The invention relates to a method for simulation-based analysis and/or optimization of a motor vehicle, preferably having the following working steps: simulating (SIOI) a driving operation of the motor vehicle (I) on the basis of a model (M) with at least one manipulated variable for acquiring values of at least one simulated variable which is suitable for characterizing an overall vehicle behaviour, in particular a driving capability, of the motor vehicle (I), wherein the model has at least one partial model, in particular a torque model, and wherein the at least one partial model is based on a function and preferably characterizes the operation of at least one component, in particular of an internal combustion engine of the motor vehicle (I); and—outputting (S I03) the values of the at least one simulated variable.

In one embodiment, a wizard can automate a setup of a welding simulation by requiring the input of data (e.g. in data entry fields labelled as required) that is used to automatically set up a welding simulation. The wizard can be part of a general purpose mechanical simulation software package, and the wizard can receive inputs from CAD software that specifies the geometrical shapes of bodies of the assembly to be welded and the filling material itself and physical properties of bodies to be welded (e.g. sizes of bodies, number of bodies, physical arrangement and geometries of bodies, melting temperatures, etc.), in addition to the material physical properties and the wizard can provide outputs to the mechanical simulation software package to provide boundary conditions for use in the mechanical simulation software that can use finite element analysis methods in simulations.

Embodiments of a variable system for simulating the operation of an autonomous system, such as an autonomous vehicle, are disclosed. A layered approach for defining variables can allow changing the specification of those variables under the rules of override and refinement, while leaving the software components that query those variables at runtime unaffected. The variable system can facilitate, among others, deterministic sampling of variables, simulation variations, noise injection, and realistic message timing. These applications can make the simulator more expressive and more powerful by virtue of being able to test the same scenario under many different conditions. As a result, more exhaustive testing can be performed without requiring user intervention and without having to change the individual software components of the simulator.

A global computer aided engineering (CAE) model representing an electronic product that contains solder joints and an individual detailed solder joint model are received. The solder joint model can include a solder ball, one or more metal pads, a portion of printed circuit board, and a portion of semiconductor chip component. The global CAE model includes locations of the solder joints to be evaluated in a drop test simulation. The solder joint model is replicated at each location to create a local CAE model via a geometric relationship between the global CAE model and the local CAE model. Simulated physical behaviors of the product under a design condition are obtained in a co-simulation using the global CAE model in a first time scale and the local CAE model in a second time scale. Simulated physical behaviors are periodically synchronized based on kinematic and force constraints.

A method of manufacturing a panel using an initial die and a series of secondary dies includes sequentially defining multi-dimensional models for the series of secondary dies. The method includes simulating a geometry of an n.sup.th pre-panel, defining a multi-dimensional model of the n.sup.th secondary die based on the simulated geometry of the n.sup.th pre-panel, simulating operation of the n.sup.th secondary die on the n.sup.th pre-panel to determine geometry of an (n+1).sup.th pre-panel, and determining a deviation between the simulated (n+1).sup.th pre-panel and a target pre-panel geometry. If the deviation is outside tolerance, the method includes iteratively: adjusting the multi-dimensional model of the n.sup.th secondary die, simulating operation thereof to determine an adjusted simulated geometry of the (n+1).sup.th pre-panel, and determining a deviation between the adjusted simulated geometry of the (n+1).sup.th pre-panel and the target (n+1).sup.th pre-panel, until the deviation is within the tolerance limit.

A method of manufacturing a panel using an initial die and a series of secondary dies includes sequentially defining multi-dimensional models for the series of secondary dies. The method includes simulating a geometry of an n.sup.th pre-panel, defining a multi-dimensional model of the n.sup.th secondary die based on the simulated geometry of the n.sup.th pre-panel, simulating operation of the n.sup.th secondary die on the n.sup.th pre-panel to determine geometry of an (n+1).sup.th pre-panel, and determining a deviation between the simulated (n+1).sup.th pre-panel and a target pre-panel geometry. If the deviation is outside tolerance, the method includes iteratively: adjusting the multi-dimensional model of the n.sup.th secondary die, simulating operation thereof to determine an adjusted simulated geometry of the (n+1).sup.th pre-panel, and determining a deviation between the adjusted simulated geometry of the (n+1).sup.th pre-panel and the target (n+1).sup.th pre-panel, until the deviation is within the tolerance limit.

Data characterizing an assembly/structure containing a first stage and a second stage are received in a computer system. The first stage can contain a first cyclic symmetry and the second stage can contain a second cyclic symmetry. The first cyclic symmetry and the second cyclic symmetry are different from each other. Each stage may be a 360-degree stage. The received data includes a first mesh representing the first stage and a second mesh representing the second stage. Multiple simulation results are obtained using corresponding models in respective dynamic analyses of the assembly. Each model includes a set of constraints for coupling the first mesh and the second mesh. The set of constraints is associated with a group of distinct linked harmonic indices. Physical behaviors of the assembly are then calculated using one or more sets of the simulation results. Constraints are in forms of constraint equations.

The present disclosure provides a strip flatness prediction method considering lateral spread during rolling. The method includes: step 1: acquiring strip parameters, roll parameters and rolling process parameters; step 2: introducing a change factor of a lateral thickness difference before and after rolling and a lateral spread factor by considering lateral metal flow, and constructing a strip flatness prediction model based on the coupling of flatness, crown and lateral spread; step 3: constructing a three-dimensional (3D) finite element model (FEM) of a rolling mill and a strip, simulating strip rolling by the 3D FEM, extracting lateral displacement and thickness data of the strip during a stable rolling stage, calculating parameters of the strip flatness prediction model based on the coupling of flatness, crown and lateral spread; and step 4: predicting the flatness of the strip by the strip flatness prediction model based on the coupling of flatness, crown and lateral spread.

A method and system for an accelerated design of a virtual product formulation based on an expert-enhanced quantitative formulation network includes sourcing qualitative expert formulation; creating a qualitative formulation network; extracting qualitative network-expansion data based on a category associated with a target product associated with the qualitative formulation network, creating a second set of network components including formulation variable nodes and formulation edge connections; integrating the second set of network components into the qualitative formulation network; transforming the qualitative formulation network integrated with the second set of network components to a quantitative formulation network; designing at least part of a virtual product formulation based on the quantitative formulation network; and generating a target formulation proposal that likely satisfies the target formulation objective based on executing the virtual product formulation as initialized.

Disclosed are a method and an apparatus for string connecting photovoltaic modules. The method includes: acquiring position information of n photovoltaic modules to be connected; categorizing the n photovoltaic modules into m partitions based on the position information of the n photovoltaic modules; generating k candidate connection solutions of an i.sup.th partition in the m partitions, wherein the i.sup.th partition includes m photovoltaic modules, and each of the k candidate connection solutions uses one photovoltaic module in the m photovoltaic modules as a starting point, and obtaining at least one string of photovoltaic modules by simulating connection of the m photovoltaic modules according to a preset connection solution; and selecting a target connection solution from the k candidate connection solutions based on an estimated cable use amount corresponding to each of the k candidate connection solutions.