Systems and Methods for Utilizing a 3D CAD Point-Cloud to Automatically Create a Fluid Model

Patent metadata

Field	Value
Publication number	US-2022292231-A1
Application number	US-202217829673-A
Country	US
Kind code	A1
Filing date	Jun 1, 2022
Priority date	Mar 10, 2017
Publication date	Sep 15, 2022
Grant date	—

Abstract

A multiple fluid model tool for utilizing a 3D CAD point-cloud to automatically create a fluid model is presented. Fr example, a system includes a modeling component, a machine learning component, and a three-dimensional design component. The modeling component generates a three-dimensional model of a mechanical device based on point cloud data indicative of information for a set of data values associated with a three-dimensional coordinate system. The machine learning component predicts one or more characteristics of the mechanical device based on input data and a machine learning process associated with the three-dimensional model. The three-dimensional design component that provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the mechanical device based on the input data and the one or more characteristics of the mechanical device on the three-dimensional model.

First claim

1 .- 20 . (canceled)

21 . A method, comprising:
obtaining, by a computer system, point cloud data regarding a mechanical device, wherein the point cloud data comprises a set of data values associated with a three-dimensional coordinate system; generating, by the computer system, a three-dimensional model of the mechanical device based on the point cloud data, wherein the three-dimensional model comprises a control volume representing at least a portion of the mechanical device; updating, by the computer system, the control volume in response to a modification of computer aided design data associated with the mechanical device; and predicting, by the computer system, at least one of a combustion behavior or a thermal behavior of the mechanical device based on input data, the three-dimensional model, and a machine learning process associated with the three-dimensional model.

22 . The method of claim 21 , wherein the control volume comprises as computational domain for a geometric feature of the three-dimensional model.

23 . The method of claim 21 , wherein the input data comprises at least one of:
fluid data indicative of a fluid provided to the mechanical device, electrical data indicative of a voltage and/or a current provided to the mechanical device, or chemical data indicative of a chemical element provided to the mechanical device.

24 . The method of claim 21 , wherein predicting the combustion behavior the mechanical device comprises determining one or more combustion characteristics of the three-dimensional model, wherein the one or more combustion characteristics comprises at least one of:
a temperature associated with one or more regions of the three-dimensional model, an elemental composition associated with one or more regions of the three-dimensional model, a moisture content associated with one or more regions of the three-dimensional model, a density associated with one or more regions of the three-dimensional model, or an acoustic property associated with one or more regions of the three-dimensional model.

25 . The method of claim 21 , wherein predicting the thermal behavior the mechanical device comprises determining one or more thermal characteristics of the three-dimensional model, wherein the one or more thermal characteristics comprises at least one of:
a temperature associated with one or more regions of the three-dimensional model, a heat capacity associated with one or more regions of the three-dimensional model, a thermal expansion associated with one or more regions of the three-dimensional model, a thermal conductivity associated with one or more regions of the three-dimensional model, or a thermal stress associated with one or more regions of the three-dimensional model.

26 . The method of claim 21 , further comprising:
generating, by the system, physics modeling data representing the mechanical device based on the control volume.

27 . The method of claim 26 , further comprising:
renders the physics modeling data on the three-dimensional model.

28 . A system comprising:
one or more processors; and one or more computer-readable media storing one or more sequences of instructions which, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
obtaining point cloud data regarding a mechanical device, wherein the point cloud data comprises a set of data values associated with a three-dimensional coordinate system;
generating a three-dimensional model of the mechanical device based on the point cloud data, wherein the three-dimensional model comprises a control volume representing at least a portion of the mechanical device;
updating the control volume in response to a modification of computer aided design data associated with the mechanical device; and
predicting at least one of a combustion behavior or a thermal behavior of the mechanical device based on input data, the three-dimensional model, and a machine learning process associated with the three-dimensional model.

29 . The system of claim 28 , wherein the control volume comprises as computational domain for a geometric feature of the three-dimensional model.

30 . The system of claim 28 , wherein the input data comprises at least one of:
fluid data indicative of a fluid provided to the mechanical device, electrical data indicative of a voltage and/or a current provided to the mechanical device, or chemical data indicative of a chemical element provided to the mechanical device.

31 . The system of claim 28 , wherein predicting the combustion behavior the mechanical device comprises determining one or more combustion characteristics of the three-dimensional model, wherein the one or more combustion characteristics comprises at least one of:
a temperature associated with one or more regions of the three-dimensional model, an elemental composition associated with one or more regions of the three-dimensional model, a moisture content associated with one or more regions of the three-dimensional model, a density associated with one or more regions of the three-dimensional model, or an acoustic property associated with one or more regions of the three-dimensional model.

32 . The system of claim 28 , wherein predicting the thermal behavior the mechanical device comprises determining one or more thermal characteristics of the three-dimensional model, wherein the one or more thermal characteristics comprises at least one of:
a temperature associated with one or more regions of the three-dimensional model, a heat capacity associated with one or more regions of the three-dimensional model, a thermal expansion associated with one or more regions of the three-dimensional model, a thermal conductivity associated with one or more regions of the three-dimensional model, or a thermal stress associated with one or more regions of the three-dimensional model.

33 . The system of claim 28 , the operations further comprising:
generating, by the system, physics modeling data representing the mechanical device based on the control volume.

34 . The system of claim 33 , the operations further comprising:
renders the physics modeling data on the three-dimensional model.

35 . One or more non-transitory computer-readable media storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform operations comprising:
obtaining point cloud data regarding a mechanical device, wherein the point cloud data comprises a set of data values associated with a three-dimensional coordinate system; generating a three-dimensional model of the mechanical device based on the point cloud data, wherein the three-dimensional model comprises a control volume representing at least a portion of the mechanical device; updating the control volume in response to a modification of computer aided design data associated with the mechanical device; and predicting at least one of a combustion behavior or a thermal behavior of the mechanical device based on input data, the three-dimensional model, and a machine learning process associated with the three-dimensional model.

36 . The one or more non-transitory computer-readable media of claim 35 , wherein the control volume comprises as computational domain for a geometric feature of the three-dimensional model.

37 . The one or more non-transitory computer-readable media of claim 35 , wherein the input data comprises at least one of:
fluid data indicative of a fluid provided to the

Assignees

• Altair Eng Inc

Inventors

• Dweik Zain S

Classifications

• G06F2119/18

  Manufacturability analysis or optimisation for manufacturability · CPC title

• G06F2111/10

  Numerical modelling · CPC title

• G06T15/005

  General purpose rendering architectures · CPC title

• G06T2207/10028

  Range image; Depth image; 3D point clouds · CPC title

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title