Abstract:
A device may include a processor and a memory. The processor may receive a request to link a model element, of a model, and a spatial element. The model, when executed, simulates behavior of a system, and the spatial element is a physical object or an object that is rendered for display in two or more dimensions. The processor may further receive information identifying the model element, receive information identifying the spatial element, and create a link between the identified model element and the identified spatial element based on the received request. The link may allow at least one of the model element to be identified based on identification of the spatial element, or the spatial element to be identified based on identification of the model element. The memory may store the link.
Abstract:
This invention allows users to build, manipulate, and finally deploy various model configurations with little performance overhead, better syntactic clarity and configuration flexibility.
Abstract:
A method may include causing a first model to be executed. The causing the first model to be executed may be performed by a device. The method may further include causing a second model to be executed to simulate a functionality of the first model. The causing the second model to be executed may be performed by the device. The method may further include interacting with a model element, of the second model, associated with implicitly accessing information regarding a state of the first model. The state may be a representation of the first model at a particular simulation time-step. The interacting with the model may be performed by the device. The method may further include accessing, by the model element, information associated with the state of the first model. The accessing the information may be performed by the device.
Abstract:
A system and method provides top-down programming in a graphical programming environment. A developer may utilize a component constructor to create a graphical skeleton component that represents a template for a procedure. The graphical skeleton component may include one or more hole elements that mark locations in the component at which functions may be specified. An instance of the component may be included in a graphical model, and one or more functions specified for the hole elements, thereby completing the component. The one or more functions may refer to model parameters, and bindings may be captured among the parameters. Upon execution or simulation of the model, the one or more functions specified for the component are executed, and the parameters evaluated. The functionality of the completed may depend on the one or more functions specified for the hole elements.
Abstract:
Systems and methods establish, activate, and deactivate variant choices within an acausal physical component model of a physical system. The systems and methods utilize variant connector blocks to establish cut points in a physical network defined by the physical model. The cut points may be programmatically controlled to activate and/or deactivate a variant choice. The variant connector blocks may include internal connections that may be programmatically controlled to be either open or closed in order to cut or include a variant choice in the acausal physical component model. Variant conditions or labels may be associated with the internal connections, and the systems and methods may evaluate the variant conditions and/or examine the labels to determine whether the internal connections are open or closed.
Abstract:
A method and system automatically generates a display of symbolic equations from a graphical model (or vice versa) which is readable, parametric, and interactive.
Abstract:
Systems and methods provide, as part of an executable graphical model, a region for providing variants that includes one or more computational choices defining alternative execution implementations of the region. Conditions assigned to the one or more computational choices indicate which of the computational choices is active. The conditions specify logical expressions of variables that evaluate to True or False. For a given simulation of the executable graphical model, all of the logical expressions may evaluate to False, such that none of the computational choices are active. All of the computational choices of the executable graphical model may be removed for the given simulation.
Abstract:
A method may include causing a first model to be executed. The causing the first model to be executed may be performed by a device. The method may further include causing a second model to be executed to simulate a functionality of the first model. The causing the second model to be executed may be performed by the device. The method may further include interacting with a model element, of the second model, associated with implicitly accessing information regarding a state of the first model. The state may be a representation of the first model at a particular simulation time-step. The interacting with the model may be performed by the device. The method may further include accessing, by the model element, information associated with the state of the first model. The accessing the information may be performed by the device.
Abstract:
Systems and methods provide, as part of an executable graphical model, a region for providing variants that includes one or more computational choices defining alternative execution implementations of the region. Conditions assigned to the one or more computational choices indicate which of the computational choices is active. The conditions specify logical expressions of variables that evaluate to True or False. For a given simulation of the executable graphical model, all of the logical expressions may evaluate to False, such that none of the computational choices are active. All of the computational choices of the executable graphical model may be removed for the given simulation.
Abstract:
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.