Candidly, while I understand the need for some amount of redundancy, I'm curious what this level of redundancy adds in terms of complexity to the system of a whole and whether or not that complexity-add almost outweighs the higher redundancy. I'm sure NASA has calculated the trade off, but I'd be curious to see the thoughts behind that.
I feel in a similar vein when learning of certain aircraft accidents over the years, where it feels like the redundancy of certain systems and the complexity it adds has been the indirect cause of accidents instead of preventing them. I suppose there's not really a way to quantify the accidents that it's prevent to be able to compare them directly.
> Orion utilizes two Vehicle Management Computers, each containing two Flight Control Modules, for a total of four FCMs. But the redundancy goes even deeper: each FCM consists of a self-checking pair of processors.
Who sits down and determines that 8 is the correct number? Why not 4? Or 2? Or 16 or 32?
They probably set an acceptable total loss rate for the mission and worked backwards to determine how many replicas of each system they need to achieve that while minimizing total cost/weight.
So the answer is "some engineers sat down after talking to management".
The fault tolerance is mostly focused on background radiation flipping bits. We've got half a century of data on the frequency of those upsets and the extent to which they're correlated under different space conditions for that, not to mention the ability to irradiate prototypes of the flight computer with representative amounts of shielding in ground based facilities...
For issues that have never occurred before, probabilities are the wrong tool. The right thing to do is list all the behaviour the vehicle must never exhibit and think of ways it still might, despite all redundancies -- maybe even despite every single component working as intended.
Lots of mission failures in history were caused by unexpected interactions between fully functional components. Probabilities of failures don't help with that.
> The self-checking pairs ensure that if a CPU performs an erroneous calculation due to a radiation event, the error is detected immediately and the system responds.
How does a pair determine which of the pair did the calculation correctly?
It doesn't have to. It raises an error that the system can detect and take action on. Usually that'll be some combination of interrupt/reset and an external pin to let the rest of the system know what's happened.
Not just CPUs, they run a whole different (but also simpler) fallback program in case the main computers fail. I think they were more worried about programming errors but this should avoid all shared failures between the main computers (be it programming or hardware).
Even if different teams write software in different languages, they end up creating very similar bugs because the bugs crop up in the complexities of the domain and insufficiencies of the specification.
N-version programming doesn't work as well as you think. See Knight and Leveson (1986).
(N-version programming does guard against "random" errors like typos or accidentally swapping parameters to a subroutine call. But so does a good test suite and a powerful compiler.)
I'm a big fan of Dissimilar Redundancies (but didn't know that was the term until today) for building system software.
Build for various Linux distros, and some of the BSDs. You'll encounter weird compile errors or edge cases that will pop up. Often times I've found that these will expose undefined behaviour or incorrect assumptions that you wouldn't notice if you were building for a single platform.
When the Apollo astronauts learned that they might need to repair the computer if it breaks they joked they might as well learn brain surgery if they end up needing that too.
(This was when they planned on sending a modular computer with them. In the end they settled for sending up a fully assembled spare computer instead, which made replacement easier.)
I feel in a similar vein when learning of certain aircraft accidents over the years, where it feels like the redundancy of certain systems and the complexity it adds has been the indirect cause of accidents instead of preventing them. I suppose there's not really a way to quantify the accidents that it's prevent to be able to compare them directly.
Who sits down and determines that 8 is the correct number? Why not 4? Or 2? Or 16 or 32?
So the answer is "some engineers sat down after talking to management".
Lots of mission failures in history were caused by unexpected interactions between fully functional components. Probabilities of failures don't help with that.
https://en.wikipedia.org/wiki/Lockstep_(computing)
Example: https://www.st.com/resource/en/datasheet/spc574k72e5.pdf
> each FCM consists of a self-checking pair of processors.
How does a pair determine which of the pair did the calculation correctly?
There's also space systems that use 3 processors and a majority vote for the correct output, but that's different.
Even if different teams write software in different languages, they end up creating very similar bugs because the bugs crop up in the complexities of the domain and insufficiencies of the specification.
N-version programming doesn't work as well as you think. See Knight and Leveson (1986).
(N-version programming does guard against "random" errors like typos or accidentally swapping parameters to a subroutine call. But so does a good test suite and a powerful compiler.)
Build for various Linux distros, and some of the BSDs. You'll encounter weird compile errors or edge cases that will pop up. Often times I've found that these will expose undefined behaviour or incorrect assumptions that you wouldn't notice if you were building for a single platform.
I other words, how over engineered is it.
(This was when they planned on sending a modular computer with them. In the end they settled for sending up a fully assembled spare computer instead, which made replacement easier.)