Skip to content
DIMECHAIN

Industry

Aerospace, Simulation & Engineering

Flow, turbulence and high-speed simulation problems at the edge of what current solvers reach.

Problems we address

  • Turbulence modelling where resolution and runtime trade against each other badly
  • Hypersonic and shock regimes that classical solvers handle only at great expense
  • Design iterations gated by simulation turnaround rather than by engineering judgement
  • Materials performance questions needing both simulation and physical test data to answer

How we approach it

Related research

Maturity labels are not decoration. Most of this is at concept stage.

Materials & aerospace
Maturity: concept

High-Entropy Alloys for Aerospace

Simulation of alloy composition, phase stability, defects and aerospace material performance.

Materials & aerospace
Maturity: concept

Programmable Matter & Smart Polymers

Molecular self-assembly, phase transitions and stimuli-responsive polymer design.

Materials & aerospace
Maturity: concept

Quantum-Encrypted Materials Databases

Consortium members want to pool materials data without exposing their own pipeline, and trust-plus-a-contract does not scale across parties who are collaborators and competitors at once. We are looking at quantum-resistant schemes for confidentiality that has to outlast current cryptography. Stated plainly: most of this is a governance problem wearing a cryptography costume, and we would want to argue the answer is boring standard cryptography before agreeing that it is not.

Materials & aerospace
Maturity: concept

Quantum Simulations for Molecular Design

Electronic-structure and molecular-interaction simulation for candidate design and screening.

Materials & aerospace
Maturity: concept

Hypersonic Aerodynamics

Shock, thermal and high-speed flow simulation and geometry optimisation. The live route is misspelled “ypersonic”.

Materials & aerospace
Maturity: in development

Quantum-Enhanced Turbulence Modeling

Turbulence is the canonical unsolved problem of classical physics, and every practical method models the small scales rather than resolving them — the modelled part is where the error lives. We are testing whether quantum representations can carry sub-grid correlation directly rather than approximating its effect. The bar is a canonical benchmark flow first, then a Reynolds number where classical models are known to degrade. We are at the first, not the second.

Working on something in aerospace, simulation & engineering?