公开(公告)号：US20240411952A1

公开(公告)日：2024-12-12

申请号：US18414348

申请日：2024-01-16

Applicant: AUTODESK, INC.

Inventor： Mehran EBRAHIMI ,  Hyunmin CHEONG ,  Pradeep Kumar JAYARAMAN

IPC: G06F30/20 ,  G06N7/01

Abstract: Techniques for generative design include a computer-implemented method for solving a design problem comprising initializing values for one or more categorical and continuous design variables, and performing a design iteration by generating sample vectors for each of one or more categorical design variables based on the categorical design variable probabilities, solving one or more governing equations for the design problem based on values of the continuous design variables and the sample vectors, computing a value of one or more constraint functions and an objective function, computing first gradients of the objective function and the constraint functions with respect to each of the continuous design variables, computing second gradients of the objective function and the constraint functions with respect to the categorical design variable probabilities, and updating values for the continuous design variables based on the first gradients and values for the categorical design variable probabilities based on the second gradients.

公开(公告)号：US20190197198A1

公开(公告)日：2019-06-27

申请号：US15854234

申请日：2017-12-26

Applicant: AUTODESK, INC.

Inventor： Hyunmin CHEONG ,  Mehran EBRAHIMI ,  Francesco IORIO ,  Adrian BUTSCHER

IPC: G06F17/50

CPC classification number: G06F17/504 ,  G06F17/5086 ,  G06F17/5095 ,  G06F2217/02 ,  G06F2217/04 ,  G06F2217/06 ,  G06F2217/12

Abstract: A design engine automates portions of a mechanical assembly design process. The design engine generates a user interface that exposes tools for capturing input data related to the design problem. Based on the input data, the design engine performs various operations to generate a formalized problem definition that can be processed by a goal-driven optimization algorithm. The goal-driven optimization algorithm generates a spectrum of potential design options. Each design option describes a mechanical assembly representing a potential solution to the design problem.

公开(公告)号：US20240411945A1

公开(公告)日：2024-12-12

申请号：US18414350

申请日：2024-01-16

Applicant: AUTODESK, INC.

Inventor： Mehran EBRAHIMI ,  Hyunmin CHEONG ,  Pradeep Kumar JAYARAMAN

IPC: G06F30/13

Abstract: Techniques for generative design include a computer-implemented method for solving a design problem comprising initializing values for one or more categorical design variable probabilities and one or more continuous design variables, and performing a design iteration by performing one or more iterations to update the categorial design variable probabilities by generating sample vectors for each of one or more categorical design variables based on the categorical design variable probabilities, computing first gradients of an objective function and one or more constraint functions with respect to the categorical design variable probabilities, and updating values for the categorical design variable probabilities based on the first gradients, then updating the sample vectors based on the updated categorical design variable probability values, computing second gradients of the objective and constraint functions with respect to each of the continuous design variables, and updating values for the continuous design variables based on the second gradients.

公开(公告)号：US20210342046A1

公开(公告)日：2021-11-04

申请号：US17377036

申请日：2021-07-15

Applicant: AUTODESK, INC.

Inventor： Hyunmin CHEONG ,  Mehran EBRAHIMI ,  Adrian BUTSCHER

IPC: G06F3/0484 ,  G06F30/00

Abstract: A design engine implements a probabilistic approach to generating designs that exposes automatically-generated design knowledge to the user during operation. The design engine interactively generates successive populations of designs based on a problem definition associated with a design problem and/or a previously-generated population of designs. During the above design process, the design engine generates a design knowledge graphical user interface (GUI) that graphically exposes various types of design knowledge to the user. In particular, the design engine generates a design variable dependency GUI that visualizes various dependencies between designs variables. The design engine also generates a design evolution GUI that animates the evolution of designs across the successive design populations. Additionally, the design engine generates a design exploration GUI that facilitates the user exploring various statistical properties of automatically-generated designs.

公开(公告)号：US20210124852A1

公开(公告)日：2021-04-29

申请号：US17141060

申请日：2021-01-04

Applicant: AUTODESK, INC.

Inventor： Hyunmin CHEONG ,  Mehran EBRAHIMI ,  Francesco IORIO ,  Adrian BUTSCHER

IPC: G06F30/17

Abstract: A design engine systematically explores a design space associated with a design problem related to mechanical assemblies. The design engine implements a constraint programming approach to produce mechanical assembly configurations that adhere to a set of design constraints. For each feasible configuration, the design engine then optimizes various parameters to generate design options that meet a set of design objectives. With these techniques, the design space can be explored very quickly to generate significantly more feasible design options for the mechanical assembly than possible with conventional manual approaches. Accordingly, numerous design options can be generated that may otherwise never be produced using those conventional approaches.

公开(公告)号：US20240411942A1

公开(公告)日：2024-12-12

申请号：US18414322

申请日：2024-01-16

Applicant: AUTODESK, INC.

Inventor： Mehran EBRAHIMI ,  Hyunmin CHEONG ,  Pradeep Kumar JAYARAMAN

IPC: G06F30/12

Abstract: Techniques for interactive generative design with sensitivity analysis and probability visualization for categorical design variables include a computer-implemented method for evaluating an impact of categorical design variables on a design problem solution comprises receiving information regarding choices for one or more categorical design variables associated with each of a plurality of design members of a design problem, determining a respective sensitivity of an objective function to the choices for the one or more categorical design variables for each design member of the plurality of design members, determining a respective visual aspect for each design member based on the respective sensitivity, displaying, on a user interface, a graphical depiction of the plurality of design members, wherein each design member is displayed using the respective visual aspect, and displaying, on the user interface, a key for interpreting the respective visual aspects.

公开(公告)号：US20240273254A1

公开(公告)日：2024-08-15

申请号：US18642546

申请日：2024-04-22

Applicant: AUTODESK, INC.

Inventor： Hyunmin CHEONG ,  Mehran EBRAHIMI ,  Francesco IORIO ,  Adrian BUTSCHER

IPC: G06F30/17 ,  G06F30/15 ,  G06F111/04

CPC classification number: G06F30/17 ,  G06F30/15 ,  G06F2111/04

Abstract: A design engine systematically explores a design space associated with a design problem related to mechanical assemblies. The design engine implements a constraint programming approach to produce mechanical assembly configurations that adhere to a set of design constraints. For each feasible configuration, the design engine then optimizes various parameters to generate design options that meet a set of design objectives. With these techniques, the design space can be explored very quickly to generate significantly more feasible design options for the mechanical assembly than possible with conventional manual approaches. Accordingly, numerous design options can be generated that may otherwise never be produced using those conventional approaches.

公开(公告)号：US20210157965A1

公开(公告)日：2021-05-27

申请号：US17164319

申请日：2021-02-01

Applicant: AUTODESK, INC.

Inventor： Hyunmin CHEONG ,  Mehran EBRAHIMI ,  Francesco IORIO ,  Adrian BUTSCHER

IPC: G06F30/3323 ,  G06F30/15 ,  G06F30/17

Abstract: A design engine automates portions of a mechanical assembly design process. The design engine generates a user interface that exposes tools for capturing input data related to the design problem. Based on the input data, the design engine performs various operations to generate a formalized problem definition that can be processed by a goal-driven optimization algorithm. The goal-driven optimization algorithm generates a spectrum of potential design options. Each design option describes a mechanical assembly representing a potential solution to the design problem.

公开(公告)号：US20200333928A1

公开(公告)日：2020-10-22

申请号：US16434082

申请日：2019-06-06

Applicant: AUTODESK, INC.

Inventor： Hyunmin CHEONG ,  Mehran EBRAHIMI ,  Adrian BUTSCHER

IPC: G06F3/0484 ,  G06F17/50

Abstract: A design engine implements a probabilistic approach to generating designs that exposes automatically-generated design knowledge to the user during operation. The design engine interactively generates successive populations of designs based on a problem definition associated with a design problem and/or a previously-generated population of designs. During the above design process, the design engine generates a design knowledge graphical user interface (GUI) that graphically exposes various types of design knowledge to the user. In particular, the design engine generates a design variable dependency GUI that visualizes various dependencies between designs variables. The design engine also generates a design evolution GUI that animates the evolution of designs across the successive design populations. Additionally, the design engine generates a design exploration GUI that facilitates the user exploring various statistical properties of automatically-generated designs.

公开(公告)号：US20230082505A1

公开(公告)日：2023-03-16

申请号：US18058210

申请日：2022-11-22

Applicant: AUTODESK, INC.

Inventor： Hyunmin CHEONG ,  Mehran EBRAHIMI ,  Adrian BUTSCHER

IPC: G06F3/0484 ,  G06F30/00

Abstract: A design engine implements a probabilistic approach to generating designs that exposes automatically-generated design knowledge to the user during operation. The design engine interactively generates successive populations of designs based on a problem definition associated with a design problem and/or a previously-generated population of designs. During the above design process, the design engine generates a design knowledge graphical user interface (GUI) that graphically exposes various types of design knowledge to the user. In particular, the design engine generates a design variable dependency GUI that visualizes various dependencies between designs variables. The design engine also generates a design evolution GUI that animates the evolution of designs across the successive design populations. Additionally, the design engine generates a design exploration GUI that facilitates the user exploring various statistical properties of automatically-generated designs.