Dassault Systemes Solidworks Corporation

The Mathworks, Inc.

Dassault Systems Solidworks Corporation

Shrikant Savant

Kyeong Hwi Lee

Makarand Apte

Jody Todd Stiles

Chin-Loo Lama

Girish Mule

Bowen Yu

Mark G Gibson

Ameya Divekar

Nikhil Amrutham

Harsh Sureshbhai Khoont

Zahra Karimi

David Blumenthal

A computer-based method includes enabling a user to create or select a geometric entity in a design in a computer-aided design program, predicting a location and orientation in the design for a copy of the geometric entity, and displaying, as a suggestion to the user, a visual representation of the copy of the geometric entity in the predicted location and orientation in the design.

Predictive modeling

A computer-implemented method includes receiving a digital representation of an image and generating CAD sketches from it. The number of surfaces in a CAD model depends upon the number entities at the sketch level. The method keeps the number of created sketch entities and constraints to a minimum. The method includes a scalable approach for a range of images. Each contour is represented by a sequence of points following a path corresponding to a boundary in the image. The method includes classifying each point in a particular one of the contours as a curve region or a corner region contour point, thereby segmenting the contour into plurality of curve regions separated by corner regions. The method includes optimally fitting a curve to each one of the curve regions to create the best possible representation of the curve region. Additionally, the refine algorithm automatically improves the fit wherever needed.

Converting images to sketches that are modifiable using computer-aided design (CAD) software

A computer-aided design (CAD) system and corresponding method enable users to manage and share information related to a three-dimensional (3D) context of a 3D CAD model with ease. The method creates a 3D-link targeting the 3D context. The 3D-link includes a static link and a variable link. The static link re-directs to the variable link in response to a user opening the 3D-link. The variable link enables (i) the 3D CAD model to be located and opened and (ii) the 3D context to be displayed within the 3D CAD model. The method stores the 3D-link in a database. The 3D-link enables the 3D context to be shared between or among users via sharing of the 3D-link from the database. The 3D-link plays an important role in helping design engineers collaborate by eliminating the need to create pictures or copies of 3D models that may become outdated.

3D-link for sharing a 3D context of 3D computer- aided design (CAD) model

A method in a computer aided drafting application for replicating a component mating in a modeled assembly includes examining constraints and geometry surrounding a selected component of the component mating in a first surface of the assembly. A first descriptor with a plurality of numerical characteristics of the constraints and geometry is captured. The first descriptor is set as a first seed descriptor. A potential first target geometry in the region of the first face is examined and a first target descriptor is computed according to the first target geometry. If first seed descriptor matches the first target descriptor, an instance of a first target component is created according to the first target descriptor.

Method for replicating a component mating in an assembly

A method for selecting a plurality of edges or faces of a displayed modeled object in a computer-aided design (CAD) system extracts a plurality of features, each feature including a measurable numeric property of one or more of edges or faces of the modeled object. The features are scaled, and a selection of a seed edge or a seed face is received. A suggested edge or face is chosen based upon the seed edge or seed face, and a graphical indication of the suggested edge or face is displayed on the modeled object.

Method for selecting multiple edges and faces in modeled object

Methods and systems identify frequently-used CAD components and apply machine learning techniques to predict mateable entities and corresponding mate types for those components to automatically add components to a CAD model. An example method includes accessing information regarding CAD model parts and related mate information stored in a computer database, and dividing parts into a plurality of clusters having parts with similar global shape signatures. In response to a new part being added, contextual signatures of entities of the new part are input into a mateability predictor neural network to determine a mateable entity of the new part. Input into a mate-type predictor neural network is (i) a contextual signature of the mateable entity and (ii) a contextual signature of an entity of another part of the CAD model to determine a mate type between the entities. A mate between the new part and the other part is automatically added based on the determined mate type.

Automatic assembly mate creation for frequently-used components

A method preserves shapes in a solid model when distributing material during topological optimization. A 3D geometric model of a part having a boundary shape is received. The geometric model is pre-processed to produce a variable-void distance field and to produce a frozen distance field representing the boundary shape. The geometric model is apportioned into a plurality of voxels, and a density value is adjusted for each voxel according to an optimization process. An iso-surface mesh is extracted from the voxel data, and an iso-surface distance field is generated from the extracted iso-surface mesh. A distance field intersection is derived between the iso-surface distance field and the variable-void distance field. A distance field union is performed between the distance field intersection and the frozen distance field, and a result iso-surface mesh is produced from the distance field union.

Method for preserving shapes in solid model when distributing material during topological optimization with distance fields

A method preserves shapes in a solid model when distributing material during topological optimization. A 3D geometric model of a part having a boundary shape is received. The geometric model is pre-processed to produce a variable-void mesh and to produce a frozen mesh representing the boundary shape. The geometric model is apportioned into a plurality of voxels, and a density value is adjusted for each voxel according to an optimization process. An iso-surface mesh is extracted from the voxel data, and a mesh Boolean intersection is derived between the extracted iso-surface mesh and the variable-void mesh. A mesh Boolean union between the mesh Boolean intersection and the frozen mesh.

Method for preserving shapes in solid model when distributing material during topological optimization

A computer-implemented method and system automatically solves constraints in a computer-aided design (CAD) model. A CAD model of a real-world object capable of assuming various positions is constructed and a constraint solver process is initiated and executes while a user defines multiple positions of the CAD model. Input of data specified during a CAD design workflow is automatically input to the constraint solver process, and unknown variables are solved for as part of the CAD design workflow.

Mechanism synthesis approach to solving design problems with position based constraints

A computer-implemented method automates motion of a computer-aided design (CAD) model. The CAD model represents a real-world object comprised of a number of parts. The part containing a user-specified entity is analyzed to collect data relevant to a motion study, for example, size data, location data, and material type data are collected. Based on the user-specified entity, parameters for automating motion are inferred and used to automate motion. The parameters include at least one of a part that is moved directly by a motor, a location on the part where the motor is mounted, a motor type, an axis of motion of the part, and a motion function indicating a change of motion over time.

Automatic motion of a computer-aided design model

A computer-implemented method and system automatically adjusts the size of a rigid body model. The method and system construct a two-dimensional model or a three-dimensional model, where the model has one or more rigid bodies. The rigid bodies are converted into geometric primitives that represent a respective rigid body and enable the respective rigid body to resize. One or more of the primitives are constrained to one another. A solver process changes a size of at least one geometric primitive and a rigid body simulation process uses the resized primitive(s) as input.

Simulation of resizable bodies using a rigid body solver

A computer-implemented method and system automatically manages relationships between moving parts of a computer-aided design model. Two parts are selected, the parts being structurally independent of one another. One of the parts is determined to be a driving part and the other part is determined to be a driven part. A new position is applied to the driving part, and temporary constraints between the driving part and the driven part are added. A constraint solver is executed to move the two parts into solved positions. Additionally, after execution of the constraint solver, the added temporary constraints are removed.

Automatic creation of temporary rigid relationships between moving parts in motion simulation

A modeling and simulation environment enables a user to create a model of a stiff chemical or biological system. The stiff chemical or biological system refers to a system that includes at least two or more different time scales of the chemical or biochemical reactions. The modeling and simulation environment also enables the user to solve the stiff chemical or biological system using a leaping algorithm. The leaping algorithm may leap over simulation of the reactions occurring in the time interval to accelerate the simulation of the chemical or biological system. The algorithm maximizes the size of the time interval by adjusting the size of the time interval using a bracketing algorithm.

Automatic selection of time interval size in implicit tau-leaping algorithm

Automatically computing the reflected mass or reflected inertia of a computer-aided design model comprised of a motor includes executing a simulation of the model, using the simulation results to compute the reflected mass or reflected inertia, and treating the non-motor parts of the model as a virtual body having a time-varying mass or a time-varying inertia. The mass or inertia of the virtual body at a specific time is the reflected mass or reflected inertia, respectively, of the model at the specific time.

Automatic computation of reflected mass and reflected inertia

A computer-implemented method for estimating a time-varying parameter of a nonlinear system includes receiving input data for the nonlinear system, the input data including a desired state and a desired state derivative of the nonlinear system for a number of time points, generating for one of the plurality of time points an approximate time-varying parameter based on at least the desired state, the desired state derivative, an approximate state of the nonlinear system, and a Lyapunov function, and providing the approximate time-varying parameter for the one of the plurality of time points.

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Shrewsbury, MA, United States of America

Shrikant Savant