Aerospace · Energy · AI for Fluid Physics

Aerial Innovation Mobility Lab

We combine massively parallel computing, LES/DNS turbulence simulation, actuator-line and immersed-boundary methods, and physics-informed AI to predict complex flow physics with speed and fidelity.

Explore Research Meet the Team

Research Scope

A research map for computational fluid dynamics

AIM Lab studies safe urban air mobility, renewable energy systems, supersonic and hypersonic flow, space vehicle aerodynamics and aerothermodynamics, rotorcraft noise, fluid-structure interaction, turbulence modeling, and AI-assisted flow prediction.

Urban Air Mobility Renewable Energy Space Vehicles Supersonic Flow Turbulence Modeling Physics-informed AI

In-house Code

CFD solvers built directly from numerical kernels

AIM Lab develops proprietary CFD solvers in C/C++ and CUDA, giving the group direct control over discretization, memory layout, parallel kernels, MPI scaling, and validation workflows for demanding flow simulations.

Explore Code

solver_kernel.cu

__global__ void updateFlux(Field q, Grid grid, Metrics metric) {
  int i = blockIdx.x * blockDim.x + threadIdx.x;
  int j = blockIdx.y * blockDim.y + threadIdx.y;
  if (!grid.interior(i, j)) return;

  State qc = q(i, j);
  Flux fx = reconstructHighOrder(q, metric, i, j, Direction::x);
  Flux fy = reconstructHighOrder(q, metric, i, j, Direction::y);

  q.residual(i, j) = divergence(fx, fy, metric(i, j));
  q.dt(i, j) = localTimeStep(qc, metric(i, j), grid.cfl);
}

Explore

Aerial Innovation Mobility Lab

A research map for computational fluid dynamics

CFD solvers built directly from numerical kernels

Navigate the lab

Research

Methods

In-house Code

Projects

Members

Publications

Teaching

Awards

Conferences

Visualization