Shaowei He

PLA Army Service Academy

Papers

1

Total Citations

27

H-Index

1

About

Shaowei He is a researcher specializing in robotic painting and computational fluid dynamics, with a focus on optimizing industrial coating processes. His most-cited work, "Paint thickness simulation for robotic painting of curved surfaces based on Euler–Euler approach" (2019), has garnered 27 citations, reflecting its significance in advancing precision manufacturing. He’s key contributions lie in developing simulation models that predict paint deposition on complex geometries, enabling robots to achieve uniform coatings on curved surfaces—a critical challenge in automotive and aerospace industries. By integrating Euler–Euler multiphase flow theory with robotic path planning, He’s research bridges simulation and real-world application, reducing material waste and improving quality control. His work stands out for its practical impact, offering a foundation for adaptive robotic systems in automated painting. He’s achievements highlight his role in merging theoretical fluid dynamics with industrial robotics, making him a notable figure in smart manufacturing and surface engineering.

Research Focus

Key Achievements

1
H-Index
1
Papers
27
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Paint thickness simulation for robotic painting of curved surfaces based on Euler–Euler approach
27 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: PLA Army Service Academy

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago