Methods and systems for developing a product using a model that satisfies a region constraint. Data is received. A region constraint is identified. A model that fits the data and satisfies the region constraint is identified using a quadratic objective function and a set of point constraints derived iteratively from the region constraint.

A discrete geometrical pattern library guides a method for design optimization of a finite element model in a computer aided design (CAD) environment. Boundary conditions are applied to the finite element model, design variables for the bounded finite element model are initialized, and an objective function for the finite element model is evaluated. A gradient of the objective function is evaluated with respect to the design variables, an appearance constraint function is evaluated for the finite element model, and a gradient of the appearance constraint function is evaluated with respect to the design variables. The design variables are updated using a mathematical programming, and a convergence in the design optimization is detected, producing a converged design optimization of the finite element model is produced.

A system and methods are disclosed for producing components via additive manufacturing. In one embodiment, a three-dimensional geometry is sliced using a slicing plane to obtain a first two-dimensional geometry. A first polyline is generated based on a first skeleton of the first two-dimensional geometry, and a first slender body is generated based on the first polyline. The first slender body is subtracted from the first two-dimensional geometry to obtain a second two-dimensional geometry. A second polyline is generated based on a second skeleton of the second two-dimensional geometry. A first bundle of fibers is produced based on a segmentation of the first polyline and a second bundle of fibers is produced based on a segmentation of the second polyline. A component is produced from the first and second bundles of fibers using an additive manufacturing process.

The present invention is a method for accessing a model of a building; selecting a set of wall panels; isolating a plurality of the wall panels, wherein the wall panels interface with another wall panels in a horizontal type interface; selecting members of the wall panels involved in the interface, wherein the interface is identified as a connection between the wall panels; detecting the member type and the interface type; calculating a set of actual values associated with the interface type; comparing the set of actual values with a set of required values and determining the delta of the actual values and the required values; and identifying each interface where the delta is outside a predetermined range.

Formal verification methods are used to solve a valid model of a design-under-test (DUT) to enumerate valid coverage points based on an architectural specification of the DUT. A formal solver can be queried to solve for valid solutions by crossing one or more fields of a variable. After each valid solve, values of the variable fields can be recorded and a count for number of valid solutions can be incremented. A new rule can be added to the solving process after each valid solve to invalidate the recorded values of the variable fields for subsequent solves. The count for the number of valid solutions can provide a running total of the valid solutions found for the query. Results of the query can be processed to convert the recorded values to provide the enumerated coverage points. The enumerated coverage points can be converted to test cases for running simulations on the DUT.

The present disclosure relates to multi-objective optimization of complex technical systems. A method of designing a Pareto-optimal layout of a system includes processing input data relating to defining a layout space of layout parameters, a target space of target parameters, and constraints in the layout parameters and the target parameters, determining one or more sets of layout parameter values, each set specifying a layout configuration of the system to be modeled, receiving objective responses for the system having layout configurations specified by the one or more sets of layout parameter values, wherein each objective response corresponds to a target parameter value achieved by the system when having a layout configuration specified by one of the sets of layout parameter values, applying multi-objective optimization with respect to the target parameters to determine one or more further sets of layout parameter values, receiving objective responses for the system having layout configurations specified by the one or more further sets of layout parameter values, repeating the steps of applying multi-objective optimization and receiving respective objective responses until an abort criterion is met, and providing a user interface for Pareto-optimal design of the system to be modeled, the user interface configured for selecting a specific layout configuration on basis of visualizing objective trade-offs inferred from the objective responses for the respective sets of layout parameter values, wherein the trade-offs are inferred from the objective responses based on determining Pareto-optimal point.

Systems and methods automatically construct a realization of a model from an available set of alternative co-simulation components, where the realization meets one or more objectives, such as fidelity, execution speed, or memory usage, among others. The systems and methods may construct the realization model by setting up and solving a constrained optimization problem, which may select particular ones of the alternative co-simulation components to meet the objectives. The systems and methods may configure the realization, and execute the realized model through co-simulation. The systems and methods may employ and manage different execution engines and/or different solvers to run the realization of the model.

A valve assembly using at least two pressure-sensitive leaky check valves has a non-linear flow-rate versus pressure-drop relation. A method for optimizing such a valve assembly is capable of determining a minimum required number of such valves and outputting the material parameters of each valve. The valve assembly and method allows for arbitrary flow control, which has numerous applications such as within drug delivery, food processing, and industrial flow control. The valve assembly is completely passive, i.e. there is no need for a feedback network. The flow control is achieved using only fluid-structure interactions.

An object of the invention is to efficiently and automatically generate a simulation model used for verification from 3D CAD information. In order to solve the above problem, the invention provides a simulation model generation device configured to identify a connection relation between part elements constituting the device. The simulation model generation device includes: a contact surface number determination unit configured to determine the number of contact surfaces between the part elements using structural model data in the device; a shared rotation axis determination unit configured to determine, using the structural model data, presence or absence of a shared rotation axis between the part elements; and a connection relation identification unit configured to identify a connection relation between the part elements indicating any one of non-contact, fixation, slide, and rotation according to the number of the contact surfaces and the presence or absence of a shared rotation axis.

Net-based checking of a circuit design includes obtaining a circuit design comprising a plurality of polygons. Further, a shape of a first polygon of the plurality of polygons, and a shape of a second polygon of the plurality of polygons is determined. The shape of the first polygon differs from a shape of the second polygon. Violations within the circuit design are detected based on a comparison of the first polygon with the second polygon.