Monday, August 10th, 2020

Time	Event
11:00a	3 Questions: Asegun Henry on five “grand thermal challenges” to stem the tide of global warming More than 90 percent of the world’s energy use today involves heat, whether for producing electricity, heating and cooling buildings and vehicles, manufacturing steel and cement, or other industrial activities. Collectively, these processes emit a staggering amount of greenhouse gases into the environment each year. Reinventing the way we transport, store, convert, and use thermal energy would go a long way toward avoiding a global rise in temperature of more than 2 degrees Celsius — a critical increase that is predicted to tip the planet into a cascade of catastrophic climate scenarios. But, as three thermal energy experts write in a letter published today in Nature Energy, “Even though this critical need exists, there is a significant disconnect between current research in thermal sciences and what is needed for deep decarbonization.” In an effort to motivate the scientific community to work on climate-critical thermal issues, the authors have laid out five thermal energy “grand challenges,” or broad areas where significant innovations need to be made in order to stem the rise of global warming. MIT News spoke with Asegun Henry, the lead author and the Robert N. Noyce Career Development Associate Professor in the Department of Mechanical Engineering, about this grand vision. Q: Before we get into the specifics of the five challenges you lay out, can you say a little about how this paper came about, and why you see it as a call to action? A: This paper was born out of this really interesting meeting, where my two co-authors and I were asked to meet with Bill Gates and teach him about thermal energy. We did a several-hour session with him in October of 2018, and when we were leaving, at the airport, we all agreed that the message we shared with Bill needs to be spread much more broadly. This particular paper is about thermal science and engineering specifically, but it’s an interdisciplinary field with lots of intersections. The way we frame it, this paper is about five grand challenges that if solved, would literally alter the course of humanity. It’s a big claim — but we back it up. And we really need this to be declared as a mission, similar to the declaration that we were going to put a man on the moon, where you saw this concerted effort among the scientific community to achieve that mission. Our mission here is to save humanity from extinction due to climate change. The mission is clear. And this is a subset of five problems that will get us the majority of the way there, if we can solve them. Time is running out, and we need all hands on deck.  Q: What are the five thermal energy challenges you outline in your paper? A: The first challenge is developing thermal storage systems for the power grid, electric vehicles, and buildings. Take the power grid: There is an international race going on to develop a grid storage system to store excess electricity from renewables so you can use it at a later time. This would allow renewable energy to penetrate the grid. If we can get to a place of fully decarbonizing the grid, that alone reduces carbon dioxide emissions from electricity production by 25 percent. And the beauty of that is, once you decarbonize the grid you open up decarbonizing the transportation sector with electric vehicles. Then you’re talking about a 40 percent reduction of global carbon emissions. The second challenge is decarbonizing industrial processes, which contribute 15 percent of global carbon dioxide emissions. The big actors here are cement, steel, aluminum, and hydrogen. Some of these industrial processes intrinsically involve the emission of carbon dioxide, because the reaction itself has to release carbon dioxide for it to work, in the current form. The question is, is there another way? Either we think of another way to make cement, or come up with something different. It’s an extremely difficult challenge, but there are good ideas out there, and we need way more people thinking about this. The third challenge is solving the cooling problem. Air conditioners and refrigerators have chemicals in them that are very harmful to the environment, 2,000 times more harmful than carbon dioxide on a molar basis. If the seal breaks and that refrigerant gets out, that little bit of leakage will cause global warming to shift significantly. When you account for India and other developing nations that are now getting access to electricity infrastructures to run AC systems, the leakage of these refrigerants will become responsible for 15 to 20 percent of global warming by 2050. The fourth challenge is long-distance transmission of heat. We transmit electricity because it can be transmitted with low loss, and it’s cheap. The question is, can we transmit heat like we transmit electricity? There is an overabundance of waste heat available at power plants, and the problem is, where the power plants are and where people live are two different places, and we don’t have a connector to deliver heat from these power plants, which is literally wasted. You could satisfy the entire residential heating load of the world with a fraction of that waste heat. What we don’t have is the wire to connect them. And the question is, can someone create one? The last challenge is variable conductance building envelopes. There are some demonstrations that show it is physically possible to create a thermal material, or a device that will change its conductance, so that when it’s hot, it can block heat from getting through a wall, but when you want it to, you could change its conductance to let the heat in or out. We’re far away from having a functioning system, but the foundation is there. Q: You say that these five challenges represent a new mission for the scientific community, similar to the mission to land a human on the moon, which came with a clear deadline. What sort of timetable are we talking about here, in terms of needing to solve these five thermal problems to mitigate climate change? A: In short, we have about 20 to 30 years of business as usual, before we end up on an inescapable path to an average global temperature rise of over 2 degrees Celsius. This may seem like a long time, but it’s not when you consider that it took natural gas 70 years to become 20 percent of our energy mix. So imagine that now we have to not just switch fuels, but do a complete overhaul of the entire energy infrastructure in less than one third the time. We need dramatic change, not yesterday, but years ago. So every day I fear we will do too little too late, and we as a species may not survive Mother Earth’s clapback. (Comment on this)
4:00p	Data systems that learn to be better Big data has gotten really, really big: By 2025, all the world’s data will add up to an estimated 175 trillion gigabytes. For a visual, if you stored that amount of data on DVDs, it would stack up tall enough to circle the Earth 222 times.  One of the biggest challenges in computing is handling this onslaught of information while still being able to efficiently store and process it. A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) believe that the answer rests with something called “instance-optimized systems.”   Traditional storage and database systems are designed to work for a wide range of applications because of how long it can take to build them — months or, often, several years. As a result, for any given workload such systems provide performance that is good, but usually not the best. Even worse, they sometimes require administrators to painstakingly tune the system by hand to provide even reasonable performance.  In contrast, the goal of instance-optimized systems is to build systems that optimize and partially re-organize themselves for the data they store and the workload they serve.  “It’s like building a database system for every application from scratch, which is not economically feasible with traditional system designs,” says MIT Professor Tim Kraska.  As a first step toward this vision, Kraska and colleagues developed Tsunami and Bao. Tsunami uses machine learning to automatically re-organize a dataset’s storage layout based on the types of queries that its users make. Tests show that it can run queries up to 10 times faster than state-of-the-art systems. What’s more, its datasets can be organized via a series of "learned indexes" that are up to 100 times smaller than the indexes used in traditional systems.  Kraska has been exploring the topic of learned indexes for several years, going back to his influential work with colleagues at Google in 2017.  Harvard University Professor Stratos Idreos, who was not involved in the Tsunami project, says that a unique advantage of learned indexes is their small size, which, in addition to space savings, brings substantial performance improvements. “I think this line of work is a paradigm shift that’s going to impact system design long-term,” says Idreos. “I expect approaches based on models will be one of the core components at the heart of a new wave of adaptive systems.” Bao, meanwhile, focuses on improving the efficiency of query optimization through machine learning. A query optimizer rewrites a high-level declarative query to a query plan, which can actually be executed over the data to compute the result to the query. However, often there exists more than one query plan to answer any query; picking the wrong one can cause a query to take days to compute the answer, rather than seconds.  Traditional query optimizers take years to build, are very hard to maintain, and, most importantly, do not learn from their mistakes. Bao is the first learning-based approach to query optimization that has been fully integrated into the popular database management system PostgreSQL. Lead author Ryan Marcus, a postdoc in Kraska’s group, says that Bao produces query plans that run up to 50 percent faster than those created by the PostgreSQL optimizer, meaning that it could help to significantly reduce the cost of cloud services, like Amazon’s Redshift, that are based on PostgreSQL. By fusing the two systems together, Kraska hopes to build the first instance-optimized database system that can provide the best possible performance for each individual application without any manual tuning.  The goal is to not only relieve developers from the daunting and laborious process of tuning database systems, but to also provide performance and cost benefits that are not possible with traditional systems. Traditionally, the systems we use to store data are limited to only a few storage options and, because of it, they cannot provide the best possible performance for a given application. What Tsunami can do is dynamically change the structure of the data storage based on the kinds of queries that it receives and create new ways to store data, which are not feasible with more traditional approaches. Johannes Gehrke, a managing director at Microsoft Research who also heads up machine learning efforts for Microsoft Teams, says that his work opens up many interesting applications, such as doing so-called “multidimensional queries” in main-memory data warehouses. Harvard’s Idreos also expects the project to spur further work on how to maintain the good performance of such systems when new data and new kinds of queries arrive. Bao is short for “bandit optimizer,” a play on words related to the so-called “multi-armed bandit” analogy where a gambler tries to maximize their winnings at multiple slot machines that have different rates of return. The multi-armed bandit problem is commonly found in any situation that has tradeoffs between exploring multiple different options, versus exploiting a single option — from risk optimization to A/B testing. “Query optimizers have been around for years, but they often make mistakes, and usually they don’t learn from them,” says Kraska. “That’s where we feel that our system can make key breakthroughs, as it can quickly learn for the given data and workload what query plans to use and which ones to avoid.” Kraska says that in contrast to other learning-based approaches to query optimization, Bao learns much faster and can outperform open-source and commercial optimizers with as little as one hour of training time.In the future, his team aims to integrate Bao into cloud systems to improve resource utilization in environments where disk, RAM, and CPU time are scarce resources. “Our hope is that a system like this will enable much faster query times, and that people will be able to answer questions they hadn’t been able to answer before,” says Kraska. A related paper about Tsunami was co-written by Kraska, PhD students Jialin Ding and Vikram Nathan, and MIT Professor Mohammad Alizadeh. A paper about Bao was co-written by Kraska, Marcus, PhD students Parimarjan Negi and Hongzi Mao, visiting scientist Nesime Tatbul, and Alizadeh. The work was done as part of the Data System and AI Lab (DSAIL@CSAIL), which is sponsored by Intel, Google, Microsoft, and the U.S. National Science Foundation.  (Comment on this)
11:59p	How airplanes counteract St. Elmo’s Fire during thunderstorms At the height of a thunderstorm, the tips of cell towers, telephone poles, and other tall, electrically conductive structures can spontaneously emit a flash of blue light. This electric glow, known as a corona discharge, is produced when the air surrounding a conductive object is briefly ionized by an electrically charged environment. For centuries, sailors observed corona discharges at the tips of ship masts during storms at sea. They coined the phenomenon St. Elmo’s fire, after the patron saint of sailors. Scientists have found that a corona discharge can strengthen in windy conditions, glowing more brightly as the wind further electrifies the air. This wind-induced intensification has been observed mostly in electrically grounded structures, such as trees and towers. Now aerospace engineers at MIT have found that wind has an opposite effect on ungrounded objects, such as airplanes and some wind turbine blades. In some of the last experiments performed in MIT’s Wright Brothers Wind Tunnel before it was dismantled in 2019, the researchers exposed an electrically ungrounded model of an airplane wing to increasingly strong wind gusts. They found that the stronger the wind, the weaker the corona discharge, and the dimmer the glow that was produced. The team’s results appear in the Journal of Geophysical Research: Atmospheres. The study’s lead author is Carmen Guerra-Garcia, an assistant professor of aeronautics and astronautics at MIT. Her co-authors at MIT are Ngoc Cuong Nguyen, a senior research scientist; Theodore Mouratidis, a graduate student; and Manuel Martinez-Sanchez, a post-tenure professor of aeronautics and astronautics. Electric friction Within a storm cloud, friction can build up to produce extra electrons, creating an electric field that can reach all the way to the ground. If that field is strong enough, it can break apart surrounding air molecules, turning neutral air into a charged gas, or plasma. This process most often occurs around sharp, conductive objects such as cell towers and wing tips, as these pointed structures tend to concentrate the electric field in a way that electrons are pulled from surrounding air molecules toward the pointed structures, leaving behind a veil of positively charged plasma immediately around the sharp object. Once a plasma has formed, the molecules within it can begin to glow via the process of corona discharge, where excess electrons in the electric field ping-pong against the molecules, knocking them into excited states. In order to come down from those excited states, the molecules emit a photon of energy, at a wavelength that, for oxygen and nitrogen, corresponds to the characteristic blueish glow of St. Elmo’s fire. In previous laboratory experiments, scientists found that this glow, and the energy of a corona discharge, can strengthen in the presence of wind. A strong gust can essentially blow away the positively charged ions, that were locally shielding the electric field and reducing its effect — making it easier for electrons to trigger a stronger, brighter glow. These experiments were mostly carried out with electrically grounded structures, and the MIT team wondered whether wind would have the same strengthening effect on a corona discharge that was produced around a sharp, ungrounded object, such as an airplane wing. To test this idea, they fabricated a simple wing structure out of wood and wrapped the wing in foil to make it electrically conductive. Rather than try to produce an ambient electric field similar to what would be generated in a thunderstorm, the team studied an alternative configuration in which the corona discharge was  generated in a metal wire running parallel to the length of the wing, and connecting a small high-voltage power source between wire and wing. They fastened the wing to a pedestal made from an insulating material that, because of its nonconductive nature, essentially made the wing itself electrically suspended, or ungrounded. The team placed the entire setup in MIT’s Wright Brothers Wind Tunnel, and subjected it to increasingly higher velocities of wind, up to 50 meters per second, as they also varied the amount of voltage that they applied to the wire. During these tests, they measured the amount of electrical charge building up in the wing, the current of the corona and also used an ultraviolet-sensitive camera to observe the brightness of the corona discharge on the wire. Scientists observe the ion “glow” of corona discharge in an electrically ungrounded object (left) compared to a grounded object (right). Courtesy of the researchers In the end, they found that the strength of the corona discharge and its resulting brightness decreased as the wind increased — a surprising and opposite effect from what scientists have seen for wind acting on grounded structures. Pulled against the wind The team developed numerical simulations to try and explain the effect, and found that, for ungrounded structures, the process is largely similar to what happens with grounded objects — but with something extra. In both cases, the wind is blowing away the positive ions generated by the corona, leaving behind a stronger field in the surrounding air. For ungrounded structures, however, because they are electrically isolated, they become more negatively charged. This results in a weakening of  the positive corona discharge. The amount of negative charge that the wing retains is set by the competing effects of positive ions blown by the wind and those attracted and pulled back as a result of the negative excursion. This secondary effect, the researchers found, acts to weaken the local electric field, as well as the corona discharge’s electric glow. “The corona discharge is the first stage of lightning in general,” Guerra-Garcia says. “How corona discharge behaves is important and kind of sets the stage for what could happen next in terms of electrification.” In flight, aircraft such as planes and helicopters inherently produce wind, and a glow corona system like the one tested in the wind tunnel could actually be used to control the electrical charge of the vehicle. Connecting to some prior work by the team, she and her colleagues previously showed that if a plane could be negatively charged, in a controlled fashion, the plane’s risk of being struck by lightning could be reduced. The new results show that charging of an aircraft in flight to negative values can be achieved using a controlled positive corona discharge. ‘’The exciting thing about this study is that, while trying to demonstrate that the electrical charge of an aircraft can be controlled using a corona discharge, we actually discovered that classical theories of corona discharge in wind do not apply for airborne platforms, that are electrically isolated from their environment,” Guerra-Garcia says. “Electrical breakdown occurring in aircraft really presents some unique features that do not allow the direct extrapolation from ground studies.” This research was funded, in part, by The Boeing Company, through the Strategic Universities for Boeing Research and Technology Program. (Comment on this)

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