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Computational Mechanics Lab
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With mathematics and numerical computation as its two pillars, the lab uses computation to explore what cannot be seen inside.
AboutAbout the lab
Seeing the unseen through mathematics and computation
The Computational Mechanics Lab takes on a wide range of phenomena, as well as inverse problems that underpin safe, secure, and healthy social life, through computational mechanics built on mathematics and numerical computation as its two pillars.
Numerical simulation is a powerful way to understand mechanical phenomena, alongside theory and experiment.
The lab also studies simulation methods themselves, examining their reliability and efficiency.
Key terms
- Inverse problem
- A problem of estimating causes or internal states that cannot be seen directly from observable results
- Numerical analysis
- The field that studies methods for approximately solving mathematical problems on computers, and the correctness and accuracy of those methods
- Tomography
- A method of creating images of cross-sections inside an object from data measured from the outside
ResearchResearch themes
The lab takes on inverse problems and other challenges with an approach that combines mathematical analysis of the mathematical models describing phenomena with numerical computation.
*Illustrative imageCapturing phenomena with mathematics
The lab models and analyzes phenomena within mathematical frameworks such as differential equations, extracting the laws behind them.
*Illustrative imageReliable simulation
Numerical analysis sits at the intersection of mathematics and numerical computation. The lab mathematically analyzes computational methods (algorithms) and develops highly reliable simulation methods that make the most of both the results of mathematical analysis and the performance of computers.
*Illustrative imageInverse problems: investigating the unseen interior
Using mathematical methods, the lab investigates internal states that cannot be observed directly, as in non-destructive testing and medical imaging.
*Illustrative imageTomography with light and radiation
Results include numerical simulation of near-infrared light propagating through living tissue, optical tomography based on it, partial X-ray CT using complex analysis that reduces radiation exposure, and high-accuracy numerical integration methods on the sphere.
MembersFaculty
The lab's faculty are Professor Hiroshi Fujiwara and Assistant Professor Daisuke Kawagoe.
- ProfessorHiroshi Fujiwara
- Assistant ProfessorDaisuke Kawagoe
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: “Gradient important contrainte dans element fini” Cdang / CC BY-SA 3.0 (cropped)
- Capturing phenomena with mathematics: “Plot of solutions to Riccati equation” Astellar87 / CC BY-SA 4.0 (cropped)
- Reliable simulation: “Kraken Supercomputer ( )” Oak Ridge National Laboratory / CC BY 2.0 (cropped)
- Inverse problems: investigating the unseen interior: “ST- Hilton 2” Asticool / CC0 (cropped)
- Tomography with light and radiation: “Diffuse Optical Tomography - fiber-optic array - journal.pone.0045714.g001” Hajihashemi MR, Grobmyer SR, Al-Quran SZ, Jiang H (2012) / CC BY 2.5 (cropped)
- Related lab (Physical Statistics Lab): “Chaos Theory & Double Pendulum - 3” Cristian V. / CC BY-SA 4.0 (cropped)
- Related lab (Nonlinear Dynamics and Computational Physics Group): “Mandel zoom 11 satellite double spiral” Created by Wolfgang Beyer with the program Ultra Fractal 3. / CC BY-SA 3.0 (cropped)
- Related lab (Theoretical Neuroscience and Mathematics of Nonequilibrium Systems Group): “Neuron Heart” Piku4chemia / CC BY-SA 4.0 (cropped)
- Related lab (Mathematical Information Systems Lab): “Cosine Series Plus Noise” Fourier1789 / CC BY-SA 4.0 (cropped)
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