Meng Li

ORCID: 0000-0001-6573-4046
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • High Temperature Alloys and Creep
  • Mineral Processing and Grinding
  • High-Temperature Coating Behaviors
  • Laser Material Processing Techniques
  • Granular flow and fluidized beds
  • Combustion and flame dynamics
  • Cellular and Composite Structures
  • Radiative Heat Transfer Studies
  • Metallurgical Processes and Thermodynamics
  • Iron and Steelmaking Processes
  • Microstructure and Mechanical Properties of Steels
  • Transportation Safety and Impact Analysis
  • Advanced Measurement and Detection Methods
  • Automotive and Human Injury Biomechanics
  • High Entropy Alloys Studies
  • Aluminum Alloy Microstructure Properties
  • Lattice Boltzmann Simulation Studies
  • Numerical methods in engineering
  • Fatigue and fracture mechanics
  • Advanced Numerical Methods in Computational Mathematics
  • Metallurgy and Material Forming
  • Advanced Battery Materials and Technologies
  • Powder Metallurgy Techniques and Materials
  • Advancements in Battery Materials
  • Heat transfer and supercritical fluids

Wuhan National Laboratory for Optoelectronics
2024

Huazhong University of Science and Technology
2018-2024

Xi’an University
2024

Beijing Jiaotong University
2024

Northwestern Polytechnical University
2009-2024

Donghua University
2024

Northeastern University
2023-2024

National Synchrotron Radiation Laboratory
2024

University of Science and Technology of China
2024

Harbin Institute of Technology
2010-2023

Abstract Predicting the thermal state of blast furnace is a crucial step in stabilizing operations, improving process efficiency, and minimizing disturbances that can increase energy consumption emissions. Traditional first-principles models are limited by system’s complexity, involving temporally spatially distributed variables non-ideal conditions. Recent advances machine learning enable development predictive using diverse data types. This study presents Dual-Channel Fusion Analysis...

10.1007/s40831-025-01042-1 article EN cc-by Journal of Sustainable Metallurgy 2025-03-06

This study introduces a novel material processing methodology termed High Repetition Frequency Selective Laser Quenching (HRF-SLQ). technique utilizes high-power lasers with maximum power of 5 kilowatts in conjunction scanning galvanometer, operating at elevated repetition rates up to 200 hertz, specifically treat surfaces high and medium carbon steels. The application this method leads the creation allotropic metal matrix composite materials (A-MMCs). In general, speed galvanometer can...

10.1016/j.jmrt.2024.05.044 article EN cc-by-nc-nd Journal of Materials Research and Technology 2024-05-01
Coming Soon ...