| [1] LI R, ZHANG Y, CHEN H. Knowledge discovery with computational fluid dynamics: Supercritical air-foil database and drag divergence prediction[J]. Phys-ics of Fluids, 2023, 35(1).[2] ZHOU H, XIE F, JI T, et al. Fast transonic flow pre-diction enables efficient aerodynamic design[J]. 2023, 35(2).[3] YANG H, CHEN S, GAO Z, et al. Reynolds number effect correction of multi-fidelity aerodynamic distri-butions from wind tunnel and simulation dat[J]. Physics of Fluids, 2023, 35(10).[4] WANG Z, ZHANG W, WANG X, et al. High precision aerodynamic heat prediction method based on data augmentation and transfer learning[J]. Aerospace Sci-ence and Technology, 2024, 155: 109663.[5] 樊云翔,艾化楠,王明振,等. 基于深度学习的水上飞机非定常水载荷重构[J]. 航空学报,2024,45(20):129882.FAN Y X,AI H N,WANG M Z,et al. Unsteady hydrodynamic load reconstruction of seaplane based on deep learning[J]. Acta Aeronautica et Astronautica Sinica, 2024,45(20):129882 (in Chinese).[6] ZHAO X, Deng Z C, Zhang W. Sparse reconstruction of surface pressure coefficient based on compressed sensing[J]. Experiments in Fluids, 2022, 63(10):156.[7] 罗长童, 胡宗民, 刘云峰, 等. 高超声速风洞气动力/热试验数据天地相关性研究进展[J]. 实验流体力学, 2020, 34(3): 78-89.LUO C T, HU Z M, LIU Y F, et al. Research progress on the correlation between heaven and earth of aero-dynamic/thermal test data in hypersonic wind tunnel [J]. Experimental Fluid Mechanics, 2020, 34 (3): 78-89 (in Chinese).[8] DOWELL E H. Eigenmode analysis in unsteady aero-dynamics-Reduced-order models[J]. AIAA Journal, 1996, 34(8):1578-1583.[9] 邓 晨,陈 功,王文正, 等. 基于飞行试验和风洞试验数据的融合算法研究[J]. 空气动力学学报, 2022, 40(6): 45-50.DENG C, CHEN G, WANG W Z, et al. Research on the data fusion algorithm based on flight test data and wind tunnel test data[J]. ActaAerodynamica Sinica, 2022, 40(6): 45-50 (in Chinese).[10] LI S, GAO Z, GAO C, et al. A Successive Gappy Proper Orthogonal Decomposition Approach and Its Application to Inverse Airfoil Design[C]//55th AIAA Aerospace Sciences Meeting. 2017:0709.[11] JIANG C, SOH Y C, Li H. Sensor and CFD data fu-sion for airflow field estimation[J]. applthermaleng, 2016, 78:149-161.[12] MOHAMED A, WOOD D. Deep learning predictions of unsteady aerodynamic loads on an airfoil model pitched over the entire operating range[J]. Physics of Fluids, 2023, 35(5).[13] LEI R, BAI J, WANG H, et al. Deep learning based multistage method for inverse design of supercritical airfoil[J]. Aerospace Science and Technology, 2021, 119: 107101.[14] LI K, KOU J, ZHANG W. Learning for Multifidelity Aerodynamic Distribution Modeling from Experi-mental and Simulation Data[J]. AIAA Journal, 2022, 60(7):4413-4427.[15] KOU J, NING C, ZHANG W. Transfer Learning for Flow Reconstruction Based on Multifidelity Data[J]. AIAA Journal, 2022, 60(10):5821-5842.[16] WANG X, KOU J, ZHANG W. Unsteady aerodynamic prediction for iced airfoil based on multi-task learn-ing[J]. Physics of Fluids, 2022, 34(8).[17] YU J, HESTHAVEN J S.Flowfield reconstruction method using artificial neural network[J]. AIAA Journal, 2019, 57(2):482-498.[18] LIU X, FENG Z, CHEN Y, et al. Multiple optimized support vector regression for multi-sensor data fusion of weigh-in-motion system[J]. Proceedings of the In-stitution of Mechnical Engineers. Part D: Journal of Automobile Engineering, 2020, 234(12):2807-2821.[19] 孙岩,邓小刚,张征宇,等. 跨声速风洞模型变形测量实验中标记点影响研究[J]. 空气动力学学报, 2013, 31(6) :769-755. SUN Y, DENG X G, ZHANG Z Y, et al. Targetinflu-ence on video model deformation experiments in transonic wind tunnel[J]. ACTA Aerodynamica Sinica, 2013, 31(6):769-755 (in Chinese).[20] 孙岩, 江盟, 孟德虹, 等. 交互式棱柱网格生成中翘曲现象形成机制及消除算法[J] . 航空学报, 2021 , 42(6) : 124443.SUN Y, JIANG M, MENG D H, et al. Formation mechanism and elimination algorithm of warpingin-interactive prismatic grid generation[J] . Acta Aero-nautica et Astronautica Sinica, 2021 , 42 (6) : 124443 (in Chinese). [21] Rendall T C S, Allen C B. Unified fluid-structure interpolation and mesh motion using radial basis functions[J]. International Journal for Numerical Methods in Engineering, 2008, 74(10):1519-1559.[22] RENDALL T C S , ALLEN C B. Multi-dimensional aircraft surface pressure interpolation using radial ba-sis functions[J]. Proceedings of the Institution of Me-chanical Engineers, Part G: Journal of Aerosapce En-gineering. 2008, 222(4):483-495.[23] 孙岩,孟德虹,王运涛,等.基于径向基函数与混合背景网格的动态网格变形方法[J].航空学报,2016,37[05]:1462-1472.SUN Y, MENG D H, WANG Y T, et al. Dynamic grid deformation method based on radial basis function and hybirid background grid[J]. Acta Aeronautica et Astronautica Sinica, 2016,37[05]:1462-1472.[24] BALLMANN J, DAFNIS A, KORSCH H, et al. Ex-perimental analysis of high Reynolds number aero-structural dynamics in ETW[R]. AIAA-2008-841, 2008 (in Chinese).[25] 郭秋亭,孙岩,郭正,等.风洞试验雷诺数/静气动弹性效应分离方法[J].航空学报,2022,43(11):52631.GUO Q T, SUN Y, GUO Z, et al. Separation method for Reynolds number/static aeroelastic coupling effect in wind tunnel test[J]. Acta Aeronautica et Astronauti-ca Sinica, 2022, 43(11):52631 (in Chinese). |