IP Library Granted Patent US 10,963,599
Granted Patent B2
US 10,963,599 · App. 16/856,392 · Granted Mar 30, 2021

Systems and methods for utilizing a 3D CAD point-cloud to automatically create a fluid model

Inventor: Zain S. Dweik (Hamilton, OH)
Assignee: Altair Engineering, Inc.
G06F30/17G06F30/20G06N20/00G06T15/005G06T17/05G06F2111/10G06F2119/18
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Quick Facts
Patent No.
US 10,963,599
App. No.
16/856,392
Filed
Apr 23, 2020
Granted
Mar 30, 2021
Kind
B2
Art Unit
2619
USPC
345/419
Abstract

A multiple fluid model tool for utilizing a 3D CAD point-cloud to automatically create a fluid model is presented. For 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.

Claims (42)

1. A system, comprising:

a memory that stores computer executable components; and

a processor that executes computer executable components stored in the memory, wherein the computer executable components comprise:

a modeling component that determines a first control volume associated with a first three-dimensional model of a first device and a second control volume associated with a second three-dimensional model of a second device, wherein the modeling component determines the first control volume and the second control volume based on respective point cloud data indicative of respective information for respective sets of data values associated with a three-dimensional coordinate system, wherein the modeling component updates the first control volume, the second control volume, or both the first control volume and the second control volume in response to modifications of respective computer aided design data associated with the first device and the second device; and

a three-dimensional design component that provides a three-dimensional design environment associated with a machine that comprises the first device and the second device, wherein the three-dimensional design environment renders modeling data of the machine based on a machine learning process associated with the first three-dimensional model indicative of a first flow through the first device and the second three-dimensional model indicative of a second flow through the second device.

2. The system of claim 1 , wherein the modeling component generates first identification data indicative of a first identifier for the first control volume, and second identification data indicative of a second identifier for the second control volume.

3. The system of claim 1 , wherein the modeling component determines a first computational geometry for the first control volume associated with the first three-dimensional model and second computational geometry for the second control volume associated with the second three-dimensional model based on point cloud data.

4. The system of claim 1 , wherein the computer executable components further comprise:

a machine learning component that predicts a first set of characteristics of the first device based on the first flow and a second set of characteristics of the second device based on the second flow.

5. The system of claim 4 , wherein the machine learning component performs the machine learning process based on the first control volume associated with the first three-dimensional model and the second control volume associated with the second three-dimensional model.

6. The system of claim 1 , wherein the modeling component determines first geometric data indicative of first geometric features of the first control volume and first surface data indicative of first surface information for the first control volume and second geometric data indicative of second geometric features of the second control volume and second surface data indicative of second surface information for the second control volume.

7. A method, comprising:

determining, by a system comprising a processor, a first flow network, represented as a first control volume associated with a first three-dimensional model of a first device and a second flow network, represented as a second control volume, associated with a second three-dimensional model of a second device;

updating, by the system, the first control volume in response to a first modification of first computer aided design data associated with the first device and a second modification of the second control volume in response to modification of second computer aided design data associated with the second device;

determining, by the system, characteristics of a machine that comprise the first device and the second device, wherein the determining is based on respective machine learning processes associated with the first three-dimensional model and the second three-dimensional model; and

rendering, by the system, a three-dimensional design environment of the machine based on the characteristics, the first three-dimensional model of the first device, and the second three-dimensional model of the second device.

8. The method of claim 7 , further comprising:

determining, by the system, a first computational geometry for the first device based on first point cloud data determined for the first device, and a second computational geometry for the second device based on second point cloud data for the second device, wherein the first point cloud data and the second point cloud data are determined based on a three-dimensional coordinate system.

9. The method of claim 7 , further comprising:

determining, by the system, a first computational geometry for the first control volume associated with the first three-dimensional model and second computational geometry for the second control volume associated with the second three-dimensional model based on point cloud data.

10. The method of claim 7 , further comprising:

generating, by the system, first identification data indicative of a first identifier for the first control volume and second identification data indicative of a second identifier for the second control volume.

11. The method of claim 10 , further comprising:

in response to the first modification and the second modification, updating, by the system, the first control volume based on the first identification data and the second control volume based on the second identification data.

12. A non-transitory computer readable media comprising instructions that, in response to execution, cause a system comprising a processor to perform operations, comprising:

determining a first flow network of a first device and a second flow network of a second device, wherein the first flow network is represented as a first control volume of a first three-dimensional model of the first device and the second flow network is represented as a second control volume of a second three-dimensional model of the second device;

updating the first control volume, the second control volume, or both the first control volume and the second control volume, based on a modification of computer aided design data associated with the first device, the second device, or both the first device and the second device;

determining characteristics of a machine based on performing a first machine learning process associated with the first three-dimensional model and a second machine learning process associated with the second three-dimensional model; and

outputting, on a display of a user device, a three-dimensional design environment associated with the machine based on the characteristics of the machine, wherein the machine comprises the first device and the second device, and wherein the three-dimensional design environment comprises the first three-dimensional model and the second three-dimensional model.

13. The non-transitory computer readable media of claim 12 , wherein the operations further comprise:

determining a first computational geometry for the first control volume associated with the first three-dimensional model based on first point cloud data; and

determining a second computational geometry for the second control volume associated with the second three-dimensional model based on second point cloud data, wherein the first point cloud data and the second point cloud data are indicative of information for respective sets of data values associated with the first device and the second device with respect to a three-dimensional coordinate system.

14. The non-transitory computer readable media of claim 12 , wherein the operations further comprise:

generating first identification data indicative of a first identifier for the first control volume and second identification data indicative of a second identifier for the second control volume.

15. The non-transitory computer readable media of claim 14 , wherein the operations further comprise:

updating, based on the first identification data, the first control volume, in response to the modification of the computer aided design data associated with the first device; and

updating, based on the second identification data, the second control volume, in response to the modification of the computer aided design data associated with the second device.

16. The method of claim 7 , wherein the first flow network and the second flow network represent respective flows of fluid through the first device and the second device.

17. The method of claim 7 , wherein the first device and the second device are electrical devices, and wherein the first flow network and the second flow network represent respective flows of electricity through the first device and the second device.

18. The method of claim 7 , wherein the first flow network and the second flow network represent respective flows of heat transfer through the first device and the second device, and wherein the three-dimensional design environment is a heat transfer design environment.

19. The method of claim 7 , wherein the three-dimensional design environment is a flow integrated design environment.

20. The method of claim 7 , wherein the three-dimensional design environment is a combustion design environment.

Assignments (4)
MERGER Recorded Feb 4, 2026
From: ALTAIR ENGINEERING INC.
To: SIEMENS INDUSTRY SOFTWARE INC.
Reel/Frame 074348/0312 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 18, 2021
From: GENERAL ELECTRIC COMPANY
To: ALTAIR ENGINEERING, INC.
Reel/Frame 054947/0406 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE NAME AND ADDRESS PREVIOUSLY RECORDED ON REEL 052477 FRAME 0269. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Sep 16, 2020
From: DWEIK, ZAIN S.
To: GENERAL ELECTRIC COMPANY
Reel/Frame 053786/0825 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 23, 2020
From: DWEIK, ZAIN S.
To: GE AVIATION SYSTEMS LLC
Reel/Frame 052477/0269 →
Continuity (4)
Continuation 16517154 · Jul 19, 2019
Continuation 15630939 · Jun 22, 2017
Provisional Application 62469953 · Mar 10, 2017
Related Publication 20200250359A1 · Aug 6, 2020
Cited By (5)
US 12,333,224 US 12,368,503 US 12,587,274 US 12,603,701 US 12,627,372