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Hasegawa Lab
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The lab optimizes heat and flow through "inverse analysis," which works backward from desired results to find their causes.
AboutAbout the lab
Tackling thermo-fluid phenomena with "inverse analysis," which finds causes from results.
The Hasegawa Lab combines knowledge of fluid mechanics and optimal control to study how to control and predict heat and flow phenomena.
Normally, you decide a shape first and then calculate its performance, but the lab uses "inverse analysis," which works backward from the desired performance to find the optimal shape.
This finds the optimal shape far more efficiently than comparing many prototypes.
The lab also studies how to estimate flow conditions and the sources of pollutants from measurements taken by environmental sensors.
Key terms
- Inverse analysis
- A method that works backward through equations from a desired result to determine the cause or how a design should be
- Turbulence
- A flow in which eddies mix chaotically and the speed and direction of the flow keep changing irregularly
- Topology optimization
- A method that computationally searches for the shape with the best performance, even changing the number of holes and how parts are connected
NewsLab news
Research presentations and facility tours at the Open Campus on the Komaba Campus
A master's student received the Excellent Presentation Award from the Turbulence Control Research Meeting
A doctoral student received the Excellence Award in the Student Awards at the Young Researchers' Meeting of the Japanese Society for Biomedical Vascular Biology
A master's student received the Excellent Presentation Award from the Turbulence Control Research Meeting
A postdoctoral researcher received the Young Researcher Excellent Presentation Award at the Annual Meeting 2025 of the Japan Society of Fluid Mechanics
ResearchResearch themes
The lab combines knowledge of fluid mechanics and optimal control to study the control and prediction of thermo-fluid phenomena. Using "inverse analysis" (adjoint analysis), a mathematical method that finds causes from results, it aims to greatly speed up optimal design and experimental validation in thermo-fluid engineering.
*Illustrative imageOptimizing heat and mass transport in turbulence
To reduce drag and enhance heat transfer in turbulent flows, the lab studies algorithms for controlling turbulence using large-scale numerical simulations and optimal control theory.
*Illustrative imageOptimizing the shape of heat exchangers
To efficiently recover renewable energy and waste heat and convert them into more usable forms of energy, the lab works on shape optimization and topology optimization of heat exchangers, which transfer heat between fluids.
*Illustrative imageModeling the structure of capillary networks
Working with researchers in medicine, biology, and biomedical engineering, the lab studies how capillary networks that carry oxygen and nutrients form, aiming to clarify the principles by which optimal structures arise inside living organisms.
*Illustrative imageEstimating flow from a small number of sensors
The lab develops a framework that integrates information from sensors at a limited number of locations into numerical simulations, working toward systems for monitoring atmospheric and ocean environments.
MembersFaculty
The members of the Hasegawa Lab include faculty, postdoctoral researchers, project researchers, technical specialists, technical assistants, doctoral and master's students, and undergraduate students from Tokyo University of Science.As of 2026
- ProfessorYosuke HasegawaPublications ↗
- Project Assistant ProfessorLIU MingPublications ↗
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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: “A340 wake turbulence simulation” Deutsches Zentrum für Luft und Raumfahrt / CC BY 3.0 de (cropped)
- Optimizing heat and mass transport in turbulence: “Boundary-Layer-Transition” Herbert.Oertel / www.prof.oertel.de / CC BY-SA 3.0 (cropped)
- Optimizing the shape of heat exchangers: “Brazed Core” Jerod00 / CC BY-SA 3.0 (cropped)
- Modeling the structure of capillary networks: “Young zebrafish brain” B. Weinstein, National Institute of Child Health and Human Development, National Institutes of Health / Public domain (cropped)
- Estimating flow from a small number of sensors: “AWS(Automatic Weather station)” Delince / CC BY-SA 3.0 (cropped)
- Related lab (Micro/Nano Thermofluids Engineering Lab (Kinefuchi Lab)): “Macro view of water droplets on transparent surface” Dreamora96x / CC BY 4.0 (cropped)
- Related lab (Fluid Engineering Lab): “Bubble Ring in Sunlight” Joe Burch / CC BY-SA 3.0 (cropped)
- Related lab (Mouterde Lab): “Lupin with superhydrophobic water droplet” Rosser1954 / CC BY-SA 4.0 (cropped)
- Related lab (Oshima Lab): “PIV analysis of a stalled flat plate” Willa / CC BY-SA 3.0 (cropped)
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