> ## Documentation Index
> Fetch the complete documentation index at: https://dynex.mintlify.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Automotive & Aerospace

> Quantum computing applications in vehicle design, traffic optimization, and aerospace engineering

# Automotive & Aerospace

Quantum computing addresses engineering optimization challenges in aerodynamics, fleet management, and satellite systems — problems where the search space is too large for classical solvers.

## Computational Fluid Dynamics (Q-CFD)

Simulating fluid flow around vehicles is computationally intensive. Quantum CFD accelerates aerodynamics simulations, enabling engineers to rapidly analyze and optimize vehicle design for drag reduction and fuel efficiency.

<Card title="Quantum Computation of Fluid Dynamics" icon="wind" href="https://github.com/dynexcoin/QCFD">
  Quantum-accelerated CFD for vehicle aerodynamics and turbulence modeling. Significant speedup over classical numerical methods.
</Card>

**Scientific background:** Bharadwaj & Sreenivasan. *An Introduction to Algorithms in Quantum Computation of Fluid Dynamics.* STO Educational Notes, 2022.

## Traffic Optimization

Urban traffic flow optimization modeled as a constrained quadratic problem. Minimizes congestion and travel time across road networks by finding optimal signal timing and routing assignments.

<Card title="Traffic Flow Optimization" icon="traffic-light" href="https://github.com/Dynex-Development/awesome-dynex/blob/main/optimization/TrafficOptimizationCQMBUG.ipynb">
  CQM-based traffic optimization. Reduces average travel time and network congestion through quantum-optimized signal coordination.
</Card>

## EV Charging Station Placement

Optimal placement of electric vehicle charging infrastructure using quantum annealing. Maximizes coverage and accessibility while minimizing installation costs under geographic and demand constraints.

<Card title="Placement of EV Charging Stations" icon="bolt" href="https://github.com/Dynex-Development/awesome-dynex/blob/main/misc/example_placement_of_charging_stations.ipynb">
  User- and destination-based location model for EV charging stations, formulated as a QUBO.
</Card>

**Scientific background:** Pagany et al. *Electric Charging Demand Location Model.* Sustainability, 2019, 11(8), 2301.

## Aircraft Loading Optimization

Optimal cargo and passenger load distribution for aircraft, ensuring weight balance constraints while maximizing capacity utilization. Based on the Airbus Quantum Computing Challenge.

<Card title="Aircraft Loading Optimization" icon="plane" href="https://github.com/Dynex-Development/awesome-dynex/blob/main/optimization/aircraft-loading-optim.ipynb">
  Airbus QCC Problem n°5: quantum optimization of aircraft weight and balance under structural and safety constraints.
</Card>

## Satellite Constellation Scheduling

Optimal scheduling of satellite observation tasks across a constellation, formulated as a weighted k-clique problem. Maximizes coverage and minimizes scheduling conflicts.

<Card title="Quantum Satellite Positioning" icon="satellite" href="https://github.com/Dynex-Development/awesome-dynex/blob/main/advanced_applications/QuantumSatellite.ipynb">
  Heterogeneous quantum computing for satellite constellation optimization. Solves the weighted K-Clique problem for task scheduling.
</Card>

**Scientific background:** Bass et al. *Heterogeneous Quantum Computing for Satellite Constellation Optimization.* Quantum Sci. Technol. 3, 024010 (2018).