代表性成果
1.Qiang WZ,Wu Q*, Long LC*. Synergistic strengthening of dislocation and hetero-deformation induced in gradient nano-grained copper film: A molecular dynamics study.Physica Status Solidi A, 2023, 2200762.
2.WuQ*,Long LC.Numerical study on grain evolution of gradient structured aluminum matrix composites induced by graphene nanoplatelets. Applied Physics A, 2022,128: 1116.
3.Wu Q, Pei N*. Structural health monitoring of carbon fiber-reinforced laminate composites with torsional loads by using acoustic emission. Journal of Materials Science, 2022, 57: 13433-13445.
4.Pei N,Wu Q*, Long LC. Comparison of off-axis angle on the low velocity impact behaviors for carbon-fiber-reinforced polymer laminates. Journal of Composite Materials, 2022, 56: 2483-2494.
5.Yang ZL, Liu H,Wu Q, Long LC*. Study of Energy Absorption Characteristics and Deformation Mechanism of Stretching–Bending Synergistic Lattices Under Dynamic Compression. Advanced Engineering Materials, 2022, 2201130.
6.Pei N*, Leonard J Bond,Wu Q. Analysis of titanium alloy pyramidal lattice core sandwich panels under bending load using acoustic emission. Applied Physics Express, 2022, 15, 076508.
7.Wu Q*, et al. Effect of content and size of reinforcements on the grain evolution of graphene-reinforced aluminum matrix composites. Nanomaterials, 2021, 11, 2550.
8.Pei N, ...,Wu Q*; Cluster analysis of acoustic emission signals for tensile damage characterization of quasi-static indented carbon/glass fiber reinforced hybrid laminate composites. Composites Part A, 2021, 150, 106597.
9.Wu Q*, et al. Simulating the effect of temperature gradient on grain growth of 6061-T6 aluminum alloy via Monte Carlo Potts algorithm. CMES - Computer Modeling in Engineering and Sciences, 2021, 129: 99-116.
10.Zhang Z*, et al.,Wu Q. Numerical methods for microstructural evolutions in laser additive manufacturing. Computers and Mathematics with Applications, 2019, 78: 2296-2307.
11.Wu Q,Zhang Z*. Precipitation-Induced Grain Growth Simulation of Friction-Stir-Welded AA6082-T6. Journal of Materials Engineering and Performance, 2017, 26: 2179-2189.
12.Zhang Z*,Wu Q, et al. Monte Carlo simulation of grain growth and welding zones in friction stir welding of AA6082-T6. Journal of Materials Science, 2016, 51: 1882-1895.
13.Zhang Z*,Wu Q, Zhang HW. Prediction of fatigue life of welding tool in friction stir welding of AA6061-T6. International Journal of Advanced Manufacturing Technology, 2016, 86: 3407-3415.
14.Wu Q, Pei N, Long LC. Failure process monitoring and performance prediction of composite and lattice sandwich materials. International academic salon and young scholar forum of Beijing Mechanics Association, Beijing, China, June 2021, invited report.
15.Wu Q, Li RQ, Long LC. Computational method in the prediction of microstructure evolutions in solid-state additive manufacture of AZ31 magnesium alloy. The 25thAnnual Conference of Beijing Mechanics Society, Beijing, China, Jan. 2019, invited report.
16.Wu Q, Zhang Z.Computational methods for prediction of tool fatigue life in friction stir welding. 6thInternational Conference on Computational Methods (ICCM2015). Auckland, New Zealand, July 2015, session report.
17.李如琦,吴奇*,龙连春.搅拌摩擦增材成型过程仿真与显微性能预测.中国有色金属学报,2020, 30: 1847-1854.
18.吴奇,等.授权国家发明专利:一种基于液压技术的石墨烯铝复合材料制备搅拌头,ZL202110977914.3.
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