Systematic Uncertainty Analysis of Aerodynamic Coefficients Obtained by Flight Tests Using the JAXA Flying Test Bed “Hisho”

2017 ◽  
Vol 65 (3) ◽  
pp. 135-136
Author(s):  
Masaru SAIJO ◽  
Kanako YASUE ◽  
Makoto UENO ◽  
Masaru NARUOKA ◽  
Hiroshi TOMITA ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
Systematic Uncertainty ◽  
Test Bed ◽  
Aerodynamic Coefficients ◽  
Flight Tests

Uncertainty Analysis of Aerodynamic Coefficients in an Automotive Wind Tunnel

2005 ◽  
Author(s):  
Joel A. Walter ◽  
Victor Canacci ◽  
R. K. Rout ◽  
Wayne Koester ◽  
Jack Williams ◽  
...  
Keyword(s):  
Wind Tunnel ◽  
Uncertainty Analysis ◽  
Aerodynamic Coefficients

scholarly journals Uncertainty Analysis of a Test Bed for Calibrating Voltage Transformers vs. Temperature

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4472 ◽  
Author(s):  
Mingotti ◽  
Peretto ◽  
Tinarelli ◽  
Ghaderi
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Uncertainty Analysis ◽  
Random Effects ◽  
Evaluation Method ◽  
Uncertainty Evaluation ◽  
Test Bed ◽  
Uncertainty Sources ◽  
The Monte Carlo Method

The paper addresses the evaluation of the uncertainty sources of a test bed system for calibrating voltage transformers vs. temperature. In particular, the Monte Carlo method has been applied in order to evaluate the effects of the uncertainty sources in two different conditions: by using the nominal accuracy specifications of the elements which compose the setup, or by exploiting the results of their metrological characterization. In addition, the influence of random effects on the system accuracy has been quantified and evaluated. From the results, it emerges that the choice of the uncertainty evaluation method affects the overall study. As a matter of fact, the use of a metrological characterization or of accuracy specifications provided by the manufacturers provides respectively an accuracy of 0.1 and 0.5 for the overall measurement setup.

A Systematic Uncertainty Analysis of an Evaluative Fate and Exposure Model

Risk Analysis ◽  
2000 ◽  
Vol 20 (4) ◽  
pp. 439-454 ◽  
Author(s):  
Edgar G. Hertwich ◽  
Thomas E. McKone ◽  
William S. Pease
Keyword(s):  
Uncertainty Analysis ◽  
Systematic Uncertainty ◽  
Exposure Model

Northern European Satellite Test Bed

1999 ◽  
Vol 52 (2) ◽  
pp. 235-245
Author(s):  
Alan Schuster-Bruce ◽  
James Lawson ◽  
Michael Quinlan ◽  
Andrew McGregor
Keyword(s):  
Test Bed ◽  
Flight Tests ◽  
Northern European ◽  
Control Centre ◽  
The Usa ◽  
Master Control ◽  
European Satellite

Satellite Based Augmentation Systems are being developed in Europe (EGNOS), the USA (WAAS), and in Japan (MSAS). As part of their support to EGNOS, NATS and Racal have developed and deployed a prototype SBAS system called the Northern European Satellite Test Bed (NEST Bed). NEST Bed uses GPS L1/L2 reference stations at: Aberdeen, Rotterdam, Ankara, Cadiz, Keflavik, and Bronnoysund. Data is sent to the Master Control Centre at NATS Gatwick Services Management Centre for processing. The resulting 250 bits-per-second message is sent to Goonhilly for up-linking by BT to the Navigation Payload of either the Inmarsat AOR-E or F5 spare satellite. NEST Bed was deployed and commissioned during summer 1998, and flight tests were successfully demonstrated at the September 1998 Farnborough Air Show where approaches were flown to Boscombe Down on the DERA BAC1-11 aircraft. In October 1998, a NATS/FAA flight trial was held in Iceland involving NEST Bed and the FAA NSTB. NEST Bed is also being used for SARPS validation.

Development and Flight Test Evaluations of an Autonomous Obstacle Avoidance System for a Rotary-Wing UAV

2013 ◽  
Vol 01 (01) ◽  
pp. 3-19 ◽  
Author(s):  
Keeryun Kang ◽  
J. V. R. Prasad
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Trajectory Optimization ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Georgia Tech ◽  
Test Bed ◽  
Optimization Scheme ◽  
Flight Tests ◽  
Rotary Wing

This paper presents the development and flight-testing of an obstacle avoidance system that can provide a rotary-wing unmanned aerial vehicle (UAV) the autonomous obstacle field navigation capability in uncertain environment. The system is composed of a sensor, an obstacle map generation algorithm from sensor measurements, an online path planning algorithm, and an adaptive vehicle controller. The novel approach of path planning presented in the paper is the integration of a newly developed receding horizon (RH) trajectory optimization scheme with a global path searching algorithm. The developed RH trajectory optimization scheme solves the local nonlinear trajectory optimization problem using approximated vehicle dynamics, maneuverability constraints, and terrain constraints within the finite range of the sensor. The global path searching by dynamic programming algorithm finds the shortest path to the destination to provide the initial guess to the RH trajectory optimization. The spline-based direct solver, Nonlinear Trajectory Generation (NTG), solves the RH trajectory optimization in real time and updates the solution continuously. The developed system is implemented within the Georgia Tech UAV Simulation Tool (GUST) and on the onboard computer of the Georgia Tech UAV test bed. Simulations and flight tests carried out for the benchmark scenarios and with sensor-in-the-loop flight tests demonstrated the viability of the developed system for autonomous obstacle field navigation capability of a UAV.

Identifiability investigation of the aerodynamic coefficients from free flight tests

2013 ◽  
Author(s):  
Marie Albisser ◽  
Simona Dobre ◽  
Claude Berner ◽  
Magalie Thomassin ◽  
Hugues Garnier
Keyword(s):  
Free Flight ◽  
Aerodynamic Coefficients ◽  
Flight Tests
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