The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 28, 2020

Filed:

Oct. 26, 2016
Applicants:

Dev Rajnarayan, Mountain View, CA (US);

Peter Sturdza, Redwood City, AZ (US);

Inventors:

Dev Rajnarayan, Mountain View, CA (US);

Peter Sturdza, Redwood City, AZ (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01M 9/06 (2006.01); G06F 17/50 (2006.01); G01M 9/08 (2006.01);
U.S. Cl.
CPC ...
G01M 9/065 (2013.01); G01M 9/08 (2013.01); G06F 17/5009 (2013.01); G06F 17/5095 (2013.01); G06F 2217/16 (2013.01); Y02T 90/50 (2018.05);
Abstract

In accordance with embodiments disclosed herein, there are provided methods, systems, and apparatuses for predicting whether a point on a computer-generated aircraft or vehicle surface is adjacent to laminar or turbulent flow is made using a transition prediction technique. A plurality of boundary-layer properties at the point are obtained from a steady-state solution of a fluid flow in a region adjacent to the point. Included in the list of boundary-layer properties are computed coefficients or weights of mode shapes that describe the boundary-layer profiles. A plurality of instability modes are obtained, each defined by one or more mode parameters. A vector of regressor weights is obtained for the known instability growth rates in a training dataset. For each instability mode in the plurality of instability modes, a covariance vector is determined, which is the covariance of a predicted local growth rate with the known instability growth rates. Each covariance vector is used with the vector of regressor weights to determine a predicted local growth rate at the point. Based on the predicted local growth rates, an n-factor envelope at the point is determined.


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