The massive amount and multi-sourced,multi-structured data in the upstream petroleum industry impose great challenge on data integration and smart application.Knowledge graph,as an emerging technology,can potentially ...The massive amount and multi-sourced,multi-structured data in the upstream petroleum industry impose great challenge on data integration and smart application.Knowledge graph,as an emerging technology,can potentially provide a way to tackle the challenges associated with oil and gas big data.This paper proposes an engineering-based method that can improve upon traditional natural language processing to construct the domain knowledge graph based on a petroleum exploration and development ontology.The exploration and development knowledge graph is constructed by assembling Sinopec’s multi-sourced heterogeneous database,and millions of nodes.The two applications based on the constructed knowledge graph are developed and validated for effectiveness and advantages in providing better knowledge services for the oil and gas industry.展开更多
This paper analyzed the relationship between entrepreneurial orientation and new product development perlormance based on the perspective of knowledge creation process. Through a questionnaire survey, we found that en...This paper analyzed the relationship between entrepreneurial orientation and new product development perlormance based on the perspective of knowledge creation process. Through a questionnaire survey, we found that entrepreneurial orientation is positively related to new product performance, and knowledge creation process plays a mediating role in this relationship. This article examines the role of entrepreneurial orientation on new product innovation performance in Chinese situations, and it is the first time to check the intermediary functions on each dimension of knowledge test between entrepreneurial orientation and new product development performance.展开更多
China is currently vigorously implementing the“energy conservation and emission reduction”and“dual carbon”strategies.As the most resource-advantaged light metal material in China,Magnesium(Mg)alloy is progressivel...China is currently vigorously implementing the“energy conservation and emission reduction”and“dual carbon”strategies.As the most resource-advantaged light metal material in China,Magnesium(Mg)alloy is progressively expanding its application in automobile,rail transportation,aerospace,medical,and electronic products.Chongqing University,Shanghai Jiaotong University,and Australian National University have conducted extensive research on the preparation,properties,and processes of Mg alloys.In the past 20 years,the proportion of Mg alloy in the automotive industry has gradually expanded,whereas currently the design and development of Mg alloy parts for automobiles has rarely been reported.Thus,the application models and typical parts cases of Mg alloy are summarized mainly from the four systems of the whole vehicle(body system,chassis system,powertrain system,interior,and exterior system).Subsequently,two actual original equipment manufacturers(OEM)cases are used to introduce the development logic of reliable die-cast Mg alloy,including forward design,formability analysis,process design analysis,structural redesign,manufacturing,and testing,aiming to share the methods,processes,and focus of attention of automotive OEMs for developing Mg alloy parts to enhance the confidence and motivation of applying Mg alloy in automotive field.Eventually,the multiple challenges faced by Mg alloy materials are sorted out and how to face these challenges are discussed.National policies and regulations,environmental protection and energy saving,and consumer demand will continue to promote the application of Mg.展开更多
The integration of artificial intelligence into the development and production of mechatronic products offers a substantial opportunity to enhance efficiency, adaptability, and system performance. This paper examines ...The integration of artificial intelligence into the development and production of mechatronic products offers a substantial opportunity to enhance efficiency, adaptability, and system performance. This paper examines the utilization of reinforcement learning as a control strategy, with a particular focus on its deployment in pivotal stages of the product development lifecycle, specifically between system architecture and system integration and verification. A controller based on reinforcement learning was developed and evaluated in comparison to traditional proportional-integral controllers in dynamic and fault-prone environments. The results illustrate the superior adaptability, stability, and optimization potential of the reinforcement learning approach, particularly in addressing dynamic disturbances and ensuring robust performance. The study illustrates how reinforcement learning can facilitate the transition from conceptual design to implementation by automating optimization processes, enabling interface automation, and enhancing system-level testing. Based on the aforementioned findings, this paper presents future directions for research, which include the integration of domain-specific knowledge into the reinforcement learning process and the validation of this process in real-world environments. The results underscore the potential of artificial intelligence-driven methodologies to revolutionize the design and deployment of intelligent mechatronic systems.展开更多
基金support is gratefully acknowledged to the National Natural Science Foundation of China(Grant No.42050104)National Science and Technology Support Program(Grant No.2012BAH34F00)National Oil and Gas Major Special Project(Grant No.2016ZX05033005).
文摘The massive amount and multi-sourced,multi-structured data in the upstream petroleum industry impose great challenge on data integration and smart application.Knowledge graph,as an emerging technology,can potentially provide a way to tackle the challenges associated with oil and gas big data.This paper proposes an engineering-based method that can improve upon traditional natural language processing to construct the domain knowledge graph based on a petroleum exploration and development ontology.The exploration and development knowledge graph is constructed by assembling Sinopec’s multi-sourced heterogeneous database,and millions of nodes.The two applications based on the constructed knowledge graph are developed and validated for effectiveness and advantages in providing better knowledge services for the oil and gas industry.
文摘This paper analyzed the relationship between entrepreneurial orientation and new product development perlormance based on the perspective of knowledge creation process. Through a questionnaire survey, we found that entrepreneurial orientation is positively related to new product performance, and knowledge creation process plays a mediating role in this relationship. This article examines the role of entrepreneurial orientation on new product innovation performance in Chinese situations, and it is the first time to check the intermediary functions on each dimension of knowledge test between entrepreneurial orientation and new product development performance.
基金supported partly by the Fundamental Research Funds for Central Universities(No.06500203 and No.00007735).
文摘China is currently vigorously implementing the“energy conservation and emission reduction”and“dual carbon”strategies.As the most resource-advantaged light metal material in China,Magnesium(Mg)alloy is progressively expanding its application in automobile,rail transportation,aerospace,medical,and electronic products.Chongqing University,Shanghai Jiaotong University,and Australian National University have conducted extensive research on the preparation,properties,and processes of Mg alloys.In the past 20 years,the proportion of Mg alloy in the automotive industry has gradually expanded,whereas currently the design and development of Mg alloy parts for automobiles has rarely been reported.Thus,the application models and typical parts cases of Mg alloy are summarized mainly from the four systems of the whole vehicle(body system,chassis system,powertrain system,interior,and exterior system).Subsequently,two actual original equipment manufacturers(OEM)cases are used to introduce the development logic of reliable die-cast Mg alloy,including forward design,formability analysis,process design analysis,structural redesign,manufacturing,and testing,aiming to share the methods,processes,and focus of attention of automotive OEMs for developing Mg alloy parts to enhance the confidence and motivation of applying Mg alloy in automotive field.Eventually,the multiple challenges faced by Mg alloy materials are sorted out and how to face these challenges are discussed.National policies and regulations,environmental protection and energy saving,and consumer demand will continue to promote the application of Mg.
文摘The integration of artificial intelligence into the development and production of mechatronic products offers a substantial opportunity to enhance efficiency, adaptability, and system performance. This paper examines the utilization of reinforcement learning as a control strategy, with a particular focus on its deployment in pivotal stages of the product development lifecycle, specifically between system architecture and system integration and verification. A controller based on reinforcement learning was developed and evaluated in comparison to traditional proportional-integral controllers in dynamic and fault-prone environments. The results illustrate the superior adaptability, stability, and optimization potential of the reinforcement learning approach, particularly in addressing dynamic disturbances and ensuring robust performance. The study illustrates how reinforcement learning can facilitate the transition from conceptual design to implementation by automating optimization processes, enabling interface automation, and enhancing system-level testing. Based on the aforementioned findings, this paper presents future directions for research, which include the integration of domain-specific knowledge into the reinforcement learning process and the validation of this process in real-world environments. The results underscore the potential of artificial intelligence-driven methodologies to revolutionize the design and deployment of intelligent mechatronic systems.
