Demand-driven feature recognition method for adaptive grid refinement of eddy current field
An adaptive grid and feature recognition technology, which is applied in design optimization/simulation, instrumentation, electrical digital data processing, etc., can solve the problem that the feature recognition method cannot flexibly respond to the demand for adaptive grid refinement of the eddy current field, and achieve both Calculation accuracy and calculation cost, and the effect of ensuring high efficiency
Active Publication Date: 2020-07-10
CHINA AGRI UNIV
View PDF9 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0004] The technical problem to be solved by the present invention is that the existing feature recognition methods cannot flexibly cope with the needs of different eddy field adaptive mesh refinement in fluid engineering
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0039] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0040] In the description of the present invention, it should be noted that unless otherwise specified and limited, the terms "installation", "connection" and "connection" should be understood in a broad sense, for example, it can be a fixed connection or a detachable connection. Connected, or integrally connected; it can be mechanically conn...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention relates to the technical field of engineering computational fluid mechanics, in particular to a demand-driven feature recognition method for adaptive grid refinement of an eddy current field. The method comprises the following steps: determining an Euclidean model of a velocity gradient Helmholtz positive symmetric component, an Euclidean model of a velocity gradient Helmholtz negative symmetric component and an empirical demand factor expressed by a transfer function coefficient; determining the Euclidean modulus of a velocity gradient Helmholtz positive symmetric component, Euclidean modulus of a velocity gradient Helmholtz negative symmetric component, an empirical demand factor and a fidelity constant to represent vortex-induced phase extreme; when self-adaptive grid refinement is carried out on the area where the concentrated vortex in the vortex field is located, taking a threshold value of vortex variation extreme for feature recognition; when self-adaptive grid refinement is carried out on an area where a shearing layer in the eddy current field is located, taking the gradient of the vortex variation phase to carry out feature identification. The core identification parameters have theoretical advantages of normalization and Galileo invariance, and the function characteristics of the core identification parameters can be adjusted through experience demandfactors so as to flexibly meet typical engineering refinement demands.
Description
technical field [0001] The invention relates to the technical field of engineering computational fluid dynamics, in particular to a demand-driven feature recognition method for adaptive grid refinement of eddy current fields. Background technique [0002] The adaptive mesh refinement of the eddy current field is an important means to ensure efficient engineering calculations, and the feature recognition method is the basic tool in the process of adaptive mesh refinement. The feature recognition method is used to determine the area that needs to be refined when calculating the eddy current field, and its recognition effect directly affects the calculation accuracy and efficiency. From the perspective of current engineering applications, among the commonly used feature recognition methods, even the relatively optimal Omega method fails to achieve this goal. The reason is that the current feature recognition methods mainly focus on the theoretical vortex features. identified, ...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/23G06F30/28G06F113/08
Inventor 王福军王超越王本宏赵浩儒汤远叶长亮安东森贾江婷
Owner CHINA AGRI UNIV