Affiliation:
1. Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China
2. Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
Abstract
A fast local refinement algorithm based on feature extraction is developed. In the mesh-based Reynolds equation solutions, two refinement features based on the physical parameters of fluid lubrication are firstly defined, namely, pressure value feature and pressure gradient feature. Then, a fast adaptive strategy different from the traditional methods based on residuals or recovery errors is constructed according to the features, which are expected to determine the element needed to be refined. Considering the update requirement of the feature parameters, an adaptive update strategy for feature parameters is also developed. Finally, the feasibility of the scheme is verified on a single-cylinder gasoline engine. Results show that the current algorithm can effectively reduce the computational scale while ensuring the computational accuracy of the mesh-based model, compared with the traditional global and local refinement strategy.
Funder
Natural Science Foundation of Hubei Province
Research Foundation of the Education Department of Hubei province
Key Laboratory of Metallurgical Equipment and Control of Education Ministry
Subject
Surfaces, Coatings and Films,Mechanical Engineering