Phase Change in Fluids Simulated

brendotroy writes "After decades of work by the physics and computer science communities, scientists at the University of Rochester have finally created a mathematical model that will allow scientists to simulate and understand phase changes. This discovery 'could have an impact on everything from decaffeinating coffee to improving fuel cell efficiency in automobiles of the future.'"

Comments

Re:Too dense

[techno-vampire]

Can it show why lakes don't freeze from the bottom up as water approaches 0 Celsius?

No, because that has to do with an entirely different, well-understood phenominum. Unlike most substances, water gets less dense when it gets near its freezing point instead of continuing to get denser. When it freezes, it gets even less dense. (This is caused by something called "hydrogen bonds," but I'm not going to go into that.) Thus, ice is slightly less dense than the water surrounding it, making it float.

Re:The decaf coffee

[Wizard Drongo]

WHAT??? Why?? THe whole purpose of coffee is the caffeine. Caffeine is like water; without it, you just can't function. If you want something that doesn't have caffeine it (again; WHY??) drink water. Coffee is a sacred drink. By drinking that horrible stuff that was once coffee but lacks its essence, you're defaming a religion. Please bear in mind the above comments were typed at (local time)04:45hrs after 9 cups of rocketfuel gurana coffee, as I've a presentation to give tomorrow and haven't exactly written it yet. Keynote.app is calling. Laters....

Re:Recordable media

[ConsumerOfMany]

or I pee in it.

Re:But

[ConsumerOfMany]

phase change is hardly fun. After a recent visit to TacoBell I changed a solid into both a liquid and a gas is less time than it took me to get home in my car, after which both my girlfriend and my dignity evaporated.

Slashdotted

[Doomedsnowball]

MEDIA CONTACT: Jonathan Sherwood (585) 273-4726, jonathan.sherwood@rochester.edu
January 6, 2006
Phase Change in Fluids Finally Simulated After Decades of Effort
Eldred Chimowitz and Yonathan Shapir

Everyone knows what happens to water when it boils--everyone, that is, except computers. Modeling the transformation process of matter moving from one phase to another, such as from liquid to gas, has been all but impossible near the critical point. This is due to the increasingly complex way molecules behave as they approach the change from one phase to another. Researchers at the University of Rochester, however, have now created a mathematical model that will allow scientists to simulate and understand phase changes, which could have an impact on everything from decaffeinating coffee to improving fuel cell efficiency in automobiles of the future. The findings have been published in Physical Review Letters.

"This problem has baffled scientists for decades," says Yonathan Shapir, professor of physics and chemical engineering at the University of Rochester, and co-author of the paper. "This is the first time a computer program could simulate a phase transition because the computers would always bog down at what's known as the 'critical slowdown.' We figured out a way to perform a kind of end-run around that critical point slowdown and the results allow us to calculate certain critical point properties for the first time."

"Critical slowdown" is a phenomenon that happens as matter moves from one phase to another near the critical point. As molecules in a gas, for instance, are cooled, they lose some of their motion, but are still moving around and bumping into each other. As the temperature drops to where the gas will change into a liquid, the molecules' motion becomes correlated, or connected, across larger and larger distances. That correlation is a bit like deciding where to go to dinner--quick and easy with two people, but takes forever for a group of 20 to take action. The broadening correlation dramatically increases the time it takes for the gas to reach an overall equilibrium, and that directly leads to an increase in computing time required, approaching infinity and bogging down as the gas crosses the point of phase change.

To illustrate the effect, imagine a perfectly pure and still lake. If you drop a pebble into this lake, its ripples would spread outward, dissipating until the lake had returned to a calm equilibrium again. But, if you were to take this impossibly perfect lake just barely above the critical point and drop your pebble, the ripples would remain as ripples much longer--likely bouncing off the distant shores. This imaginary lake would take seemingly forever to return to its calm equilibrium again.

The research team of Shapir, Eldred Chimowitz, professor in the Department of Chemical Engineering, and physics graduate student Subhranil De created a novel approach to tackle the phase-change process. They devised a computational model consisting of two separate reservoirs of fluid at equilibrium and near the critical point threshold. One reservoir was slightly more pressurized than its neighbor. The reservoirs were opened to each other and the pressure difference caused the fluids to mix. The team let the simulation run until the entire system reached thermodynamic equilibrium. By watching the rate that equilibrium returned, the team was able to calculate the behavior at the critical point. Their simulation findings match predictions and experimental results, including very precise measurements performed in microgravity on the Space Shuttle.

"In principle, it's a difficult calculation," says Chimowitz. "Fluid systems require a different class of models than the common lattice models used by researchers who have studied dynamic critical behavior. These different classes give rise to different dynamic critical exponents and we found them, for the first time, in real fluid systems."

The best known examples of phase changes are perhaps water to ice and

Re:Phase Change and Complexity

[wass]

The article says :

"This is the first time a computer program could simulate a phase transition because the computers would always bog down at what's known as the 'critical slowdown.' We figured out a way to perform a kind of end-run around that critical point slowdown and the results allow us to calculate certain critical point properties for the first time."

There have been previous methods to look at systems arbitrarily close to the critical point in phase transitions, and the article is misleading when it says this area has been off-limits to computers. I haven't read the actual Physical Review Letters article, but it appears the authors have come up with a novel algorithm, perhaps more ideally suited for fluids, to overcome critical slowdown. But this is not the first such algorithm, and there has been loads of prior computer simulation of phase transitions and critical phenomena to boot.

For example, in the Ising Model or the Potts Model, one can examine system parameters arbitrarily close to the critical point, in finite time, using a Cluster Algorithm. This page gives some information on how the cluster algorithm. The page has a java applet graphically depicting the system for a variety of algorithms.

Just for completeness, here's an Ising model applet that I wrote, which doesn't just have a system animation, but allows you to calculate and plot data (specific heat, magnetization, etc) as the system passes through the critical point. This applet uses the Metropolis algorithm for time advancement, hence it is subject to critical slowdown. In that respect, the applet is flawed because close to the critical point I don't generate enough Metropolis iterations to ensure the subsequent frame is sufficiently thermally indepdent from the previous state. However, the cluster algorithm would remove these limitations. This applet has actually been used in graduate physics classes at Johns Hopkins to demonstrate magnetic phase transitions.

And also for completeness, here's a Potts model applet, but it doesn't acquire data for plotting like the Ising model. The Potts applet actually uses the Microcanonical ensemble, whereby the energy of the system is conserved, but the Ising applet uses the Canonical ensemble, where the system is in contact with a heat bath at some settable temperature.

And in case anyone's curious, these applets (except for the first one) are part of the Java Virtual Physics Lab , which contains a few different physics java simulations I wrote to help with conceptual understanding.