46results about How to "Shorten the modeling cycle" patented technology

The invention discloses a computer-aided design (CAD) graphical modeling method for a software / hardware system and belongs to the field of graphical modeling. The method is characterized by comprising a user graph manipulation interface F1, a software / hardware module library management device F2, a graphics modeling device F3, a program task allocation mapping device F4, a core data module F5, a model and mapping file resolver F6 and a model and mapping file F7. The user graph manipulation interface F1 is used for completing the function of modeling according to instructions such as the drawing instruction of a user; the software / hardware module library management device F2 is used for managing a software / hardware basic module with parameters capable of being configured; the graphics modeling device F3 is used for building a software / hardware graphical model by use of the software / hardware basic module; the program task allocation mapping device F4 is used for building a task allocation mapping relationship from software to hardware; the core data module F5 is used for defining various data contents of a modeling system; the model and mapping file resolver F6 is used for resolving files stored according to formats to acquire the various data contents, or storing the data contents as the files according to the formats; and the model and mapping file F7 is used for storing the files according to the formats. By means of the CAD graphical modeling method for the software / hardware system, visualized and efficient software / hardware integrated modeling can be achieved by the user, and an allocation mapping scheme of software tasks on the hardware can be specified.

The present invention provides a humanized mouse model of cytomegalovirus infection and a construction method thereof. The construction method includes: constructing an initial model by infusing G-CSF mobilized human peripheral stem cells into NSG mice; wherein, the The input of G‑CSF mobilized human peripheral stem cells was 1×10 6 per mouse; after the human peripheral stem cells are engrafted, cytomegalovirus is injected into the initial model to obtain a stable cytomegalovirus-infected humanized mouse model. The construction method provided by the present invention can reduce the occurrence of GVHD, and provide a stable place for experimental research based on the model in the later stage; meanwhile, the engraftment period of human peripheral stem cells is short, which greatly shortens the modeling period and speeds up the later stage. Based on the experimental research progress of the model, the modeling method provided by the present invention has broad application prospects.

The invention relates to a car body beam frame collision modeling and analysis method considering characteristics of a plastic hinge, and belongs to the field of car body design. The method comprises the steps of firstly solving a cross section area and a bending-twisting inertial moment characteristic of the cross section, with a complex shape, of a car body beam frame; secondly creating a car body beam frame model; thirdly generating a plastic hinge model characteristic of a thin-walled beam unit, and assigning a value to a material characteristic of a Belytschko-Schwer (BS) beam unit, wherein an MAT 29# material type of LS-DYNA software is selected for the material characteristic; and finally generating a keyword text file that can be solved by the LS-DYNA software, and calling the LS-DYNA software to perform collision solving. The car body frame model is established by adopting the beam unit; the plastic hinge model simulates bending, twisting and crushing deformation of a beam to perform collision analysis; a solving result is reliable, the user operation is convenient, and the modeling period is greatly shortened; and the method has an important guide effect for car body design.

The invention belongs to the field of modeling of microwave circuits and devices, and provides a neural network space mapping modeling method for large-signal power transistors. The method first establishes a neural network space mapping model with capacitance and inductance, and changes the DC and AC characteristics of the model, respectively; then uses a novel nonlinear function to extract additional current signals to improve the large-signal characteristics of the existing device model while maintaining The S parameters are unchanged. Finally, a step-by-step training method is adopted to quickly train the proposed neural network spatial mapping model, which avoids repeated adjustment of variables and shortens the modeling cycle.