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Designing an efficient drone propeller involves far more than choosing the right diameter or number of blades. Small changes in blade geometry can affect thrust, drag, structural strength, flight time and payload capacity. With thousands of possible combinations, engineers often have to limit how many designs they simulate because conventional optimization can take days to produce a useful result.
Drone manufacturer Modovolo is using a quantum-inspired simulation platform to accelerate that process. The company has integrated BQP’s BQPhy software into its development workflow, allowing engineers to explore tens of thousands of potential propeller configurations using existing high-performance computers and GPUs.
Despite the name, the system does not require a quantum computer. The software’s QuantumNOW solver applies algorithms inspired by quantum computing techniques to conventional computing hardware. The goal is to search large engineering design spaces more efficiently, reducing the computing resources and time required to compare possible solutions.
For drone propellers, that design space can become particularly complicated. The shape, angle and structure of a blade continuously change from its center to its tip, and each modification affects both aerodynamic performance and mechanical stresses. Traditional optimization methods therefore require engineers to evaluate enormous numbers of interacting variables before arriving at a practical design.
The company had already been using genetic algorithms, which mimic natural selection by repeatedly generating and comparing different designs. However, the company says those calculations could take days on local servers and occasionally converge on a local minimum, which is a design that appears optimal compared with nearby alternatives but is not necessarily the best solution available across the entire design space.
According to Interesting Engineering, the software allows engineers to broaden that search, examining significantly more combinations before selecting candidates for manufacturing. The results have already been applied to the company’s patent-pending 3D-printed propellers, with the company reporting improvements in flight endurance and payload lift capacity. Specific performance figures were not disclosed.
The technology also has potential implications for defense. Military UAV developers face constant pressure to increase endurance, payload capacity and efficiency while keeping platforms inexpensive enough for large-scale deployment. Faster simulation could allow engineers to optimize propellers, airframes and other components more rapidly, shortening the cycle between identifying an operational requirement and producing improved hardware.
More broadly, quantum-inspired engineering demonstrates how some concepts associated with quantum computing can provide practical benefits without waiting for mature quantum hardware. Because the software runs on computing infrastructure already available to manufacturers, it can be incorporated into existing development pipelines.
For drone development, the immediate advantage is straightforward: engineers can examine far more possibilities before committing a design to hardware. As UAVs become increasingly specialized, tools capable of rapidly exploring thousands of configurations could help manufacturers improve performance without proportionally increasing development time and cost.
