Abstract:
An iterative design environment performs an iterative design process of a product by implementing usage feedback of the product when utilized under real-world conditions. Sensors are installed on the physical product and collect data about the behavior of the product under real-world conditions. The sensor data comprise usage feedback implemented to inform and produce a design problem statement and one or more design solutions. The sensor data is received by a problem statement engine to produce a problem statement based, at least in part, on the sensor data. A design engine then produces one or more design solutions for the problem statement and one of the design solutions is fabricated to produce a new physical product. Sensors are then installed onto the new physical product and the iterative design process may be performed again. The iterative design process may be performed multiple times until a satisfactory physical product is achieved.
Abstract:
A computer-implemented method for method for selecting visual subject matter stored in a database includes receiving user input that indicates a first region of a first image that is stored in the database and, based on metadata associated with the first image stored in the database, determining at least one visual feature in the first region of the first image stored in the database. The method further includes, based on metadata associated with other images stored in the database, selecting a second image from the database that includes a visual feature that correlates with the visual feature in the first region of the first image, wherein the metadata associated with the first image stored in the database and the metadata associated with the other images stored in the database include image correlation information received from a remote server device.
Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for modeling turbine parameters. One of the methods includes obtaining, along multiple points of a blade of a turbine from a minimum radius rmin of the blade to a maximum radius rmax of the blade, lift coefficients Cyi and drag coefficients Cxi. At the multiple points of the blade from rmin to rmax, corresponding components of an upstream fluid flow velocity vector uh,Ri and uφ,Ri and components of a downstream fluid flow velocity uh,Li and uφ,Li are obtained. Averaged directions βi of the upstream and downstream fluid flow velocity vectors are computed using the components of the upstream fluid flow velocity vector uh,Ri and uφ,Ri and the components of the downstream fluid flow velocity uh,Li and uφ,Li. The total torque M of the turbine is computed including summing, from rmin to rmax, (Cxi sin βi+Cyi cos βi).
Abstract:
A design application receives an exemplary design from an end-user having one or more functional attributes relevant to solving a design problem. The design application then generates a set of labels that describes the functional attributes of the exemplary design. Based on the set of labels, the design application explores a functional space to retrieve one or more system classes having functionally descriptive labels that are similar to the set of labels generated for the exemplary design. The one or more system classes include different approaches to solving the design problem, and represent systems having at least some functional attributes in common with the exemplary design.
Abstract:
A design application is configured to perform a system-level optimization of a collection of system components. The design application iteratively executes a multi-objective solver to optimize structural and functional relationships between the system components in order to meet global design criteria and generate a system design. The design application initializes the design process by extracting from a knowledge base system templates having taxonomic, structural, or functional attributes relevant to the system design. The design application generates the knowledge base by mining taxonomic, structural, and functional relationships from a corpus of engineering texts.
Abstract:
A design application is configured to perform a system-level optimization of a collection of system components. The design application iteratively executes a multi-objective solver to optimize structural and functional relationships between the system components in order to meet global design criteria and generate a system design. The design application initializes the design process by extracting from a knowledge base system templates having taxonomic, structural, or functional attributes relevant to the system design. The design application generates the knowledge base by mining taxonomic, structural, and functional relationships from a corpus of engineering texts.
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.
Abstract:
Design process that performs geometry synthesis on a 3D model of a product based on a design problem statement and manufacturing constraints associated with a manufacturing machine intended to manufacture the product. The manufacturing constraints may include dimensions for a tool bit, dimensions for a tool head, a set of machining directions of the manufacturing machine, or any combination thereof. For a 5-axis manufacturing machine, the set of machining directions may be determined by a “NormalSearch” algorithm and/or a “HeatSearch” algorithm. The geometry synthesis produces a design solution comprising a final 3D model of the product, whereby each point on the boundary of the final 3D model is determined to be accessible by a tool bit and/or tool head in at least one machining direction of the manufacturing machine. Thus, the design solution for the product is more easily and directly manufacturable by the manufacturing machine.
Abstract:
A design application receives an exemplary design from an end-user having one or more functional attributes relevant to solving a design problem. The design application then generates a set of labels that describes the functional attributes of the exemplary design. Based on the set of labels, the design application explores a functional space to retrieve one or more system classes having functionally descriptive labels that are similar to the set of labels generated for the exemplary design. The one or more system classes include different approaches to solving the design problem, and represent systems having at least some functional attributes in common with the exemplary design.
Abstract:
A design application is configured to perform a system-level optimization of a collection of system components. The design application iteratively executes a multi-objective solver to optimize structural and functional relationships between the system components in order to meet global design criteria and generate a system design. The design application initializes the design process by extracting from a knowledge base system templates having taxonomic, structural, or functional attributes relevant to the system design. The design application generates the knowledge base by mining taxonomic, structural, and functional relationships from a corpus of engineering texts.