Techniques for generating comprehensive information models for automobile designs

    公开(公告)号:US11775709B2

    公开(公告)日:2023-10-03

    申请号:US16387526

    申请日:2019-04-17

    Applicant: AUTODESK, INC.

    CPC classification number: G06F30/23 G06F30/15 G06T19/00 G06T2210/36

    Abstract: In various embodiments, an automobile modeling application generates automobile designs. In operation, the automobile modeling application determines a first parameter value associated with a first instance of a first parameterized automobile component. The automobile modeling application then computes a second parameter value associated with a second instance of a second parameterized automobile component based on a structural relationship between the first instance and the second instance. Subsequently, the automobile modeling application generates a computer-aided design (CAD) geometry model for an automobile based on the first parameter value, the second parameter value, and one or more functional relationships defined between two or more instances included in a set of parameterized automobile component instances. Advantageously, because the automobile modeling application automatically propagates changes throughout the automobile design, the amount of time required to make significant changes to the automobile design can be substantially reduced.

    Automated generation and evaluation of architectural designs

    公开(公告)号:US11748527B2

    公开(公告)日:2023-09-05

    申请号:US17820867

    申请日:2022-08-18

    Applicant: AUTODESK, INC.

    CPC classification number: G06F30/13

    Abstract: A design engine is configured to interact with potential occupants of a structure in order to generate data that defines the usage preferences of those occupants. The design engine generates multiple candidate designs for the structure via a generative design process, and then evaluates each candidate design using a set of metrics determined relative to the usage preferences. Based on these evaluations, the design engine selects at least one candidate design that optimizes the set of metrics across all potential occupants.

    Generative design techniques for automobile designs

    公开(公告)号:US11475178B2

    公开(公告)日:2022-10-18

    申请号:US16387527

    申请日:2019-04-17

    Applicant: AUTODESK, INC.

    Abstract: In various embodiments, a generative design application generates and evaluates automotive designs. In operation, the generative design application computes a first set of metric values based on a set of metrics associated with design goal(s) and a first set of parameter values for a parameterized automobile model. The generative design application then performs optimization operation(s) on the first set of parameter values based on the first set of metric values to generate a second set of parameter values. Subsequently, the generative design application generates at least one design based on the second set of parameter values that is more convergent with respect to at least one of the design goals than a previously generated design. Advantageously, less time and effort are required to generate and evaluate multiple designs and then optimize those designs relative to more manual prior art approaches.

    Automated generation and evaluation of architectural designs

    公开(公告)号:US11423191B2

    公开(公告)日:2022-08-23

    申请号:US16112562

    申请日:2018-08-24

    Applicant: AUTODESK, INC.

    Abstract: A design engine is configured to interact with potential occupants of a structure in order to generate data that defines the usage preferences of those occupants. The design engine generates multiple candidate designs for the structure via a generative design process, and then evaluates each candidate design using a set of metrics determined relative to the usage preferences. Based on these evaluations, the design engine selects at least one candidate design that optimizes the set of metrics across all potential occupants.

    Analyzing a design space to effect more efficient design space exploration

    公开(公告)号:US11256834B2

    公开(公告)日:2022-02-22

    申请号:US15979432

    申请日:2018-05-14

    Applicant: AUTODESK, INC.

    Abstract: A design space analyzer generates a parametric model associated with a design problem. The design space analyzer then discretizes various parameters associated with the model and generates a plurality of sample designs using different combinations of discretized parameters. The design space analyzer also computes one or more metrics for each sample design. In this fashion, the design space analyzer generates a coarse approximation of the design space associated with the design problem. The design space analyzer then evaluates portions of that approximation, at both global and local scales, to identify portions of the design space that meet certain feasibility criteria. Finally, the design space analyzer modifies the design space to facilitate more efficient exploration during optimization.

    Designing objects using lattice structure optimization

    公开(公告)号:US11501029B2

    公开(公告)日:2022-11-15

    申请号:US16727862

    申请日:2019-12-26

    Applicant: AUTODESK, INC.

    Abstract: A design engine for designing an object using structural analysis. The design engine generates a lattice structure for the object comprising a plurality of nodes and a plurality of lines connecting the nodes. The lattice structure is optimized to remove one or more lines using structural analysis based on at least one load-related design requirement. Several design options are provided for generating and optimizing the lattice structure. The design engine then generates a 3D model of the object by thickening each line of the lattice structure into a pipe volume. The thickness of each pipe is determined using structural analysis based on the at least one load-related design requirement. The 3D model represents the volume of the object and is exportable to a fabrication device.

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