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  4. Shape optimisation of technical devices via gradient descent using convolutional neural network proxies
 
patent

Shape optimisation of technical devices via gradient descent using convolutional neural network proxies

Baqué, Pierre Bruno  
•
Fua, Pascal  
•
Fleuret, Francois  
2019

The present invention generally relates to a method, a system and a computer program for shape optimisation of a technical device adapted to be exposed to a fluid flowing around a contour of said device with respect to its fluid dynamic parameters. In order to provide an improved method for shape optimisation of a technical device with respect to its fluid dynamic parameters which is faster, a method is provided comprising discretizing the shape of the technical device into a plurality of points along the contour of the technical device or into a surface mesh,and inputting the plurality of points or the surface mesh into a Convolutional Neural Network (CNN) for computing a prediction of the at least one fluid dynamic parameter.

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Type
patent
EPO Family ID

59982331

Author(s)
Baqué, Pierre Bruno  
Fua, Pascal  
Fleuret, Francois  
Note

Alternative title(s) : (fr) Optimisation de forme de dispositifs techniques par descente du gradient à l'aide de mandataires de réseaux neuronaux à convolution

TTO classification

TTO:6.1764

EPFL units
AVP-R-TTO  
CVLAB  
DOICountry codeKind codeDate issued

US11768983

US

B2

2023-09-26

US2021157962

US

A1

2021-05-27

EP3679495

EP

A1

2020-07-15

CN111295657

CN

A

2020-06-16

WO2019048085

WO

A1

2019-03-14

Available on Infoscience
December 5, 2019
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/163741
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