Category Archives: Space

A Glimpse Of The Singularity

Charlie Stross sees it.

What I found interesting, though, is how quickly the discussion in comments transitioned to how slow the progress has been in space access, with NASA taking a beating.

There is no question that space technology, with high-powered (megawatts/gigawatts) devices is fundamentally different than things that switch bits and electrons around, and it’s not reasonable to expect it to come close to Moore’s Law. But there’s also no question that, given different policies for the past half century, things could be much further along than they are. We may not (as Monte Davis noted in comments over there) have seen 2001: A Space Odyssey by 2001, or even now, but we’d be on a lot clearer path to it, I think.

But that has never been a societal goal, even when we were pouring four percent of the federal budget (and doesn’t that make the NASA fanboys drool) into the problem during Apollo. We were just trying to beat the Russkies to the moon, and after we did that, we got preoccupied, and public-choice economics took over, as it always does when things aren’t important any more. And that’s the way it’s been ever since. But because of false myths promulgated during that era, it’s been tough to raise the money privately as well.

It won’t happen as fast as we’d like it to, nor will it happen as slowly as those who continue to cheer for government spaceflight expect, either. And most importantly, it will have trouble keeping up with the electronics singularity (though a lot of those advances will eventually accelerate space technology as well, and it will happen much sooner than most expect).

But I think that we are seeing real, measurable progress now, and I expect it to continue, and to continue to confound those who continue to cheer NASA five- and ten-year plans.

A Space Race With China?

Jeff Foust lays out the case, pro and con. As he points out, there is a lot of ignorance and misinterpretation in this area, on both sides. I don’t think that we’re in a race, and if and when we are, it will become clear long before it’s “too late,” in any sense. We will not be surprised by a Chinese lunar landing.

As noted previously, the real race is not between governments, but between plodding politicized bureaucracies and cash-starved private space enterprises.

And I found this bit amusing:

It is difficult, though, to get a handle on some information, such as exactly how much money China spends on its space program; estimates vary widely and even Chinese officials have said that their budgets are “very complicated…”

Does that distinguish them in any useful way from NASA’s?

The Real Space Race

Chair Force Engineer writes about it:

In a true competition for transporting astronauts to low earth orbit, NASA would be beaten hands-down by SpaceX at this stage in the game. SpaceX has a capsule with more astronauts (seven versus six,) a cheaper booster (Falcon 9 vs. Ares I,) and a faster schedule.

The only thing SpaceX doesn’t have is thousands of jobs, and access to billions of dollars of taxpayer money.

[Update about 5 PM EST]

Mark Whittington continues to live in a fantasyland on this subject:

My sense is that under the scenario, COTS will be cancelled and the manned space program will consist of astronauts going in circles around the Earth forever and ever.

At least until the Chinese land men on the Moon. Then there will be a rather rude awakening.

Like it or not, the only hope for near term commercial space flight in LEO is that NASA continues to explore beyond LEO.

COTS is helpful, but in no way essential for commercial human spaceflight.

SpaceX was developing the Falcon 1 and 9 before COTS, and it would continue to do so in the absence of COTS. OSC might not move forward without COTS, but Dragon development will continue, Falcon 9 development will continue, and Atlas V upgrades will continue. The real market is not COTS, which is a sideshow from a payload standpoint, but Bigelow’s private space facilities, which were also moving forward before COTS, and would continue to do so in its absence.

I simply don’t understand Mark’s blindness to these realities that intrude so rudely on his theories, and his continuing obtuse insistence that commercial space is doomed without COTS, other than some sort of faith-based belief that it is not possible to put people into space without government funding.

And the notion that China is going to land a man on the moon any time within the next twenty years, at their current pace of development (far slower than Apollo was) remains laughable. So is the notion that they would suddenly do so out of the blue and that it would be a “rude awakening.”

This isn’t the Sputnik era, in which one can slip a satellite on a missile, in a world in which there was no space-based surveillance. There will be no surprise. If the development pace of the Chinese program picks up, it will be quite obvious, given the need for either a very large Saturn-class vehicle or (if they’re smart) orbital infrastructure, long before it actually happens. We will have plenty of time to respond, from a policy perspective, should we decide to.

CFE has it right–the race is between NASA and the private sector, not between slow-paced, expensive and moribund government space programs.

No Sizzle To The Steak

There’s an old saying in marketing, that you don’t sell the steak, you sell the sizzle. Which is why I’m always bemused by people who bemoan NASA’s PR abilities. Not that I admire PAO, but I have to agree with Clark Lindsey:

Why anyone at NASA thinks that simply doing better PR will arouse great interest among young people in the agency’s Apollo Do-Over is beyond me. I’ve not detected any great enthusiasm for it even among many lifelong space advocates who are well informed about it.

In fact, the more we learn, the less enthused many of us get.

Regretful

About five years ago, I did a “regret analysis” on whether or not we should remove Saddam Hussein:

From a “minimax” standpoint, the current course is the lowest-cost one.

Of course, some would argue that this is too simplistic an analysis, because (among numerous other reasons) it doesn’t take into acccount the probabilities of the various scenarios being true, which, if you had them, you could multiply them by the costs to get expected values.

Of course, the problem with that approach here is that, if the cost estimates are wild-ass guesses, the probabilities would be even more so. How much confidence could we have in the output of such an analysis?

What we’re dealing with here is not risk, in which the probabilities can be reliably quantified, but uncertainty, in which they cannot.

As an example, a thirty percent chance of rain represents risk. “It might rain, or it might not, but we have no idea what the probability is” constitutes uncertainty. It’s much easier to decide whether or not to take an umbrella in the first circumstance than the second.

For this reason, economists have come up with a more sophisticated technique for decision making in the absence of probabilities of outcomes. Rather than simply looking for the lowest cost, they instead try to minimize how bad you’ll feel if you make the wrong decision–they minimize “regret.”

It’s based on the notion that when you make a decision, you shouldn’t compare it to some unattainable ideal of zero cost–you should compare it to the best decision you could have possibly made.

Take a simple case–do you take an umbrella when it rains, or not?

Consider a generic cost matrix:

State 1 State 2 Max
3 4 4
1 5 5

It looks like we can minimize our maximum cost by choosing action 1, since four is less than five. But is that really the right decision?

Let’s derive a “regret” matrix from it. This is done by finding the minimum cost for any state, and subtracting each cell of that state from it. The minimum cost for state one is 1, so the column would be three minus one for the first row and one minus one (or zero) for the second row. That makes intuitive sense, since if you made the right decision for that state, you’ll have no regrets. The regret matrix for the example cost matrix is shown below:

State 1 State 2 Max
2 0 2
0 1 1

Note now that if we want to minimize regret, we should actually choose action 2. Note also that this is independent of the relative probabilities of the two states.

NASA is confronted with exactly this kind of uncertainty with the vibration issue on the Ares 1. They don’t know how big the problem is, and have no way of quantifying it with current knowledge. Thus, they’re going to spend billions on getting to an initial flight test, and hope that they don’t find out that they’ll have to spend additional billions (not currently budgeted) to fix the problem, or give up completely and go to a new design (with more billions not currently budgeted), whereas if they knew now that it was intractable, they could stop wasting money on it and move directly (so to speak) on to a different concept.

Now, I don’t have access to the program data to properly fill out the cost matrix, so the following numbers are pulled out of an orifice, but hopefully not the nether one–my WAGs are better than those of many with such things.

Let’s keep it simple, with two courses of action, and three states.

One course is to abandon the concept now (noting that there are other reasons to do this than only the vibration problem–that’s just the latest issue). The other is to continue forward with NASA’s current plan.

The three states are:

  1. There is no problem–the frequencies of the solid don’t resonate with the vehicle structure, and don’t present any hazard to upper stage, crew vehicle, or crew
  2. There is a problem, and it will take a lot of time and money to mitigate it with dampers, shifting mass around, beefing up structure, etc.
  3. There is a problem and it’s not mitigatable, because the measures that would be required to do so would make it too heavy to deliver the required payload to orbit.

This provides us with six cells in the matrices, which have three columns (corresponding to states of reality) and two rows (the potential courses of action).

First let’s consider Row 1: NASA’s current plan.

Option 1: There is no problem. That is the hope (but as military planners will tell you, hope is not a plan).

What is the cost? Nothing. Or rather, the cost is what they expect to spend on the program if it’s nominal. Let’s call it a billion, on the assumption that this is what it will cost to get us to the flight test (if anyone has a better number, let me know).

Option 2: There is a problem, but it involves major changes to the vehicle design to compensate for it.

Let’s say (to be kind) that it costs a year in schedule (what’s the value of that?) and an additional billion dollars in development costs. Let’s be generous again, and say that the year delay (in terms of “gap”) is only an additional couple of billion. So the cost is the billion it takes to get there, a billion to fix plus the two billion for the delay–a total of four billion.

Option 3: The problem is intractable. There is no way to build the vehicle in such a way that it can deliver the required payload into orbit without shaking itself and/or the payload apart.

Now the cost is the billion dollars to get to flight test, plus a new design, almost from scratch, and about three years lost. Let’s say that the new vehicle is a two billion dollar program, relative to what NASA would have spent to complete Ares 1 post flight test. If the gap costs two billion a year, then we have a total of nine billion dollars cost in this worst case.

OK, now for Row 2–scrapping the concept now and getting a head start on a design that will work. The cost is the same in all three cases. It’s the cost of developing the new vehicle relative to expected expenditures on the Ares from here forward, plus, say, a two-year addition to the gap. Call it seven billion.

So the cost matrix looks like this:
COST MATRIX

No Problem Fixable Problem Insoluble Problem

Max
1 4 9 9
7 7 7 7

So the minimax solution, based on the cost matrix alone, is to switch now. It all depends on what you think the likelihood is that the problem will be intractable. We don’t know that that is, so let’s look at the regret matrix.

REGRET MATRIX

No Problem Fixable Problem Insoluble Problem

Max
0 0 2 2
6 3 0 6

Now, the course of minimum regret is to move forward. Regret is zero if there is no problem or it’s fixable, and a max of two billion if they have to start over, whereas they risk a six billion dollar regret by giving up now.

So, at least a cursory analysis would indicate that NASA’s approach makes sense, but I could be way off on the numbers. In addition, I’m not counting all of the less tangible costs of having to switch gears after a flight-test failure. Any thoughts from anyone else? Am I missing something?