%0 Conference Paper %1 gavrilenko2022order %A Gavrilenko, Pavel %A Haasdonk, Bernard %A Iliev, Oleg %A Ohlberger, Mario %A Schindler, Felix %A Toktaliev, Pavel %A Wenzel, Tizian %A Youssef, Maha %B Large-Scale Scientific Computing %C Cham %D 2022 %E Lirkov, Ivan %E Margenov, Svetozar %I Springer International Publishing %K exc2075 from:tizianwenzel ians myown peerreviewed pn6 pn6-1 %P 378--386 %T A Full Order, Reduced Order and Machine Learning Model Pipeline for Efficient Prediction of Reactive Flows %X We present an integrated approach for the use of simulated data from full order discretization as well as projection-based Reduced Basis reduced order models for the training of machine learning approaches, in particular Kernel Methods, in order to achieve fast, reliable predictive models for the chemical conversion rate in reactive flows with varying transport regimes. %@ 978-3-030-97549-4

@inproceedings{gavrilenko2022order, abstract = {We present an integrated approach for the use of simulated data from full order discretization as well as projection-based Reduced Basis reduced order models for the training of machine learning approaches, in particular Kernel Methods, in order to achieve fast, reliable predictive models for the chemical conversion rate in reactive flows with varying transport regimes.}, added-at = {2022-04-22T14:48:52.000+0200}, address = {Cham}, author = {Gavrilenko, Pavel and Haasdonk, Bernard and Iliev, Oleg and Ohlberger, Mario and Schindler, Felix and Toktaliev, Pavel and Wenzel, Tizian and Youssef, Maha}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2918f84b215506197a18d55d6c0e130da/mathematik}, booktitle = {Large-Scale Scientific Computing}, editor = {Lirkov, Ivan and Margenov, Svetozar}, interhash = {b3f223235af91c94685ca80f690ff321}, intrahash = {918f84b215506197a18d55d6c0e130da}, isbn = {978-3-030-97549-4}, keywords = {exc2075 from:tizianwenzel ians myown peerreviewed pn6 pn6-1}, pages = {378--386}, publisher = {Springer International Publishing}, timestamp = {2022-05-02T13:56:19.000+0200}, title = {A Full Order, Reduced Order and Machine Learning Model Pipeline for Efficient Prediction of Reactive Flows}, year = 2022 }