Yoshiharu Tsugeno (M2), Department of Nuclear Engineering and Management, received Best Student Presentation Award


On 20th November 2021, Yoshiharu Tsugeno (M2), Sakai Labo, Department of Nuclear Engineering and Management, received “Best Student Presentation Award” at The 3rd International Symposium on Computational Particle Technology.

<Name of award and short explanation about the award>
The 3rd International Symposium on Computational Particle Technology Best Student Presentation Award
It was given for the greatest presentations at the student session.

About awarded research>
Title: Numerical investigation on optimal design parameter for powder mixing in a ribbon mixer using the DEM

Powder mixing is a common process and has a significant impact on the quality of the final products. A ribbon mixer is widely employed for powder mixing in various engineering fields such as food engineering, pharmaceutical engineering and chemical engineering. However, the structure of the ribbon mixer is extremely complex, which prevents investigation of powder mixing in the ribbon mixer by experimental approaches. For example, identification of the optimal design of the ribbon mixer has not been sufficiently carried out, and hence the geometry and operating conditions of the ribbon mixer has been empirically designed. Furthermore, there is a lack of measurement method to evaluate the convective mixing in the ribbon mixer, even though the dominant mixing mechanism in the ribbon mixer is empirically regarded as being the convection. In this study, an effective parameter for better mixing is identified through sensitivity analyses by numerical simulations. Furthermore, a novel method for identification of the dominant mixing mechanism as being the convection is proposed, and the adequacy of the proposed measurement method is shown. Incidentally, the effectiveness of the identified parameter is highly consistent with the effectiveness of the proposed measurement method.

<Your impression & future plan>
It’s a great honor for me to win this award. I sincerely thank Prof. Mikio Sakai for his excellent supervision and thank Sumi Yamazaki-san and Takeshi Nishinomiya-san in Ajinomoto Co., Inc. for their collaborative research, and I also thank all members of my laboratory. I will keep doing my best.