EFFICIENT SENSITIVITY ANALYSIS FOR GENERATIVE PARAMETRIC DESIGN OF DYNAMIC MECHANICAL ASSEMBLIES

Patent №

US 11,620,418

Granted

2023-04-04

Filed 2018

Owner

AUTODESK, INC.

Lab

AI components

3

kr · planning · evo

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15924138

A design engine generates a configuration option that includes a specific arrangement of interconnected mechanical elements adhering to one or more design constraints. Each element within a given configuration option is defined by a set of design variables. The design engine implements a parametric optimizer to optimize the set of design variables associated with each configuration option. For a given configuration option, the parametric optimizer discretizes continuous equations governing the physical dynamics of the configuration. The parametric optimizer then determines the gradient of an objective function based on the discretized equations the gradient of objective and constraint functions based on discrete direct differentiation method or discrete adjoint variable method derived directly from the discretized motion equations. Then, the parametric optimizer traverses a design space where the configuration option resides to reduce improve the objective function, thereby optimizing the design variables.

AI classification

Planning1.00
Knowledge representation0.71
Evolutionary computation0.64
AI hardware0.20
Machine learning0.10
Vision0.01
Natural language0.00
Speech0.00

Ownership

AUTODESK, INC.

assignment · 452950033

Assignors

EBRAHIMI, MEHRAN, BUTSCHER, ADRIAN, CHEONG, HYUNMIN, IORIO, FRANCESCO

On an employer assignment, the assignors are typically the inventors.

© 2026 NYSGPT2525 LLC