My topics in Aerospace Engineering
Aerospace engineering is a beast. Maybe the last remaining engineering discipline that still embraces so many massive domains: aerodynamics, astrodynamics, GNC, propulsion and all the advanced engineering mathematics. It’s overwhelming. The solution is to find the topics that suits you and gives enough happiness, success and passion to keep you going. I think there is no other way to achieve something meaningful in this field. After almost a year of reading and exploring aerospace engineering as a field of science, I believe I have found my topics.
Aerodynamics, astrodynamics and GNC. When I define the problem spaces they cover, I arrive at: - atmospheric re-entry, - satellites / megaconstellations in Low Planetary Orbit (or around small bodies), - spacecraft landing.
Besides these serious, industry-relevant topics, my inner child still dreams about:
- modelling any phenomenon mathematically — even chaotic ones like human communication — and not to mention the elegant (and probably impossible) concept of psychohistory,
- and not only epic, but also tactically and strategically sound sound dogfights and battles in space.
I can have dreams, can’t I?
Aerodynamics
This is where it all began. As a young teenager I devoured a monthly aviation/military tech magazine called Top Gun. There was an article about the development of the F-18 Hornet and the fact that its wing was designed using mathematical models. I still clearly remember asking myself: “How?” That same question has haunted me — in different forms — for the past 30 years. When I learned software engineering, one of my recurring (somewhat naive but infinitely motivating) questions was: how much compute (code, CPU, memory…) is actually needed to model airflow and turbulence? Into this fertile mental soil landed the Theodore von Kármán biography. Unfortunately it doesn’t go deep into the mathematical modelling — but it remains the book I open when I need a boost.
Last year I read Boyd — the book about Colonel John Boyd, father of the OODA loop and spiritual father of the F-15/16/18 family — and his energy-maneuverability theory based on thermodynamics, which became foundational for modern dogfighting. For me, this is where mechanical sympathy builds a bridge between the physical world and numbers. Pure, hardcore engineering. It genuinely gives me chills.
Another reason aerodynamics keeps teasing me: it is widely considered one of the most mathematically and computationally demanding fields in engineering.
The daydreamer in me still wants a hobby project: building my personal “dream fighter” concept, or running local CFD simulations on an F-15/F-16 model I own just to deepen that mechanical sympathy. And spin up the beauty in DCS and just fly.
Astrodynamics
For me, the most captivating scenes in any sci-fi movie are always the ones showing flight in space. How does it actually work? What are the real physical constraints? I want enough knowledge to imagine why the hull starts rattling during landing — and to feel it. Yes — mechanical sympathy again.
Then two experiences hit me almost simultaneously:
- The Expanse miniseries landed with its high-fidelity space operations
- Elite: Dangerous was released with its “Flight Assist Off” mode that actually simulates real orbital & attitude physics
I didn’t realise it at the time, but my brain was screaming for answers. That hunger eventually crystallised into the romantic (and very difficult) dream of dogfight in space.
From a serious industry perspective, astrodynamics is simply “how do we actually get there?” — which is fascinating in itself, even though it imposes very strict limits on the space opera dreams in my head.
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GNC
Looks like the most boring of the three at first glance — yet in reality it sits at the very heart of everything. It is the essence of engineering mathematics: control. “What input must I give to achieve this desired output?” It’s about feedback loops — and even though it may sound dry, it is an extraordinarily beautiful field.
I’ve mentioned mechanical sympathy several times already. GNC is mechanical sympathy taken to its highest level. It demands that you understand a system so intimately that you can identify the smallest, most efficient input needed to make it behave exactly as desired. In other words: you become the Master of Puppets, the Man Behind the Curtain — except there is no evil scheme, only elegant physics.
This is where mathematics steps in and whispers: Dynamical Systems. Control is about (a) cleverly exploiting already-known stable points and (b) discovering and stabilising new ones inside chaotic systems — building architecture out of chaos. This is why I want to be able to model anything mathematically.
This is my master plan.
All three topics will get their own, more detailed blog entries in the future. For that clarification process I plan to use AI tools heavily — they excel at summarising enormous amounts of literature and giving useful pointers. The result will be topic overviews + curated lists of the most important/relevant papers and textbooks in each sub-segment.