Digital twin modeling
The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of t...
Ausführliche Beschreibung
Autor*in: |
Tao, Fei [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2022transfer abstract |
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18 |
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Übergeordnetes Werk: |
Enthalten in: Tilting at windmills? Electoral repercussions of wind turbine projects in Minnesota - Bayulgen, Oksan ELSEVIER, 2021, Dearborn, Mich |
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Übergeordnetes Werk: |
volume:64 ; year:2022 ; pages:372-389 ; extent:18 |
Links: |
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DOI / URN: |
10.1016/j.jmsy.2022.06.015 |
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520 | |a The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. | ||
520 | |a The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. | ||
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10.1016/j.jmsy.2022.06.015 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001931.pica (DE-627)ELV058888519 (ELSEVIER)S0278-6125(22)00110-8 DE-627 ger DE-627 rakwb eng 620 VZ 83.65 bkl Tao, Fei verfasserin aut Digital twin modeling 2022transfer abstract 18 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. Enabling technologies Elsevier Digital twin Elsevier Enabling tools Elsevier Digital twin modeling Elsevier Digital twin model Elsevier Xiao, Bin oth Qi, Qinglin oth Cheng, Jiangfeng oth Ji, Ping oth Enthalten in Soc Bayulgen, Oksan ELSEVIER Tilting at windmills? Electoral repercussions of wind turbine projects in Minnesota 2021 Dearborn, Mich (DE-627)ELV00685088X volume:64 year:2022 pages:372-389 extent:18 https://doi.org/10.1016/j.jmsy.2022.06.015 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 83.65 Versorgungswirtschaft VZ AR 64 2022 372-389 18 |
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10.1016/j.jmsy.2022.06.015 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001931.pica (DE-627)ELV058888519 (ELSEVIER)S0278-6125(22)00110-8 DE-627 ger DE-627 rakwb eng 620 VZ 83.65 bkl Tao, Fei verfasserin aut Digital twin modeling 2022transfer abstract 18 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. Enabling technologies Elsevier Digital twin Elsevier Enabling tools Elsevier Digital twin modeling Elsevier Digital twin model Elsevier Xiao, Bin oth Qi, Qinglin oth Cheng, Jiangfeng oth Ji, Ping oth Enthalten in Soc Bayulgen, Oksan ELSEVIER Tilting at windmills? Electoral repercussions of wind turbine projects in Minnesota 2021 Dearborn, Mich (DE-627)ELV00685088X volume:64 year:2022 pages:372-389 extent:18 https://doi.org/10.1016/j.jmsy.2022.06.015 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 83.65 Versorgungswirtschaft VZ AR 64 2022 372-389 18 |
allfields_unstemmed |
10.1016/j.jmsy.2022.06.015 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001931.pica (DE-627)ELV058888519 (ELSEVIER)S0278-6125(22)00110-8 DE-627 ger DE-627 rakwb eng 620 VZ 83.65 bkl Tao, Fei verfasserin aut Digital twin modeling 2022transfer abstract 18 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. Enabling technologies Elsevier Digital twin Elsevier Enabling tools Elsevier Digital twin modeling Elsevier Digital twin model Elsevier Xiao, Bin oth Qi, Qinglin oth Cheng, Jiangfeng oth Ji, Ping oth Enthalten in Soc Bayulgen, Oksan ELSEVIER Tilting at windmills? Electoral repercussions of wind turbine projects in Minnesota 2021 Dearborn, Mich (DE-627)ELV00685088X volume:64 year:2022 pages:372-389 extent:18 https://doi.org/10.1016/j.jmsy.2022.06.015 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 83.65 Versorgungswirtschaft VZ AR 64 2022 372-389 18 |
allfieldsGer |
10.1016/j.jmsy.2022.06.015 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001931.pica (DE-627)ELV058888519 (ELSEVIER)S0278-6125(22)00110-8 DE-627 ger DE-627 rakwb eng 620 VZ 83.65 bkl Tao, Fei verfasserin aut Digital twin modeling 2022transfer abstract 18 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. Enabling technologies Elsevier Digital twin Elsevier Enabling tools Elsevier Digital twin modeling Elsevier Digital twin model Elsevier Xiao, Bin oth Qi, Qinglin oth Cheng, Jiangfeng oth Ji, Ping oth Enthalten in Soc Bayulgen, Oksan ELSEVIER Tilting at windmills? Electoral repercussions of wind turbine projects in Minnesota 2021 Dearborn, Mich (DE-627)ELV00685088X volume:64 year:2022 pages:372-389 extent:18 https://doi.org/10.1016/j.jmsy.2022.06.015 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 83.65 Versorgungswirtschaft VZ AR 64 2022 372-389 18 |
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Tilting at windmills? Electoral repercussions of wind turbine projects in Minnesota |
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Tilting at windmills? Electoral repercussions of wind turbine projects in Minnesota |
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The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. |
abstractGer |
The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. |
abstract_unstemmed |
The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented. |
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Digital twin modeling |
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Xiao, Bin Qi, Qinglin Cheng, Jiangfeng Ji, Ping |
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