During model-based development, a processing target is sometimes broken down into partial structures. At such time, a long calculation time and a large quantity of computer resources are required if each partial structure has a large number of degrees of freedom. The present invention is a hierarchical reduced-order matrix generation device 600 that generates a hierarchical reduced-order matrix for performing numerical analysis of a physical object, and has: a storage unit 62 that stores physical object data indicating properties of the physical object; and a computation unit 61 that generates a hierarchical reduced-order matrix for a model of the physical object data. The computation unit 61 divides the overall structure into a plurality of partial structures, and calculates the reduced-order matrix using a unique mode and a static mode of each of the divided plurality of partial structures.

During model-based development, a processing target is sometimes broken down into partial structures. At such time, a long calculation time and a large quantity of computer resources are required if each partial structure has a large number of degrees of freedom. The present invention is a hierarchical reduced-order matrix generation device 600 that generates a hierarchical reduced-order matrix for performing numerical analysis of a physical object, and has: a storage unit 62 that stores physical object data indicating properties of the physical object; and a computation unit 61 that generates a hierarchical reduced-order matrix for a model of the physical object data. The computation unit 61 divides the overall structure into a plurality of partial structures, and calculates the reduced-order matrix using a unique mode and a static mode of each of the divided plurality of partial structures.

In some embodiments, a computer-implemented method for creating a fabricable segmented design for a physical device is provided. A computing system receives a design specification. The computing system generates a proposed segmented design based on the design specification. The computing system determines two or more loss values based on the proposed segmented design. The computing system combines the two or more loss values to create a combined loss value. The computing system creates an updated design specification using the combined loss value. At least some of the generating, determining, combining, and creating actions are repeated until a fabricable segmented design is generated.

In some embodiments, a computer-implemented method for creating a fabricable segmented design for a physical device is provided. A computing system receives a design specification. The computing system generates a proposed segmented design based on the design specification. The computing system determines two or more loss values based on the proposed segmented design. The computing system combines the two or more loss values to create a combined loss value. The computing system creates an updated design specification using the combined loss value. At least some of the generating, determining, combining, and creating actions are repeated until a fabricable segmented design is generated.

A method for creating a segmented alignment rod, the method including receiving a request for a segmented alignment rod, receiving at least one image of a deformed spine, generating, a normal spinal curvature, and generating a segmented alignment rod design.

A method for creating a segmented alignment rod, the method including receiving a request for a segmented alignment rod, receiving at least one image of a deformed spine, generating, a normal spinal curvature, and generating a segmented alignment rod design.

A target system is coupled to a diagnosis engine that uses a lumped parameter model of the system for diagnosis. A proximity search in is performed in a computer-aided design model of the system to find groups of components that may be affected by resistive or parasitic interactions between the individual components in the groups. The lumped parameter model is augmented by adding elements that emulate the resistive or parasitic interactions between the individual components in the groups. The augmented lumped model is used by the diagnosis engine to perform diagnosis on the system.

A target system is coupled to a diagnosis engine that uses a lumped parameter model of the system for diagnosis. A proximity search in is performed in a computer-aided design model of the system to find groups of components that may be affected by resistive or parasitic interactions between the individual components in the groups. The lumped parameter model is augmented by adding elements that emulate the resistive or parasitic interactions between the individual components in the groups. The augmented lumped model is used by the diagnosis engine to perform diagnosis on the system.

Three-dimensional (3D) modeling systems and methods are described for automatically generating photorealistic, virtual 3D package and product models from two-dimensional (2D) imaging assets and dimensional data. The 3D modeling systems and methods include storing, by a memory with one or more processors, 2D imaging assets and dimensional datasets, obtaining, with an imaging asset manipulation script, a shape classification defining a real-world product or product package to be virtually modeled in 3D space, generating, with the imaging asset manipulation script, a spline based on an alpha channel extracted from a 2D imaging asset depicting the real-world product or package, and generating, with the imaging asset manipulation script, a parametric model based on the spline, the dimensional dataset, and the shape classification. A virtual 3D model is generated based on the parametric model and rendered, via a graphical display or environment, as a photorealistic image representing the real-world product or product package.

A method includes: generating a three-dimensional grid of cells representing respective portions of an interior of a container, each cell having a status indicator defining an occupancy state of the corresponding portion of the container interior; during loading of the container: maintaining, for each of the cells, a current status indicator, controlling a depth sensor to capture a sequence of point clouds, each point cloud depicting the container interior, in response to each point cloud capture in the sequence, generating updated status indicators for the cells, based on (i) the point cloud, and on (ii) the current status indicators, replacing the current status indicators with the updated status indicators, measuring a current fullness of the container based on the current status indicators, and transmitting the current fullness to a computing device for at least one of display of the current fullness, or alert generation associated with the current fullness.