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Mitsume Lab
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A lab that develops numerical analysis methods for solving complex coupled problems.

AboutAbout the lab
Tackling coupled problems with new analysis methods.
The Mitsume Lab studies how to solve coupled problems, in which multiple phenomena are intertwined, using numerical analysis (simulation).
The lab develops new analysis methods and mathematical models of phenomena from the perspectives of computational engineering and applied mathematics.
Assistant Professor Mitsume, who leads the lab, became interested in coupled problems related to tsunamis and has worked on them for many years.
The lab also conducts joint research with researchers in mechanical engineering, civil engineering, architectural engineering, and other fields, and makes an effort to let members choose the fields they are interested in.
Key terms
- Coupled problem
- A problem in which multiple phenomena influence each other. It is harder to handle with numerical analysis than a single phenomenon
- Galerkin method
- A method that approximately solves differential equations by superposing a finite number of basis functions. The finite element method is a representative example
- Meshfree method
- A numerical analysis method that solves problems without using grids or meshes. Examples include the SPH and MPS methods
NewsLab news
ICML paper on joint research with RICOS Co., Ltd. published
Paper on joint research with the Morita Lab at the University of Tsukuba published
A student received the Paper Encouragement Award from the Japan Society for Computational Engineering and Science
Paper on joint research with the Morita Lab at the University of Tsukuba published
Paper with a master's student as first author published
ResearchResearch themes
To handle complex problems with numerical analysis, the lab conducts research on building foundational analysis technologies and research on building analysis strategies for individual engineering problems. On the lab's website, its research projects are presented in two groups: foundational technology development and individual strategy development.
*Illustrative imageGeneralizing coupled analysis from a graph perspective
As analysis targets become more complex, the programs also become more complex, which has become a bottleneck for research on numerical analysis strategies. Using a graph-based perspective, the lab aims to generalize multiphysics analysis and data-distributed parallel analysis.
*Illustrative imageDimensionality reduction and intelligent numerical analysis
Numerical analysis is approaching the stage where it can replace optimization and decision-making by designers. Using data science techniques such as multivariate analysis, as well as machine learning, the lab works on dimensionality reduction and intelligent numerical analysis.
*Illustrative imageAdvancing the Galerkin method and developing new methods
The Galerkin method approximately solves differential equations by superposing a finite number of basis functions. The lab explores ways to build information and prior knowledge about each engineering or physics problem into these basis functions, so that strategies can be designed at the level of the analysis method itself.
*Illustrative imageAdvancing meshfree methods
Meshfree methods are a relatively new numerical analysis methodology that uses no grids or meshes, and they are an active area of research. The lab works on advancing this methodology, which includes the SPH and MPS methods, and on developing new analysis methods.
MembersFaculty
The members of the Mitsume Lab consist of faculty, secretaries, researchers, doctoral, master's, and undergraduate students, collaborators, and alumni.As of 2026
- Assistant ProfessorNaoto Mitsume
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Bubble-rising” Atif Masood (FetchCFD) / CC BY 4.0 (cropped)
- Generalizing coupled analysis from a graph perspective: “Finite element mesh” Bruno Sudret / CC BY 4.0 (cropped)
- Dimensionality reduction and intelligent numerical analysis: “Geodesic grid MPAS ocean simulation vorticity 4096x4096” Jinrong Xie / CC BY-SA 4.0 (cropped)
- Advancing the Galerkin method and developing new methods: “Triangulation with edge midpoints” Grawiuton / CC0 (cropped)
- Advancing meshfree methods: “Sibernetic - a software platform aimed at simulation of invertebrates biomechanics” A-palyanov / CC BY-SA 4.0 (cropped)
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(鈴木研悟研究室) ): “Electrical grid and power plants” Wikideas1 / CC0 (cropped) - Related lab (インフラ情報研究室): “Storm drain pushed up through road in the 2010 Canterbury earthquake” Martin Luff from Christchurch, New Zealand / CC BY-SA 2.0 (cropped)
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