Research
Advancing computational science
Tanuki is built on peer-reviewed research in computational mechanics, scientific computing, and machine learning. We develop methods that are rigorous enough for academia and accessible enough for industry.
01
AI-driven geometry generation
Describe a component in natural language and receive simulation-ready 3D CAD geometry. Fully parametric, watertight, and mesh-ready.
- Programmatic solid modelling from conversational input
- Iterative refinement through follow-up instructions
- Automatic mesh generation with adaptive resolution
- Export to standard engineering formats
02
High-fidelity simulation
Research-grade finite-element solvers handle structural, thermal, and fluid problems with the rigour expected in academic and industrial settings.
- Linear and nonlinear elasticity
- Heat conduction and convection
- Incompressible flow and shallow water equations
- Modal analysis and eigenvalue problems
03
Machine learning for physics
Hybrid approaches that combine data-driven models with physical laws, accelerating solvers, learning constitutive relations, and enabling surrogate modelling.
- Physics-informed neural network integration
- Surrogate model training from simulation data
- Adjoint-based sensitivity and shape optimisation
- Automated model selection and hyperparameter tuning
04
Geospatial modelling
Build ocean meshes, terrain models, and geographic simulation domains from a place name. Real-world data is incorporated automatically.
- Coastline extraction and domain construction
- Seafloor bathymetry integration
- Satellite-derived ice edge boundaries
- Multi-resolution unstructured meshing for large domains
Academic collaborations
Imperial College London
Finite-element methods for fracture mechanics and deformation modelling, and AI for scientific computing through the I-X Centre.
University College London
Geomechanics, fault mechanics, and fluid–rock interaction research applied to subsurface and environmental systems.
University of Leicester
PDE-constrained shape optimisation and inverse-problem methodologies for geoscience applications.
University of Cambridge
Collaboration on the ARIA Re-thickening Arctic Sea Ice programme, applying computational mechanics to climate intervention research.
If you are a researcher or institution interested in collaborating with Tanuki, we would love to hear from you.
Get in touch