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Aerodynamic Parameter Prediction via Artificial Hair Sensors with Signal Power in Turbulent Flow
- Source :
- AIAA Journal. 57:898-903
- Publication Year :
- 2019
- Publisher :
- American Institute of Aeronautics and Astronautics (AIAA), 2019.
-
Abstract
- Spatiotemporal surface flow information obtained from distributed arrays of bioinspired hair sensors are capable of predicting the real-time aerodynamic parameters (i.e., lift, moment, angle of att...
- Subjects :
- Physics
020301 aerospace & aeronautics
Lift coefficient
Turbulence
Acoustics
Computer Science::Neural and Evolutionary Computation
Flow (psychology)
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Aerospace Engineering
02 engineering and technology
Aerodynamics
01 natural sciences
Signal
010305 fluids & plasmas
Physics::Fluid Dynamics
Lift (force)
Moment (mathematics)
Boundary layer
0203 mechanical engineering
0103 physical sciences
ComputingMethodologies_COMPUTERGRAPHICS
Subjects
Details
- ISSN :
- 1533385X and 00011452
- Volume :
- 57
- Database :
- OpenAIRE
- Journal :
- AIAA Journal
- Accession number :
- edsair.doi...........ffe21c20e8a2b14fd4863a81562b9129
- Full Text :
- https://doi.org/10.2514/1.j057632