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Job Record #15545
TitlePressure reconstruction from PIV measurements using AI
LocationFrance, TOULOUSE
InternationalYes, international applications are welcome
Closure Date* None *
Context and Objectives

The department of Aerodynamics, Energetic and Propulsion (DAEP) at ISAE-Supaero is 
currently studying nano drones with flapping wings (Fig. 1, left). A crucial step in this design is 
the assessment of the aerodynamic forces (lift and drag) generated by this tiny drone when 
flapping its wings. However, while in computational fluid dynamics (CFD) all local data can be 
extracted (pressure, velocity, density etc.), in experiment only the velocity field can be easily 
obtained, especially for such small devices. Therefore, reconstructing the pressure field based 
on velocity PIV measurements is required, prior to reconstruct the aerodynamic forces. 
Classical methods exist, but have been found very sensitive to noise. Following a previous 
project (Fig. 1, right), an innovative approach based on Artificial Intelligence (AI) is proposed: 
using numerical simulations which provide both the velocity and pressure fields, a deep neural 
network is trained to reproduce the latter from the former. After the learning phase, the 
network is able to reconstruct an unknown pressure field from a noisy PIV velocity 
measurements with a high robustness to noise. This project will continue a previous work 
carried out on this topic (cylinder configurations, Fig. 1, right) to more complex configurations 
and flows. The target application is the reconstruction of the unsteady lift and drag forces 
from an actual experimental campaign. 
Contact Information:
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Email ApplicationYes
Record Data:
Last Modified13:05:16, Thursday, December 20, 2018

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