Zhengxiong Dai

ORCID: 0009-0009-4106-5736
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About
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Research Areas
  • Astrophysics and Cosmic Phenomena
  • Precipitation Measurement and Analysis
  • Plasma and Flow Control in Aerodynamics
  • Lightning and Electromagnetic Phenomena
  • Adhesion, Friction, and Surface Interactions
  • Tribology and Lubrication Engineering
  • Fluid Dynamics and Turbulent Flows
  • Gear and Bearing Dynamics Analysis
  • 3D Surveying and Cultural Heritage
  • Computational Fluid Dynamics and Aerodynamics

Hangzhou Dianzi University
2023

Bridge University
2022

To explore the tribological properties of a seawater-lubricated friction pair, influence cavitation and multi-scale texture on load-carrying capacity is investigated under seawater lubrication conditions. In this paper, numerical simulation method proposed to reveal mechanism capacity, results are verified by experiments. The show that cavitation, wedge action, vortex flow effect main mechanisms responsible for affecting capacity. Cavitation not always advantageous indicate enhances when...

10.1063/5.0160229 article EN Physics of Fluids 2023-08-01

The Large High Altitude Air Shower Observatory (LHAASO) has three sub-arrays, KM2A, WCDA and WFCTA. flux variations of cosmic ray air showers were studied by analyzing the KM2A data during thunderstorm on 10 June 2021. number shower events that meet trigger conditions increases significantly in atmospheric electric fields, with maximum fractional increase 20%. rates (increases or decreases) are found to be strongly dependent primary zenith angle. secondary particles significantly, following...

10.1088/1674-1137/ac9371 article EN Chinese Physics C 2022-09-21

Real-time and accurate prediction of aerodynamic flow fields around airfoils is crucial for control optimization. However, achieving this remains challenging due to the high computational costs non-linear nature physics. Traditional Computational Fluid Dynamics (CFD) methods face limitations in balancing efficiency accuracy, hindering their application real-time scenarios. To address these challenges, study presents AeroDiT, a novel surrogate model that integrates scalable diffusion models...

10.48550/arxiv.2412.17394 preprint EN arXiv (Cornell University) 2024-12-23
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