Buran - the Soviet 'space shuttle'

By Anatoly Zak
Russianspaceweb.com

Despite its looks, Buran was not a facsimile of the US shuttle

Some 20 years ago, on 30 September 1988, many readers of the Pravda newspaper - the official mouthpiece of the Soviet communist party - could not believe their eyes.

Published somewhat inconspicuously on the second page, there was a photo depicting the familiar shape of the US space shuttle, but with Soviet insignia on its wings.

Finally, years of rumours about a Soviet "copy" of the shuttle had been confirmed.

However, the official Soviet press was quick to point out that despite its superficial resemblance to the US counterpart, the Russian shuttle, dubbed Buran or "snowstorm", was better and more capable.

Within days, the new ship got a chance to prove it.

On November 15, 1988, as snowy clouds and winds were swirling around Baikonur Cosmodrome in Kazakhstan, the Buran orbiter, attached to its giant Energia rocket, thundered into the gloomy early morning sky.

They obliterated this crowning achievement of the Soviet space programme

Three hours and two orbits later, the 100-tonne bird glided back to a flawless landing just a few miles from its launch pad.

Despite the kind of strong winds that would rule out any launch or landing attempt by the US space shuttle, Buran touched down just 3m off the runway centreline.

And this planet-wide ballet was performed with its "pilots" safely on the ground.

Born of paranoia

Buran's pioneering mission was the culmination of an effort by more than 600 Soviet institutions which, since 1976, had secretly laboured on this largest of Soviet space projects.

Upon the spacecraft's triumphant landing, the Soviet newspapers promised a new era in space exploration. Few could predict at the time that it would be Buran's only mission.

Unlike Nasa, Soviet developers never had any grand illusions about replacing traditional rockets with a reusable space truck.

Instead, the Soviet shuttle was conceived primarily as a "symmetrical response" to the perceived military threat from America's winged orbiters.

A fully assembled Energia rocket with the first flown Buran orbiter, in 2002

Years after a sceptical Pentagon had given up on the shuttle, even as a delivery truck for spy satellites, the Russian officials continued whispering to journalists that the US orbiter had a secret capability - to make an undetected "dive" into the Earth's atmosphere and suddenly glide over Moscow dropping nuclear bombs.

Never mind that such a scenario was not supported by physics or by common sense.

Energia-Buran's chief architect, Valentin Glushko, hardly tried to educate warmongers at the Politburo about the questionable merits of the re-usable orbiter as a weapon.

Glushko was one of the first generation of Soviet rocket pioneers, who were experimenting in the 1930s under the tutelage of Konstantin Tsiolkovsky - one of the "fathers" of spaceflight. Like many of his contemporaries, he had little interest in designing weapons.

He did dream, however, about building a permanent base on the surface of the Moon.

Unfortunately, after losing the Moon race to America in 1969, Soviet leaders had little appetite for another deep-space adventure.

The launch and test facility where the Energia rocket first took off in 1987

Still, Glushko probably hoped to exploit Cold War paranoia about the threat of the US shuttle as an opportunity to lay a detour road to the Moon, and possibly even to Mars.

Glushko carefully steered the Soviet shuttle project away from being a carbon copy of the American design, which could not be easily modified.

Instead, he proposed a winged orbiter along with a fully functional rocket which could carry any cargo - including lunar landers, orbital tugs and even pieces of a Martian expeditionary complex.

In the end, Kremlin bosses had committed to the monumental expense of money and human talent with only vague hopes that real tasks for the grandiose vehicle would emerge as it came online.

Instead, after long delays and cost overruns, the Buran appeared on the scene in the last act of the Cold War and amid a crumbling Soviet economy.

The Berlin Wall had come down just a year after its first flight, and the Soviet Defence Ministry was suddenly more preoccupied with resettling thousands of troops returning from Eastern Europe than with servicing orbital anti-missile platforms and deploying killer satellites in space.

The first stage of the Energia rocket inside Building 112 in Baikonur

The collapse of the Soviet Union in December 1991 sealed the fate of the Energia-Buran system.

There was a flicker of hope for Buran's giant booster - Energia - when Russia joined the effort to build the International Space Station (ISS).

Still unfinished today, after a decade of efforts and dozens of assembly flights, the ISS could have been hauled into orbit by only a few Energia boosters, had international partners adopted it into the program, say the rocket's proponents.

In the mid-1990s, a flight-ready Buran orbiter, which made the historic trip in 1988, had been mounted on the back of a fully assembled Energia rocket at Baikonur's Building 112.

This eye-popping display became a popular stop for journalists and foreign tourists, who periodically "invaded" Baikonur for high-profile launches.

To the untrained eye, the gargantuan rocket and its orbiter looked all but ready for a rollout to the launch pad.

Last resting place

In 2001, this spectacle, combined with the optimistic and mis-translated comments of a Russian guide, had such a profound effect on one Western reporter that he filed a story claiming that the Energia-Buran programme was about to be re-started.

The article proved that a decade after its demise, the Buran had already become a legend.

However, if one looked closely in Building 112 it was possible to see water dripping from the high ceiling on a rainy day and accumulating on the floor, under the dead torsos of Energia rockets.

The keeper of the facility, who showed reporters around the building, said that he could hardly find money to send repair men to patch up the giant roof.

Rescue workers search the devastated hangar at Baikonur

Eventually, a repair team, believed to include eight people, did make it to the roof, climbing on top of Building 112 on May 12, 2002.

According to eyewitnesses, at about 0920 local time, the entire structure shook violently, as if hit by an earthquake, and enormous pieces of debris plunged dozens of metres to the ground below.

They obliterated this crowning achievement of the Soviet space programme.

But the Energia-Buran programme did leave a lasting legacy.

The cavernous launch facilities at Baikonur and a state-of-the-art mission control centre in Korolev have continued serving the Russian space programme and its international partners.

The rocket technology developed for Energia-Buran has been put to use in other launchers.

A mighty RD-170 engine, originally developed for the first stage of Energia, today powers the Ukrainian Zenit rocket.

This engine's scaled-down descendants - the RD-180 and RD-190 - have been adopted for the US Atlas booster and Russia's next-generation Angara rockets.

While the US space shuttle will soon share the fate of the Buran orbiter - as a museum exhibit - emerging plans for lunar exploration have revived concepts of super-heavy rockets, on both sides of the Atlantic.

If they are ever built, their creators will have to re-trace the path once made by Valentin Glushko and his colleagues.

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Forgotten But Not Gone: How The Brain Re-learns

Store room for future learning: nerve cells retain many of their newly created connections and if necessary, inactivate only transmission of the information. This makes relearning easier. (Credit: Image: Max Planck Institute of Neurobiology / Hofer)

Thanks to our ability to learn and to remember, we can perform tasks that other living things can not even dream of. However, we are only just beginning to get the gist of what really goes on in the brain when it learns or forgets something. What we do know is that changes in the contacts between nerve cells play an important role. But can these structural changes account for that well-known phenomenon that it is much easier to re-learn something that was forgotten than to learn something completely new?

Scientists at the Max Planck Institute of Neurobiology have been able to show that new cell contacts established during a learning process stay put, even when they are no longer required. The reactivation of this temporarily inactivated "stock of contacts" enables a faster learning of things forgotten.

While an insect still flings itself against the window-pane after dozens of unsuccessful attempts to gain its freedom, our brain is able to learn very complex associations and sequences of movement. This not only helps us to avoid accidents like walking into glass doors, but also enables us to acquire such diverse skills as riding a bicycle, skiing, speaking different languages or playing an instrument. Although a young brain learns more easily, we retain our ability to learn up to an advanced age. For a long time, scientists have been trying to ascertain exactly what happens in the brain while we learn or forget.

Flexible connections

To learn something, in other words, to successfully process new information, nerve cells make new connections with each other. When faced with an unprecedented piece of information, for which no processing pathway yet exists, filigree appendages begin to grow from the activated nerve cell towards its neighbours. Whenever a special point of contact, called synapse, forms at the end of the appendage, information can be transferred from one cell to the next - and new information is learned. Once the contact breaks down, we forget what we have learned.

The subtle difference between learning and relearning

Although learning and memory were recently shown to be linked to the changes in brain structure mentioned above, many questions still remain unanswered. What happens, for example, when the brain learns something, forgets it after a while and then has to learn it again later? By way of example, we know from experience that, once we have learned to ride a bicycle, we can easily pick it up again, even if we haven’t practiced for years. In other cases too, "relearning" tends to be easier than starting "from scratch". Does this subtle difference also have its origins in the structure of the nerve cells?

Cell appendages abide the saying "a bird in the hand …"

Scientists at the Max Planck Institute of Neurobiology have now managed to show that there are indeed considerable differences in the number of new cell contacts made - depending on whether a piece of information is new or is being learned second time around. Nerve cells that process visual information, for instance, produced a considerably higher number of new cell contacts if the flow of information from their "own" eye was temporarily blocked. After approximately five days, the nerve cells had rearranged themselves so as to receive and process information from the other eye - the brain had resigned itself to having only one eye at its disposal. Once information flowed freely again from the eye that had been temporarily closed, the nerve cells resumed their original function and now more or less ignored signals from the alternative eye.

"What surprised us most, however, was that the majority of the appendages which developed in response to the information blockade, continued to exist, despite the fact that the blockade was abolished ", project leader Mark Hübener explains. Everything seems to point to the fact that synapses are only disabled, but not physically removed. "Since an experience that has been made may occur again at a later point in time, the brain apparently opts to save a few appendages for a rainy day", Hübener continues. And true enough, when the same eye was later inactivated again, the nerve cells reorganized themselves much more quickly - because they could make use of the appendages that had stayed in place.

Useful reactivation

Many of the appendages that develop between nerve cells are thus maintained and facilitate later relearning. This insight is crucial to our understanding of the fundamental processes of learning and memory. And so, even after many years of abstinence, it should be no great problem if we want to have a go at skiing again this winter.

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Complex Systems Science: How Do Math And Intuition Help Us Understand Whole Systems?

Peter Dodds is lost. Well, not exactly. He knows he's going to meet me at 2:30 in the Davis Center. But just where? He doesn't remember. And yet, without hesitation, he walks into the atrium, past crowds of people, up the sweeping staircase and directly into Henderson's coffee shop.

There I sit, gulping a latte. How did he figure out where to go?

"t's an interesting kind of search problem," he says. "It just seemed like the right place to go. I figured you wouldn't be hanging out with the students, and that coffee might have something to do with this. I was right."

That kind of intuitive problem solving, he thinks, is not simple to explain and even harder to replicate with a computer. It's way beyond the best artificial intelligence programs, and it would be charitable to say that neuroscience has a firm grasp of how the brain manages such a task. But it's not magical either.

"It's complex," he says.

And complexity lies at the heart of Dodd's research and teaching as an assistant professor of mathematics and statistics. He's part of a group of researchers who make up UVM's Complex Systems Center launched in 2006 by the College of Engineering and Mathematical Sciences.

"In its most simple form, a complex system is many distributed parts interacting in some distributed way," Dodds says, "giving rise to some interesting, often unexpected, macrophenomena." Take a neuron. Alone, it's a cell that conducts a chemical signal. But billions together, each woven with thousands of links that adapt and change over time, emerge as a brain capable of following a hunch and the smell of coffee.

Big Band, no conductor

While the human brain may be the ultimate complex system, other examples appear everywhere. Take army ants. Despite their name, they have no general, and their queen sends out no instructions. No ant is aiming to get across that gully, and there is no blueprint or traffic light. Yet millions of ants, following the same instinctive rules of individual behavior, can build bridges with their bodies and forage for food along vast efficient highways.

"That's emergence," says computer scientist Maggie Eppstein, director of the UVM Complex Systems Center. "You can't just look at the rules each little thing is following and then describe what is going to happen in the whole system. You've got to run the model or observe the whole to understand what happens at the next scale."

Ferociously chaotic air currents resolve into a tornado that moves across the landscape maintaining its form. "In complex systems, through local interactions and self-organization, stable or semi-stable patterns emerge at a next level or a higher scale," she says, "but they are difficult to predict because they are so sensitive to small changes in the system or initial conditions."

Applying insights like these, Eppstein and her colleagues across the university are helping to lead the rapidly developing field of complex systems science. They aim to bring new approaches to some of the world's most vexing problems like improving hurricane forecasts, understanding the effects of phosphorous pollution in a watershed, slowing the spread of invasive species, making robots that can start to discern the intentions behind an action, and untangling the genetic and environmental threads that lead to heart disease.

The lights are on

Recall what happened on the afternoon of Aug. 14, 2003. In a cascade, the lights went out in Cleveland, New York City, Baltimore, Albany and Detroit. Eventually, more than 50 million people were without power across the Northeast and Canada as 265 power plants shut down.

This famous blackout was a complex systems failure. No one pulled the plug; numerous local problems and mistakes created a series of dynamic feedback loops. The result: an unpredictable regional disaster.

"Nobody's in charge of the electric grid," says Paul Hines, a power engineer who is part of the UVM complex systems group, "there are hundreds of companies and entities who all have a role. What's amazing is that in the midst of this system, with millions of human and non-human actors — a lot that we can't predict — we still get order. Most of the time, when you flip the switch, you get light."

Or, as Dodds says, complex systems are "typically highly balanced, flexible, and robust, but are also susceptible to systemic collapse."

Decades of work to improve overall control of this patchwork of operators, powerplants, substations, and transmission wires — a product of history more than rational design — haven't gotten very far. "The reliability of the grid has basically been constant for the last 25 years," Hines says. He recently presented data that shows the frequency of blackouts has remained the same since 1984, and also that very large blackouts are more frequent than would be expected from traditional exponential statistics and risk assessments.

"Traditional methods have tried to estimate the reliability of the system by taking each component individually," Hines says. Any one substation is pretty straightforward and may not appear to be hard to manage. "But this misses what happens when combinations of components fail," he says.

In a complex system, one plus one might add up to a lot more than you'd guess. These kinds of nonlinear interactions don't show up in a static model that simply describes the electric grid. Which is why Hines is developing dynamic graph-based models instead that draw on new methods from network theory.

"Our goal is not to create a complex model, our goal is to create a useful model," he says, "a simple model that helps us understand a complex system." He's feeding data from actual power systems into his model, seeking sets of components that cluster together when he runs the model since these may be particularly important to maintaining the robustness of electricity delivery systems.

Parts is not parts

"Complex systems science is just the evolution of science," Dodds says. Since the revolution that Newton and Descartes helped launch, the main thrust of so-called normal science has been to look for smaller pieces and more fundamental laws. Molecules yield atoms yield quarks.

"There are many problems that we figured out by breaking things into little pieces," Dodds says. "Scientists figured out DNA with its double helix. And then they figured out the human genome by measuring like crazy. There was a sense conveyed that once we understood all the bits of the genome, we'd understand everything human," he says, "but that's totally insane."

"It's like saying once we understand atoms we understand matter," he says, "But we don't."

Of course, many of the underlying ideas behind complex systems are far older than the name. It was Aristotle who stated that the "whole is more than the sum of the parts." But complex systems science takes this realization further. As physicist PW Anderson wrote in a seminal 1972 paper in Science, in a complex system “the whole becomes not only more than, but very different from the sum of its parts."

"The ability to reduce everything to simple fundamental laws does not imply the ability start from those laws and reconstruct the universe," Anderson wrote.

Peter Dodds stands at the bottom of the Davis Center stairs and watches students playing pool. One after the other, they rub their cue sticks with chalk and lean over the table. "If you want to understand how humans behave collectively you have to understand what their psychology is: and you will never get that from studying quarks or DNA or cells," he says, as a stream of students pass around him like he's a rock in a river. "Never."

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