Citation: | Wang Peng, Jin Xin. Study on artificial neural network modeling and wind tunnel test for the FADS system applied to the vehicle with sharp nosed fore-bodies[J]. Journal of Experiments in Fluid Mechanics, 2019, 33(5): 57-63. doi: 10.11729/syltlx20180125 |
[1] |
Ellsworth J C, Whitmore S A. Simulation of a flush air-data system for transatmospheric vehicles[J]. Journal of Spacecraft and Rockets, 2008, 45(4):716-732. doi: 10.2514/1.33541
|
[2] |
Siemers P M III, Wolf H, Henry M. Shuttle Entry Air Data System (SEADS)-flight verification of an advanced air data system concept[R]. AIAA-88-2014, 2014.
|
[3] |
Larson T J, Siemers P M III. Use of nose cap and fuselage pressure orifices for determination of air data for Space Shuttle Orbiter below supersonic speeds[R]. NASA TR-1643, 1980.
|
[4] |
Whitmore S A, Cobleigh B R, Haering E A Jr. Design and calibration of the X-33 Flush Airdata Sensing (FADS) system[R]. NASA/TM-1998-206540, 1998.
|
[5] |
Larson T J, Whitmore S A, Ehernberger L J, et al. Qualitative evaluation of a flush air data system at transonic speeds and high angles of attack[R]. NASA TP-2716, 1987.
|
[6] |
Larson T J, Siemers P M III. Subsonic tests of an all-flush-pressure-orifice air data system[R]. NASA TP-1871, 1981.
|
[7] |
Terry L J, Timothy R M, Siemers P M III. Wind-tunnel investigation of a flush airdata system at Mach numbers from 0.7 to 1.4[R]. NASA TM-101697, 1990.
|
[8] |
Westhelle C H. X-38 backup Air Data System(AeroDAD)[R]. AIAA 2002-0007, 2002.
|
[9] |
Ellsworth J C, Whitmore S A. Reentry air data system for a sub-orbital spacecraft based on X-34 design[R]. AIAA 2007-1200, 2007.
|
[10] |
Crowther W J, Lamont P J. A neural network approach to the calibration of a flush air data system[J]. The Aeronautical Journal, 2011, 105(1044):85-95. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=cb3d4fbbfee5264c0a7aa7990ca5627b
|
[11] |
Calia A, Denti E, Galatolo R, et al. Air data computation using neural networks[J]. Journal of Aircraft, 2008, 45(6):2078-2083. doi: 10.2514/1.37334
|
[12] |
Rohloff T J, Whitmore S A, Catton I. Fault-tolerant neural network algorithm for flush air data sensing[J]. Journal of Aircraft, 1999, 36(3):541-549. doi: 10.2514/2.2489
|
[13] |
Samy I, Postlethwaite I, Gu D W. Neural-network-based flush air data sensing system demonstrated on a mini air vehicle[J]. Journal of Aircraft, 2010, 47(1):18-31. doi: 10.2514/1.44157
|
[14] |
王鹏, 胡远思, 金鑫.尖楔前体飞行器FADS系统驻点压力对神经网络算法精度的影响[J].宇航学报, 2016, 37(9):1072-1079. doi: 10.3873/j.issn.1000-1328.2016.09.006
Wang P, Hu Y S, Jin X. Effect of stagnation pressure on the neural network algorithm accuracy for the FADS system applied to the vehicle with sharp wedged fore-bodies[J]. Journal of Astronautics, 2016, 37(9):1072-1079. doi: 10.3873/j.issn.1000-1328.2016.09.006
|
[15] |
王鹏, 金鑫, 张卫民, 等.钝头机体用FADS系统的校准[J].实验流体力学, 2016, 30(2):97-102. http://www.syltlx.com/CN/abstract/abstract10924.shtml
Wang P, Jin X, Zhang W M. Calibration for the FADS system applied to the vehicle with blunt fore-bodies[J]. Journal of Experiments in Fluid Mechanics, 2016, 30(2):97-102. http://www.syltlx.com/CN/abstract/abstract10924.shtml
|
[16] |
王鹏, 金鑫, 张卫民. FADS系统测压孔配置对攻角校准的影响[J].战术导弹技术, 2013, (2):51-55. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zsddjs201302011
Wang P, Jin X, Zhang W M. The effect of configuration of pressure ports on calibration for angle of attack in FADS system[J]. Tactical Missile Technology, 2013, (2):51-55. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zsddjs201302011
|
[17] |
Li Y, Sundararajan N, Saratchandran P. Analysis of minimal radial basis function network algorithm for real-time identifi-cation of nonlinear dynamic systems[J]. IEE Proceedings-Control Theory and Applications, 2000, 147(4):476-484. doi: 10.1049/ip-cta:20000549
|