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Smart Manufacturing for the Oil Refining and Petrochemical Industry
Zhihong Yuan,Weizhong Qin,Jinsong Zhao
Engineering 2017, Volume 3, Issue 2, Pages 179-182 doi: 10.1016/J.ENG.2017.02.012
Smart manufacturing will transform the oil refining and petrochemical sector into a connected, information-drivenenvironment.the petrochemical sector are demonstrated, such as the fault detection of a catalytic cracking unit drivenby big data, advanced optimization for the planning and scheduling of oil refinery sites, and more.
Keywords: Smart manufacturing Petrochemical Data-/information-driven environment
Frontiers in Energy 2022, Volume 16, Issue 1, Pages 121-129 doi: 10.1007/s11708-021-0780-x
Keywords: power distribution network data-driven topology identification distributed energy resource maximalinformation coefficient
Berardo NATICCHIA, Alessandra CORNELI, Alessandro CARBONARI
Frontiers of Engineering Management 2020, Volume 7, Issue 1, Pages 131-141 doi: 10.1007/s42524-019-0071-y
Keywords: information flow management BIM mixed reality common data environment facility management
Data driven models for compressive strength prediction of concrete at high temperatures
Mahmood AKBARI, Vahid JAFARI DELIGANI
Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 2, Pages 311-321 doi: 10.1007/s11709-019-0593-8
Keywords: data driven model compressive strength concrete high temperature
Prediction of hydro-suction dredging depth using data-driven methods
Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 3, Pages 652-664 doi: 10.1007/s11709-021-0719-7
Keywords: sedimentation water resources dam engineering machine learning heuristic
Digital twin for healthy indoor environment: A vision for the post-pandemic era
Frontiers of Engineering Management 2023, Volume 10, Issue 2, Pages 300-318 doi: 10.1007/s42524-022-0244-y
Keywords: digital twin healthy indoor environment building information modeling occupant–building interaction
Physics-Informed Deep Learning-Based Real-Time Structural Response Prediction Method
Ying Zhou,Shiqiao Meng,Yujie Lou,Qingzhao Kong,
Engineering doi: 10.1016/j.eng.2023.08.011
Keywords: Structural seismic response prediction Physics information informed Real-time prediction Earthquake engineering Data-driven machine learning
Optimal Antibody Purification Strategies Using Data-Driven Models Article
Songsong Liu, Lazaros G. Papageorgiou
Engineering 2019, Volume 5, Issue 6, Pages 1077-1092 doi: 10.1016/j.eng.2019.10.011
Keywords: Antibody purification Multiscale optimization Antigen-binding fragment Mixed-integer programming Data-driven
Connecting Information to Promote Public Health
Xue-mei Su,Jia Zhao
Frontiers of Engineering Management 2016, Volume 3, Issue 4, Pages 384-389 doi: 10.15302/J-FEM-2016054
Keywords: public health information system data exchange China
Data-Driven Anomaly Diagnosis for Machining Processes Article
Y.C. Liang, S. Wang, W.D. Li, X. Lu
Engineering 2019, Volume 5, Issue 4, Pages 646-652 doi: 10.1016/j.eng.2019.03.012
Keywords: Computer numerical control machining Anomaly detection Fruit fly optimization algorithm Data-driven
Li Sun, Fengqi You
Engineering 2021, Volume 7, Issue 9, Pages 1239-1247 doi: 10.1016/j.eng.2021.04.020
Keywords: Smart power generation Machine learning Data-driven control Systems engineering
Information Sunshine: the Collisionless Information Sharing Architecture
Li Youping
Strategic Study of CAE 2000, Volume 2, Issue 1, Pages 24-27
The novel information sharing architecture, Information Sunshine, is presented in the paper.Two core concepts of the Information Sunshine idea are Data Stream Environment (DSE) and Personal Demandingpush .capacity of DVB, and then the nationwide flow of the high speed data stream forms a digital environmentAfter storing, users can locally interact with the information without remote connection requirement.Only single-way broadcasting network required by the Information Sunshine architecture, so it is low
Keywords: Data broadcasting DVB network collisionless
An adaptive data-driven method for accurate prediction of remaining useful life of rolling bearings
Yanfeng PENG, Junsheng CHENG, Yanfei LIU, Xuejun LI, Zhihua PENG
Frontiers of Mechanical Engineering 2018, Volume 13, Issue 2, Pages 301-310 doi: 10.1007/s11465-017-0449-7
A novel data-driven method based on Gaussian mixture model (GMM) and distance evaluation techniqueThe data sets are clustered by GMM to divide all data sets into several health states adaptively andThus, either the health state of the data sets or the number of the states is obtained automatically.training data sets.sets into several health states and remove the abnormal data sets.
Keywords: Gaussian mixture model distance evaluation technique health state remaining useful life rolling bearing
Hybrid Data-Driven and Mechanistic Modeling Approaches for Multiscale Material and Process Design Perspective
Teng Zhou, Rafiqul Gani, Kai Sundmacher
Engineering 2021, Volume 7, Issue 9, Pages 1231-1238 doi: 10.1016/j.eng.2020.12.022
Keywords: Data-driven Surrogate model Machine learning Hybrid modeling Material design Process optimization
A hierarchical system to predict behavior of soil and cantilever sheet wall by data-driven models
Nang Duc BUI; Hieu Chi PHAN; Tiep Duc PHAM; Ashutosh Sutra DHAR
Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 6, Pages 667-684 doi: 10.1007/s11709-022-0822-4
Keywords: finite element analysis cantilever sheet wall machine learning artificial neural network random forest
Title Author Date Type Operation
Smart Manufacturing for the Oil Refining and Petrochemical Industry
Zhihong Yuan,Weizhong Qin,Jinsong Zhao
Journal Article
Data-driven distribution network topology identification considering correlated generation power of distributed
Journal Article
Framework based on building information modeling, mixed reality, and a cloud platform to support information
Berardo NATICCHIA, Alessandra CORNELI, Alessandro CARBONARI
Journal Article
Data driven models for compressive strength prediction of concrete at high temperatures
Mahmood AKBARI, Vahid JAFARI DELIGANI
Journal Article
Physics-Informed Deep Learning-Based Real-Time Structural Response Prediction Method
Ying Zhou,Shiqiao Meng,Yujie Lou,Qingzhao Kong,
Journal Article
Optimal Antibody Purification Strategies Using Data-Driven Models
Songsong Liu, Lazaros G. Papageorgiou
Journal Article
Data-Driven Anomaly Diagnosis for Machining Processes
Y.C. Liang, S. Wang, W.D. Li, X. Lu
Journal Article
Machine Learning and Data-Driven Techniques for the Control of Smart Power Generation Systems: An Uncertainty
Li Sun, Fengqi You
Journal Article
An adaptive data-driven method for accurate prediction of remaining useful life of rolling bearings
Yanfeng PENG, Junsheng CHENG, Yanfei LIU, Xuejun LI, Zhihua PENG
Journal Article
Hybrid Data-Driven and Mechanistic Modeling Approaches for Multiscale Material and Process Design
Teng Zhou, Rafiqul Gani, Kai Sundmacher
Journal Article