Academic Journal

Feature extraction and reduced-order modelling of nitrogen plasma models using principal component analysis

التفاصيل البيبلوغرافية
العنوان: Feature extraction and reduced-order modelling of nitrogen plasma models using principal component analysis
المؤلفون: Bellemans, Aurélie, Aversano, Gianmarco, Coussement, Axel, Parente, Alessandro
المصدر: Computers & chemical engineering
سنة النشر: 2018
المجموعة: DI-fusion : dépôt institutionnel de l'Université libre de Bruxelles (ULB)
مصطلحات موضوعية: Sciences de l'ingénieur, Mécanique des fluides, Chemistry reduction, Dynamical study, Physical interpretation, Plasma flows, Principal component analysis
الوصف: Principal component analysis has been presented in recent research as an accurate and efficient method to reduce the complex chemistry and kinetics of large reacting mechanisms. Following the reduction, the original variables are transformed and projected onto a set of independent, orthogonal variables maximizing the total variance in the system: the principal components. However, these new variables are difficult to interpret physically and may introduce instabilities in the low dimensional representation of the manifold. In the present paper we will show the benefits of coupling PCA to a rotation method: the interpretation of the principal components can be related back to the physics. The advantages of rotation are demonstrated on a PCA reduced model for modelling dissociation and excitation processes in nitrogen shock flows. ; This project has received funding from the European Unions Horizon 2020 re- search and innovation program under the Marie Sklodowska-Curie grant agreement No 643134. ; SCOPUS: ar.j ; info:eu-repo/semantics/published
نوع الوثيقة: article in journal/newspaper
وصف الملف: 2 full-text file(s): application/pdf | application/pdf
اللغة: English
Relation: uri/info:doi/10.1016/j.compchemeng.2018.05.012; uri/info:pii/S0098135418304551; uri/info:scp/85047624128; https://dipot.ulb.ac.be/dspace/bitstream/2013/271048/3/Cace6111_Postprint.pdf; https://dipot.ulb.ac.be/dspace/bitstream/2013/271048/4/Elsevier_254675.pdf; http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/271048
الاتاحة: http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/271048
https://dipot.ulb.ac.be/dspace/bitstream/2013/271048/3/Cace6111_Postprint.pdf
https://dipot.ulb.ac.be/dspace/bitstream/2013/271048/4/Elsevier_254675.pdf
رقم الانضمام: edsbas.B64A5D72
قاعدة البيانات: BASE