Drones and eVTOL aircraft continue to develop at a rapid pace, driven by both commercial ambitions and evolving operational needs. Over the past decade, a wide range of vehicle configurations have developed, from multirotors and tilt-rotors to lift-plus-cruise hybrids and tailsitters. Each approach offers different trade-offs in performance, manufacturability, and mission flexibility.
As these designs move closer to real-world operations, teams face increasing regulatory scrutiny, particularly around safety and airworthiness. At the same time, noise remains a critical concern. Even small acoustic differences can determine whether a vehicle gains public acceptance in urban environments.
Beneath these external pressures lies a fundamental engineering challenge. Every design change affects multiple, tightly coupled disciplines. Aerodynamic efficiency, acoustic behavior, and thermal performance must all be balanced carefully. A modification to the wing geometry, rotor placement, or tail configuration can cascade through the aircraft’s behavior, changing lift, noise profiles, cooling effectiveness, and stability. This interdependence makes the design process highly iterative and technically demanding, especially for teams exploring novel configurations.
One engineer navigating these challenges is John Lou, an aerospace engineer based in Munich, Germany. He is designing his own custom drone and building solutions to support other drone companies through advanced UAV prototyping.
John is now building a startup focused on supplying flying test platforms for the growing drone and UAV ecosystem in Europe. Rather than developing one vehicle for a single mission, his goal is to offer configurable, instrumented, and validated UAV platforms that other companies can use to prototype and test a range of ideas, including perception systems, control algorithms, swarming behaviors, or counter-unmanned aerial systems (C-UAS) applications.
“My vision is to support these customers by offering them a range of functional and proven flying test platforms with various configurations and customization options, helping them investigate ideas on proven and well-documented hardware platforms without having to hard-commit early on.”
While a variety of testing platforms will be offered from John’s startup in the future, one of the first he is designing is a tailsitter configuration drone.
The tailsitter configuration being designed and tested was inspired by current real-world scenarios and the need for new C-UAS designs. Tailsitters can take off and land vertically but transition to efficient wing-borne flight in cruise. This configuration offers several advantages:
However, it also introduces complex aerodynamic challenges, particularly during the transition between hover and cruise. Additionally, John is exploring tail designs for static stability and investigating thermal management strategies for electronic speed controllers (ESCs), which can run hot under sustained loads.
Flight testing has been one of the steps John has taken to continue refining the drone’s design, but this only provides a certain level of insight. Combined with Germany’s strict flight testing rules that limit how freely he can experiment; the process becomes even more challenging.
Knowing he needed a solution to shorten the process and accelerate design iterations, John turned to computational fluid dynamics (CFD) simulation.
While John has years of aerospace experience and aerodynamic intuition, he recognizes that he is no CFD expert, having only occasionally used CFD software in the past. Like many small-team engineers, he wears multiple hats and doesn’t have the luxury of deep specialization in every discipline.
“To be perfectly honest, I am not a CFD expert. Like many drone builders, I am a generalist. I have used CFD tools before and know what I want to achieve, and I have a sense for when results look right or wrong. But I definitely do not consider myself an expert.”
This played a key role in his selection process when evaluating the right software for the job. He needed a solution with a quick learning curve, high accuracy, and fast results.
For this, he turned to Flexcompute Flow360.
“A big selling point of Flow360 is how accessible it is. It also has a ‘modern’ touch, in terms of looks and functionality. Since Flow360 is completely cloud-based and browser-based, I only needed an internet connection.”
John noted that in the past, he often ran into installation and compatibility issues between his hardware and other CFD software. With Flow360, this was not a problem. Because the platform is fully browser-based, he was able to get up and running in less than five minutes.
Once inside the software, John quickly familiarized himself with the intuitive user interface and began exploring the range of capabilities available to him. He leaned on the thorough online documentation and highly experienced technical support team, stating:
“I found the learning curve to be quite easy, and the support engineer was very friendly and helpful. It was great to have technical support help me figure things out.”
After figuring out the basics and moving past some rookie mistakes, he was able to import his geometry and try out a few different mesh settings. Using Flow360’s default options, which automate most of the physics setup, he successfully ran his first simulation.
“It was quite exciting to see the results on my window for the first time – it was evidence that this workflow can work and that I now have access to a powerful tool.”
Simply put, John’s biggest goal is to verify the flight.
To make this a reality, John will continue expanding his use of Flow360. He says he feels he has only scratched the surface and will now begin using the Python API to customize automations, simulations, and physics models to improve his workflow and ultimately prototype even faster.
John’s story illustrates a broader shift in the aerospace landscape. Simulation is no longer exclusive to large companies with dedicated analysis teams. With modern, cloud-native CFD platforms like Flow360, technically savvy founders and small engineering teams can access high-fidelity simulation without steep infrastructure or learning burdens.
But don’t just take our word for it — take John’s:
“Flow360 has a very unique set of characteristics. Simulation speed, user-friendliness, and its Python API are very clear advantages. Being web-browser and cloud-based makes it very easy to set up. It stands out as a tool for use cases that require fast results yet high fidelity, but low resources for learning a new CFD tool.”
If you are interested in trying Flow360 for your drone development process, request a Free Trial of Flow360 today.