Junze Jiang

Papers

Total Citations

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About

Dr. Junze Jiang is a leading researcher in the field of robotic spray painting and coating technology, with a primary focus on computational fluid dynamics (CFD) modeling for industrial finishing processes. His work addresses critical challenges in paint atomization, film formation, and thickness prediction, directly impacting the trajectory planning of intelligent spray-painting robots. Dr. Jiang’s most influential contribution is his 2019 paper on paint thickness simulation for curved surfaces using the Euler–Euler approach, which has garnered 27 citations and provides a foundational method for predicting coating uniformity on complex geometries. He further advanced the field with his 2022 study on airless spray film formation, proposing a novel CFD-based model that enables accurate thickness prediction—a key step toward automating high-precision robotic spraying. In a third notable paper, Dr. Jiang introduced a hybrid Euler–Lagrange model to simulate the multi-scale paint atomization process in air spraying, overcoming a longstanding barrier in whole-process CFD simulation. With a total of over 40 citations across his core works, Dr. Jiang’s research is instrumental in bridging the gap between fluid dynamics theory and practical robotic coating applications, offering significant improvements in coating quality and process efficiency.