SpaceX update: The engine did not explode
spacex.com
spacex.com
No, it just became a "Falcon 8" while enroute.
All joking aside, as a former NASA Space Shuttle engineer I'm very impressed by this private-enterprise venture into heavy-lift launch services. People have often speculated about how much cheaper launch services might be if they were in the private sector -- now we can find out. The preliminary signs are very good.
I read your IAmA where you had a reply to a message, now deleted, in which you must have been asked about aerial circumnavigation. You mentioned that you'd use a solar balloon, and that you merely would have to have a strategy for darkness.
I've spent a fair amount of time thinking about this, and it may interest you to know that:
Water vapor has both a lower molar density than air The phase transition of water vapor gives more than enough energy to heat up more than the equivalent volume of air to displace the reduced volume of water vapor turning to liquid.
So, a possible strategy for darkness is to have a two bladdered balloon, one with water vapor + air, one with just air. Then, when the water vapor condenses, transfer the heat to air sourced from outside the balloon via a counterflow heat exchanger. Put that warmed air in the air bladder. You won't stay at precisely the same height, but you will retain volume and you can stay buoyant.
Many things work well when your thermal energy storage is positively buoyant.
Regards,
Come visit the next time you're free around Berkeley or Oakland.
The advantage is that the method doesn't just throw away the helium, it recycles it, but the recycling activity require a lot of power. And it's way complicated compared to your method.
I intend to build it at some point. (There's a long list, obviously, but this is a keeper) so if you're ever interested in it, let's chat. :-)
http://en.wikipedia.org/wiki/Paul_Lutus
Some key parts: "Lutus designed electronics for the NASA Space Shuttle and created a mathematical model of the solar system that was used by the Jet Propulsion Laboratory during the Viking Mars mission" and then "... he started writing computer programs on his first personal computer, an Apple II. In the 80s, he would eventually program Apple Writer,"
I also recommend his book about sailing around the world "Confessions of a Long-Distance Sailor"!
Yes, the Joshua Slocum book, a classic well worth reading.
My book isn't in the same league, but it's developed a loyal following over the years -- it's online and free:
My all-time favorite sailing book quote, from a book titled "Never Again", about a sail in the terrifying "South 40s" near Antarctica: "After the mast blew off, the boat become much more stable." :)
"Cape Horn: One Man's Dream, One Woman's Nightmare"
http://www.amazon.com/Cape-Horn-Dream-Womans-Nightmare/dp/09...
But I have to say, I've been telling that story for 25 years now, and honestly, I can't be sure the above is the title that contains the quote.
stallker 4 hours ago | link [dead]
Why 'f * ing'? (Sorry, I'm italian... of course I know the meaning of the word, but I would like to know why do you use it for Paul Lutus, TIA)
I'm not the OP, but in some circles the four-letter expletive is used to emphasize the importance or intensity of something. E.g. "William [freaking] Shatner" means the original, unique, William Shatner, not some other William Shatner. "So [freaking] good!" means extremely good.
I feel like there was another word in the phrase as used by the engineer I heard it from, but I can't for the life of me remember what it was.
It really means "The plane crashed because of pilot error, not because the pilot lost control due to a mechanical fault or extreme weather."
Usually, but not always. The "controlled flight" part means the airplane wasn't either broken or outside its normal control envelope. The implication is that the crash resulted from something other than an inability to control the airplane. The usual assumption at that point is pilot error, but there are other possibilities -- malfunctioning navaids, bad charts, bad instructions from the ground such as incorrect headings or altimeter settings.
Once an airliner pilot asked for clearance into La Guardia in NYC involving a path that led across the downtown area after dark. He was given a flight level in meters but understood his assigned altitude to be in feet. He was flying between the buildings when the ATC and pilot sorted out their unit-of-measurement difficulties. The only reason ATC knew something was wrong was because the aircraft had an altitude-reporting transponder, or we might have had a 9/11 level catastrophe much earlier.
On that topic, in 1945 a B-25 flew into the Empire State Building in fog, something most people have long since forgotten:
http://en.wikipedia.org/wiki/B-25_Empire_State_Building_cras...
My favorite air-crash story with interesting pilot-comprehension issues was this ferry flight with only crew onboard:
http://en.wikipedia.org/wiki/Northwest_Airlines_Flight_6231
To summarize, the aircraft model with which the crew were most familiar had a pitot heat switch that was activated by an upward movement (the ergonomic standard direction), but this aircraft required a downward movement (or the reverse, I forget which it was, but they were reversed). This meant they went through the checkist and set all the controls, but this control was set wrong through no fault of the pilots (more the fault of the manufacturer). Result: no pitot heat in winter conditions.
Next, during the after dark flight, the pitot tube froze solid in icing conditions, after which the airspeed indication became an altitude indication, at a time when the aircraft was in a climb. This made the pilots think they were overspeeding the aircraft, and they responded by pulling back on the controls. The stick shaker worked as it should have (warning of a speed approaching a stall), But the pilots interpreted this as ... get this ... mach buffet. The pitot system kept delivering seemingly higher and higher airspeeds as they climbed and (in reality) approached stall speed.
The aircraft finally stalled fully, deeply, and unrecoverably. For those who don't know this, you must not ever stall an airliner, because they are perfectly balanced front to back, to save fuel, but the side effect is if the aircraft is stalled, it cannot be recovered and will flat-spin right into the ground.
Small private planes will typically nose down in a stall, often recovering right away for an inexperienced pilot, but airliners have different priorities, one of which is economical operation. An economical airplane cannot afford to have a constant air pressure on the top of the elevator control surfaces, so this is designed out. But in trade, you must not ever stall the aircraft or you will lose it.
In the final analysis, multiple factors were involved (as usual), but the fact that the pitot heater switch had an activation direction opposite the ergonomic standard, all by itself could have prevented the crash.
It's my favorite story about the value of adopting consistent ergonomic standards -- to increase a quantity or activate something, controls should move up, or to the right, or clockwise. To deactivate or decrease a quantity, the reverse. How hard is that?
For those reading this who aren't pilots: pilots aren't ghouls, we like reading accident reports because every report teaches us something that we might use to save ourselves and/or our passengers if we encounter the same conditions.
DUDE, give them a break.....
read next line
Oh. OH! I have no business commenting on this subject.
Watching this private space stuff manifest is absolutely thrilling. I was tangentially involved in things way back in the early 90's, when the private space geeks were regarded as crackpots by the mainstream aerospace community, if indeed they were acknowledged at all. They certainly didn't have any money (aside from odd forays such as Andrew Beal's[2] and Gary Hudson's[3] abortive adventures), and often did come across as crackpots, but for the life of me it seemed like they had a valid point. To see those sort of folks finally succeed is just infinitely thrilling.
[1] http://news.ycombinator.com/item?id=4625221
The fact that an engine failed, should be viewed as a success, as it allowed for the validation of the fault tolerant design.
It's not that one should never have failures, what matters is how they mitigate and adapt, in order to complete the mission.
Just a heads up - I tried to send a message to you on your website (arachnoid.com) and got the following error:
Error: embedded tags.
Warning: eregi() [function.eregi]: REG_EMPTY in /home/arachn5/public_html/messages/processMessage.php on line 84 Please press the "back" button to correct your entry.
I don't have any HTML in my message, and I'd really like to send it :-) Do you have an email address I could use please?
Yes, But for obvious reasons I don't want to post it in this forum.
Please post a plain-text message to my message board and I will reply. Then you can embed links and tags in your reply if you want. That way neither of us needs to post our e-mail addresses in a public forum.
Thanks!
I found that under a simple Bayesian model, the estimated probability of catastrophic failure during the next launch is 3.6%. See http://bentilly.blogspot.com/2012/10/how-reliable-will-falco... for details.
Update: I made a careless calculation error. Change 3.6% to 2%. Oops.
Often a more useful and appropriate construct in the Bayesian world, is the use of a belief network or Bayesian Network. This is a probabilistic directed acyclic graph (DAG) that encodes priors, often in the form of subjective beliefs (yes subjectivity can be useful), including specific domain knowledge.
Common example: Consider a naive Bayesian classifier (a specialized form of belief network) that identifies individual pieces of spam. Do we arrive at the spam score by entering the probability of past events into a simple model based of the Bayes theorem formula?
No, it's trained using the vast amount of domain knowledge and pattern recognition (through our experience and own estimation of what 'spam' is) encoded in our minds, that provide the priors. Thus, even though there is a large amount of subjectivity involved, the overall result can objectively be measured, within a given utility function. Incidentally, this is often what makes many hardcore empiricists 'nervous', and hence avoid belief networks altogether.
Coming back to the Falcon 9: A piece of prior information outside the scope of historic safety records, for example, one of the lead engineers having a nagging doubt about a particular technical risk based on some observed phenomenon, could have an impact on the real world probability of the next event being a failure. (Which is a pretty useful thing to know!)
In fact, this exact scenario happened in 2003 with the disastrous destruction of the Space Shuttle Columbia. [1] An engineer spotted something wrong on previous flights, but management failed to heed the warning[2]. This could quite possibly have been averted, if a risk mitigation model were in place to account for such evidence.
Looking forward, it's quite possible to imagine a future where this decision making has been outsourced to a sophisticated AI based off a Bayes net, with far more accurate real world modeling of risk and failure probabilities, outclassing the amount of evidence and a human or committee could possibly hope to compete with.
While I've nothing against frequentist approaches (albeit Bayesian naturally makes more intuitive sense to me), a minor drawback is the reliance on the past to predict the future. For example if you had safety records on 1 million previous flights, then one might be tempted to say, "well that's that then, we now know objectively the probability of failures in the future -- end of story". But, the 1 000 001 flight may have been designed to fly on a completely different type of technology, that will change significantly change the safety record of space flight going forward for the next "x" years. Thus using a Bayesian approach account for all relevant priors, it would in theory be possible to reflect a more accurate probability for the 1 000 001 flight, before it took place.
Lastly Bayes nets are not the best tool for every job, and do have drawbacks in certain situations. They are vulnerable to things like Bayesian poisoning or confirmation bias. A Bayesian approach is only as useful as the ongoing real world relevancy and accuracy of the priors. As the old adage goes, GIGO - garbage in, garbage out.
[1] http://en.wikipedia.org/wiki/Space_Shuttle_Columbia_disaster
[2] http://www.guardian.co.uk/science/2003/jun/22/spaceexplorati...
You should know that there's no such thing as "real world probability". The rocket will crash, or it will not, period.[1] Probability, as a measure of your own ignorance, is subjective.[2] Your main point still stands though: knowing about the uncertainty of that lead engineer certainly should influence your assessments of the risks involved.
[1] What will actually happen is, the universe splits into many "worlds" (blobs of amplitude in configuration space), a fraction of which will have the rocket crash, and the rest won't. That's the closest thing we have from "real world probability", though it really isn't: the laws of physics as we currently know them are still deterministic.
Indeed. We pretty much agree then. If you re-read the "real world probability" in the context, I was talking specifically about a belief network. The degree to which a justified belief, in an outcome will occur. All beliefs are by their definitions 'subjective' and occurring in a mind.
Actually my current thinking over the last decade mostly aligns with what could be described as physicalist view of the reality, so even 'subjective' thoughts, ideas, concepts etc exist objectively in a physical sense as well (glia cells, neurons etc). (but that's a whole other topic ;)
I simply worded it 'real word' because I was attempting (perhaps ineloquently I will concede), to differentiate between frequentist and the Bayesian understanding of the term probability, because they differ [1].
Bayesian favors bringing in a priori beliefs into the model whereas a posteriori consideration of a problem, as occurs in frequentist approaches, favor isolation of the model.
>What will actually happen is, the universe splits into many "worlds"
Interesting, you state that so.. assertively :p I'd give the chance of a many worlds interpretation corresponding well with our physical reality, a low probability event, with a pretty high credibility interval ;)
[1] http://www.experiment-resources.com/bayesian-probability.htm...
Well, you probably guessed where I came from: http://lesswrong.com/lw/r5/the_quantum_physics_sequence/
I think most physicists agree that at the bottom, we have a distribution of "complex amplitude"[1] over a "configuration space"[2]. But as you can see from my second link, many (most?) physicists insist that we can derive a "probability" from a complex number. Note that such probability would then be an actual real world probability, where the universe itself is uncertain about what to do. True non-determinism.
It's only natural. At the experimental level, the researcher does observe Born statistics. Same setup, different results, so there is probability in the territory after all.
There's a problem with that however: The equations, which make such wonderfully accurate predictions, (i) are dederministic, and (ii) do not state at any point that the blob of amplitude we don't see disappear in a puff of smoke. They merely say that the blobs eventually stop interacting. The same way that if you launch a photon to outer space, never to meet it again, it won't disappear the instant it reaches the boundary of our observable universe. If you insist on a mono world, you have to assert that the other blob, despite being predicted by those otherwise accurate equations, somehow doesn't exist when you don't see it.
One way to do it is to believe that, contrary to what the equations say, the blob you don't see does disappear in a puff of smoke. Its amplitudes are literally zeroed out behind your back. In hindsight, this one looks nuts to me. I mean, how can we justify distrusting accurate equations in a way that doesn't even make experimental predictions?
Another way is to call the square moduli of those amplitude "probabilities", and pretend that because it's probabilities, the blob you are not in isn't real. But the equations do not make any difference between the two blobs. Then how come the other blob is less real than our own?
To me, those two explanations really feel bizarre. You have to start from a mono world assumption to come up with that. An easy mistake to make, since personal experience is telling us all the time that there is only one world. A bit like a leaf in a binary tree: its ancestors form a line, not a tree. But Kolmogorov complexity says a literal interpretation of the equations (which means many world) is simpler than anything else we currently know about. So to hell with personal experience (which by the way is responsible for much worse whackery than mono world).
Now there is a way out: we can admit that current physics imply many worlds, but insist that real physics probably don't. Current physics are not complete after all. We may have big surprises. This argument is certainly be much saner than the Copenhagen interpretation. So much that it does lower my probability for many worlds somewhat. Just not enough to squash my confidence. :-)
There is a theorem that if an experiment and observational apparatus are both quantum mechanical systems, then the many worlds hypothesis describes what happens when that experiment is observed with that apparatus. If quantum mechanics is merely a good approximation of some better theory, then to whatever extent it is a good approximation of the system, the many world hypothesis remains a good description of that interaction.
Therefore your confidence that the many-world's hypothesis is an inaccurate description of what happens when you observe the outcome of a quantum mechanical experiment is an insistence that your brain and body are not well-described by the best theory that physics has for how the world works.
What gives you that confidence?
You are criticizing me for trying to rely on data rather than a complex subjective model based on information from the beliefs of people that I have never met and have no input from? There is no way for me to attempt that approach that does not come down to some form of "making shit up".
More generally you are right that I prefer to work off of data rather than subjective opinion. Data I understand. Subjective opinion is valuable, but suffers from major potential biases. Correcting for that can be very hard.
Horizontal axis is how many engines failed, and vertical axis is how many times that number of engines failed in the simulation.
The code that generated this is:
from scipy.stats import *
from pylab import *
failures = [binom(9,p).rvs() for p in beta(1,1,1e5) if binom(9,p).rvs() == 1]
hist(failures, bins=9, range=(0,9))
show()
So the posterior probability on the entire rocket failing for uniform prior is around 25%. Uniform prior means that you believe that all single engine failure probabilities are equally likely: you think it's equally likely that engines fail with 10% probability as with 63% probability. Tweak the first two parameters to beta to change your prior belief. If you've seen n engines fail in your life and k engines succeed, then setting the first parameter to n+1 and the second to k+1 is a reasonable choice (so the current setting corresponds to not having seen any rocket launches prior to this one). For example if you've seen 2 engines fail and 99 engines succeed you use `beta(3,100,1e5)`: https://dl.dropbox.com/u/388822/rocketfailuredistr_for_optim... Hardly any probability mass left for entire rocket failure :)
An important detail is what happens when 3 or more engines fail simultaneously. Can they transform the mission in a soft landing or the "payload" is totally doomed? (For example, the Apollo XIII mission was a failure, but no one died.)
It isn't clear whether it was on the way to complete engine failure or it was shut down to play it safe.
At least I am explicit in the assumptions behind that model. They are:
1. A priori, all possible reliability numbers for a single engine are assumed equally likely. (This can be debated endlessly, but you need SOME prior for Bayesian analysis. If we had more data, then the prior would matter a lot less, but we don't so it does.)
2. Failure of engines is independent.
3. The rocket actually operates according to design parameters. That is it will survive the loss of any 2 engines, but not the loss of 3.
4. Past performance is a predictor of future performance.
Every one of those assumptions is questionable.
Short version: The right engine compressor failed due to apparent fuel ingestion, causing a major over-temp. The noise was mistakenly attributed to a blown tire, so the pilot left the gear down. This required MAX Afterburner on the remaining engine to recover, except the engine had a afterburner blowout, and didn't provide MAX power and the jet departed controlled flight due to low speed.
In summary, after the right engine failed due to fuel ingestion, the left engine had to push some air over to the non-functioning engine (for cooling I assume but it isn't stated). When the left engine afterburner did not light, it's "relight logic" did not trigger possibly because of the lower air amount. So the engineer who wrote the relight logic, assumed that the temperature would drop at a certain rate when the afterburner failed to light. Because the engine was working to assist the failed engine, that temperature drop did not happen and thus the afterburner did not attempt to automatically relight itself.
Sounds like it may be dependent after all.
I invite you to create a toy model that takes that into account in some way and see what answers you come up with.
This is your real error. SpaceX is effectively acting in perpetual “test” mode. New lessons are learned with each flight and each rocket test, and that greatly informs all follow-on operations.
The type of analysis you've done is reasonable for a fleet of deployed 747's. It is (forgive me) entirely useless for this sort of endeavour at it's current stage.
I wonder what your analysis of SpaceX's future performance would have been in Oct 2008, right after their first successful Falcon 1 launch and three failed priors?
https://gist.github.com/3855660
And the probability of any rocket engine failing, per launch, is 1 in 3!
In Bayesian analysis you have some set of prior theories with associated probabilities, you observe data, you alter your estimate of the likelihood of those theories, and then your next prediction becomes a weighted average of those predictions.
That number has no attached variance.
First, you haven't really done a Bayesian analysis, for several reasons.
The easiest problem to fix is, you didn't specify any priors. We could validate your style of calculation by assuming single-engine failures are IID with parameter "p," uniform on the unit interval. (A beta distribution would be the standard conjugate prior.)
If we go ahead and make the uniform-p assumption, then what you've calculated is a most-likely posterior value of "p" (35/36). (This is the maximum-likelihood estimate for p.) But in a Bayesian world, "p" has a full posterior distribution, not just a most-likely value.
So, still in the Bayesian world, the probability of failure (P(N_fail > 2)) must be calculated on the basis of not the most likely p, but the posterior of "p". You didn't do this; you just used the most-likely p.
Which brings us to the second problem with your reply. You really can get a confidence value on P(N_fail > 2). You can get a full posterior distribution! It will be a 1-dimensional density on [0,1]. And you could calculate this, either by simulation or by an analytic procedure (because it's a low-dimensional problem).
This posterior on P(N_fail > 2) would be the answer to the parent's question. It would probably be rather "fat", validating the intuition that we don't have much data.
My reply might be a little smarty-pants. Sorry if it is! As I said, your analysis is a reasonable first cut.
Read the whole thing more carefully. I started with the calculation for the maximum likelihood estimate, but I ended with a prior with equal a priori likelihoods for failure rates 0%, 0.01%, 0.02%, ..., 99.99%, 100%. This is a reasonable discretization of uniform on the unit interval.
My reply might be a little smarty-pants. Sorry if it is!
I would suggest that before indulging a tendency to be a smarty pants, that it is good to read the whole thing.
You are still in error that there is not a way to describe the uncertainty in your estimate of the posterior probability of system failure. It has a posterior distribution, like everything else in a Bayesian analysis. You would compute it as I described -- Monte Carlo would be easiest.
If I have a normal coin and a coin which is double-sided (but I don't know which side), I'll give 50% for both of them coming up heads next time I toss. But if I toss them a hundred times each, my probability distributions for them look totally different.
I suspect this information is encoded in your priors, but I don't know offhand how to access it.
Uniform prior, updated on the evidence that 1/36 engines have failed, I think this gives P(TFR = x) = x(1-x)^35 / (int x(1-x)^35 dx from 0 to 1). Apparently the integral is 1/1332, so P(TFR=x) = 1332·x·(1-x)^35. But that seems to have a mean of 5%, compared to your value of 2%, so I may have done something dumb?
You can answer that question for each prior. The probability of, say, 3 failures is the sum over all priors of the probability that that prior is true, times the probability that it would leave you with 3 failures.
I leave writing a program to calculate this as an exercise to the reader. I've put enough time in on this one already, I have paying work to get back to.
How many failures are required to change your model from 2% to, say, 4%?
If 2 engines failed on the next launch, the model would predict a 4.8% chance of failure on the following launch.
As for your "build your model from a billion launches and 20 million failures" comment, if I had that much data, then it wouldn't much matter what reasonable set of priors that I started with, I'd wind up convinced that the true failure rate was very close to 2%.
Note that the prior that I am talking about is the distribution of possible theories before I saw ANY data.
For instance one such interval has a MLE of an engine failure rate of 2.78%, a lower bound of 0.1% and an upper bound of around 15%. (Corresponding rocket failure rates range from 1 in 10 million to about 9.9%.)
In fact the failure of your neighbor likely affects the odds of your failure. So I'm being too nice to SpaceX.
Can anyone that knows something about the Falcon 9 design or rockets in general shed some light on this? That sentence makes it sound like the panels were purposefully jettisoned, which doesn't make sense to me. What do those panels do, what do they look like, and where are they?
How quickly do engines explode? Is it faster than 2 cars colliding? Computers deploy air bags quickly because electricity travels faster along wires in your car chassis than the car travels into something else.
Visualize a bumper with sensors - as the bumper is deformed by a collision, a sensor shifts an electron in the copper wire, and the electron next to it shifts. There's a cascade of shifting electrons along the wire, and it races backwards through the car's body, chased by the destruction of the car as it collides with another object. The cascade of electrons hits the air bag computer, which begins another cascade of electrons to the air bag. The wave of destruction has covered most of the distance to your windshield by now. The air bag deploys as molecules of air rush from their high-pressure canister to fill it. As the bag hits its most pressurized point, your car is coming to a stop as its kinetic energy is combined with energy from the other object.
Sidenote about airbags: they have to be folded to fit inside their module, so as it inflates it's also unfolding. In order to make sure it unfolds properly they coat it in a lubricant that can't evaporate – either talcum powder or cornstarch depending on the vehicle.
I learned this only after I scrambled out of the car my sister put in a ditch thinking it was on fire. The best part? It was a diesel car.
Who knows, maybe the engineers consider it a feature because after an accident it sure gets people out of the car quick!
Wonderful explanation.
They're also most likely built as the designated point of failure, like a safety valve on a boiler. If the pressure builds too high they are blown out by the pressure. Ex. engine goes critical and explodes before computer can react, the panels fail before other structural components do.
Their statement suggests these came off when pressures radically changed during engine cut off, which is plausible. It was at max aerodynamic pressure, and removing all the pressure the motor generates is a big swing. I find it more likely that the nozzle (bell) shattered, as it is more exposed to both aero and combustion pressures. Maybe both happened.
A visual guide:
1) naked engine: http://farm3.static.flickr.com/2355/2230438397_487afd40a2.jp...
When a liquid engine fails energetically, it's usually going to be a failure in the chamber. Nozzle or throat burn-through or other failure may also happen. The turbo pump might also let go and shred some stuff nearby. Plumbing failures may also kill the engine, but not destroy much; there are plenty of valves to fix leakage before it gets bad.
2) un faired: http://www.spacenews.com/images/Falcon9engines_SpaceX02.jpg
Here you can see the armored tub around the chamber section of each engine. It is meant to contain any problems. Mostly these would be hot gas from holes burned in the chamber or throat, fuel or oxidizer from leaks in the plumbing, or shrapnel from the turbo pump coming apart. Note that the other major failure mode, excessive vibration, cannot be armored against, but that is more a design thing than a random failure.
Most to all of these failures are easily detected by various pressure and flow sensors, and usually before they become big problems. Turn off the propellant valves, and the engine rapidly becomes safe, though off. But the armor does keep the neighbors safe from any problems, presuming it holds. I would guess it is good enough for most failures.
3) faired vehicle: http://www.brendans-island.com/blogsource/20101015ff/falcon-...
Here you can see pretty white fairings hiding everything but the nozzles. Note that they appear to be a bunch of different pieces. Probably that is because they are meant to break away individually if something goes wrong.
Those are what I think the statement refers to. I doubt they are actively jettisoned, but may certainly be designed to pop off in an over-pressure situation. One could probably compare vs the video to see if the pieces look like that, the nozzle, or other engine parts. The corner fairing might also have failed under some circumstances.
Having seen the video in slow mo a few times, I think their assessment is plausible. Probably they will be able to tell what happened by telemetry. I don't know if they are still trying to recover stages, but if they are, they might get their hands in some physical evidence. Whether we will ever see any of this data, though, I don't know. They've been reasonably open in the past.
Chills down my spine as I read this. I try to write eloquently, but sometimes the fact should stand alone: "No other rocket currently flying has this ability."
What I wanted to say by this is that while it's a great thing for Falcon 9 to have fail-over in its maiden flights (as we could see yesterday), I wouldn't worry too much about "other rockets" not having this. Soyuz rockets are a great example (100% success rate for manned flights to ISS and over 97% success rate for all Soyuz rockets (that's since 1966)[1]).
1. my numbers are only from wiki: http://en.wikipedia.org/wiki/R-7_(rocket_family) and http://en.wikipedia.org/wiki/List_of_Russian_manned_space_mi...
I am now getting hopeful that I'll be able to experience zero-G before I die. SpaceX team, you are my heroes. Keep up the great work!
www.orbcomm.com/Collateral/Documents/English-US/ORBCOMM%20Launches%20Prototype%20OG2%20Satellite%20FINAL.pdf
Is everything fine now, or is it not? "Nominally" in this sense to me means that something is amiss, but reading the rest of the article seems to imply that everything is on track.
"Aerospace & Engineering. According to plan or design: a nominal flight check."
Live and learn, I guess. Thanks frabcus!
I find that to be a sufficient explanation, though I'm just guessing.
nominal |ˈnɒmɪn(ə)l|
adjective
1 (of a role or status) existing in name only: Thailand retained nominal independence under Japanese military occupation.
• relating to or consisting of names.
2 (of a price or charge) very small; far below the real value or cost: they charge a nominal fee for the service.
3 (of a quantity or dimension) stated or expressed but not necessarily corresponding exactly to the real value: EU legislation allowed variation around the nominal weight (that printed on each packet).
• Economics expressed in terms of current prices or figures, without making allowance for changes over time: the nominal exchange rate.
4 Grammar relating to or functioning as a noun: a nominal group.
5 informal (chiefly in the context of space travel) functioning normally or acceptably.
One aspect that's worth consideration is the private/corporate aspects of spaceflight. When there were failures in Apollo and the shuttle, the public had a right to know everything that happened since we'd paid for everything. SpaceX has been super cool about disclosure here, but how long can we count on that? At some point, there's too much money at stake for them to maintain full transparency.
But I think that SpaceX understands that NASA is funded by the public and it will be easier to get the support of NASA if they have the support of the public. I would suspect that for this reason they will continue a decent amount of public disclosure.
"It is worth noting that Falcon 9 shuts down two of its engines
to limit acceleration to 5 g's even on a fully nominal flight.
The rocket could therefore have lost another engine and still
completed its mission."