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 THE UNIVERSITY OF WISCONSIN-MADISON

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Mechanical Engineering

Justin Madsen, Professor Dan Negrut, Yakira Braden and Toby Heyn

Assistant Professor Dan Negrut (foreground) with students (from left) Justin Madsen, Yakira Braden and Toby Heyn. (large image)

Uncovering the real dirt
on granular flow

A handful of sand contains countless grains, which interact with each other via friction and impact forces as they slip through your fingers. When a handful becomes a load in an excavator bucket, those interactions multiply exponentially.

By solving large sets of differential equations, researchers can predict how sand or other granular material will move. Assistant Professor Dan Negrut and his team at the UW-Madison Simulation-Based Engineering Laboratory are developing innovative computer simulation methods for parallel computers to analyze granular material motion much faster than is possible with current technologies.

Even a supercomputer takes days to run a simulation charting the motion of millions of sand grains. Negrut hopes his simulation will analyze millions of grains in a single day, if not a matter of hours.

The difference lies in how parallel computers approach the task. The central processing unit of a regular computer processes information sequentially, so grains are analyzed one after another. Parallel computers rely on the graphics-processing unit (GPU), which can simultaneously execute one command multiple times. This is how a graphics card processes pixels to render scene after scene in video games.

Negrut uses GPU computation to determine in-parallel sand movement. He and his students assembled a fast computer from scratch that handles almost 50,000 parallel computational threads at any given time.

Understanding the dynamics of granular material has a variety of applications, especially for improving vehicle designs. Beyond vehicle applications, researchers could use such simulations to study atomic particles, pebble-bed nuclear reactors, pressure in silos and crystals in prescription pills. The National Science Foundation and U.S. Army subcontracts support the work. NVIDIA Corporation, a GPU manufacturer, is also a sponsor.

Mirror image: Self-assembling micro tiles
look promising as optical devices

Associate Professor Tom Krupenkin is developing materials with multiple personalities. With Senior Scientist J. Ashley Taylor and colleagues at Bell Labs, Alcatel-Lucent, Krupenkin is exploring new ways for liquids and solids to interact.

In addition to developing “nanonails” that repel liquid totally until voltage is added (read more on the inside cover), Krupenkin’s team has developed microscale liquid mirrors. When voltage is applied, these micromirrors can change their focal distance and position. They maintain their reflectivity even when shaken or deformed.

To make a micromirror, the researchers use gold-covered silicon wafers to fabricate hexagonally shaped micro-tiles. Sandwiched between oil and water, these tiles—dubbed “Janus tiles” by the team—self-assemble into a highly reflective micromirror. When introduced into the liquids, the tiles flip back and forth between their hydrophilic and hydrophobic sides, eventually settling into a honeycomb shape that covers the concave curve of the liquid like a carpet.

Similar optofluidic devices known as liquid lenses now are used in some cell phones and disposable cameras. Unfortunately, those lenses require the refractive index contrast between two liquids to be very high, limiting their applications. A mirror does not have such restrictions, but it is challenging to form a mirror out of liquid. The best reflector is liquid mercury, a toxic substance—and Krupenkin and his colleagues developed the Janus tiles as a safe alternative.

By varying voltages and tile types, Krupenkin could develop a new family of optical devices. Applications could include projectors able to cast images on curved or moving surfaces, or projectors small enough to fit in a cell phone. Other applications might be optoelectronic devices such as light detectors or homogenizers that create more uniform laser beams.

Shape optimization software
makes thin components easier to model

When UW-Madison vehicle teams design custom parts, they start by making a computer model. The 3-D modeling software they use, which incorporates finite element analysis, will simulate, for example, the effect of fatigue loading or rapid acceleration on various parts.

The standard software works until the team tries to apply it to thin parts, like chassis or other beam-like components. Thin parts are notoriously difficult to design because current technologies rely on processes meant to analyze objects with three closely matching dimensions. Also, even a minor design change warrants a painstaking reanalysis.

Associate Professor Krishnan Suresh is developing the next generation of shape optimization software to make the design process for thin structures and other geometrically complex shapes more efficient and sophisticated—meaning engineers easily can design parts with varying thicknesses or geometries.

Supported by a 2008 Faculty Early Career Development Award (CAREER) from the National Science Foundation, Suresh and his team are creating a new mathematical framework based on two innovative concepts: feature sensitivity and dual representation.

Feature sensitivity allows design changes to be made efficiently. Currently, if a small change is made to an approved design, it can take weeks or months to reanalyze and verify the entire design. An engineer using feature sensitivity could add a rivet to a completed design and know immediately how the stresses or frequency of the object changed.

Dual representation blends 3-D geometry with 1-D physics, giving engineers working with thin structures the best of both modeling options.

New shape optimization technology has cross-disciplinary, industry and military applications. The UW-Madison SAE formula and hybrid vehicle teams will be the first case studies, which is a win-win situation: While Suresh tests his software, students will learn the underlying concepts of shape optimization and create cutting-edge vehicle designs.

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