Microscopic Imaging of Spray Droplet Distribution

Lecture Topic: Microscopic Imaging of Spray Droplet Distribution
Expert: Keiya Nishida
Date: June 10, 2025
Time: 10:00
Location: Lecture Hall 1517, Energy Research Institute
Organizer: Energy Research Institute

Speaker Profile:
Keiya Nishida is a professor in the Graduate School of Advanced Science and Engineering at Hiroshima University, Japan. He earned his Bachelor's, Master's, and Ph.D. degrees in Mechanical Engineering from Hiroshima University in 1978, 1980, and 1989, respectively. He previously worked as an internal combustion engine R&D engineer at Kubota Corporation and has served as a visiting scholar at the University of Michigan, a guest professor at Shanghai Jiao Tong University, and a "High-End Foreign Expert" at Dalian University of Technology. He has published over 190 journal papers, 130 international conference papers, 6 review articles, and authored 3 books. He has held positions such as President of ILASS-Japan, Chair of the JSAE Diesel Engine Committee, Chair of the JSME Research Committee on Advanced Combustion Systems for Diesel Engines, and Chair of the JSME Engine Systems Division.
Research Expertise: Internal combustion engine spray and combustion.

Lecture Summary:
Droplet size distribution is a critical parameter determining spray characteristics, as droplet size directly influences evaporation rates, thereby affecting fuel-air mixture homogeneity and subsequent combustion behavior. Current techniques for measuring droplet size distribution, such as laser Doppler and laser diffraction methods, are limited by their reliance on sparse individual particles or theoretical model assumptions to infer size distribution. This presentation employs laser-based imaging—specifically Particle Image Analysis (PIA)—to experimentally investigate changes in droplet size distribution along the spray axis under varying ambient pressures for both single-hole and multi-hole (10-hole) nozzles. The experimental results are compared with classic distribution models, including the Log-Normal distribution, Nukiyama-Tanasawa distribution, and Rosin-Rammler distribution.

Faculty and students are welcome to attend!