Technology

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Mon, 01/27/2025 - 13:14

Assistant Professor Areen Alsaid says the growing suite of semi-autonomous technologies have the ability to make driving safer, more convenient and less stressful. But we’ll only fully realize these benefits if the learning curve doesn’t confuse drivers.

Assistant Professor Areen Alsaid (right), pictured here with doctoral student Shiva Rasouli, has been using a driving simulator to study how drivers respond to interactions between driver assist features. Photo by Julianne Lindsey

Planning for EV infrastructure is complicated. Here’s a better way to do it.

lblouin — Wed, 22 Jan 2025 13:45:53 +0000

Planning for EV infrastructure is complicated. Here’s a better way to do it. lblouin Wed, 01/22/2025 - 08:45

Electric vehicles still represent less than 1% of registered vehicles in the U.S. and comprised just over 8% of new U.S. vehicle sales in 2024. But government officials across the country are already planning for a future in which EVs are the go-to mode of private transportation — as evidenced by increasingly large public investments in EV charging infrastructure, like the $7.5 billion pledged under the Biden administration. When it comes to actually making a plan for building out that infrastructure, however, the devil is in a complex web of largely unknown details, says Associate Professor of Industrial and Manufacturing Systems Engineering Jian Hu. Ideally, Hu says, you’d want to build a charging system that serves people’s needs for the next 10 years. The tricky part is that involves correctly anticipating a host of trendlines which are basically impossible to predict. “There are so many uncertainties,” Hu says. “We don’t know how fast the EV market will grow, which means we don’t know what the charging demand will be. Will the public want fast or slow charging? Will people charge at home or at work? During peak hours, or non-peak hours? Will utilities adopt dynamic pricing so it’s cheaper to charge at certain times of day? And how will this affect charging behavior? And what if there are new technologies that emerge? There are so many things we don’t know.”

Typically, when government agencies are planning for things like this, Hu says they might use what statisticians call a deterministic model. When you’re making this kind of model, you take account of what data you have, plug it into a formula that defines the relationship between the variables, and then you typically get a single answer, which then guides your plan of action. A simple retirement calculator, which takes your current age, retirement age, anticipated rate of return, the rate of inflation, and monthly savings target and tells you how much money you’ll have when you retire is a simple kind of deterministic model. But Hu argues that these kinds of prediction models aren’t the best tools when you’re dealing with complex situations with lots of uncertainty. “What if your rate of return on your investments isn’t the 7% you’ve put into that calculator? What if it is less and then you don’t have the money you expect when you retire? If you only use this kind of model, you’ll have this single prediction and you base everything on that. But you’re not preparing for a possible worst-case scenario.”

Because of this, statisticians often use different tools for forecasting complex, highly uncertain phenomena, like investment performance. One of the most popular is called stochastic modeling, which, instead of giving you just one answer, provides a range of results represented by thousands of different simulated scenarios in which the values and probabilities of the underlying variables are allowed to change. A popular type of stochastic model is a Monte Carlo simulation, which is used in financial planning. Unlike a simple retirement calculator, which assumes fixed values for things like the rate of inflation or a rate of return, a Monte Carlo analysis will run thousands of simulations in which all the variables you have in your model have different values and assigned probabilities. As a result, you get a much wider representation of possible outcomes, including best-case, worst-case and most likely scenarios. A Monte Carlo simulation might tell you, say, that in 98 percent of its simulated scenarios, which account for a wide range of possible economic conditions, your savings plans are going to get you to the end of your life with money in the bank. That might give you much more confidence in your investment strategy. You might even decide to take a more aggressive approach. Or, as Hu frames it, stochastic modeling gives us a much more complete way to understand risk.

Because stochastic models are so much better at helping us understand risk of uncertain events, Hu says they could be an excellent approach for planning EV infrastructure, given that reliable data on important details, like consumer charging preferences and future electricity demand, are sparse or lacking altogether. As part of a National Science Foundation-funded project, and in collaboration with Argonne National Laboratory, which is itself partnering with the Chicago Transit Authority, Hu will be creating novel approaches to stochastic modeling that he hopes can profoundly improve this planning process. To get just a little bit technical for a moment: Hu says one of the big challenges of stochastic modeling is coping with “distributional ambiguity,” which is where you’re lacking a lot of reliable information about the probability of key phenomena. Currently, one of the ways statisticians deal with this is a method called distributionally robust optimization, but Hu says DRO has a few limitations. One, it’s computationally intensive, which means as models get more complex, it becomes increasingly cumbersome and time consuming to run them and adapt them to new data. Second, DRO tends to hedge against worst-case scenarios and can therefore lead to overly conservative outcomes. Third, it's a machine learning-based process that is a “black box,” meaning it does not show how it arrives at its answers. It therefore might not be a great option for publicly funded agencies, who, in spending large sums of taxpayer dollars, could certainly benefit from transparent or interpretable models. Hu says his novel stochastic modeling strategy aims not only to improve on these limitations, but also provide more overall usability for public agencies, including models that can be more easily updated as better data emerge.

After developing the model, Hu is looking forward to a big field test toward the end of the project: helping the Chicago Transit Authority as it embarks on electrifying their massive fleet of public buses. Current electric bus battery technology generally provides a range of around 60 miles. But many of CTA’s current scheduled vehicle route blocks are much longer; nearly a third of weekday blocks are longer than 100 miles. CTA therefore envisions building out a bus-charging infrastructure that’s integrated with their garages and bus routes, which will also require enhancements to the local electric grid to accommodate the new electricity load. Figuring out where these grid modifications need to be made and the ideal placement for the charging stations in a way that harmonizes with the complex bus routes — which are likely to change in the future — is exactly the kind of complicated, ambiguous planning task Hu says his model can help with. Most importantly, it gives a government agency its best chance of spending limited public resources for EV charging as effectively as possible.

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Story by Lou Blouin

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Wed, 01/22/2025 - 13:40

Given a web of uncertainties, like future electricity price, consumer charging behavior and EV market growth, Associate Professor Jian Hu says a novel type of stochastic modeling can minimize the risks of public investments in EV infrastructure.

Associate Professor of Industrial and Manufacturing Systems Engineering Jian Hu is testing a new approach to planning charging infrastructure with the Chicago Transit Authority. Photo by Annie Barker

The challenges with younger drivers and autonomous vehicles

lblouin — Mon, 13 Jan 2025 15:28:25 +0000

The challenges with younger drivers and autonomous vehicles lblouin Mon, 01/13/2025 - 10:28

Autonomous vehicles promise a future of almost unimaginable driver convenience. After all, who wouldn't want to be able to watch a movie during a tedious stop-and-go rush hour commute? But proponents of AVs think the technology’s even more meaningful impact will be in the realm of safety, given that more than 90% of traffic accidents are thought to be the result of human error. Indeed, we’re already seeing some of the safety benefits as semi-autonomous driver assist features, like lane keep assist, blind spot monitoring and emergency braking, become commonplace on newer vehicles. Even so, the next big developmental leap to so-called Level 3 vehicles, which are capable of doing all the driving for us in certain situations and are now starting to enter American and European markets, could introduce a whole new set of safety and driver behavior challenges, says Associate Professor of Industrial and Manufacturing Systems Engineering Bochen Jia. That’s because Level 3 AVs still require full driver intervention when conditions are beyond the system’s capability — like when lane markers aren’t clearly marked or are obscured by weather; or in the event of system malfunction. That introduces a whole new type of driver experience, which the AV research community calls “takeover.” That’s the tricky liminal moment when a driver has to abruptly shift their focus from, say, watching their favorite Netflix series, to dealing with a potential road emergency.

Intuitively, takeover is a fraught, psychologically complex space, which is why Jia says a lot of research has been devoted to studying how drivers respond to this type of demand. For example, early research has indicated, somewhat counterintuitively, that the risk of driver fatigue actually increases when operating a Level 3 vehicle. It seems the mental task of constantly monitoring a vehicle doing the driving for us can actually be more draining than doing the driving ourselves. And in Jia’s lab, he’s been focusing on a neglected area of takeover research: younger, inexperienced drivers. From a research perspective, he says it’s a fascinating population. First, young people’s brains are still developing, particularly when it comes to attention resources and situational awareness, which can influence things like fatigue development and how well they respond to potentially hazardous situations, like takeover. In addition, younger people tend to, in general, be more trusting of technology, which could lead to less intense monitoring of the vehicle and undesirable takeover outcomes. Moreover, Jia says we might not be too far away from an era where young drivers’ only driving experience is on Level 3 vehicles. “That would mean they actually aren’t getting much experience doing actual driving, which could influence how well they respond to situations when the vehicle asks them to take over,” Jia says.

In focusing on younger drivers, Associate Professor of Industrial and Manufacturing Systems Engineering Bochen Jia has been exploring a neglected area of AV research. Photo by Annie Barker

For one of his latest projects, Jia has been digging into the particular issue of fatigue onset in younger, novice drivers. For this study, he recruited both drivers under the age of 19 who had limited driving experience and middle-aged drivers who had years of experience. Using a high-fidelity driving simulator, both sets of participants engaged in extended periods of autonomous driving and were instructed to take control of the vehicle when the autonomous mode was not safe or had failed. During their driving experience, Jia then introduced several types of takeover events to see how drivers would react. By combining physiological measures and self-reported assessments collected periodically during their driving task, Jia then monitored each set of participants for fatigue onset. The results were pretty interesting: Novice young adult drivers developed both physical and mental fatigue earlier than their middle-aged counterparts during extended periods of autonomous driving. "This is somewhat surprising to people because they think young people naturally have more energy," Jia explains. "However, it appears that the mental demands of autonomous driving, or the tendency of younger drivers to be more engaged in non-driving tasks during autonomous operation, may accelerate the onset of fatigue in younger drivers." Moreover, the takeover outcomes for fatigued drivers were often far from desirable. “Essentially, we were looking at how often participants would fail to prevent a collision,” Jia says. “And it happened more frequently than we had hoped.”

Jia says the results point to a need for highly effective fatigue warning systems for Level 3 AVs that have special considerations for younger, inexperienced drivers. Interestingly, Jia envisions this system would be most effective if it wasn’t just part of the vehicle, but integrated with other readily available wellness monitoring technologies, like wearable fitness trackers that monitor heart rates and sleep quality. “I don't think you can have a system that’s confined to the car — that’s not enough,” Jia says. “It should be part of your life monitoring — an overall system — because they don’t suddenly become a different person when they get in the car. With all the personal data monitoring technologies we have nowadays, we could easily identify younger drivers, and we likely have a lot of the data we would need.”

Next up, Jia says he plans to continue his research on fatigue onset with a study that puts participants in real automated vehicles within a closed testbed, such as the Mcity test facility. In addition, he has a similar project that is studying differences in distraction levels between younger, novice drivers and middle-aged experienced drivers. He hopes both studies will provide critical insights into improving the safety and usability of autonomous vehicle systems for drivers of all experience levels.

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Story by Lou Blouin. Want to learn more about Jia's work on driver fatigue? You can read the full-text of his recent article on the subject in the “Journal of Safety Research,” which was co-authored by Jia's student Yourui Tong, ��-Dearborn Associate Professor of Industrial and Manufacturing Systems Engineering Shan Bao, Tsinghua University Professor of Industrial Engineering Changxu Wu and ��-Dearborn Associate Professor of Psychology Nitya Sethuraman.

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Mon, 01/13/2025 - 15:22

Associate Professor Bochen Jia’s latest research is revealing some surprising things about how fatigue can impact younger, inexperienced drivers when they're operating semi-autonomous vehicles.

Associate Professor of Industrial and Manufacturing Systems Engineering Bochen Jia (right) and graduate student Darlington Egeonu check out the driving simulator Jia used for his most recent project on driver fatigue. Photo by Annie Barker

‘Healing’ batteries with ultrasonics

lblouin — Wed, 08 Jan 2025 17:59:20 +0000

‘Healing’ batteries with ultrasonics lblouin Wed, 01/08/2025 - 12:59

High-capacity batteries have emerged as an essential building block of the clean energy future, but it likely won’t be today’s lithium-ion batteries alone that get us there. That’s because, as powerful and ubiquitous as they are, lithium-ion batteries have some major limitations. For starters, they are very heavy — a fundamental quality that curbs the range of today’s electric vehicles and basically rules them out as an option for powering commercial aircraft. The world’s growing demand for the minerals needed to manufacture lithium-ion batteries also requires ever expanding mining operations, which have environmental, climate and geopolitical consequences. And on the safety front, the liquid electrolytes used in lithium-ion batteries are highly flammable, which is one reason why electric vehicle battery fires can be so catastrophic.

Because of these issues, researchers are developing new kinds of batteries, including solid-state batteries, which are lighter, can hold more energy for their weight and require fewer materials. They are also considered safer, since, as the name suggests, they don’t require a liquid electrolyte. But mechanical engineering postdoc research fellow Yaohong Xiao, who works with Associate Professor Lei Chen, says that last quality is both a blessing and a curse. Inside a typical lithium-ion battery, the liquid electrolyte is responsible for transferring charged particles back and forth between the cathode and anode sides of the battery, which is necessary both for charging and discharging. Because this electrolyte is a liquid, Xiao says it creates a nearly uniform interface between the two sides of the battery, since liquids naturally fill tiny nooks and crannies that might exist between the anode and cathode materials. In a solid-state battery, however, the electrolyte separating the anode and cathode sides is a strong, stiff, solid piece of material, and Xiao says that makes it more difficult to get really good contact between the two sides. “Essentially, you have solid on solid on solid,” Xiao explains. “Right after manufacturing, you might have no problem with this interface, but after a few cycles, or after the battery has experienced vibrations from being on the road, you start to get little voids in the interface so the electrolyte is no longer making perfect contact with both sides of the battery.” As a result, Xiao says a battery can develop zones of higher than usual current, which reduces its overall effectiveness.

Typically, Xiao says researchers have tried to solve this solid-state battery interface problem in a couple of different ways. First, they use pressure to basically squish all the components back together. Or they can use an “interlayer” material, which, kind of like double-sided tape, keeps the anode and cathode materials snug up against the solid electrolyte. But each approach has its limitations. Xiao says introducing interlayers to a process is typically expensive. That might not be a huge deal for experiments in a lab, but it would increase the already high costs of solid-state batteries when they’re being manufactured at scale. On the other hand, Xiao says using pressure to smooth out the interface is sort of like trying to squish two pieces of wood together. The rigidity of the lumber and any imperfections along the surfaces mean that pressure alone often isn’t enough to create perfect contact.

A couple years ago, Xiao began kicking around a sort of unconventional solution for this interface challenge. Xiao’s background is actually in metallurgy, not battery chemistry, and he saw this issue primarily as a question of how to get different metals to stick together. As it turns out, this is actually a pretty common problem in the metals universe, and one with a variety of well-established solutions. Specifically, Xiao was thinking that a technique called ultrasonic welding might be able to “heal” the voids in the interface, restoring uniform contact with the electrolyte. Ultrasonic healing, which is commonly deployed in a wide range of industries to weld pieces of plastic or thin pieces of metal together, uses high-frequency acoustic vibrations instead of high temperatures or solders to join materials together. The result is a highly uniform bond, but the process doesn’t use a whole lot of energy and can be done very quickly. Xiao worked with his postdoc colleague in Chen’s lab, XinXin Yao, who helped provide the theoretical feasibility for the welding concept, to set up an experiment, which revealed that ultrasonic welding could indeed nearly completely restore the uniformity of the electrolyte interface in as little as a minute. Moreover, the process required temperatures barely warmer than the water in your hot water heater and used about as much energy as an old-fashioned incandescent light bulb.

Xiao says the effectiveness of this metals-based approach came as a surprise to many of his colleagues, most of whom are experts in battery chemistry. Now, he’s hoping the results, which were recently published in “Advanced Energy Materials,” will help inspire other researchers to further explore the technique’s full potential. He says one possible application would be to use this as a tune-up strategy for eventual solid-state battery-powered EVs, which could come in for a quick ultrasonic healing treatment and get their optimal range back. And one other surprise finding from his experiment is that ultrasonic welding actually increased the conductivity of the electrolyte, albeit temporarily. That result was particularly intriguing to some colleagues at ��-Ann Arbor, who recently visited the newly established Battery Manufacturing and Testing Lab for a firsthand look. “They were very interested in this point,” Xiao says. “The conductivity would slowly recover after treatment, but they were thinking, what if we can fix that? What if we can figure out a way to not let it recover? So it’s very exciting to see this research already inspiring further work in this area.”

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Story by Lou Blouin

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Wed, 01/08/2025 - 17:58

Two mechanical engineering postdoc research fellows have discovered a novel way to solve a pesky challenge with next-generation solid-state batteries.

In Associate Professor of Mechanical Engineering Lei Chen's lab, postdoc research fellow Yaohong Xiao has been working on developing solid-state batteries, a safer, more energy dense alternative to today's lithium-ion batteries. Photo by Annie Barker

Class of Fall 2024: CECS graduate Dania Ammar

lblouin — Mon, 16 Dec 2024 16:46:13 +0000

Class of Fall 2024: CECS graduate Dania Ammar lblouin Mon, 12/16/2024 - 11:46

When Dania Ammar moved with her family from Beirut to southeast Michigan in 2017, her plan was to build on her civil engineering background and start the master’s in construction management program at ��-Ann Arbor. But some family circumstances led to her deferring her enrollment. As it happened, during the unexpected semester off, she reconnected with a friend from Lebanon who was studying mechanical engineering on the Dearborn campus. He had a lot of good things to say about the college, particularly how the research enterprise was growing quickly, giving graduate students a lot of opportunities. It was enough to pique Ammar’s interest. She got on the ��-Dearborn website, checked out the programs and research labs, particularly those in Industrial and Manufacturing Systems Engineering, and set up a meeting with then-College of Engineering and Computer Science Associate Dean for Undergraduate Education and current CECS Dean Ghassan Kridli. “Dean Kridli was very generous in giving me some time to talk with him about the programs and all the research that was going on at ��-Dearborn at that time. I decided this was definitely one of the best options,” Ammar says.

The following semester, Ammar decided to go for it — enrolling in the IMSE master’s program at ��-Dearborn in 2018. IMSE is a broad discipline, and Ammar recalls feeling very open to exploring all the possibilities. That first semester, she took a variety of classes and found an early champion in Associate Professor Jian Hu, who specializes in using data analytics and machine learning in risk management applications. “I had a very good math background and knew some programming, but I had no background in that field,” Ammar says. “Professor Hu provided me with all kinds of support, told me which books I should start reading, and gave me time to get accustomed to programming models that we were using. I learned so much and it was a phenomenal experience.” A little later in her master’s program, she crossed paths with Professor Shan Bao, a specialist in human factors who was helping develop a new master’s program in Human-Centered Design and Engineering, a field that roots engineering solutions in deep understandings of human needs. Ammar says a lot of people think of human factors as a psychology-based discipline — and it does draw on psychology and user feedback quite a bit. But with Bao’s work, Ammar saw how the discipline’s deepest potential lay in combining those insights with complex data analytics and even artificial intelligence. “You can’t really develop any product, whether it is something simple or something very complicated, like an automated vehicle, without going into the human factors aspects of it,” she says. “But I saw this isn’t just about psychology. It’s about figuring out ways to quantify the psychology — to measure human preferences and behaviors so you can build models that help you gain insights into those measures.”

Ammar loved working with Bao and chose to continue her journey at Dearborn with a PhD. For her dissertation research, she took on an ambitious multiphase project in transportation safety that explored one of the more fascinating emerging challenges related to autonomous vehicles: How will pedestrians learn to trust and safely interact with vehicles when humans aren’t doing the driving? Ammar says both pedestrians and drivers typically rely on an exchange of visual signals, like eye contact and waving, to negotiate who has the right of way, and absent a human driver, cars will presumably need some way of declaring their intentions. She began her work with a deep dive into road crash data, identifying the factors that lead to the most dangerous situations between pedestrians and human-driven vehicles in order to derive potentially problematic pedestrian-AV scenarios. She then embarked on building a cueing system designed to satisfy pedestrians' needs while interacting with AVs in these evaluation scenarios. That phase of her research led to several interesting conclusions. For example, Ammar discovered that pedestrians tend to favor technologies that closely mimic their interactions with human drivers, e.g. AVs that communicate a symbolic message, like the familiar flashing silhouette used at crosswalks, either directly on the vehicle or via crosswalk infrastructure (or both). She also investigated many fine-grain details, like whether a pedestrian’s age, gender, and driving and pedestrian behavior (conservative versus nonconservative) influenced their preferences for AV cueing. The final stage of her research involved creating a VR simulation, where she observed participants reacting in tricky situations, like an autonomous vehicle quickly approaching a red light before eventually stopping. By measuring how long pedestrians took to leave the curb and using physiological measures like pupil diameter, she could see which safety cues inspired trust or distrust. She’s hoping the results, which have led to several publications, will help other researchers, automakers and civil engineers as they design cueing systems for the era of autonomous vehicles.

Since officially finishing her PhD program, Ammar has switched gears a little bit, and in some ways, it’s a moment when her diverse studies are all coming together. Since August, she’s been working as a data science project engineer with Hottinger Brüel & Kjær, where she focuses on data analytics and machine learning-based solutions for a wide variety of industries. “These skills can be leveraged in any application, including civil engineering-related fields, which have changed a lot even in the short time since I was an undergraduate student,” Ammar says. “Let’s say you had a project and you needed insights about soil mechanics or wanted to predict settlements in the soil over time. In the past, we would have done that with a bunch of physics-based and numerical equations. But now, with more sensors being installed and collected data becoming available, researchers are developing machine learning-based models to answer those questions. That’s where the field is going now, and in the future, most engineering solutions will be built with data collection in mind so these models can keep getting better.”

Ammar now just has one finishing touch to put on her ��-Dearborn career: Walking across the commencement stage in December. She expects it’s going to be a pretty emotional moment. “��-Dearborn has been my home for the last seven years,” she says. “It’s only been a few months since I left, but to see everyone again is going to be very special. I’ve had the opportunity to work with so many different people, and I always felt, sincerely, that every day I spent with them was a chance to learn something new.”

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Story by Lou Blouin

Commencement

Student Success

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Mon, 12/16/2024 - 16:44

The recent PhD graduate almost pursued a career in construction management until ��-Dearborn helped her unlock a future in data analytics and artificial intelligence.

Since finishing her PhD, Dania Ammar has been working as a data science project engineer. She'll be putting the punctuation mark on her seven-year ��-Dearborn career on Saturday, when she walks across the commencement stage. Photo by Annie Barker

How organ-on-a-chip technology is changing research of human diseases

lblouin — Mon, 04 Nov 2024 17:25:26 +0000

How organ-on-a-chip technology is changing research of human diseases lblouin Mon, 11/04/2024 - 12:25

Those who study human disease, and those of us who benefit from treatments developed by their research, owe a great debt to mice. The tiny animals get many of the same diseases as us and have very similar genetics and biological processes, making them a useful stand-in for understanding what goes wrong in our bodies and how we might respond to novel therapies. But as a surrogate for humans, mice aren’t perfect, says Assistant Professor of Mechanical Engineering Aditya Raghunandan, who started at ��-Dearborn in 2023. All you have to do, he says, is look at the thousands of human clinical trials for new treatments that showed promise in mice but failed to deliver similar results in humans. Experimenting on human cells in the lab offers a promising alternative, because researchers can theoretically study diseases more directly. But, like mice, this technique has limitations: Raghunandan says how cells behave, isolated from their neighbors and living in an artificial environment in the lab, isn’t necessarily how they behave in our bodies.

In his early days as a researcher, Raghunandan often speculated that there had to be a better way, and as luck would have it, his career intersected an era of bioengineering in which some transformative new methods were emerging. In the early 2000s, researchers from the Wyss Institute at Harvard University developed a novel technology they dubbed “organ-on-a-chip.” Like traditional cell culturing, the idea was to create an experimental environment for human cells in which researchers could subject them to all kinds of things — genetic engineering, toxins, new drugs, mechanical and chemical signals — and then see how they behave. But their technique promised several advantages. Traditional cell cultures typically contain just one or two cell types, living in some kind of media, but that environment isn’t particularly representative of how things work in our bodies. For one, Raghunandan says our cells don’t just float around statically in goo; they're constantly being subjected to things like fluid flow and mechanical forces, which greatly influence their health and regulate their function. Moreover, a key part of cell function is interacting with other cell types. If you’re just observing how one cell type reacts to something in a Petri dish, he says you’re only getting a small slice of the picture.

Organ-on-a-chip technology, which has been tweaked and improved in the decades since its invention, directly addresses these shortcomings. Raghunandan says you can sort of think of the difference between an organ-on-a-chip and a traditional static cell culture like the difference between a house and a studio apartment. In a traditional cell culture, there’s just one room and everything is just kind of thrown in that room. But with an organ-on-a-chip, you can put up to three or four different cell types in different rooms within the house. Just as walls divide the rooms of the house, membranes keep the cells where you want them, and by tweaking the porosity of the membranes, you can also facilitate different kinds of interactions between cell types. Most importantly, tiny microfluidic channels, smaller than the width of a human hair, function like hallways, connecting the rooms, allowing researchers to pump in fluids to mechanically and chemically stimulate the cells in very precise ways.

Organs-on-a-chip are small devices that can do big things. In Raghunandan's lab, he uses them to study the dynamics of fluid flow in the brain that contribute to Alzheimer's disease.

The setup much more closely resembles how things work in our bodies, Raghunandan says. For example, in his own lab, where he studies how fluid flow in the brain impacts protein aggregation, one of the factors linked to neural diseases like Alzheimer’s, he builds layered organs-on-a-chip that mimic the way that neural and blood vessel tissues are organized in our brains. “If we go from the bloodstream into your brain, the first barrier are endothelial cells. And then the next layer of cells are smooth muscle cells, then you have an empty compartment where you have fluid, and then you have astrocytes,” he explains. “So the brain is layered, and we can reproduce these compartments and membranes and fluid flow where everything can interact with each other.” You can breed a mouse to have a predisposition to develop a certain disease. But you can’t manipulate fluid flow in its brain in real time, he says. “I can do that just by turning a knob on a pump.”

Being able to manipulate fluid flow is extremely important for Raghunandan’s current research. During his recent postdoc at the University of Rochester, he worked with the teams of Mechanical Engineering Professor Douglas Kelley and Neuroscience Professor Maiken Nedergaard, where they discovered that the brain actually has a separate “plumbing system” that bypasses the blood-brain barrier and flushes away waste while we sleep — almost like an alternative lymph system that only exists within the brain. Raghunandan says about half of the waste is physically flushed away, the way your plumbing removes waste from your house. But the other half requires specialized enzymes that are secreted by specific brain cells, like smooth muscle cells, which chop up or digest waste proteins. What’s surprising, Raghunandan says, is that abnormal fluid flow can actually change these cells' behavior in ways that make them less effective. That is, fluid flow in the brain isn’t just a plumbing system. It’s a dynamic that, in itself, can directly change cells and how they function.

Raghunadan says the research teams made these initial discoveries using mice models. But to investigate the details of how abnormal brain fluid flow was impacting Alzheimer's patients — and potentially develop therapeutics — he knew he’d need a different platform. This led to a fruitful collaboration with University of Rochester Biomedical Engineering Professor James McGrath, who had developed a new organ-on-a-chip technology to study inflammation in the brain. Now, Raghunadan is adapting that technology in his own lab to expose brain cells to varying types of fluid flow and precisely measure the effects. That’s something he could never do in a static cell culture or with mice. Raghunandan and McGrath have also created their own custom organ-on-a-chip devices that are much faster to build. “With the original design, it took a long time to build them — maybe a couple days to build 10 devices, and not all of them were going to be successful,” Raghunandan says. “We’ve streamlined the design, so now you can put together the parts like Legos and it takes three minutes.” McGrath even started a company so other researchers can use the snap-together version in their work.

Raghunandan, who’s one of only two researchers that he’s aware of at ��-Dearborn currently using this technique, sees some big practical benefits if this technology is more widely adopted. First, he says you could test new drugs on human cells in an organ-on-a-chip device to get some preliminary indication of their efficacy before moving them to full-blown human clinical trials. Second, we could use organs-on-a-chip to do patient-specific modeling for drugs. “If you had a certain disease, we could biopsy your cells, build a ‘you-on-a-chip’ and then test a drug to see if it had the potential to be a useful therapy for you,” he says.

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Story by Lou Blouin. Photos by Annie Barker.

Faculty Research

Research

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Mon, 11/04/2024 - 17:24

Assistant Professor of Mechanical Engineering Aditya Raghunandan explains how this technology offers a better platform than mice or traditional cell culturing for understanding the complex processes in our bodies.

Assistant Professor of Mechanical Engineering Aditya Raghunandan (right) talks with student researchers Sena Alenzi (center) and Michael Molloy in his bioengineering lab, where Raghunandan uses organ-on-a-chip technology to study Alzheimer's disease.

Research targets billion-dollar problem of counterfeit electronic components

lblouin — Fri, 30 Aug 2024 13:22:04 +0000

Research targets billion-dollar problem of counterfeit electronic components lblouin Fri, 08/30/2024 - 09:22

In early 2023, a mechanic at a Portuguese airline discovered something a little unusual while performing maintenance on a jet engine. A replacement damper designed to quiet mechanical vibrations was already showing signs of wear — despite the maintenance log showing the component had just recently been installed. The airline started digging into the issue and came to an alarming conclusion: The documentation provided with the replacement part had been faked — the part was a counterfeit. The discovery set off a wave that would ripple through the airline industry over the coming months, in which dozens of airlines, including all major U.S. carriers, discovered they had aircraft in the skies flying with counterfeit parts. Professor of Electrical and Computer Engineering Hafiz Malik says the airline scandal is hardly an isolated incident. This particular problem ended up being traced back to a shady supplier in London, but Malik says there are countless others in both the black and gray markets fueling a lucrative worldwide trade in counterfeit electronic components. Indeed, though it’s difficult to estimate, analysts think the market for things like knock-off batteries, motors, sensors and printed circuit boards is likely in the hundreds of billions of dollars. The dubious, subpar components are not just a costly headache for companies and consumers. They’re also a huge safety and cybersecurity issue for all stakeholders. “No one wants to fly in an airplane or drive a car that has counterfeit parts,” Malik says. “But the problem is so widespread that many of us probably have no choice.”

Moreover, Malik contends the old ways of countering counterfeit components are largely outdated. “Today, making counterfeit electronic parts is super easy compared to the old days,” he says. “With 3D printing and generative AI, you can recreate some parts almost to perfection. And serial numbers, or logos stamped on the parts, forget about it — those can be easily forged.” Even newer security features, like holograms, can be replicated now, says Malik. So he and a frequent collaborator, Associate Professor of Electrical and Computer Engineering Alireza Mohammadi, are working on a new system that could radically transform the transportation industry’s counterfeiting defenses. Rather than attaching something external to a component, like a serial number, stamp or hologram, the two researchers are attempting to harness the power of “digital fingerprints” that originate from within the components themselves. The core idea is that electronic devices, by their nature, create electrical outputs. And by closely analyzing these signals for, say, unique patterns of distortion that are particular to a device, they could tell if something is an authentic part or a knock-off, because the counterfeit would create a different electronic fingerprint. Malik says the digital fingerprints could then be easily verified by comparing them to a cloud-based library, maintained by the manufacturer.

In addition, Mohammadi, as co-PI on the project, will be working on a complementary defense system that focuses on the coding that controls electronic components. “Let’s say you have a malicious actor, and instead of using a counterfeit electronic control unit, or ECU, they actually reprogram the authentic part in a very smart fashion. Here, the electronic fingerprinting would not work,” Mohammadi explains. However, Mohammadi says the new programming would ultimately show itself in some kind of altered functionality of the vehicle, like, for example, steering or braking systems that aren’t performing exactly as expected. If a manufacturer or technician detected these kinds of performance anomalies, and they couldn’t be traced back to an obvious source, it would clue them in to start checking the code, which could be verified using a cloud-based database. In fact, this approach could even be useful for detecting more routine benign errors, like corrupted code.

The command line interface for Malik and Mohammadi's real-time device authentication system.

Interestingly, this new approach to threat detection could also serve as a highly efficient diagnostic tool. Right now, Malik says when a vehicle comes in for maintenance and a technician runs computer diagnostics to try to identify the problem for baseline models, it takes an average of 90 minutes to zero in on the actual issue. With their more sophisticated electronic fingerprinting system in the loop, Malik says it could help technicians quickly identify which components are malfunctioning. “We’re hoping to shrink the diagnostic time from 90 minutes to less than 30 minutes. That’s a very big deal in today’s world, where maintenance of large fleets of delivery vehicles for, say, Amazon, UPS or FedEx, is essential to their profitability,” Malik says. Another perk of the digital fingerprinting system: The fingerpointing between parts suppliers and OEMs that sometimes happens when something isn’t behaving as expected could be avoided — since the electronic fingerprints would help establish a benchmark for expected performance of electronic systems. In fact, though their research for this project will focus on components for the transportation sector, they say their anti-counterfeiting measures could ultimately be useful in any industry that uses electronic parts.

The two researchers have three years to work on the project, which is supported by a $1 million grant from the National Science Foundation — the second largest NSF award in ��-Dearborn history. But Mohammadi and Malik say the runway for this particular research has been even longer. Several related grants, including an incubator grant from the ��-Dearborn Office of Research, helped support related work that ultimately culminated in their current project. And the original idea was spawned way back in 2019, when Malik bumped into Mohammadi in a Canton coffee shop and asked if he could pick his brain about an idea he was kicking around. “Alireza immediately started diagramming his ideas about control theory on a napkin, and everything just kind of grew from there. I hope we still have the napkin,” Malik says.

In all likelihood, the napkin is long gone. But the two researchers are hopeful a much larger legacy for this work lies ahead.

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Story by Lou Blouin. The researchers would like to acknowledge several awards in the lineage of this project, including “SaTC: CORE: Small: Linking2Source: Security of In-Vehicle Networks via Source Identification,” sponsored by the NSF through Award #2035770; “I-Corps: Physics-based Automotive Cybersecurity,” sponsored by the NSF through Award #2317368; and “Cyber-Physical Security of Industrial Robotic System,’’ sponsored by the ��-Dearborn Office of Research.

Faculty Research

Research

Electrical and Computer Engineering

Off

Tue, 09/03/2024 - 13:04

With a new NSF-funded project, Professor Hafiz Malik and Associate Professor Alireza Mohammadi are creating a novel digital fingerprinting system to solve a massive safety challenge in the transportation sector.

Professor of Electrical and Computer Engineering Hafiz Malik (left) and Associate Professor of Electrical and Computer Engineering Alireza Mohammadi (right) demonstrate an early version of their digital fingerprinting system with student Hasan Arif.

��-Dearborn bolsters battery engineering curriculum with new courses this fall

lblouin — Thu, 29 Aug 2024 13:25:25 +0000

��-Dearborn bolsters battery engineering curriculum with new courses this fall lblouin Thu, 08/29/2024 - 09:25

The College of Engineering and Computer Science has been busy retooling its popular Automotive and Mobility Systems Engineering master’s program, with new classes and concentrations that reflect ongoing shifts in the industry. One newer emphasis, not surprisingly, is electric vehicles, though Mechanical Engineering Professor and Department Chair Oleg Zikanov says the plethora of headlines about slowing EV sales growth in the U.S. have made the optics of that pivot a bit more complicated. “Some students are asking about it,” says Zikanov, who often takes time to chat with new students as they enter the program. “Especially the students who are coming from an automotive or mechanical engineering background, they’re saying, ‘I thought I would do electric vehicles, but now I’m not so sure. Should I do something else?’”

Zikanov’s advice to them is two-fold. First, it’s true the all-EV future may not arrive as quickly as overly optimistic hype people claimed a few years ago, a line Zikanov says many serious people in the industry were skeptical about anyway. But batteries will undoubtedly play a major role in both the automotive and energy industries now and in the coming decades. He notes that even in the short term, if we see a pivot back to hybrid vehicles, which is how some manufacturers are coping with tepid consumer appetite for today’s EVs, advanced batteries are a critical component, especially in larger vehicles. Second, Zikanov counsels students to “not put all your eggs in one basket.” To that end, he says the AMSE degree is set up well for students, since they can take a wide variety of coursework in traditional areas like powertrain and manufacturing, as well as emerging ones like electrification and autonomy.

For students who are interested in batteries and storage, however, Zikanov says this fall’s addition of two new courses to those already in the ME curriculum gives students a background in all major subjects. One course, taught by Associate Professor Lei Chen, whose research focuses on EV battery fires and e-mobility manufacturing, introduces students to battery materials, manufacturing and recycling. “For many of our students, they may know something about charging and discharging,” Chen says. “But I think the materials and manufacturing process for batteries, and how the materials contribute to things like the structure of the battery and energy density, will be a totally new area.” Recycling of battery materials is an especially important subject for the industry right now, as finding ways to reuse expensive elements like lithium and cobalt could be vital to making energy storage and EVs more affordable and environmentally sustainable.

Mechanical Engineering Professor Hong Tae Kang is leading the other new course, which focuses on structural design of battery pack casings. This is a crucial design element of EVs, because the large, very heavy battery packs must be mounted in the car in a way that doesn’t negatively impact the vehicle’s structural integrity, safety and performance. Kang says they’ll be focusing on computer-aided engineering analysis to determine how the battery cages, which are typically mounted underneath the vehicle floor, stand up to different loads, impacts and levels of vibration over the life of the vehicle.

Associate Professor of Mechanical Engineering Youngki Kim will also be reprising his Battery System Modeling and Control course in Winter 2025. In that class, students learn the basics of battery system operations and how to describe them with mathematical models. In particular, the course focuses on key functions of battery management systems, like tracking a battery’s charge, power and health, which are crucial for EVs and consumer electronics alike. In keeping with the university’s focus on practice-based learning, Kim has nixed all quizzes and exams for his class, opting instead for a team project where students get to apply what they’ve learned to battery modeling or state estimator design.

Indeed, as ��-Dearborn debuts this new bolstered battery curriculum this fall, it’s already looking like the panic over EV sales may have been an overreaction. First, it’s important to note that EV sales aren’t actually falling in the U.S.; the rate of growth merely slowed in the early part of 2024. In fact, the lion’s share of that can be attributed to slumping sales at Tesla, which has such a large share of the domestic EV market that it’s capable of skewing the overall picture. EV sales were actually up at six other automakers during the first quarter of 2024, including by more than 80 percent at Toyota and Ford. Even GM, which was hit hard in early 2024, expects sales growth to rebound by year’s end. Meanwhile, long-term forecasts for EV growth continue to look quite rosy, especially globally.

“I think there is still widespread recognition that EVs will dominate the auto market,” Kim says. “Stringent emissions regulations in the U.S., E.U. and other countries make it clear that internal combustion engines alone cannot meet future requirements. I reassure students that the fundamentals of battery modeling and control remain the same, so their education and skills will continue to be relevant and valuable regardless of market fluctuations.”

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Want to learn more about battery research at ��-Dearborn? Read more about Associate Professor Lei Chen’s research on EV fires, or students and faculty who are participating in the national Battery Workforce Challenge.

Student Success

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Wed, 09/04/2024 - 13:18

Despite a recent blip in domestic EV sales growth, there are good reasons to keep the foot on the accelerator when it comes to battery engineering education.

Graduate student Hossein Abbasi works in the lab of Associate Professor Lei Chen, one of several faculty working on battery research at ��-Dearborn.

Undergrad students develop an improved sleep apnea mask

lblouin — Mon, 12 Aug 2024 14:01:44 +0000

Undergrad students develop an improved sleep apnea mask lblouin Mon, 08/12/2024 - 10:01

An estimated 930 million people worldwide struggle with sleep apnea, but two of them in particular played an inspirational role in a group of ��-Dearborn students' recent senior design project. Engineering undergrads Saja Samra’s and Maggie Bustamante’s dads both live with the condition, which causes people to stop and start breathing, sometimes hundreds of times, during their sleep cycle. To treat their condition, their dads both use a CPAP machine, which utilizes a face mask to keep airways open during sleep. The devices can help people get much better — and safer — rest, but the technology isn’t without problems. “Both our dads had similar issues — things like air leakage and discomfort, and that it was too bulky,” Samra says. “Portability was a big issue for my dad,” Bustamante says. “Whenever he would go camping or go on a trip for work, a lot of times he would choose not to bring it, and then he wouldn’t sleep nearly as well.”

This feedback prompted Samra and Bustamante to take a pitch to their senior design teammates: What if we designed a better CPAP mask? Both Ammel Mutahr and Sajida Tohfe liked the idea, so they started digging into what exactly that would involve. All four students majored in Human-Centered Engineering Design, a relatively new program at ��-Dearborn that emphasizes human needs and blends traditional engineering with skills borrowed from art, anthropology, psychology and sociology. So they quickly deployed the strategies they learned over their previous three years in their program. In typical HCED fashion, they started by talking with potential users, surveying more than a dozen people who have sleep apnea about their specific, real-world challenges with their CPAP devices. They also had more in-depth conversations with both dads. From that feedback, they learned that some of the most common issues involve fit around the nose and chin, comfort, the clumsiness of getting the mask on and the overall bulkiness of the device. With only two semesters to work on the project, they decided to focus on the first three issues, to see if they could create a better CPAP mask.

They began with a design brainstorming session, pulling inspiration from things like military pilot oxygen masks, which have inflatable head straps to create a tight fit, and even the Ironman helmet, a full head covering with interlocking panels. They then created low-fidelity prototypes with simple materials like cardboard and masking tape, and gradually moved through a series of higher-fidelity 3D-printed models. The dads proved to be a huge help in making some important tweaks along the way. “We knew comfort was a concern, so for one of our earlier prototypes we used TPU, which is a kind of plastic that has a little more give to it,” Bustamante explains. “But when Saja’s dad tested it, he said it was a little rough on his skin. So we tried this silicone resin, which is this relatively new type of resin used in 3D printing, and that ended up being much more comfortable.”

In addition to the silicone resin, their final prototype included a number of features designed to improve fit and comfort. Mutahr played a key role in developing the inflatable auto-adjusting straps, which not only make the mask fit better but make it easier to get off and on. Bustamante and Samra focused on an auto-sealing mechanism, which used two small motors around the bridge of the nose to seal the mask if pressure sensors detect an air leakage. One of the biggest breakthroughs was when Tohfe discovered a quick and cheap way to create individualized masks. Using a smartphone app called Scandy Pro: 3D Scanner, people could use their phone cameras to perform detailed scans of their faces, which then could be used to create 3D-printing files for custom masks.

The team’s innovative design earned the Best in College Award at this year’s Senior Design Competition. Still, the team says their final prototype by no means feels complete, as the compressed timeframe for the competition meant they couldn’t do everything they wanted. For example, Samra says the motors added some bulk to the mask, a quality they were trying to avoid, so she’d like to explore using a lighter-footprint technology, like actuators. And they’d likely add those to more places on the mask, like along the chin, where some of the people they surveyed say they experience air leakages. Mutahr, who also designed an app interface for their mask, pointed out that even Senior Design Day, when they presented their design to the public and the competition judges, gave them ideas for improvements. “For example, we got a comment from one of the judges, who had sleep apnea, and he had a really large beard, but he had to shave it because of the mask,” she says. “That’s something you probably wouldn't think about unless you’re actually talking with people who have sleep apnea. We heard comments like that from so many people who have issues with their masks. So you do the research, you read the statistics online, but seeing it in real life and how our solution could actually be helpful, that’s probably when you get the best design ideas.”

Mutahr says one of the most gratifying pieces of feedback was that their idea “could be on ‘Shark Tank.’” Indeed, they’re not ruling out trying to commercialize the product. One of their team’s faculty advisors is a patent lawyer, and a different project that Samra, Tohfe and Mutahr worked on in one of their HCED classes is already under review for a patent. The big challenge right now is getting the band back together. Bustamante graduated this spring and is busy with her new process engineering position at GM, where she’s helping retool a factory for EV production. Samra and Tohfe, who also graduated recently, are interviewing for jobs. And Mutahr still has a semester to go. “But we’d definitely love to pursue that,” Samra says. “Maybe after Ammel graduates, we can make it happen.”

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Story by Lou Blouin

Experiential Learning

Student Success

College of Education, Health, and Human Services

Off

Mon, 08/12/2024 - 14:00

Four seniors from the Human-Centered Engineering Design program built a precision-fit face mask that could bring relief to the millions of adults who live with sleep apnea.

From left, Saja Samra, Maggie Bustamante, Ammel Mutahr and Sajida Tohfe show off their work at Senior Design Day. Photo courtesy of Ammel Mutahr

PhD student is helping pave the way for high-performance metals

jpow — Fri, 26 Jul 2024 19:47:57 +0000

PhD student is helping pave the way for high-performance metals jpow Fri, 07/26/2024 - 15:47

Metals are one of the most essential classes of materials for modern life, prized for their strength, flexibility, conductivity, durability and aesthetic beauty. But you don’t always get all these properties in a single metal; in fact, those qualities are sometimes at odds with each other, says second-year mechanical engineering doctoral student Hossein Abbasi. One of the property tradeoffs engineers regularly encounter is between strength and ductility, the latter of which Abbasi says can be thought of as a metal’s elastic ability to temporarily deform and spring back to its original state. Typically, metals that are very strong aren’t very ductile, which makes them brittle. Conversely, metals that have high ductility usually sacrifice strength. The reason, Abbasi says, has to do with their crystalline structure — particularly the size of the “grains” that comprise the metal’s base architecture. Large grains, Abbasi says, make a metal more ductile, while smaller grains give it strength.

Materials scientists are trying to defy this basic rule of physics, however, with a new class of metals called gradient nano-grained metals. Unlike most metals, which have a singular grain size throughout their entire thickness, GNG metals have large grains toward the material’s interior that gradually taper into very small grains at the surface. This continuum of grain sizes gives GNG metals a rare combination of ductility and strength — and thus dozens of interesting possible applications. A turbine blade in an airplane engine, for example, must be both very strong and able to bounce back after impacts in order to avoid catastrophic failure. Similarly, Abbasi says, GNG metals could one day be an ideal material for vehicle suspension components, which have to be strong but also stand up to dynamic loads.

So if GNG metals have such desirable properties, why aren’t they in widespread use already? Abbasi says one reason is they’re still a relatively new class of materials, and as such, materials scientists and engineers don’t fully understand how they perform under a wide variety of conditions. Abbasi’s doctoral research, supervised by Associate Professor of Mechanical Engineering Lei Chen, is focused on helping engineers get a clearer picture of GNG metal behavior. Abbasi’s biggest contributions thus far are some advanced computer models, which map not only GNG metals’ ideal crystal structure but also defects within the metal. This makes his models much more representative of metals in the real world. “It’s almost impossible to create a perfect metal. In the real world, all metals have some defects, which we call geometrically necessary dislocations,” Abbasi explains, owing to the fact that the grain crystals don’t fit perfectly together. “So if we run our simulations without accounting for these voids in the underlying structure, we don’t get very accurate results compared to the real world.”

Using these highly detailed models, Abbasi can perform a battery of relatively quick, inexpensive tests. In one simulation, for example, he predicted how different grain sizes affect stress and strain behavior. In another, he modeled the effects of different strain rates on the metal’s tendency to “recrystallize,” which refers to the process in which large grains are subdivided into smaller grains as a result of applied stress. Simulations, of course, are only useful if they reflect what happens in the real world, so Abbasi then validated his simulated experiments with collaborators at Michigan State University, who put actual GNG materials through the same tests. This demonstrated that Abbasi’s models are able to provide highly accurate predictions of how the materials actually behave — making them an incredibly useful tool for engineers interested in GNG metal applications.

Abbasi’s work has won the ��-Dearborn doctoral student poster competition two years running — which is particularly impressive given he’s relatively new to the field of computer modeling and simulation. Abbasi came to ��-Dearborn from Iran, where he studied and then lectured at the University of Tabriz. His work focused on nanomaterials, but his research was focused on the manufacturing of experimental materials in the lab. When he was looking for a PhD program in the United States, he says he was attracted to Chen’s work because it combined manufacturing and modeling, giving him an opportunity to broaden his skillset.

Abbasi says his experience at an American university has been great so far, even if his studies will likely require him to be away from his family until his doctoral program is complete. With political relations strained between Iran and the U.S., he said he honestly didn’t know what to expect from Americans, and he was pleasantly surprised by how friendly most people are. “Right from the very start, in fact, when I arrived in Chicago, the border officer asked me to take everything out of my pockets, and I had some snacks I had brought with me from Iran,” he explains. “And he told me that I could not take them with me, that they had to go in the trash. But then a few moments later, he tapped me on the shoulder and brought me a package of nuts to replace the snacks. So here I am, my first minutes in the United States and a border officer is being very nice to me. That made me feel good about my new adventure in the United States.”

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Story by Lou Blouin