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Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil

机译：机器学习非典型模型顺序降低参数型跨型跨越流过翼型

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S. Ashwin Renganathan; Romit Maulik; Vishwas Rao;
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1. Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil [J] . Renganathan S. Ashwin, Maulik Romit, Rao Vishwas Physics of fluids . 2020,第4期

机译：机器学习非典型模型顺序降低参数型跨型跨越流过翼型
2. Parametric Study of Flutter for an Airfoil in Inviscid Transonic Flow [J] . Denis B. Kholodar, Jeffrey P. Thomas, Earl H. Dowell, Journal of Aircraft . 2003,第2期

机译：跨音速流中翼型颤振的参数研究
3. Parametric non-intrusive model order reduction for flow-fields using unsupervised machine learning [J] . Lee SiHun, Jang Kijoo, Cho Haeseong, Computer Methods in Applied Mechanics and Engineering . 2021,第Octa1期

机译：使用无监督机器学习的流场的参数非侵入式模型顺序减少
4. Aerodynamic Data Predictions for Transonic Flows via a Machine-Learning-based Surrogate Model [C] . Remain Dupuis, Jean-Christophe Jouhaud, Pierre Sagaut AIAA/ASCE/AHS/ASC structures, structural dynamics and materials conference;AIAA SciTech Forum . 2018

机译：通过基于机器学习的替代模型进行跨音速流动的空气动力学数据预测
5. NUMERICAL CALCULATION OF UNSTEADY INVISCID ROTATIONAL TRANSONIC FLOW PAST AIRFOILS USING EULER EQUATIONS. [D] . DAMODARAN, MURALI. 1987

机译：使用EULER方程的非定常无粘性旋转跨音速流翼型的数值计算。
6. Benchmarking Parametric and Machine Learning Models for Genomic Prediction of Complex Traits [O] . Christina B. Azodi, Emily Bolger, Andrew McCarren, 2019

机译：复杂性状基因组预测的基准参数化和机器学习模型
7. Machine Learning-augmented Predictive Modeling of Turbulent Separated Flows over Airfoils [O] . Singh, Anand Pratap, Medida, Shivaji, Duraisamy, Karthik 2016

机译：机械学习增强的湍流分离预测模型飞过翼型
8. DIFFERENCES IN INVISCID ISENTROPIC MODELS USED FOR FINITE DIFFERENCE CALCULATION OF TRANSONIC FLOW WITH SHOCKS ABOUT AIRFOILS;THE PREDICTION OF WAVE DRAG [R] . J. Van Der Vooren, J. W. Slooff 1974

机译：用于翼型冲击的跨音速流动的有限差分计算的INVIsCID等幂模型的差异;波浪预测

Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil

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