest University of Political Science and Law.The keyword extraction algorithm TF-IDF is adopted for constructing the terrorism vocabularies from the classified text corpus,combining natural language processing technology.Then,semantic role and syntactic dependency analyses are conducted to mine the attributive posttargeting relationship,the name//place name//organization,and the mediator-like relationship.Finally,regular expressions and constructed lexical terrorism-specific vocabularies are used to extract six entities and attributes(occurrence time,occurrence location,casualties,attack methods,weapon types and terrorist organizations)of terrorism event based on the four types of triad short texts.The F1 values of the six types of entity attribute extraction evaluation results exceeded 80%based on the experimental data of 4221 articles collected.Therefore,the method proposed has practical significance for maintaining social public safety because of the positive effect in monitoring and predicting cyberspace terrorism events.
{"title":"Entity and attribute extraction of terrorism event based on text corpus","authors":"曹文斌, 武卓峰, 杨涛, 凡友荣","doi":"10.13374/J.ISSN2095-9389.2019.09.13.003","DOIUrl":"https://doi.org/10.13374/J.ISSN2095-9389.2019.09.13.003","url":null,"abstract":"Affected by complex international factors in recent years, terrorism events are increasingly rampant in many countries,thereby posing a great threat to the gloal community. In addition, with the widespread use of emerging technologies in military and commercial fields, terrorist organizations have begun to use emerging technologies to engage in destructive activities. As the Internet and information technology develop, terrorism has been rapidly spreading in cyberspace. Terrorist organizations have created terrorism websites, established multinational networks of terrorist organizations, released recruitment information and even conducted training activities through various mainstream websites with a worldwide reach. Compared with traditional terrorist activities, cyber terrorist activities have a greater degree of destructiveness. Cybercrime and cyber terrorism have become the most serious challenges for societies. Terrorist organizations take advantage of the Internet in rapid dissemination of extremism ideas, and develop a large number of terrorists and supporters around the world, especially in developed Western countries. Terrorist organizations even use the Internet and\"dark net\" networks to conduct terrorist training, and their activities are concealed. As a result, the \"lone wolf\" terrorist attacks in various countries have emerged in an endless stream, which is difficult to prevent. This study proposed a method of extracting entities and attributes of terrorist events based on semantic role analysis, and provided technical support for monitoring and predicting cyberspace terrorism activities. Firstly, a naive Bayesian text classification algorithm is used to identify terrorism events on the cleaned text corpus collected from the Anti-Terrorism Information Site of the Northwest University of Political Science and Law.The keyword extraction algorithm TF-IDF is adopted for constructing the terrorism vocabularies from the classified text corpus,combining natural language processing technology.Then,semantic role and syntactic dependency analyses are conducted to mine the attributive posttargeting relationship,the name//place name//organization,and the mediator-like relationship.Finally,regular expressions and constructed lexical terrorism-specific vocabularies are used to extract six entities and attributes(occurrence time,occurrence location,casualties,attack methods,weapon types and terrorist organizations)of terrorism event based on the four types of triad short texts.The F1 values of the six types of entity attribute extraction evaluation results exceeded 80%based on the experimental data of 4221 articles collected.Therefore,the method proposed has practical significance for maintaining social public safety because of the positive effect in monitoring and predicting cyberspace terrorism events.","PeriodicalId":31263,"journal":{"name":"工程设计学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81464069","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 : 2020-04-01DOI: 10.13374/J.ISSN2095-9389.2019.07.07.001
邓南阳, 施晓芳, 陈佳顺, 常凯华, 于雯春, 王建军, 常立忠
High-speed steel contains a large amount of carbides, the shape and distribution of which have an important influence on its quality. To improve the distribution of carbides in M high-speed steel, the temperature field and the shape of the metal pool during the mold-rotation process were investigated in detail using a numerical simulation. Moreover, the effect of the mold-rotation speed on the electroslag remelting process was investigated using a rotating bifilar electroslag remelting furnace under laboratory conditions. The morphology and distribution of carbides in an ESR ingot were observed using an SEM, and the composition of carbides was analyzed through an electrolytic extraction experiment. Results show that with increase in mold rotation speed, the high-temperature zone of the slag pool moves from the core to the edge. Moreover, the temperature distribution becomes uniform. The depth of the metal pool becomes shallow, and the thickness of the two-phase region decreases, which results in a short local solidification time and small secondary dendrite spacing. Correspondingly, with the increase in the mold rotation speed, the slag skin of ESR ingot becomes thin and more uniform than earlier. The cooling intensity of the mold on the ESR ingot is high, and the carbide network begins to break and become thin. The morphology of carbides changes from flake to fine rod. XRD analysis determines whether the mold rotates or not, carbides always comprise M2C, MC, and M6C. However, the content of M2C increases and the contents of MC and M6C decrease with the increase in mold-rotation speed.The main reason for the improvement in the carbide structure is that the mold rotation decreases the metal pool depth and two-phase zone thickness,which improves the solidification conditions and reduces the element segregation.
{"title":"Numerical simulation of mold rotation and its effect on carbides in HSS ESR ingot","authors":"邓南阳, 施晓芳, 陈佳顺, 常凯华, 于雯春, 王建军, 常立忠","doi":"10.13374/J.ISSN2095-9389.2019.07.07.001","DOIUrl":"https://doi.org/10.13374/J.ISSN2095-9389.2019.07.07.001","url":null,"abstract":"High-speed steel contains a large amount of carbides, the shape and distribution of which have an important influence on its quality. To improve the distribution of carbides in M high-speed steel, the temperature field and the shape of the metal pool during the mold-rotation process were investigated in detail using a numerical simulation. Moreover, the effect of the mold-rotation speed on the electroslag remelting process was investigated using a rotating bifilar electroslag remelting furnace under laboratory conditions. The morphology and distribution of carbides in an ESR ingot were observed using an SEM, and the composition of carbides was analyzed through an electrolytic extraction experiment. Results show that with increase in mold rotation speed, the high-temperature zone of the slag pool moves from the core to the edge. Moreover, the temperature distribution becomes uniform. The depth of the metal pool becomes shallow, and the thickness of the two-phase region decreases, which results in a short local solidification time and small secondary dendrite spacing. Correspondingly, with the increase in the mold rotation speed, the slag skin of ESR ingot becomes thin and more uniform than earlier. The cooling intensity of the mold on the ESR ingot is high, and the carbide network begins to break and become thin. The morphology of carbides changes from flake to fine rod. XRD analysis determines whether the mold rotates or not, carbides always comprise M2C, MC, and M6C. However, the content of M2C increases and the contents of MC and M6C decrease with the increase in mold-rotation speed.The main reason for the improvement in the carbide structure is that the mold rotation decreases the metal pool depth and two-phase zone thickness,which improves the solidification conditions and reduces the element segregation.","PeriodicalId":31263,"journal":{"name":"工程设计学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90162178","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 : 2020-03-01DOI: 10.13374/J.ISSN2095-9389.2019.04.01.004
邢奕, 崔永康, 苏伟, 尹丽鲲, 刘应书, 李子宜, 路培
In 2017, China’s industrial dust emissions accounted for 7.96 million tons, of which the iron and steel industry contributed approximately 25%. Particulate matter discharged from the iron and steel industry is mostly of a small size, high in temperature, and complex in composition. The mass concentration of ultrafine particles(UFPs) with particle sizes that are less than0.1 μm is low;however, the proportion of quantity concentration can be as high as 90%. Currently, the commonly used bag filters and electrostatic precipitators are not sufficiently efficient at collecting fine particles. Additionally, owing to the larger specific surface area of fine dust particles, they easily become carriers of adsorbing harmful gases, which has a greater impact on the environment and human health;thus, it is imperative to determine a simple and efficient filtration method to remove ultrafine particles. In this paper, the removal efficiency and mechanism of UFPs(2.5–25 nm) were investigated by using a scanning electromobility particle size spectrometer(SMPS)test system for SBA-15 for different pore sizes. This was done to provide a theoretical basis for the application of mesoporous materials in the control of ultra-low emission of particulate matter in the iron and steel industry. Based on the experimental results and characterization analysis, it is found that a mesoporous filtration medium with a large pore size is more efficient at affecting UFPs entry.There are many affinity sites for UFPs on the inner and outer surfaces of mesoporous materials with a specific pore size. Increasing the complexity of the ends is beneficial for improve the filtration performance of the materials. The presence or absence of nitrogen has little effect on the removal of UFPs. The diffusion effect of UFPs is stronger owing to the existence of mesoporous particles, and the diffusion coefficient is increased when particles enter the pore. Therefore, there is a difference between the theoretical exponent(m=-2/3) in the traditional model for particle diffusion and the actual diffusion results of UFPs in mesoporous materials.
{"title":"Study of the mechanism of removing ultrafine particles using SBA-15","authors":"邢奕, 崔永康, 苏伟, 尹丽鲲, 刘应书, 李子宜, 路培","doi":"10.13374/J.ISSN2095-9389.2019.04.01.004","DOIUrl":"https://doi.org/10.13374/J.ISSN2095-9389.2019.04.01.004","url":null,"abstract":"In 2017, China’s industrial dust emissions accounted for 7.96 million tons, of which the iron and steel industry contributed approximately 25%. Particulate matter discharged from the iron and steel industry is mostly of a small size, high in temperature, and complex in composition. The mass concentration of ultrafine particles(UFPs) with particle sizes that are less than0.1 μm is low;however, the proportion of quantity concentration can be as high as 90%. Currently, the commonly used bag filters and electrostatic precipitators are not sufficiently efficient at collecting fine particles. Additionally, owing to the larger specific surface area of fine dust particles, they easily become carriers of adsorbing harmful gases, which has a greater impact on the environment and human health;thus, it is imperative to determine a simple and efficient filtration method to remove ultrafine particles. In this paper, the removal efficiency and mechanism of UFPs(2.5–25 nm) were investigated by using a scanning electromobility particle size spectrometer(SMPS)test system for SBA-15 for different pore sizes. This was done to provide a theoretical basis for the application of mesoporous materials in the control of ultra-low emission of particulate matter in the iron and steel industry. Based on the experimental results and characterization analysis, it is found that a mesoporous filtration medium with a large pore size is more efficient at affecting UFPs entry.There are many affinity sites for UFPs on the inner and outer surfaces of mesoporous materials with a specific pore size. Increasing the complexity of the ends is beneficial for improve the filtration performance of the materials. The presence or absence of nitrogen has little effect on the removal of UFPs. The diffusion effect of UFPs is stronger owing to the existence of mesoporous particles, and the diffusion coefficient is increased when particles enter the pore. Therefore, there is a difference between the theoretical exponent(m=-2/3) in the traditional model for particle diffusion and the actual diffusion results of UFPs in mesoporous materials.","PeriodicalId":31263,"journal":{"name":"工程设计学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80291008","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 : 2020-03-01DOI: 10.13374/J.ISSN2095-9389.2019.04.23.001
邵慧琪, 张又文, 曲琛, 厉文辉, 赵妍珺, 刘凝, 蔡寒梅, 吴传东, 刘杰民
Phytoremediation is an important means of soil heavy metal pollution remediation. In order to figure out the soil pollution status of the water source in the middle line of the South-to-North Water Transfer Project and repair it, soil samples(n = 14)and local dominant terrestrial plants(n = 113) were collected in typical areas around Chaobei River and the typical vanadium smelter in Hubei Province in four seasons. Microwave digestion–inductively coupled plasma mass spectrometry(ICP-MS) was applied to analyze the concentrations of vanadium(V), chromium(Cr), arsenic(As), and cadmium(Cd) in soils and plants. Soil pollution levels were evaluated on the basis of the Nemerow index method.The enrichment capabilities of plants for the four heavy metals were also analyzed.Results show that the heavy metal content of soil around the junction of the sewage outfall and the river is the highest among the seven sampling sites around Chaobei River.The concentration of V in the raw ore stacking area exceeds the limit by approximately 83 times and the concentrations of Cr,As,and Cd exceed the limit by approximately 2 times,which make the soil in the raw ore stacking area heavily contaminated.The soils in the six other sampling sites in the smelter are polluted in different degrees.The results of the evaluation of the enrichment and tolerance capabilities indicate that Gnaphalium affine,Erigeron multifolius,and Erigeron annuus have the highest tolerance capability for the four heavy metals.Conyza canadensis,Imperata cylindrica,Solanum photeinocarpum,Dendranthema indicum,Trifolium repens,and Echinochloa crusgalli are the hyperaccumulators for V,Cr,and Cd.The enrichment capabilities of Pteris vittata and Broussonetia papyrifera for As are extremely high.Moreover,Artemisia lavandulaefolia has a high enrichment capability for Cr and Cd,Ludwigia prostrata and Picris japonica have prominent tolerance and enrichment specificities for Cr and V,and Potentilla chinensis and Phytolacca americana have obvious enrichment capabilities for Cd specifically.The pot experiments of five local dominant terrestrial plants illustrate that,under the composite heavy metal contaminant conditions,Boehmeria nivea has the highest tolerance capability and Potentilla chinensis has the highest enrichment capability.
{"title":"Analysis of heavy metal contamination in the soil and enrichment capabilities of terrestrial plants around a typical vanadium smelter area","authors":"邵慧琪, 张又文, 曲琛, 厉文辉, 赵妍珺, 刘凝, 蔡寒梅, 吴传东, 刘杰民","doi":"10.13374/J.ISSN2095-9389.2019.04.23.001","DOIUrl":"https://doi.org/10.13374/J.ISSN2095-9389.2019.04.23.001","url":null,"abstract":"Phytoremediation is an important means of soil heavy metal pollution remediation. In order to figure out the soil pollution status of the water source in the middle line of the South-to-North Water Transfer Project and repair it, soil samples(n = 14)and local dominant terrestrial plants(n = 113) were collected in typical areas around Chaobei River and the typical vanadium smelter in Hubei Province in four seasons. Microwave digestion–inductively coupled plasma mass spectrometry(ICP-MS) was applied to analyze the concentrations of vanadium(V), chromium(Cr), arsenic(As), and cadmium(Cd) in soils and plants. Soil pollution levels were evaluated on the basis of the Nemerow index method.The enrichment capabilities of plants for the four heavy metals were also analyzed.Results show that the heavy metal content of soil around the junction of the sewage outfall and the river is the highest among the seven sampling sites around Chaobei River.The concentration of V in the raw ore stacking area exceeds the limit by approximately 83 times and the concentrations of Cr,As,and Cd exceed the limit by approximately 2 times,which make the soil in the raw ore stacking area heavily contaminated.The soils in the six other sampling sites in the smelter are polluted in different degrees.The results of the evaluation of the enrichment and tolerance capabilities indicate that Gnaphalium affine,Erigeron multifolius,and Erigeron annuus have the highest tolerance capability for the four heavy metals.Conyza canadensis,Imperata cylindrica,Solanum photeinocarpum,Dendranthema indicum,Trifolium repens,and Echinochloa crusgalli are the hyperaccumulators for V,Cr,and Cd.The enrichment capabilities of Pteris vittata and Broussonetia papyrifera for As are extremely high.Moreover,Artemisia lavandulaefolia has a high enrichment capability for Cr and Cd,Ludwigia prostrata and Picris japonica have prominent tolerance and enrichment specificities for Cr and V,and Potentilla chinensis and Phytolacca americana have obvious enrichment capabilities for Cd specifically.The pot experiments of five local dominant terrestrial plants illustrate that,under the composite heavy metal contaminant conditions,Boehmeria nivea has the highest tolerance capability and Potentilla chinensis has the highest enrichment capability.","PeriodicalId":31263,"journal":{"name":"工程设计学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86401631","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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