Min Li

Mr. Min Li


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 July 2025 in Materials
Verified
Journal Article
Open access
PDF file
MLMin Li
Min Li
XCXue Chen
Xue Chen
YDYu Deng
Yu Deng
WWWenjun Wang
Wenjun Wang
JLJian Li
Jian Li
Chuyang LuoChuyang Luo
Chuyang Luo
In composites, fiber–matrix thermal mismatch induces stress heterogeneity that is beyond the resolution of macroscopic approaches. The asymptotic expansion homogenization method is used to create a multi-scale thermo-mechanical coupling model that predicts the elastic modulus, thermal expansion coefficients, and thermal conductivity of ceramic matrix composites at both the macro- and micro-scales. These predictions are verified to be accurate with a maximum relative error of 9.7% between the measured and predicted values. The multi-scale analysis method is then used to guide the vane’s thermal stress analysis, and a macro–meso–micro multi-scale model is created. The thermal stress distribution and stress magnitudes of the guide vane under a transient high-temperature load are investigated. The results indicate that the temperature and thermal stress distributions of the guide vane under the homogenization and lamination theory models are rather comparable, and the locations of the maximum thermal stress are predicted to be reasonably close to one another. The homogenization model allows for the rapid and accurate prediction of the guide vane’s thermal stress distribution. When compared to the macro-scale stress values, the meso-scale predicted stress levels exhibit excellent accuracy, with an inaccuracy of 11.7%. Micro-scale studies reveal significant stress concentrations at the fiber–matrix interface, which is essential for the macro-scale fatigue and fracture behavior of the guide vane.

2 January 2025 in Materials
Verified
Journal Article
Open access
PDF file
WWWenjun Wang
Wenjun Wang
QZQi Zeng
Qi Zeng
CLChaochao Li
Chaochao Li
MLMin Li
Min Li
LCLiang Cao
Liang Cao
peng Caopeng Cao
peng Cao
Obtaining the mechanical parameters of SiCf/SiC composites quickly and accurately is crucial for the performance evaluation and optimal design of novel turbine disc structures. A representative volume element (RVE) model of 2D woven SiCf/SiC composites was developed using CT scanning and machine learning-driven image reconstruction techniques. The stress-strain curve was obtained by uniaxial tensile test, and the anisotropic mechanical parameters were obtained by inverse analysis using a non-dominated sorting genetic algorithm (NSGA-II). Subsequently, the uniaxial tension simulation was carried out based on the RVE model and mechanical parameters. The results show that the simulation curve is in good agreement with the test, and the errors of initial modulus and peak stress were 3.98% and 2.75%, respectively. Finally, the finite element models of the turbine disc with two braiding schemes were established to simulate the damage of the turbine disc. And the simulation results were verified by a centrifugal test. The failure modes of the two kinds of turbine discs are similar to the centrifugal test results, and the maximum rotating speed was close to the test results. The findings of this study provide a novel solution for obtaining the anisotropic mechanical parameters of SiCf/SiC composites with different woven schemes.