SpaceX’s superpower is doing things slightly better, which yields substantial gains thanks to the large exponent on the rocket equation.
Agree with the rest of this comment, but I don’t think SpaceX’s success is due to the rocket equation. Their engine specific impulse is not better than state-of-the-art, and as a consequence their payload fraction to orbit isn’t better either. The success is driven by huge reductions in cost per ton at launch of each rocket.
That’s reasonable. I had in mind things like the thrust to weight ratios, the use of supercooled liquids, and methane as a propellant. In retrospect, I was confused.
You are right, that cost reduction is the super power. I believe that this is (mostly) a combination of standardization, volume, simplicity, CAD/simulation, and modern production processes.
(The goal of this comment is simply to stimulate more conversation in an area of interest to me)
I often find myself disagreeing with both self-declared SpaceX fanboys (or girls) and vehement SpaceX opposers, who I find more often than not just have varying levels of distaste for Elon Musk (some complaints here are valid I feel).
To get at the root of the idea, it seems that SpaceX hasn’t accomplished a miracle for space flight more so that they succeeded in developing some (difficult but not semi-impossible) engineering designs into usable rockets before going bankrupt, which is ‘the’ miracle.
Prior to the wave of new space companies starting in the late ’90s and early ’00s the old titans on industry (which are still around today and can still be characterized in the same way) were in the late stage of institutional lifetime with lots of bureaucratic bloat inhibiting launcher development. This is in part to to the fairly stagnant market and low demand, and part due to the bureaucratic nature of their customers (read military, NASA), with a simple dose of institutional age.
I would also note that the original authors seems to miss that there were dozens of other space startups at the same time as SpaceX some with even more radical ideas than SpaceX (and some with less) for changing the space industry. Almost none of them survived the transition from startup to profitability.
I would just like to add to your list of things SpaceX seemingly does better than it’s competition is control and guidance, the amount for work it took get those 1st stages to land on their own must’ve been massive. And also computationally impossible for a space endeavor of any size until the late 90’s (citation needed here and would love to hear from someone with experience).
And also computationally impossible for a space endeavor of any size until the late 90’s (citation needed here and would love to hear from someone with experience).
I looked into it and, yes, this looks basically correct with a caveat: it’s computationally very expensive to get those first stages to land on their own at a convenient, precisely chosen location. We’ve been doing propulsive landings for decades with e.g. the Apollo moon landers and the Viking Mars probes, the latter of which had to be fully autonomous because of speed-of-light delays. Landing a big long rocket is a bit harder because of its somewhat unwieldy shape, but inverted pendulum control problems are definitely not a new thing.
So where does it get computationally hard? There are two parts to it. The first part is computing a trajectory and a flight plan—when you should fire up the engines, which way you should be pointing them, what the aerodynamic control surfaces should be doing—which should get you to the desired landing location. This is a tricky optimization problem, with a bunch of annoyingly non-convex control constraints. The second hard part, and the reason you can’t just precompute the flight plan on a really big computer before launching the rocket, is that you need to adjust the plan in realtime. There will inevitably be unpredictable deviations from the original plan caused by things like wind or variation in atmospheric density. If you don’t compensate for them, those deviations will add up; the Curiosity Mars rover, for example, was a big improvement over its predecessors because its predicted landing zone was an ellipse that only measured 20 km by 7 km.
The algorithm (PDF) that I hear SpaceX is using does require some pretty serious processing power if you’re going to be recomputing your entire flight plan several times per second. A version suitable for realtime use wasn’t flight-tested until the early 2010s.
Agree with the rest of this comment, but I don’t think SpaceX’s success is due to the rocket equation. Their engine specific impulse is not better than state-of-the-art, and as a consequence their payload fraction to orbit isn’t better either. The success is driven by huge reductions in cost per ton at launch of each rocket.
That’s reasonable. I had in mind things like the thrust to weight ratios, the use of supercooled liquids, and methane as a propellant. In retrospect, I was confused.
You are right, that cost reduction is the super power. I believe that this is (mostly) a combination of standardization, volume, simplicity, CAD/simulation, and modern production processes.
(The goal of this comment is simply to stimulate more conversation in an area of interest to me) I often find myself disagreeing with both self-declared SpaceX fanboys (or girls) and vehement SpaceX opposers, who I find more often than not just have varying levels of distaste for Elon Musk (some complaints here are valid I feel). To get at the root of the idea, it seems that SpaceX hasn’t accomplished a miracle for space flight more so that they succeeded in developing some (difficult but not semi-impossible) engineering designs into usable rockets before going bankrupt, which is ‘the’ miracle. Prior to the wave of new space companies starting in the late ’90s and early ’00s the old titans on industry (which are still around today and can still be characterized in the same way) were in the late stage of institutional lifetime with lots of bureaucratic bloat inhibiting launcher development. This is in part to to the fairly stagnant market and low demand, and part due to the bureaucratic nature of their customers (read military, NASA), with a simple dose of institutional age. I would also note that the original authors seems to miss that there were dozens of other space startups at the same time as SpaceX some with even more radical ideas than SpaceX (and some with less) for changing the space industry. Almost none of them survived the transition from startup to profitability. I would just like to add to your list of things SpaceX seemingly does better than it’s competition is control and guidance, the amount for work it took get those 1st stages to land on their own must’ve been massive. And also computationally impossible for a space endeavor of any size until the late 90’s (citation needed here and would love to hear from someone with experience).
I looked into it and, yes, this looks basically correct with a caveat: it’s computationally very expensive to get those first stages to land on their own at a convenient, precisely chosen location. We’ve been doing propulsive landings for decades with e.g. the Apollo moon landers and the Viking Mars probes, the latter of which had to be fully autonomous because of speed-of-light delays. Landing a big long rocket is a bit harder because of its somewhat unwieldy shape, but inverted pendulum control problems are definitely not a new thing.
So where does it get computationally hard? There are two parts to it. The first part is computing a trajectory and a flight plan—when you should fire up the engines, which way you should be pointing them, what the aerodynamic control surfaces should be doing—which should get you to the desired landing location. This is a tricky optimization problem, with a bunch of annoyingly non-convex control constraints. The second hard part, and the reason you can’t just precompute the flight plan on a really big computer before launching the rocket, is that you need to adjust the plan in realtime. There will inevitably be unpredictable deviations from the original plan caused by things like wind or variation in atmospheric density. If you don’t compensate for them, those deviations will add up; the Curiosity Mars rover, for example, was a big improvement over its predecessors because its predicted landing zone was an ellipse that only measured 20 km by 7 km.
The algorithm (PDF) that I hear SpaceX is using does require some pretty serious processing power if you’re going to be recomputing your entire flight plan several times per second. A version suitable for realtime use wasn’t flight-tested until the early 2010s.