IP Library Granted Patent US 12682136
Granted Patent B2
US 12682136 · App. 19/345,097 · Granted Jul 14, 2026

Morphing of watertight spline models using as-executed manufacturing data

Inventors: Benjamin Urick (Roseville, CA); Daniel L. Keller (Waitsfield, VT); Richard H. Crawford (Austin, TX)
Assignee: nVariate, Inc.
G06F30/20G06F30/17G06F2101/00G06F2111/04G06F2119/18
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12682136
App. No.
19/345,097
Granted
Jul 14, 2026
Kind
B2
Abstract

Methods, computer systems, and computer-readable memory media for determining a warp function. An as-designed watertight spline model of an object is received. A point cloud and the as-designed watertight spline model are used to construct a model of the object. The point cloud is obtained from a physical or virtual (simulated) inspection and/or manufacturing process. A warp function is determined based on a difference between the as-designed watertight spline model and the constructed model. The warp function is a continuous function quantifying differences between the as-designed model and the constructed model. As-preprocessed instructions for a simulation or analysis process of the object are determined based on metadata of the as-designed watertight spline model and the warp function. The simulation or analysis process is performed on the object according to the as-preprocessed instructions to produce as-simulated data, and the as-simulated data is stored in a non-transitory computer-readable memory medium.

Claims (63)

1 . A computer-implemented method, comprising:

performing, by a computer:

receiving an as-designed watertight spline model of an object, wherein the as-designed watertight spline model is described in a Computer-Aided Design (CAD) model domain;

constructing a model of the object based at least in part on a point cloud and the as-designed watertight spline model, wherein the constructed model comprises a watertight spline model, wherein a spline structure of the constructed model is based at least in part on a spline structure of the as-designed watertight model;

determining a warp function based on a difference between the as-designed watertight spline model and the constructed model, wherein the warp function comprises a continuous function describing differences between the constructed model and the as-designed watertight spline model, wherein the warp function comprises a spline model with a spline structure commensurate with the as-designed watertight model;

determining as-preprocessed instructions for a simulation or analysis process of the object based at least in part on metadata of the as-designed watertight spline model and the warp function, wherein the as-preprocessed instructions are described in a Computer-Aided Engineering (CAE) model domain;

performing the simulation or analysis process on the object according to the as-preprocessed instructions to produce as-simulated data; and

storing the as-simulated data in a non-transitory computer-readable memory medium.

2 . The computer-implemented method of claim 1 ,

wherein the as-preprocessed instructions comprise one or both of loading information and boundary conditions.

3 . The computer-implemented method of claim 1 ,

wherein the as-preprocessed instructions are determined further based at least in part on metadata associated with a manufacturing or inspection process for the object.

4 . The computer-implemented method of claim 1 ,

wherein the point-cloud used to construct the constructed model is obtained from a simulated or physical inspection and/or manufacturing process.

5 . The method of claim 1 , further comprising:

receiving semantic product manufacturing information (PMI) for one or both of the as-designed watertight spline model and the constructed model,

wherein constructing the model of the object is performed further based at least in part on the semantic PMI.

6 . The method of claim 5 ,

wherein constructing the model based at least in part on the semantic PMI comprises:

determining one or more constraints of the object based on the semantic PMI; and

interpolating between adjacent points of the point cloud based on the one or more constraints, wherein the one or more constraints are determined based at least in part on a sampling density of the point cloud indicated by the semantic PMI.

7 . The method of claim 5 ,

wherein constructing the model based at least in part on the semantic PMI comprises:

determining one or more control point derivatives for the constructed model based at least in part on geometric constraints indicated by the semantic PMI.

8 . The method of claim 1 ,

wherein constructing the model of the object based at least in part on the point-cloud and the as-designed watertight spline model comprises performing an interpolation or approximation procedure of points of the point-cloud to the as-designed watertight spline model.

9 . The method of claim 1 , further comprising:

displaying, on a display, a colorized visual representation of the warp function.

10 . The method of claim 1 ,

wherein constructing the model of the object based at least in part on the point-cloud and the as-designed watertight spline model comprises:

performing an interpolation or approximation procedure utilizing a spline structure of the as-designed watertight spline model to determine a plurality of degrees, control points and knot vectors of the constructed model.

11 . The method of claim 10 , further comprising:

determining a discrepancy between the knot vectors of the constructed model and knot vectors of the as-designed watertight spline model; and

performing knot insertion on the knot vectors of the as-designed watertight spline model to remove the determined discrepancy.

12 . The method of claim 1 ,

wherein the constructed model comprises a same spline structure as the as-designed watertight spline model.

13 . The computer-implemented method of claim 1 , further comprising:

determining as-planned instructions for an inspection process of the object based at least in part on metadata of the as-designed watertight spline model and the warp function, wherein the as-planned instructions are described in a Computer-Aided Inspection (CAI) model domain;

performing the inspection process on the object according to the as-planned instructions to produce as-inspected data; and

storing the as-inspected data in the non-transitory computer-readable memory medium.

14 . A non-transitory computer-readable memory medium comprising program instructions which, when executed by a processor, cause a computer to:

receive an as-designed watertight spline model of an object, wherein the as-designed watertight spline model is described in a Computer-Aided Design (CAD) model domain;

construct a model of the object based at least in part on a point cloud and the as-designed watertight spline model, wherein the constructed model comprises a watertight spline model, wherein a spline structure of the constructed model is based at least in part on a spline structure of the as-designed watertight model;

determine a warp function based on a difference between the as-designed watertight spline model and the constructed model, wherein the warp function comprises a continuous function describing differences between the constructed model and the as-designed watertight spline model, wherein the warp function comprises a spline model with a spline structure commensurate with the as-designed watertight model;

determine as-preprocessed instructions for a simulation or analysis process of the object based at least in part on metadata of the as-designed watertight spline model and the warp function, wherein the as-preprocessed instructions are described in a Computer-Aided Engineering (CAE) model domain;

perform the simulation or analysis process on the object according to the as-preprocessed instructions to produce as-simulated data; and

store the as-simulated data in the non-transitory computer-readable memory medium.

15 . The non-transitory computer-readable memory medium of claim 14 ,

wherein the as-preprocessed instructions comprise one or both of loading information and boundary conditions.

16 . The non-transitory computer-readable memory medium of claim 14 ,

wherein the as-preprocessed instructions are determined further based at least in part on metadata associated with a manufacturing or inspection process for the object.

17 . The non-transitory computer-readable memory medium of claim 14 ,

wherein the point-cloud used to construct the constructed model is obtained from a simulated or physical inspection and/or manufacturing process.

18 . The non-transitory computer-readable memory medium of claim 14 , wherein the program instructions are further executable to cause the computer to:

receive semantic product manufacturing information (PMI) for one or both of the as-designed watertight spline model and the constructed model,

wherein constructing the model of the object is performed further based at least in part on the semantic PMI.

19 . The non-transitory computer-readable memory medium of claim 18 ,

wherein, in constructing the model based at least in part on the semantic PMI, the program instructions are further executable to cause the computer to:

determine one or more constraints of the object based on the semantic PMI; and

interpolate between adjacent points of the point cloud based on the one or more constraints, wherein the one or more constraints are determined based at least in part on a sampling density of the point cloud indicated by the semantic PMI.

20 . The non-transitory computer-readable memory medium of claim 18 ,

wherein, in constructing the model based at least in part on the semantic PMI, the program instructions are further executable to cause the computer to:

determine one or more control point derivatives for the constructed model based at least in part on geometric constraints indicated by the semantic PMI.