An elastic body is modelled as a plurality of models of particles and models of geometric elements. Each particle model has a position attribute. Each geometric element has a boundary defined by two or more of the particles as nodes of the geometric element, nodes being points shared with neighbouring geometric elements. The interior area or volume of the geometric elements is modelled via non-linear interpolation functions that use the positions of the particles of the respective geometric elements as inputs to compute position and/or strain of interior points of the geometric elements. Energy is summed over the interior region of the element, the energy computation based on (a) position and/or stress of the geometric element computed by the non-linear interpolation functions and/or (b) non-linear material parameters that depend on position and/or strain at the interior points of the geometric elements. New positions of the particles are computed based minimizing total energy of the element.

A computer-implemented method of generating an operation procedure for a simulation of a system, in particular a mechatronic system is disclosed. A source node has at least one source parameter (Ps) and a first simulation system with at least one first simulation node is determined, wherein the first simulation node includes at least one input parameter (Pi) and at least one output parameter (Pa). The first simulation node includes a simulation function for determining the output parameter (Pa) based on the input parameter (Pi) of the first node. When the input parameter (Pi) is available based on the source parameter (Ps), a global operation graph is built describing a link between the source node and the first simulation node for describing an operating procedure of the simulation of the system.

The present invention discloses an optimization method for a screen surface dynamic load of a vibrating screen. The method includes the following steps: step 1. selecting design variables, and establishing an experimental matrix; step 2. performing a response curved surface experiment; step 3. establishing two double-objective optimization models and solving the same to obtain two groups of Pareto solution sets, wherein the solution sets respectively represent screening efficiency optimization paths of the vibrating screen under the conditions of a high screen surface dynamic load and a low screen surface dynamic load; and step 4. calculating an optimization space for a screen surface dynamic load under a high screening efficiency. According to the method of the present invention, the screen surface dynamic load can be directly reduced, and the service life of the screen surface and the whole vibrating screen is prolonged.

The present invention discloses an optimization method for a screen surface dynamic load of a vibrating screen. The method includes the following steps: step 1. selecting design variables, and establishing an experimental matrix; step 2. performing a response curved surface experiment; step 3. establishing two double-objective optimization models and solving the same to obtain two groups of Pareto solution sets, wherein the solution sets respectively represent screening efficiency optimization paths of the vibrating screen under the conditions of a high screen surface dynamic load and a low screen surface dynamic load; and step 4. calculating an optimization space for a screen surface dynamic load under a high screening efficiency. According to the method of the present invention, the screen surface dynamic load can be directly reduced, and the service life of the screen surface and the whole vibrating screen is prolonged.

To provide a simulation method in which a zooming analysis method is applied to a particle method to analyze displacement and stress.

An analysis model in which an object to be analyzed is divided by a first mesh is analyzed by using a finite element method or a particle method. A partial region of the analysis model is selected as a zooming region, the zooming region is divided by a second mesh, and a particle is disposed at each node of the second mesh. The particle at the node is displaced based on displacement by the analysis using the first mesh. A boundary condition of the zooming region is set based on a particle position at the node after the displacement. The particle is displaced by using the particle method under the boundary condition. Stress acting on the zooming region is obtained based on a particle position after the displacement.

To provide a simulation method in which a zooming analysis method is applied to a particle method to analyze displacement and stress.

An analysis model in which an object to be analyzed is divided by a first mesh is analyzed by using a finite element method or a particle method. A partial region of the analysis model is selected as a zooming region, the zooming region is divided by a second mesh, and a particle is disposed at each node of the second mesh. The particle at the node is displaced based on displacement by the analysis using the first mesh. A boundary condition of the zooming region is set based on a particle position at the node after the displacement. The particle is displaced by using the particle method under the boundary condition. Stress acting on the zooming region is obtained based on a particle position after the displacement.

A lithography method using a multiscale simulation includes estimating a shape of a virtual resist pattern for a selected resist based on a multiscale simulation; forming a test resist pattern by performing an exposure process on a layer formed of the selected resist; determining whether an error range between the test resist pattern and the virtual resist pattern is in an allowable range; and forming a resist pattern on a patterning object using the selected resist when the error range is in the allowable range. The multiscale simulation may use molecular scale simulation, quantum scale simulation, and a continuum scale simulation, and may model a unit lattice cell of the resist by mixing polymer chains, a photo-acid generator (PAG), and a quencher.

A lithography method using a multiscale simulation includes estimating a shape of a virtual resist pattern for a selected resist based on a multiscale simulation; forming a test resist pattern by performing an exposure process on a layer formed of the selected resist; determining whether an error range between the test resist pattern and the virtual resist pattern is in an allowable range; and forming a resist pattern on a patterning object using the selected resist when the error range is in the allowable range. The multiscale simulation may use molecular scale simulation, quantum scale simulation, and a continuum scale simulation, and may model a unit lattice cell of the resist by mixing polymer chains, a photo-acid generator (PAG), and a quencher.

Techniques for simulating an atmospheric effect in an AV simulation system are described. In one embodiment, a method for simulating an atmospheric effect including a plurality of particles suspended in an atmosphere may include receiving a first parameter defining a density of the plurality of particles comprising the atmospheric effect; receiving at least one second parameter defining a location of the atmospheric effect relative to a vehicle in a scene generate by the simulation system; and simulating the atmospheric effect in the scene as defined by the first parameter and the at least one second parameter.

Techniques for simulating an atmospheric effect in an AV simulation system are described. In one embodiment, a method for simulating an atmospheric effect including a plurality of particles suspended in an atmosphere may include receiving a first parameter defining a density of the plurality of particles comprising the atmospheric effect; receiving at least one second parameter defining a location of the atmospheric effect relative to a vehicle in a scene generate by the simulation system; and simulating the atmospheric effect in the scene as defined by the first parameter and the at least one second parameter.