Four Quantum Computing Aviation Applications Being Researched by Airbus

May 20, 2024

Airbus recently published an update on some of the latest research and development that the Toulouse, France-based airplane maker has been exploring around the use of quantum computing for aviation design and operational applications. Take a look at the roundup below.

Computational Fluid Dynamics for Aircraft Design

The first port of call when designing a new aircraft is often computational fluid dynamics, or CFD. This sophisticated digital simulation of airflow around an airframe informs its shape and aerodynamic efficiency. Today, CFD is performed by energy-intensive, high-performance computers (HPC) and it has become a bottleneck in the aircraft design cycle as HPCs reach their maximum processing power.

Airbus has signed a partnership with two leading European Research facilities, ONERA (French Aerospace Research Center) and DLR (German Aerospace Center) during an official ceremony at Paris Air Show.

Quantum computing is able to operate on a far larger canvas, or mesh, permitting CFD calculations to be performed at an exponentially higher scale. It has the potential to break the design bottleneck for future aircraft.

CFD is an area under study in the Quantum Mobility Quest and through EQUALITY, a European consortium which counts Airbus as a member. The consortium is dedicated to developing quantum algorithms in order to solve a set of ‘paradigmatic’ industry problems.

As these examples show, quantum computing clearly has the potential to support aviation on its decarbonization journey.

Aircraft Fuel Cell Simulation

Hydrogen-powered aircraft produce no carbon dioxide or nitrous oxide emissions during flight. They release only water vapor into the atmosphere.

There are two options for designing hydrogen propulsion systems: burning the gas directly in a turbine engine; or installing fuel cells which use hydrogen to create electricity.

Airbus has joined forces with the automotive sector to advance fuel cell development for aeronautic applications. However, the cells must be lightweight as well as powerful enough to get a plane off the ground.

This combination relies on some complex chemistry. Electrolysis requires a catalyst to get going. Platinum is particularly suitable for this purpose, yet relatively expensive. The alternative is to create alloys – platinum with cobalt or nickel, for example – which also show a higher beginning-of-life performance than pure platinum. However, lab testing these alloys can be an expensive task.

Instead, alongside colleagues at BMW Group, Airbus researchers have shown for the first time that quantum computing can perform atomic-level reaction modelling. Harnessing quantum’s exponential power that is beyond the reach of today’s computers, engineers can model the relative catalytic behavior of each alloy. Their observations contribute to propulsion and design choices that will one day have a significant, favorable impact on aerospace’s carbon footprint.

Trajectory Optimization

In the future, quantum algorithms could help optimize an aircraft’s trajectory in real time by taking air traffic restrictions and weather patterns into account. This has obvious safety, economic and ecological benefits.

Flights operate in a dynamic environment affected by an intractably large number of variables, especially during climb-out. The speed and accuracy of calculations are key. Quantum algorithms may be able to outperform current high-performance computers for each.

To this end, in 2023 Airbus’ Silicon Valley innovation center Acubed carried out a study into quantum trajectory optimization.

Air Cargo Loading

Half of global airfreight travels onboard passenger flights. Filling cargo containers and then fitting them into the hold of a jetliner is like a giant game of Tetris. Space is at a premium, and the loading of each container must be just so. If the overall center of gravity in the hold is off, the aircraft will burn more fuel. If the cargo is stacked too far to the left, the left-hand engine has to work harder, consuming even more fuel.

Like trajectory optimization, cargo loading is fraught with constraints. Quantum computers leverage the so-called ‘knapsack problem’ to calculate an optimum solution for loading packages into cargo containers, and the containers into the hold. In 2022, Airbus performed a use case demonstrator using IonQ’s quantum computer.

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