Abstract: This application relates to apparatus and methods for electronically generating, and executing, component models for systems and system components, and determining component options for the system based on the executed component models. In some examples, a computing device generates component models for one or more components of a system. The component models may be based on features, inputs, and outputs to each system component. The computing device may execute the component models to determine one or more requirements for each component. The computing device may then search a database to determine component options that can satisfy the one or more requirements. In some examples, the computing device may display the determined component options, and may allow for the selection of one or more of the determined component options. In some examples, the computing device may allow for the purchase of the component options.

Abstract: This application relates to apparatus and methods for electronically generating, and executing, component models for systems and system components, and determining component options for the system based on the executed component models. In some examples, a computing device generates component models for one or more components of a system. The component models may be based on features, inputs, and outputs to each system component. The computing device may execute the component models to determine one or more requirements for each component. The computing device may then search a database to determine component options that can satisfy the one or more requirements. In some examples, the computing device may display the determined component options, and may allow for the selection of one or more of the determined component options. In some examples, the computing device may allow for the purchase of the component options.

Abstract: This application relates to apparatus and methods for generating, and executing, surrogate models. In some examples, a computing device generates and evaluates correlations between input and output variables for a system to identify highly correlated input and output parameters. In addition, weights for one or more of the parameters may be determined. The computing device identifies a mathematical relationship between input and output variables to generate a physics model. The computing device may also identify other features not captured by the physical relationship that are highly correlated to each other, and generates a feature model that is based on the highly correlated features. The computing device may optimize the feature model based on a culling process that reduces the computational resources required to execute the feature model. The physics model is then combined with the feature model to generate a system output model that can simulate the system.

Abstract: This application relates to apparatus and methods for generating, and executing, surrogate models. In some examples, a computing device generates and evaluates correlations between input and output variables for a system to identify highly correlated input and output parameters. In addition, weights for one or more of the parameters may be determined. The computing device identifies a mathematical relationship between input and output variables to generate a physics model. The computing device may also identify other features not captured by the physical relationship that are highly correlated to each other, and generates a feature model that is based on the highly correlated features. The computing device may optimize the feature model based on a culling process that reduces the computational resources required to execute the feature model. The physics model is then combined with the feature model to generate a system output model that can simulate the system.