4results about How to "Fast modeling" patented technology

The application discloses a tokamak discharge modeling system based on a bidirectional long short-term memory neural network, which is composed of multiple modules, and the modules are low-coupling functional units.The modules at least include a data transfer module, a Batch data access input module, a training self-defined parameter module, a bidirectional long short-term memory neural network modeling module and a data visualization module.The whole system architecture is mainly divided into two paths, namely data training and data modeling.Using the visualization technology, the tokamak discharge experiment personnel can refer to the discharge modeling results and visualize the model training process.The application can one-key type in the experiment proposal stage to model the whole process of the tokamak discharge curve in advance, so that the experiment personnel and the proposal design personnel can check the validity and rationality of the proposal.The application can also be used for assisting data discovery after the experiment.

The application belongs to the technical field of power secondary equipment modeling, and discloses a power secondary equipment visual modeling and configuration system and method based on external electrical signal labeling, equipment and medium, to solve the problems of large manual workload, poor configuration consistency, missing function model and non-uniform engineering model in traditional processes. The system comprises: a geometric modeling module for establishing a geometric model; a PLP construction module for organizing physical terminals Pin, ports Port and logic layers L to form physical logic ports PLP; an external electrical signal import module for receiving external signals and labeling to Port; a semantic binding module for binding electrical signal semantics to PLP; a Function organization module for combining multiple PLPs to form a function object Function; and a model export module for exporting a structured file. The application realizes the standardization and semanticization of equipment modeling, and improves the design efficiency and data consistency.

This invention discloses a method for constructing a structured light dataset based on a digital twin model of a fringe projection system. A digital twin model of the system is constructed in computer graphics software based on the hardware and calibration parameters of a real fringe projection system. Then, a node tree is used to simulate the surface properties of the object under test and the system's ambient light source is set. The parameters are adjusted to diversify the target surface properties and ambient light. Fringe images are then imported, and automated projection and data acquisition of the digital twin model are achieved through programming. Finally, fringe images and corresponding depth images that meet the user's quantity requirements are generated, completing the construction of the structured light dataset. This invention solves the problems of complex fringe projection data acquisition processes, high dataset production costs, and limited data samples in real-world scenarios, achieving rapid and high-precision construction of fringe projection system datasets.

This invention relates to a dual-scale finite element analysis method and system for steel-concrete composite bridges, belonging to the field of civil engineering technology. The method includes the following steps: S1, establishing the length division of large-scale (macro-element) and small-scale (fine-element) regions in the steel-concrete composite bridge model, clarifying the focus of local stress analysis; S2, establishing components in both large and small scale regions and selecting element types for each component, simplifying the dual-scale model; S3, defining the material constitutive models of both large and small scale components to achieve consistency in material scale between macro-element and fine-element models; S4, assembling the spatial positions of each component and connecting the large and small scale regions to achieve consistency in deformation between the macro and fine models; S5, defining the internal contacts of each component and completing mesh generation; S6, applying actual loads and arranging actual boundary conditions to perform dual-scale finite element analysis. The technical solution of this invention has advantages such as high accuracy, high computational efficiency, and fast modeling speed.