MIT News: MIT Develops A Continuum Model That Predicts The Flow of Granular Materials Like Sand

Sand is composed of finely divided rock and mineral particles. It is naturally occuring and granular. The actual composition of sand is highly variable, depending on the local rock sources and conditions, but the most common constituent of sand is silica (silicon dioxide, or SiO2), usually in the form of quartz.

Shifting sands
New model predicts how sand and other granular materials flow.

CAMBRIDGE, Mass. -- Sand in an hourglass might seem simple and straightforward, but such granular materials are actually tricky to model. From far away, flowing sand resembles a liquid, streaming down the center of an hourglass like water from a faucet. But up close, one can make out individual grains that slide against each other, forming a mound at the base that holds its shape, much like a solid.

Sand’s curious behavior — part fluid, part solid — has made it difficult for researchers to predict how it and other granular materials flow under various conditions. A precise model for granular flow would be particularly useful in optimizing processes such as pharmaceutical manufacturing and grain production, where tiny pills and grains pour through industrial chutes and silos in mass quantities. When they aren’t well-controlled, such large-scale flows can cause blockages that are costly and sometimes dangerous to clear.

Now Ken Kamrin of MIT’s Department of Mechanical Engineering has come up with a model that predicts the flow of granular materials under a variety of conditions. The model improves on existing models by taking into account one important factor: how the size of a grain affects the entire flow. Kamrin used the new model to predict sand flow in several configurations — including a chute and a circular trough — and found that the model’s predictions were a near-perfect match with actual results. A paper detailing the new model will appear in the journal Physical Review Letters.

“The basic equations governing water flow have been known for over a century,” says Kamrin, the Class of ’56 Career Development Assistant Professor of Mechanical Engineering. “There hasn’t been something similar for sand, where I can give you a cupful of sand, and tell you which equations will be necessary to predict how it will squish around if I squeeze the cup.”

MIT News: Smart Sand Capable of Shaping Itself Being Developed

Marvel comics has a reformed supervillain called The Sandman (Not to be confused with another Sandman of DC). Because of a freak accident, he can transform his whole body into sand. With this ability, in "sand form" he can manipulate his body into various shapes and tools. This character was featured in the movie, Spiderman 3

Researchers at MIT are now looking into the advantages of using sand to do exactly the same thing as Sandman can do, but in real world scenarios: Sand that can automatically mold and sculpt itself into any object.

Self-sculpting sand

New algorithms could enable heaps of ‘smart sand’ that can assume any shape, allowing spontaneous formation of new tools or duplication of broken mechanical parts.

Imagine that you have a big box of sand in which you bury a tiny model of a footstool. A few seconds later, you reach into the box and pull out a full-size footstool: The sand has assembled itself into a large-scale replica of the model.

That may sound like a scene from a Harry Potter novel, but it’s the vision animating a research project at the Distributed Robotics Laboratory (DRL) at MIT’s Computer Science and Artificial Intelligence Laboratory. At the IEEE International Conference on Robotics and Automation in May — the world’s premier robotics conference — DRL researchers will present a paper describing algorithms that could enable such “smart sand.” They also describe experiments in which they tested the algorithms on somewhat larger particles — cubes about 10 millimeters to an edge, with rudimentary microprocessors inside and very unusual magnets on four of their sides.

Unlike many other approaches to reconfigurable robots, smart sand uses a subtractive method, akin to stone carving, rather than an additive method, akin to snapping LEGO blocks together. A heap of smart sand would be analogous to the rough block of stone that a sculptor begins with. The individual grains would pass messages back and forth and selectively attach to each other to form a three-dimensional object; the grains not necessary to build that object would simply fall away. When the object had served its purpose, it would be returned to the heap. Its constituent grains would detach from each other, becoming free to participate in the formation of a new shape.

Distributed intelligence

Algorithmically, the main challenge in developing smart sand is that the individual grains would have very few computational resources. “How do you develop efficient algorithms that do not waste any information at the level of communication and at the level of storage?” asks Daniela Rus, a professor of computer science and engineering at MIT and a co-author on the new paper, together with her student Kyle Gilpin. If every grain could simply store a digital map of the object to be assembled, “then I can come up with an algorithm in a very easy way,” Rus says. “But we would like to solve the problem without that requirement, because that requirement is simply unrealistic when you’re talking about modules at this scale.” Furthermore, Rus says, from one run to the next, the grains in the heap will be jumbled together in a completely different way. “We’d like to not have to know ahead of time what our block looks like,” Rus says.

MIT News: The Future of Battery Technology: Liquid Metal Energy

MIT Research: Liquid batteries for utilities could make renewables competitive

CAMBRIDGE, MA) -- The biggest drawback to many real or proposed sources of clean, renewable energy is their intermittency: The wind doesn’t always blow, the sun doesn’t always shine, and so the power they produce may not be available at the times it’s needed. A major goal of energy research has been to find ways to help smooth out these erratic supplies.

New results from an ongoing research program at MIT, reported in the Journal of the American Chemical Society, show a promising technology that could provide that long-sought way of leveling the load — at far lower cost and with greater longevity than previous methods. The system uses high-temperature batteries whose liquid components, like some novelty cocktails, naturally settle into distinct layers because of their different densities.

The three molten materials form the positive and negative poles of the battery, as well as a layer of electrolyte — a material that charged particles cross through as the battery is being charged or discharged — in between. All three layers are composed of materials that are abundant and inexpensive, explains Donald Sadoway, the John F. Elliott Professor of Materials Chemistry at MIT and the senior author of the new paper.

“We explored many chemistries,” Sadoway says, looking for the right combination of electrical properties, abundant availability and differences in density that would allow the layers to remain separate. His team has found a number of promising candidates, he says, and is publishing their detailed analysis of one such combination: magnesium for the negative electrode (top layer), a salt mixture containing magnesium chloride for the electrolyte (middle layer) and antimony for the positive electrode (bottom layer). The system would operate at a temperature of 700 degrees Celsius, or 1,292 degrees Fahrenheit.

MIT NEWS: The faster-than-fast Fourier transform

CAMBRIDGE, Mass. -- The Fourier transform is one of the most fundamental concepts in the information sciences. It’s a method for representing an irregular signal — like the voltage fluctuations in the wire that connects an MP3 player to a loudspeaker — as a combination of pure frequencies. It’s universal in signal processing, but it can also be used to compress image and audio files, solve differential equations, and price stock options, among other things.

The reason the Fourier transform is so prevalent is an algorithm called the fast Fourier transform (FFT), devised in the mid-1960s, which made it practical to calculate Fourier transforms on the fly. Ever since the FFT was proposed, however, people have wondered whether an even faster algorithm could be found.

At the 2012 Association for Computing Machinery’s Symposium on Discrete Algorithms (SODA), a group of MIT researchers will present a new algorithm that, in a large range of practically important cases, improves on the fast Fourier transform. Under some circumstances, the improvement can be dramatic — a tenfold increase in speed. The new algorithm could be particularly useful for image compression, enabling, say, smart phones to wirelessly transmit large video files without draining their batteries or consuming their monthly bandwidth allotments.

Like the FFT, the new algorithm works on digital signals. A digital signal is just a series of numbers — discrete samples of an analog signal, such as the sound of a musical instrument. The FFT takes a digital signal containing a certain number of samples and expresses it as the weighted sum of an equivalent number of frequencies.

MIT Research: Here Comes The Sun

A new sunflower-inspired pattern increases concentrated solar efficiency.

CAMBRIDGE, Mass. -- Just outside Seville, in the desert region of Andalucia, Spain, sits an oasis-like sight: a 100-meter-high pillar surrounded by rows of giant mirrors rippling outward. More than 600 of these mirrors, each the size of half a tennis court, track the sun throughout the day, concentrating its rays on the central tower, where the sun’s heat is converted to electricity — enough to power 6,000 homes.

The sprawling site, named PS10, is among a handful of concentrated solar power (CSP) plants in the world, although that number is expected to grow. CSP proponents say the technology could potentially generate enough clean, renewable energy to power the entire United States, provided two factors are in ample supply: land and sunlight.

Now researchers at MIT, in collaboration with RWTH Aachen University in Germany, have come up with a design that reduces the amount of land required to build a CSP plant, while increasing the amount of sunlight its mirrors collect. The researchers found that by rearranging the mirrors, or heliostats, in a pattern similar to the spirals on the face of a sunflower, they could reduce the pattern’s “footprint” by 20 percent and increase its potential energy generation. The sunflower-inspired pattern allows for a more compact layout, and minimizes heliostat shading and blocking by neighboring mirrors. The researchers published their results in the journal Solar Energy, and have recently filed for patent protection.