Aether Simulation.
One model that forward-rolls every physics.
Simulation is the act Aether was trained for: it rolls a physical system forward in time — CFD, FEA, electromagnetics, thermal, acoustics, quantum chemistry and molecular dynamics — coupled on one mesh, validated against measured reality, from a real-time surrogate to first-principles DNS. Ten physics domains under one model, with the uncertainty on every result and the setup automated.
- Domains
- 10 physics
- Coupling
- Multiphysics, one mesh
- Validation
- Measured reality
- Tiers
- Surrogate → DNS
Every physics, under one model.
The incumbent CAE stack is a dozen seat-licensed solvers that each speak one physics and a different file format. Aether Simulation is one model and one mesh — built so the flow that loads a structure and the heat that warps it are solved together, not imported between two tools with a fudge factor in the middle.
Computational fluid dynamics
Incompressible and compressible flow, turbulence, multiphase and reacting flow — steady and transient, validated against wind-tunnel and rig data.
Structural & FEA
Linear and nonlinear statics, dynamics, contact, plasticity and fatigue — the load path resolved, not approximated.
Electromagnetics
Full-wave, quasi-static and high-frequency EM for antennas, signal integrity, motors and EMC.
Thermal & heat transfer
Conduction, convection and radiation, steady and transient — coupled to flow and structure where they meet.
Multiphysics coupling
Fluid-structure, electro-thermal, thermo-mechanical and beyond — solved together on one mesh, where single-physics tools silently drop the interaction that matters.
Acoustics & vibration
Modal, harmonic and aeroacoustic analysis for NVH, sound radiation and resonance.
Quantum chemistry / DFT
First-principles electronic structure for energies, forces and properties across the periodic table.
Molecular dynamics
Classical and ML-interatomic-potential MD for materials, fluids and soft matter at scale.
Mesh & geometry
Automatic meshing, defeaturing and adaptive refinement from CAD — the setup that usually eats the schedule, automated.
Solver autoconfiguration
Natural language to a configured case: solver, boundary conditions, time-step and convergence chosen and justified.
UQ & validation
Calibrated uncertainty on every result, with residuals reported against measured data — a number you can sign off, or an honest “not yet”.
Optimization & inverse
Latin-hypercube DOE, sensitivity, multi-objective optimization and inverse design driven by the same solver that validates the answer.
Every solve knows how good it is.
A surrogate is never presented as high-fidelity, and a simulation is never presented as measurement. The four-tier ladder makes the fidelity explicit, and every result carries its calibrated uncertainty.
Reduced-order surrogate
Distilled, real-time models for screening, control and many-query design — milliseconds, always labelled with their accuracy bound.
Real-time simulation
Interactive multiphysics at the fidelity most engineering iteration lives in — fast enough to sit in the loop.
High-fidelity
Full-resolution coupled solves validated against measured data — the tier behind a decision you have to be right about.
First-principles / DNS (escalation)
Direct numerical simulation, DFT and detailed multiphysics. A regime the model cannot yet resolve returns the engine it requires — never a fabricated field.
Six engineering worlds, one solver.
Not a tool per domain — one model whose physics changes per problem but whose contract does not.
External aero, crash, NVH, thermal and coupled FSI — the cases that used to need three solvers and an import in between.
Electro-thermal, signal integrity and EMC on the same model that runs the chip flow.
Combustion, multiphase flow, heat exchangers and structural integrity for power and process plant.
DFT and MD for properties, reactions and transport, closing the loop with the materials discipline.
Sound radiation, cabin noise and resonance, coupled to the flow and structure that drive them.
Hemodynamics, soft-tissue mechanics and device interaction with deformables.
Coupled, and measured.
The difference between a simulation that ships and one that demos is whether it's coupled and validated. We report what was solved and what was measured.
Coupled on one mesh, not stitched across tools
Surrogate → real-time → high-fidelity → DNS
Calibrated uncertainty on every result
Validated against wind-tunnel, rig and counters
Setup, mesh and solver chosen by the model
Ten physics domains, one model
Every solver, one model.
The incumbents each own a physics and a file format, coupled across tools with a fudge factor in the middle. Aether solves them together on one mesh, with calibrated uncertainty.
Engineering cycles, compressed.
What compounds is solves per quarter, not any single run being faster.
CFD, FEA, EM, thermal, acoustics, quantum chemistry, MD and their couplings — one model instead of a shelf of seat-licensed solvers.
Surrogate → real-time → high-fidelity → first-principles. Every solve carries its tier, provenance and calibrated uncertainty.
Validated against wind-tunnel, rig and field data — the difference between a simulation you trust and a pretty contour plot.
“We're not buying a tool that competes with the incumbent. We're buying a tool that makes the question of renewing irrelevant.”
An AI that runs the analysis, not a solver seat.
It reads the problem, sets it up, picks fidelity, validates against data, and writes the rationale — for an expert audience.
- 01
Reads the problem
Ingests the geometry, the loads and the question, and decomposes it into a typed study — physics, couplings and acceptance criteria — before any solve runs.
- 02
Sets it up
Meshes, picks the solver, boundary conditions and time-step, and justifies each choice — the setup that usually eats the schedule.
- 03
Picks the right tier
Knows when a real-time surrogate suffices and when a decision needs high-fidelity or DNS — by the confidence the conclusion requires.
- 04
Validates against data
Reports residuals against measured reality and calibrated uncertainty; out-of-domain inputs are flagged, not silently extrapolated.
- 05
Writes the rationale
Each result ships with its fidelity tier, the assumptions, the margins and the model-version hash — an engineer can sign it off.
- 06
Closes the loop
Measured outcomes return into the model, so the simulation that designed a part gets better at predicting the next one.
Simulation that gets truer with every test.
Each measured result returns into the model, so the solver that designed a part this quarter predicts it better the next — and the gap between simulation and the rig closes.
Good to know.
Those are single-physics or loosely-coupled solvers with per-domain seat licences and inter-tool imports. Aether forward-rolls every physics on one model and one mesh, validated against measured reality, from real-time surrogate to first-principles.
High-fidelity solves are validated against wind-tunnel, rig and field data with calibrated uncertainty and reported residuals. When the model can't resolve a regime, it says so and names the engine required — it never fabricates a field.
Yes — fluid-structure, electro-thermal, thermo-mechanical and more solve together on one mesh, so the cross-domain interaction that drives real failures isn't dropped.
Yes — like the rest of Aether it deploys managed, in your VPC, on-prem or fully air-gapped, on Aether Cloud's compute.
Run the physics on one model.
Aether forward-rolls every physics — coupled, validated and uncertainty-quantified — from a real-time surrogate to first-principles. Request access to deploy it behind your firewall, or see the engineering discipline it powers.
Simulation is the act under every discipline — one model, every physics.