GENERATIVE DESIGN SHAPE OPTIMIZATION BASED ON A TARGET PART RELIABILITY FOR COMPUTER AIDED DESIGN AND MANUFACTURING

    公开(公告)号:US20250068145A1

    公开(公告)日:2025-02-27

    申请号:US18939137

    申请日:2024-11-06

    Applicant: Autodesk, Inc.

    Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes: obtaining a design space and design criteria for a modeled object including a design constraint on an acceptable likelihood of failure, wherein a statistical model that relates a structural performance metric to specific likelihoods of failure for material(s) is used to translate between the acceptable likelihood of failure and a value for the structural performance metric; iteratively modifying a generatively designed shape of the modeled object in the design space in accordance with the design criteria including the design constraint to stay under the acceptable likelihood of failure for the physical structure, wherein the numerical simulation includes computing the structural performance metric, which is evaluated against the design constraint; and providing the generatively designed shape of the modeled object for use in manufacturing a physical structure.

    Generative design shape optimization based on a target part reliability for computer aided design and manufacturing

    公开(公告)号:US12169398B2

    公开(公告)日:2024-12-17

    申请号:US17459710

    申请日:2021-08-27

    Applicant: Autodesk, Inc.

    Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes: obtaining a design space and design criteria for a modeled object including a design constraint on an acceptable likelihood of failure, wherein a statistical model that relates a structural performance metric to specific likelihoods of failure for material(s) is used to translate between the acceptable likelihood of failure and a value for the structural performance metric; iteratively modifying a generatively designed shape of the modeled object in the design space in accordance with the design criteria including the design constraint to stay under the acceptable likelihood of failure for the physical structure, wherein the numerical simulation includes computing the structural performance metric, which is evaluated against the design constraint; and providing the generatively designed shape of the modeled object for use in manufacturing a physical structure.

    GENERATIVE DESIGN SHAPE OPTIMIZATION BASED ON A TARGET PART RELIABILITY FOR COMPUTER AIDED DESIGN AND MANUFACTURING

    公开(公告)号:US20230088537A1

    公开(公告)日:2023-03-23

    申请号:US17459710

    申请日:2021-08-27

    Applicant: Autodesk, Inc.

    Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes: obtaining a design space and design criteria for a modeled object including a design constraint on an acceptable likelihood of failure, wherein a statistical model that relates a structural performance metric to specific likelihoods of failure for material(s) is used to translate between the acceptable likelihood of failure and a value for the structural performance metric; iteratively modifying a generatively designed shape of the modeled object in the design space in accordance with the design criteria including the design constraint to stay under the acceptable likelihood of failure for the physical structure, wherein the numerical simulation includes computing the structural performance metric, which is evaluated against the design constraint; and providing the generatively designed shape of the modeled object for use in manufacturing a physical structure.

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