scholarly journals Projectile drag coefficient identification based on extreme learning

AIP Advances ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 095108
Author(s):  
Zhendong Liang ◽  
Jun Guan ◽  
Youran Xia ◽  
Wenjun Yi
2014 ◽  
Vol 687-691 ◽  
pp. 787-790
Author(s):  
Rong Jun Yang ◽  
Yao Ye

. For effectively using flight test data to extract drag coefficient, an optimal observer based on parameter estimation technique is proposed. The point mass dynamic equation is used to form the Unscented Kalman Filter (UKF) and the smoother (URTSS) for the estimation of a projectile’s flight states. The projectile flight states are then solved and utilized to extract the drag coefficient information using the observer techniques. The simulation verifies the feasibility of the method: with measurement noise, the accurate drag coefficient is obtained by using the smoother.


2012 ◽  
Vol 424-425 ◽  
pp. 464-470
Author(s):  
Zhou Zhong ◽  
Yi Jiang ◽  
Yong Yuan Li ◽  
Chong Zhang

The Firing Tables Compiling of a new type of the very low altitude interception device is studied in this paper. Based on the analysis of drag coefficient identification during the date processing of the Firing Tables experiment, and the theoretical trajectory correction, then according to the defects of the traditional methods for the Compilation of Firing Tables, a new method of determining the correction data is developed which replaces the simple data with the correction function. This method will reduce the error to an obvious degree.


2021 ◽  
Author(s):  
Shunchenqiao Bai ◽  
Guangwei Wen ◽  
Zhaokui Wang

Abstract Atmospheric drag calculation error greatly reduce the low-earth orbit spacecraft trajectory prediction fidelity. To solve the issue, the "correction - prediction" strategy is usually employed. In the method, one parameter is fixed and other parameters are revised by inverting spacecraft orbit data. However, based on a single spacecraft data, the strategy usually performs poorly as parameters in drag force calculation are coupled with each other, which result in convoluted errors. A gravity field recovery and atmospheric density detection satellite, Q-Sat, developed by xxxxx Lab at xxx University, is launched on August 6th, 2020. The satellite is designed to be spherical for a constant drag coefficient regardless of its attitude. An orbit prediction method for low-earth orbit spacecraft with employment of Q-Sat data is proposed in present paper for decoupling atmospheric density and drag coefficient identification process. For the first step, by using a dynamic approach-based inversion, several empirical atmospheric density models are revised based on Q-Sat orbit data. Depends on the performs, one of the revised atmospheric density model would be selected for the next step in which the same inversion is employed for drag coefficient identification for a low-earth orbit operating spacecraft whose orbit needs to be predicted. Finally, orbit forecast is conducted by extrapolation with the dynamic parameters in the previous steps. Tests are carried out for the proposed method by using a GOCE satellite 15-day continuous orbit data. Compared with legacy “correction - prediction” method in which only GOCE data is employed, the accuracy of the 24-hour orbit prediction is improved by about 171m the highest for the proposed method. 14-day averaged 24-hour prediction precision is elevated by approximately 70m.


2020 ◽  
pp. 34-42
Author(s):  
Thibault Chastel ◽  
Kevin Botten ◽  
Nathalie Durand ◽  
Nicole Goutal

Seagrass meadows are essential for protection of coastal erosion by damping wave and stabilizing the seabed. Seagrass are considered as a source of water resistance which modifies strongly the wave dynamics. As a part of EDF R & D seagrass restoration project in the Berre lagoon, we quantify the wave attenuation due to artificial vegetation distributed in a flume. Experiments have been conducted at Saint-Venant Hydraulics Laboratory wave flume (Chatou, France). We measure the wave damping with 13 resistive waves gauges along a distance L = 22.5 m for the “low” density and L = 12.15 m for the “high” density of vegetation mimics. A JONSWAP spectrum is used for the generation of irregular waves with significant wave height Hs ranging from 0.10 to 0.23 m and peak period Tp ranging from 1 to 3 s. Artificial vegetation is a model of Posidonia oceanica seagrass species represented by slightly flexible polypropylene shoots with 8 artificial leaves of 0.28 and 0.16 m height. Different hydrodynamics conditions (Hs, Tp, water depth hw) and geometrical parameters (submergence ratio α, shoot density N) have been tested to see their influence on wave attenuation. For a high submergence ratio (typically 0.7), the wave attenuation can reach 67% of the incident wave height whereas for a low submergence ratio (< 0.2) the wave attenuation is negligible. From each experiment, a bulk drag coefficient has been extracted following the energy dissipation model for irregular non-breaking waves developed by Mendez and Losada (2004). This model, based on the assumption that the energy loss over the species meadow is essentially due to the drag force, takes into account both wave and vegetation parameter. Finally, we found an empirical relationship for Cd depending on 2 dimensionless parameters: the Reynolds and Keulegan-Carpenter numbers. These relationships are compared with other similar studies.


2016 ◽  
Vol 10 (6) ◽  
pp. 390 ◽  
Author(s):  
Qummare Azam ◽  
Mohd Azmi Ismail ◽  
Nurul Musfirah Mazlan ◽  
Musavir Bashir

Author(s):  
Seyed Reza Amini Niaki ◽  
Joseph Mouallem ◽  
Christian Milioli ◽  
Fernando Milioli

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