Some state Republican lawmakers hope President Donald Trump’s recent executive order restricting funding for so-called “gain-of-function” research will accomplish their goal of clamping down on what they see as dangerous pathogen studies in Wisconsin.
The post Wisconsin GOP lawmakers praise Trump order restricting funds for ‘gain-of-function’ research appeared first on WPR.
The lobby of the Wisconsin Institutes for Medical Research, where researchers say pauses to federal grants have stifled science. (Henry Redman | Wisconsin Examiner)
Earlier this year, Dr. Avtar Roopra, a professor of neuroscience at UW-Madison, published research that shows a drug typically used to treat arthritis halts brain-damaging seizures in mice that have a condition similar to epilepsy. The treatment could be used to provide relief for a subset of people with epilepsy who don’t get relief from other current treatments.
But even as the culmination of a decade-long project was making headlines as a possible breakthrough for the 50 million people worldwide with epilepsy, Roopra’s research was put on hold because the National Institutes of Health (NIH) under President Donald Trump has stopped reviewing grant requests.
Now, months after his funding was paused, Roopra says he is facing the choice between cutting corners in experiments to save costs or laying off research staff — which comes with its own loss of years of experience and institutional knowledge.
“Experiments are being trimmed down,” Roopra says. “So the perfect experiment, which is what every experiment must be, we’re now trying to reanalyze and say, ‘Well, can we get by with less?’ If we do, we’re not going to have the perfect answer, and that’s always a danger.”
Roopra’s lab is currently working on an experiment comparing data from healthy mouse brains to diseased brains and, ideally, he’d have ten of each. But to save costs he now has to use three of each. The result is that the conclusions that can be made from the data are less certain, which only creates more expenses in the long term.
“What that means is we’ll still get some data, but the confidence we have in our conclusions will be drastically reduced,” he says. “And so any experiments we then decide to do based on that will be on more shaky ground, and experiments further on that will be on even shakier ground. And so you have this propagating knock-on effect, but ultimately, the conclusions you get, they’re going to have to be interpreted cautiously, whereas, if we did the perfect experiment for which we were expecting funds, we would have robust data, robust conclusions. We could move forward, forthright into trials.”
Science is expensive, Roopra says, because results have to be replicated many times. Cutting grant funding, as the Trump administration has done, results in austerity measures at labs and universities. Those budget cuts mean experiments aren’t repeated as many times, which means data isn’t as complete and results in less work reaching the end goal — treatments that improve people’s lives.
Roopra says that when a patient sees a doctor and is prescribed a drug, that is just the tip of an iceberg, underneath which are the thousands of hours of research and millions of dollars spent at pharmaceutical companies conducting clinical trials and university departments testing theories.
“So it’s actually going to cost everybody more money if we do it this way, because we have to go back,” he says. “And once this moves to clinical trials, which is our goal, if we don’t have the very best, the most solid foundation for doing so, if that trial goes ahead and it fails, it may never be done again. Because trials cost hundreds of millions of dollars, you’ve got to get it right the first time. So that’s what this new normal looks like.”
Roopra’s work is just one research focus in one department on one campus. Wisconsin institutions alone receive about $750 million annually from the NIH. The Medical College of Wisconsin has lost at least $5 million in research grants since Trump took office.
The cuts affect “every lab, every department, and we’re very biomedical-research centric, but it’s also happening outside of biomedical research,” Dr. Betsy Quinlan, chair of UW-Madison’s neuroscience department, says. “It’s happening in physics and it’s happening in engineering. It’s happening to all research, environmental science.”
Researchers in Wisconsin have had at least $26.8 million in expected grant funding terminated, according to data compiled by Grant Watch, a project to track cuts to grant funding at the NIH and National Science Foundation (NSF).
“I’ve heard a lot of panic in the community as if the support that the federal government has for science has ended and that science is no longer the priority,” NIH director Jay Bhattacharya said at an event at the Medical College of Wisconsin earlier this month. “One of the reasons I was delighted to be able to come here was to assure people that is not true.”
Nonetheless, among the terminated grants here in Wisconsin are projects to study science misinformation in Black communities, how to engage the public in water stewardship in urban areas such as Milwaukee, the effect of technology on children’s development, the cardiovascular side effects of hormone treatment on transgender men and ways to increase HIV prevention measures among gay men in rural areas.
“It’s vital that we adopt reforms, real reforms in the research enterprise of this country, so that we depoliticize it, ground it in reality and build a culture of respect for dissent and free speech,” Bhattacharya said.
But discoveries can come from unexpected places, says Quinlan, who warns that the top-down approach to approving research grants that the administration appears to be moving toward will stifle scientific exploration.
“If the agency says, ‘Here’s a very narrow range of things we will fund,’ it will squash all creativity and real discovery, because real discovery comes when you see something that is unexpected and you follow the unexpected lead,” she says.
While the cuts to grants are having an immediate impact on research in Wisconsin, there are also concerns about morale among lab staff and a “brain drain” as researchers choose to leave the U.S. or even abandon science entirely.
“The biggest problem I think most researchers are facing is the uncertainty and decline in morale that these changes have wrought,” Jo Handelsman, director of the Wisconsin Institute for Discovery, says. “These are extremely real and fairly devastating effects on the research community in terms of what’s already happened, almost every week there’s a wave of NIH termination. No one feels their grant is going to continue for sure. That’s a difficult way to do research.”
For decades, scientists have come from all over the world to work in the U.S. Now cuts to grants and the Trump administration’s harsh immigration policies are changing that. Last week, after decisions from a number of judges, the Trump administration walked back an effort to cancel the visas of 27 students at University of Wisconsin schools. Roopra says those fears hurt research.
“Every minute that that researcher is worried is a minute they’re not thinking about the science,” says Roopra, whose work has also focused on breast cancer. “And so what it looks like is a continuous, chronic fear, which pushes us to think about maybe looking at other options, which we’d rather not do.”
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President Donald Trump's budget request, released on May 2, 2025, proposes slashing $21 billion in unspent funds from the 2021 bipartisan infrastructure law for renewable energy, electric vehicle charging infrastructure and other efforts to cut climate-warming carbon dioxide emissions. Shown are solar panels and wind turbines. (Photo by Marga Buschbell-Steeger/Getty Images)
President Donald Trump’s budget request for the next fiscal year proposes deep cuts to renewable energy programs and other climate spending as the administration seeks to shift U.S. energy production to encourage more fossil fuels and push the focus away from reducing climate change.
The budget proposes slashing $21 billion in unspent funds from the 2021 bipartisan infrastructure law for renewable energy, electric vehicle charging infrastructure and other efforts to cut climate-warming carbon dioxide emissions. The request also targets climate research spending and initiatives meant to promote diversity.
“President Trump is committed to eliminating funding for the globalist climate agenda while unleashing American energy production,” a White House fact sheet on climate and environment spending said. The budget “eliminates funding for the Green New Scam.”
The president’s budget request is a wish list for Congress, which controls federal spending, to consider. Even with both chambers of Congress controlled by Republicans who have shown an unusual willingness to follow Trump’s lead on a host of policies, it is best understood as a starting point for negotiations between the branches of government and a representation of the administration’s priorities.
A White House official speaking on background Friday, though, said the Trump administration is exploring ways to exert more control over the federal spending process, including by potentially refusing to spend funds appropriated by lawmakers.
The first budget request of Trump’s second term calls on Congress to cut non-defense accounts by $163 billion to $557 billion, while keeping defense funding flat at $893 billion.
The proposal drew criticism for a focus on culture-war buzzwords, even from groups that are not always inclined to support environment and climate spending.
The request “is long on rhetoric and short on details,” Steve Ellis, president of the nonpartisan budget watchdog Taxpayers for Common Sense, said in a statement.
“This year’s version leans heavily on political talking points—taking aim at so-called ‘woke’ programs and the ‘Green New Scam,’ while proposing a massive Pentagon spending hike to pay for wasteful fantasies like the Golden Dome and diverting military resources to immigration enforcement missions.”
The administration proposal would roll back funding Trump’s predecessor, Democrat Joe Biden, championed for renewable energy.
It would cancel more than $15 billion from the 2021 infrastructure law “purposed for unreliable renewable energy, removing carbon dioxide from the air, and other costly technologies that burden ratepayers and consumers,” according to the White House fact sheet.
It would also eliminate $6 billion for building electric vehicle charging infrastructure.
“EV chargers should be built just like gas stations: with private sector resources disciplined by market forces,” the fact sheet said.
And it would decrease spending on the Energy Department’s Energy Efficiency and Renewable Energy program, which helps private-sector projects secure financing and conducts research on low-carbon energy sources, by $2.5 billion.
In a statement, Rep. Marcy Kaptur, the ranking Democrat on the House Appropriations subcommittee that writes the bill funding energy programs, slammed the cuts to renewable energy programs, saying they would cost consumers and hurt a growing domestic industry.
“The Trump Administration’s proposal to slash $20 Billion from the Department of Energy’s programs — particularly a devastating 74% cut to Energy Efficiency and Renewable Energy — is shortsighted and dangerous,” the longtime Ohio lawmaker said. “By gutting clean energy investments, this budget threatens to raise energy prices for consumers, increase our reliance on foreign energy, and stifle American competitiveness. … We must defend the programs that power America’s future — cleaner, cheaper, and made right here at home.”
Throughout the request, the administration targets programs out of line with Trump’s ideology on social issues, including those meant to promote diversity.
For energy and environment programs, that includes spending on environmental justice initiatives, which target pollution and climate effects in majority-minority and low-income communities, and organizations “that advance the radical climate agenda,” according to the fact sheet.
Research and grant funding for the National Oceanic and Atmospheric Administration would be particularly hard hit by the proposal, which would terminate “a variety of climate-dominated research programs that are not aligned with Administration policy of ending ‘Green New Deal’ initiatives, saving taxpayers $1.3 billion.”
The budget also proposes eliminating $100 million from a U.S. Environmental Protection Agency fund dedicated to environmental justice. That funding “enabled a witch hunt against private industry” and “gave taxpayer dollars to political cronies who exploited the program’s racial preferencing policies to advance an anti-oil and gas crusade,” according to the White House.
The budget also proposes cutting $900 million from National Park Service operations, which the administration said would come from defunding smaller sites while “supporting many national treasures.”
The document indicates the administration would prefer to leave responsibility for smaller sites currently under NPS management to states and refocus the federal government on the major parks that attract nationwide and international tourists.
“There is an urgent need to streamline staffing and transfer certain properties to State-level management to ensure the long-term health and sustainment of the National Park system,” according to a budget spreadsheet highlighting major line items in the request.
Despite laws in recent years to boost spending for maintenance at parks, the National Park Service faces a $23.3 billion deferred maintenance backlog, according to a July 2024 report from the nonpartisan Congressional Research Service.
The proposed NPS cut represents the largest single funding change – either positive or negative – of any line item under the Department of Interior, which would receive a funding decrease of more than $5 billion, about 30%, under the proposal.
Jennifer Shutt contributed to this report.
In the village of Noatak in Alaska’s Northwest Arctic region, Pregnancy Risk Assessment Monitoring System (PRAMS) data showed the community had lower breastfeeding initiation and six-week breastfeeding rates than the statewide average. This data supported funding to offer culturally-adapted peer breastfeeding services in the region. (Courtesy of Laura Norton-Cruz)
In the remote villages of Alaska where social worker Laura Norton-Cruz works to improve maternal and infant health, there are no hospitals.
Pregnant patients, almost all of whom are Alaska Native, often fly on small 10-seat planes to the region’s larger hub community of Kotzebue. While some give birth there, many more then take a jet out of the Northwest Arctic region to Anchorage, the state’s largest city. By the time they fly back to Kotzebue for their six-week checkup, a high percentage have stopped breastfeeding because of a lack of ongoing supports.
Norton-Cruz knows that because of data collected by Alaska’s Pregnancy Risk Assessment Monitoring System (PRAMS)— a grantee of the U.S. Centers for Disease Control and Prevention’s PRAMS program, started in 1987 in an effort to reduce infant morbidity and mortality.
But earlier this month, the Trump administration cut the federal program, its 17-member team and more workers in the Division of Reproductive Health as part of sweeping layoffs within the U.S. Department of Health and Human Services.
Rita Hamad, associate professor at Harvard School of Public Health, said PRAMS helps researchers understand what kinds of state policies are improving or harming child health.
“I can’t overemphasize what an important dataset this is and how unique it is to really show national trends and help us try to understand how to optimize the health of moms and young kids,” Hamad said.
PRAMS does not ask abortion-related questions, but some anti-abortion groups still try to make a connection.
“The cuts seem appropriate given all the bias in choosing topics and analyzing data, but if Pregnancy Risk Assessment Monitoring System wishes to justify their reporting, point to the study that has most helped women and their children, born and preborn, survive and thrive,’’ Kristi Hamrick, vice president of media and policy at Students for Life of America, told States Newsroom in an email.
Over the past two years, Norton-Cruz used Alaska’s PRAMS data to identify low breastfeeding rates in the region, connect with people in the villages and interview them about what would help them continue to breastfeed. What they wanted, she said, was a peer in the community who understood the culture — so that’s what she’s been working to set up through federal programs and funding that is now uncertain.
Norton-Cruz also uses responses from PRAMS surveys to identify risk factors and interventions that can help prevent domestic and sexual violence and childhood trauma, particularly in rural communities, where the rates of domestic violence and maternal death are high.
“PRAMS data not being available, I believe, is going to kill mothers and babies,” she said. “And it’s going to result in worse health for infants.”
Individual states collect and report their own data, and the CDC team was responsible for aggregating it into one national picture. Some localities, such as New York City, maintain a full dashboard of data that can be explored by year and survey question. The most recent fully published data is from 2022 and shows responses by region, marital status, Medicaid status and more.
For instance, 2022 data showed women on Medicaid experienced depressive symptoms at a higher rate after giving birth than those not on Medicaid. It also showed that a much higher percentage of women not on Medicaid reported putting their babies on their backs to sleep, the recommended method for safe sleep — 63% of women on Medicaid reported following that method, versus 85% not on Medicaid.
Hamad said PRAMS is the only national survey dataset dedicated to pregnancy and the postpartum period. Her team has studied the outcomes of the Women, Infants, and Children food assistance program, and how state paid family leave policies have affected rates of postpartum depression.
“This survey has been going on for decades and recruits people from almost all states,’’ she said. “There’s really no other dataset that we can use to look at the effects of state and federal policies on infant health and postpartum women.”
Under Secretary Robert F. Kennedy Jr., Health and Human Services laid off about 10,000 employees as part of a restructuring effort in early April. The overhaul is part of the “Make America Healthy Again” initiative, and the agency said it focused cuts on redundant or unnecessary administrative positions. It rescinded some of the firings in the weeks since, with Kennedy telling reporters that some were “mistakes.” It’s unclear if any of those hired back were PRAMS employees.
The cuts, Hamad said, also run counter to the administration’s stated goals of wanting to protect women, children and families.
“The government needs this data to accomplish what it says it wants to do, and it’s not going to be able to do that now,” she said.
The funding for local PRAMS programs seems to be unaffected for now. Spokespersons for health department teams in Alaska, New Mexico, Oklahoma and Kansas told States Newsroom they have not had any layoffs or changes to their grants, but the funding for this fiscal year ends on April 30. Forty-six states, along with D.C., New York City and two U.S. territories, participate in the program. According to the CDC, those jurisdictions represent 81% of all live births in the United States.
New York State Department of Health spokesperson Danielle De Souza told States Newsroom in an email their program has received another year of funding that begins May 1 and supports one full-time and two part-time staffers. But without the assistance of the national CDC team to compile, clean, and prepare the data, maintain the data collection platform and establish standards, De Souza said their state-level operations are on pause.
“We remain hopeful that the data collection platform will be fully reactivated, and that CDC coordination of PRAMS will resume,” De Souza said. “The department is assessing the challenges and feasibility of continuing operations if that does not occur.”
Hamad said some states might be willing to allocate state dollars to the programs to keep them running, but the states that have some of the worst maternal and infant health outcomes — such as Arkansas, Mississippi and Alabama — are the least likely to have the political will to do that. And it would still make the data less robust and valuable than it was before.
“If one state is asking about how often you breastfed in the last week, and another one is asking about the last month, then we won’t have comparable data across states,” she said.
Jacqueline Wolf, professor emeritus of social medicine at Ohio University, has studied the history of breastfeeding and childbirth practices and said the rates of maternal and infant death were high in the late 19th and early 20th centuries. For every breastfed baby, 15 raw milk-fed babies died. Wolf said 13% of babies didn’t live to their 1st birthday, and more than half were dying from diarrhea.
To help determine what was causing those deaths and prevent it, public health specialists created detailed forms and collected information from families about a mother’s age, the parents’ occupations, race, income level, household conditions, and how the babies were fed.
Researchers at that time were able to determine that babies who weren’t breastfed were getting sick from unpasteurized milk and tainted water supply, and more than half were dying from diarrhea. Through public health reforms, like requiring cow’s milk to be pasteurized, sold in individual sterile bottles and kept cold during shipping, infant death rates dropped, Wolf said.
Health officials also increased education campaigns around the issue. Today, PRAMS uses survey data the same way.
“These were detectives,” Wolf said. “That’s what public health really is, detective work, which is why this data is so important.”
Project 2025, the blueprint document of directives for the next Republican presidential administration crafted by conservative group Heritage Foundation in 2024 and closely followed by President Donald Trump and his cabinet, details plans for the CDC’s data collection efforts. Page 453 of the 900-page document, written by Heritage Foundation executive Roger Severino says it’s proper for the CDC to collect and publish data related to disease and injury, but the agency should not make public health recommendations and policies based on that data because it is “an inescapably political function.”
The agency should be separated into two, Severino wrote, with one agency responsible for public health with a “severely confined ability to make policy recommendations.”
“The CDC can and should make assessments as to the health costs and benefits of health interventions, but it has limited to no capacity to measure the social costs or benefits they may entail,” the document says.
On page 455, Severino says the CDC should also eliminate programs and projects that “do not respect human life” and undermine family formation. It does not name PRAMS as a program that does this, but says the agency should ensure it is not promoting abortion as health care.
Hamrick, of Students for Life of America, told States Newsroom in an email that because there is no national abortion reporting act that tracks outcomes for women who end a pregnancy, assumptions in current reports “taint the outcomes.” Hamrick said the CDC has done a poor job of getting a complete picture of pregnancy risks, including the risk of preterm birth after having an abortion.
“Taxpayers don’t have money to waste on purely political messaging,” Hamrick said.
If researchers like Laura Norton-Cruz don’t have PRAMS data moving forward, she said they will be operating in the dark in many ways, using anecdotal and clinical data that is not as reliable and accurate as the anonymous surveying. That can make it more difficult to push for funding and program changes from lawmakers as well.
“Moms need safe housing and domestic violence resources, moms need health care and breastfeeding support, and if we can’t show that, then they can justify not providing those things, knowing that those most affected by not having those things will be groups who are already marginalized,” Norton-Cruz said.
While HHS did not cite the administration’s ongoing efforts to remove any content from the federal government that acknowledges disparities in race or gender as its motivation for cutting the PRAMS team, researchers who spoke with States Newsroom think that could be the underlying reason.
Wolf said race matters in data collection just as much as household economics or class, and it is just as relevant today as it was when PRAMS was established, as maternal death rates for Black women and other women of color are disproportionately high in a number of states. Those states are also often the poorest and have higher infant mortality rates.
Wolf recalled that during Trump’s first term in 2020, the first year of COVID, the administration ordered the CDC to stop publishing public data about the pandemic. She sees a parallel to today.
“I fear that is exactly what’s going on with PRAMS,” she said. “To pretend like you don’t have the data, so the problem doesn’t exist, is just about the worst response you can think of, because more and more mothers and babies are going to get hurt.”
States Newsroom state outlet reporters Anna Kaminski, Danielle Prokop and Emma Murphy contributed to this report.
A new book shares the story of how researcher Karl Paul Link discovered Warfarin in a UW-Madison lab.
The post New book explores Wisconsin origins of common blood-thinning medication also used as rat poison appeared first on WPR.
Advocates for faculty and staff at the University of Wisconsin-Madison said it’s time for collective organizing against federal attacks on higher education.
The post UW-Madison staff mobilize against federal attacks appeared first on WPR.
There’s a lot of untapped potential in our homes and vehicles that could be harnessed to reinforce local power grids and make them more resilient to unforeseen outages, a new study shows.
In response to a cyber attack or natural disaster, a backup network of decentralized devices — such as residential solar panels, batteries, electric vehicles, heat pumps, and water heaters — could restore electricity or relieve stress on the grid, MIT engineers say.
Such devices are “grid-edge” resources found close to the consumer rather than near central power plants, substations, or transmission lines. Grid-edge devices can independently generate, store, or tune their consumption of power. In their study, the research team shows how such devices could one day be called upon to either pump power into the grid, or rebalance it by dialing down or delaying their power use.
In a paper appearing this week in the Proceedings of the National Academy of Sciences, the engineers present a blueprint for how grid-edge devices could reinforce the power grid through a “local electricity market.” Owners of grid-edge devices could subscribe to a regional market and essentially loan out their device to be part of a microgrid or a local network of on-call energy resources.
In the event that the main power grid is compromised, an algorithm developed by the researchers would kick in for each local electricity market, to quickly determine which devices in the network are trustworthy. The algorithm would then identify the combination of trustworthy devices that would most effectively mitigate the power failure, by either pumping power into the grid or reducing the power they draw from it, by an amount that the algorithm would calculate and communicate to the relevant subscribers. The subscribers could then be compensated through the market, depending on their participation.
The team illustrated this new framework through a number of grid attack scenarios, in which they considered failures at different levels of a power grid, from various sources such as a cyber attack or a natural disaster. Applying their algorithm, they showed that various networks of grid-edge devices were able to dissolve the various attacks.
The results demonstrate that grid-edge devices such as rooftop solar panels, EV chargers, batteries, and smart thermostats (for HVAC devices or heat pumps) could be tapped to stabilize the power grid in the event of an attack.
“All these small devices can do their little bit in terms of adjusting their consumption,” says study co-author Anu Annaswamy, a research scientist in MIT’s Department of Mechanical Engineering. “If we can harness our smart dishwashers, rooftop panels, and EVs, and put our combined shoulders to the wheel, we can really have a resilient grid.”
The study’s MIT co-authors include lead author Vineet Nair and John Williams, along with collaborators from multiple institutions including the Indian Institute of Technology, the National Renewable Energy Laboratory, and elsewhere.
Power boost
The team’s study is an extension of their broader work in adaptive control theory and designing systems to automatically adapt to changing conditions. Annaswamy, who leads the Active-Adaptive Control Laboratory at MIT, explores ways to boost the reliability of renewable energy sources such as solar power.
“These renewables come with a strong temporal signature, in that we know for sure the sun will set every day, so the solar power will go away,” Annaswamy says. “How do you make up for the shortfall?”
The researchers found the answer could lie in the many grid-edge devices that consumers are increasingly installing in their own homes.
“There are lots of distributed energy resources that are coming up now, closer to the customer rather than near large power plants, and it’s mainly because of individual efforts to decarbonize,” Nair says. “So you have all this capability at the grid edge. Surely we should be able to put them to good use.”
While considering ways to deal with drops in energy from the normal operation of renewable sources, the team also began to look into other causes of power dips, such as from cyber attacks. They wondered, in these malicious instances, whether and how the same grid-edge devices could step in to stabilize the grid following an unforeseen, targeted attack.
Attack mode
In their new work, Annaswamy, Nair, and their colleagues developed a framework for incorporating grid-edge devices, and in particular, internet-of-things (IoT) devices, in a way that would support the larger grid in the event of an attack or disruption. IoT devices are physical objects that contain sensors and software that connect to the internet.
For their new framework, named EUREICA (Efficient, Ultra-REsilient, IoT-Coordinated Assets), the researchers start with the assumption that one day, most grid-edge devices will also be IoT devices, enabling rooftop panels, EV chargers, and smart thermostats to wirelessly connect to a larger network of similarly independent and distributed devices.
The team envisions that for a given region, such as a community of 1,000 homes, there exists a certain number of IoT devices that could potentially be enlisted in the region’s local network, or microgrid. Such a network would be managed by an operator, who would be able to communicate with operators of other nearby microgrids.
If the main power grid is compromised or attacked, operators would run the researchers’ decision-making algorithm to determine trustworthy devices within the network that can pitch in to help mitigate the attack.
The team tested the algorithm on a number of scenarios, such as a cyber attack in which all smart thermostats made by a certain manufacturer are hacked to raise their setpoints simultaneously to a degree that dramatically alters a region’s energy load and destabilizes the grid. The researchers also considered attacks and weather events that would shut off the transmission of energy at various levels and nodes throughout a power grid.
“In our attacks we consider between 5 and 40 percent of the power being lost. We assume some nodes are attacked, and some are still available and have some IoT resources, whether a battery with energy available or an EV or HVAC device that’s controllable,” Nair explains. “So, our algorithm decides which of those houses can step in to either provide extra power generation to inject into the grid or reduce their demand to meet the shortfall.”
In every scenario that they tested, the team found that the algorithm was able to successfully restabilize the grid and mitigate the attack or power failure. They acknowledge that to put in place such a network of grid-edge devices will require buy-in from customers, policymakers, and local officials, as well as innovations such as advanced power inverters that enable EVs to inject power back into the grid.
“This is just the first of many steps that have to happen in quick succession for this idea of local electricity markets to be implemented and expanded upon,” Annaswamy says. “But we believe it’s a good start.”
This work was supported, in part, by the U.S. Department of Energy and the MIT Energy Initiative.
© Credit: Courtesy of the researchers
Car design is an iterative and proprietary process. Carmakers can spend several years on the design phase for a car, tweaking 3D forms in simulations before building out the most promising designs for physical testing. The details and specs of these tests, including the aerodynamics of a given car design, are typically not made public. Significant advances in performance, such as in fuel efficiency or electric vehicle range, can therefore be slow and siloed from company to company.
MIT engineers say that the search for better car designs can speed up exponentially with the use of generative artificial intelligence tools that can plow through huge amounts of data in seconds and find connections to generate a novel design. While such AI tools exist, the data they would need to learn from have not been available, at least in any sort of accessible, centralized form.
But now, the engineers have made just such a dataset available to the public for the first time. Dubbed DrivAerNet++, the dataset encompasses more than 8,000 car designs, which the engineers generated based on the most common types of cars in the world today. Each design is represented in 3D form and includes information on the car’s aerodynamics — the way air would flow around a given design, based on simulations of fluid dynamics that the group carried out for each design.
Each of the dataset’s 8,000 designs is available in several representations, such as mesh, point cloud, or a simple list of the design’s parameters and dimensions. As such, the dataset can be used by different AI models that are tuned to process data in a particular modality.
DrivAerNet++ is the largest open-source dataset for car aerodynamics that has been developed to date. The engineers envision it being used as an extensive library of realistic car designs, with detailed aerodynamics data that can be used to quickly train any AI model. These models can then just as quickly generate novel designs that could potentially lead to more fuel-efficient cars and electric vehicles with longer range, in a fraction of the time that it takes the automotive industry today.
“This dataset lays the foundation for the next generation of AI applications in engineering, promoting efficient design processes, cutting R&D costs, and driving advancements toward a more sustainable automotive future,” says Mohamed Elrefaie, a mechanical engineering graduate student at MIT.
Elrefaie and his colleagues will present a paper detailing the new dataset, and AI methods that could be applied to it, at the NeurIPS conference in December. His co-authors are Faez Ahmed, assistant professor of mechanical engineering at MIT, along with Angela Dai, associate professor of computer science at the Technical University of Munich, and Florin Marar of BETA CAE Systems.
Filling the data gap
Ahmed leads the Design Computation and Digital Engineering Lab (DeCoDE) at MIT, where his group explores ways in which AI and machine-learning tools can be used to enhance the design of complex engineering systems and products, including car technology.
“Often when designing a car, the forward process is so expensive that manufacturers can only tweak a car a little bit from one version to the next,” Ahmed says. “But if you have larger datasets where you know the performance of each design, now you can train machine-learning models to iterate fast so you are more likely to get a better design.”
And speed, particularly for advancing car technology, is particularly pressing now.
“This is the best time for accelerating car innovations, as automobiles are one of the largest polluters in the world, and the faster we can shave off that contribution, the more we can help the climate,” Elrefaie says.
In looking at the process of new car design, the researchers found that, while there are AI models that could crank through many car designs to generate optimal designs, the car data that is actually available is limited. Some researchers had previously assembled small datasets of simulated car designs, while car manufacturers rarely release the specs of the actual designs they explore, test, and ultimately manufacture.
The team sought to fill the data gap, particularly with respect to a car’s aerodynamics, which plays a key role in setting the range of an electric vehicle, and the fuel efficiency of an internal combustion engine. The challenge, they realized, was in assembling a dataset of thousands of car designs, each of which is physically accurate in their function and form, without the benefit of physically testing and measuring their performance.
To build a dataset of car designs with physically accurate representations of their aerodynamics, the researchers started with several baseline 3D models that were provided by Audi and BMW in 2014. These models represent three major categories of passenger cars: fastback (sedans with a sloped back end), notchback (sedans or coupes with a slight dip in their rear profile) and estateback (such as station wagons with more blunt, flat backs). The baseline models are thought to bridge the gap between simple designs and more complicated proprietary designs, and have been used by other groups as a starting point for exploring new car designs.
Library of cars
In their new study, the team applied a morphing operation to each of the baseline car models. This operation systematically made a slight change to each of 26 parameters in a given car design, such as its length, underbody features, windshield slope, and wheel tread, which it then labeled as a distinct car design, which was then added to the growing dataset. Meanwhile, the team ran an optimization algorithm to ensure that each new design was indeed distinct, and not a copy of an already-generated design. They then translated each 3D design into different modalities, such that a given design can be represented as a mesh, a point cloud, or a list of dimensions and specs.
The researchers also ran complex, computational fluid dynamics simulations to calculate how air would flow around each generated car design. In the end, this effort produced more than 8,000 distinct, physically accurate 3D car forms, encompassing the most common types of passenger cars on the road today.
To produce this comprehensive dataset, the researchers spent over 3 million CPU hours using the MIT SuperCloud, and generated 39 terabytes of data. (For comparison, it’s estimated that the entire printed collection of the Library of Congress would amount to about 10 terabytes of data.)
The engineers say that researchers can now use the dataset to train a particular AI model. For instance, an AI model could be trained on a part of the dataset to learn car configurations that have certain desirable aerodynamics. Within seconds, the model could then generate a new car design with optimized aerodynamics, based on what it has learned from the dataset’s thousands of physically accurate designs.
The researchers say the dataset could also be used for the inverse goal. For instance, after training an AI model on the dataset, designers could feed the model a specific car design and have it quickly estimate the design’s aerodynamics, which can then be used to compute the car’s potential fuel efficiency or electric range — all without carrying out expensive building and testing of a physical car.
“What this dataset allows you to do is train generative AI models to do things in seconds rather than hours,” Ahmed says. “These models can help lower fuel consumption for internal combustion vehicles and increase the range of electric cars — ultimately paving the way for more sustainable, environmentally friendly vehicles.”
“The dataset is very comprehensive and consists of a diverse set of modalities that are valuable to understand both styling and performance,” says Yanxia Zhang, a senior machine learning research scientist at Toyota Research Institute, who was not involved in the study.
This work was supported, in part, by the German Academic Exchange Service and the Department of Mechanical Engineering at MIT.
© Credit: Courtesy of Mohamed Elrefaie
As a major contributor to global carbon dioxide (CO2) emissions, the transportation sector has immense potential to advance decarbonization. However, a zero-emissions global supply chain requires re-imagining reliance on a heavy-duty trucking industry that emits 810,000 tons of CO2, or 6 percent of the United States’ greenhouse gas emissions, and consumes 29 billion gallons of diesel annually in the U.S. alone.
A new study by MIT researchers, presented at the recent American Society of Mechanical Engineers 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, quantifies the impact of a zero-emission truck’s design range on its energy storage requirements and operational revenue. The multivariable model outlined in the paper allows fleet owners and operators to better understand the design choices that impact the economic feasibility of battery-electric and hydrogen fuel cell heavy-duty trucks for commercial application, equipping stakeholders to make informed fleet transition decisions.
“The whole issue [of decarbonizing trucking] is like a very big, messy pie. One of the things we can do, from an academic standpoint, is quantify some of those pieces of pie with modeling, based on information and experience we’ve learned from industry stakeholders,” says ZhiYi Liang, PhD student on the renewable hydrogen team at the MIT K. Lisa Yang Global Engineering and Research Center (GEAR) and lead author of the study. Co-authored by Bryony DuPont, visiting scholar at GEAR, and Amos Winter, the Germeshausen Professor in the MIT Department of Mechanical Engineering, the paper elucidates operational and socioeconomic factors that need to be considered in efforts to decarbonize heavy-duty vehicles (HDVs).
Operational and infrastructure challenges
The team’s model shows that a technical challenge lies in the amount of energy that needs to be stored on the truck to meet the range and towing performance needs of commercial trucking applications. Due to the high energy density and low cost of diesel, existing diesel drivetrains remain more competitive than alternative lithium battery-electric vehicle (Li-BEV) and hydrogen fuel-cell-electric vehicle (H2 FCEV) drivetrains. Although Li-BEV drivetrains have the highest energy efficiency of all three, they are limited to short-to-medium range routes (under 500 miles) with low freight capacity, due to the weight and volume of the onboard energy storage needed. In addition, the authors note that existing electric grid infrastructure will need significant upgrades to support large-scale deployment of Li-BEV HDVs.
While the hydrogen-powered drivetrain has a significant weight advantage that enables higher cargo capacity and routes over 750 miles, the current state of hydrogen fuel networks limits economic viability, especially once operational cost and projected revenue are taken into account. Deployment will most likely require government intervention in the form of incentives and subsidies to reduce the price of hydrogen by more than half, as well as continued investment by corporations to ensure a stable supply. Also, as H2-FCEVs are still a relatively new technology, the ongoing design of conformal onboard hydrogen storage systems — one of which is the subject of Liang’s PhD — is crucial to successful adoption into the HDV market.
The current efficiency of diesel systems is a result of technological developments and manufacturing processes established over many decades, a precedent that suggests similar strides can be made with alternative drivetrains. However, interactions with fleet owners, automotive manufacturers, and refueling network providers reveal another major hurdle in the way that each “slice of the pie” is interrelated — issues must be addressed simultaneously because of how they affect each other, from renewable fuel infrastructure to technological readiness and capital cost of new fleets, among other considerations. And first steps into an uncertain future, where no one sector is fully in control of potential outcomes, is inherently risky.
“Besides infrastructure limitations, we only have prototypes [of alternative HDVs] for fleet operator use, so the cost of procuring them is high, which means there isn’t demand for automakers to build manufacturing lines up to a scale that would make them economical to produce,” says Liang, describing just one step of a vicious cycle that is difficult to disrupt, especially for industry stakeholders trying to be competitive in a free market.
Quantifying a path to feasibility
“Folks in the industry know that some kind of energy transition needs to happen, but they may not necessarily know for certain what the most viable path forward is,” says Liang. Although there is no singular avenue to zero emissions, the new model provides a way to further quantify and assess at least one slice of pie to aid decision-making.
Other MIT-led efforts aimed at helping industry stakeholders navigate decarbonization include an interactive mapping tool developed by Danika MacDonell, Impact Fellow at the MIT Climate and Sustainability Consortium (MCSC); alongside Florian Allroggen, executive director of MITs Zero Impact Aviation Alliance; and undergraduate researchers Micah Borrero, Helena De Figueiredo Valente, and Brooke Bao. The MCSC’s Geospatial Decision Support Tool supports strategic decision-making for fleet operators by allowing them to visualize regional freight flow densities, costs, emissions, planned and available infrastructure, and relevant regulations and incentives by region.
While current limitations reveal the need for joint problem-solving across sectors, the authors believe that stakeholders are motivated and ready to tackle climate problems together. Once-competing businesses already appear to be embracing a culture shift toward collaboration, with the recent agreement between General Motors and Hyundai to explore “future collaboration across key strategic areas,” including clean energy.
Liang believes that transitioning the transportation sector to zero emissions is just one part of an “energy revolution” that will require all sectors to work together, because “everything is connected. In order for the whole thing to make sense, we need to consider ourselves part of that pie, and the entire system needs to change,” says Liang. “You can’t make a revolution succeed by yourself.”
The authors acknowledge the MIT Climate and Sustainability Consortium for connecting them with industry members in the HDV ecosystem; and the MIT K. Lisa Yang Global Engineering and Research Center and MIT Morningside Academy for Design for financial support.
© Photo: Bob Adams/Flickr
Charging stations for electric vehicles are essential for cleaning up the transportation sector. A new study by MIT researchers suggests they’re good for business, too.
The study found that, in California, opening a charging station boosted annual spending at each nearby business by an average of about $1,500 in 2019 and about $400 between January 2021 and June 2023. The spending bump amounts to thousands of extra dollars annually for nearby businesses, with the increase particularly pronounced for businesses in underresourced areas.
The study’s authors hope the research paints a more holistic picture of the benefits of EV charging stations, beyond environmental factors.
“These increases are equal to a significant chunk of the cost of installing an EV charger, and I hope this study sheds light on these economic benefits,” says lead author Yunhan Zheng MCP ’21, SM ’21, PhD ’24, a postdoc at the Singapore-MIT Alliance for Research and Technology (SMART). “The findings could also diversify the income stream for charger providers and site hosts, and lead to more informed business models for EV charging stations.”
Zheng’s co-authors on the paper, which was published today in Nature Communications, are David Keith, a senior lecturer at the MIT Sloan School of Management; Jinhua Zhao, an MIT professor of cities and transportation; and alumni Shenhao Wang MCP ’17, SM ’17, PhD ’20 and Mi Diao MCP ’06, PhD ’10.
Understanding the EV effect
Increasing the number of electric vehicle charging stations is seen as a key prerequisite for the transition to a cleaner, electrified transportation sector. As such, the 2021 U.S. Infrastructure Investment and Jobs Act committed $7.5 billion to build a national network of public electric vehicle chargers across the U.S.
But a large amount of private investment will also be needed to make charging stations ubiquitous.
“The U.S. is investing a lot in EV chargers and really encouraging EV adoption, but many EV charging providers can’t make enough money at this stage, and getting to profitability is a major challenge,” Zheng says.
EV advocates have long argued that the presence of charging stations brings economic benefits to surrounding communities, but Zheng says previous studies on their impact relied on surveys or were small-scale. Her team of collaborators wanted to make advocates’ claims more empirical.
For their study, the researchers collected data from over 4,000 charging stations in California and 140,000 businesses, relying on anonymized credit and debit card transactions to measure changes in consumer spending. The researchers used data from 2019 through June of 2023, skipping the year 2020 to minimize the impact of the pandemic.
To judge whether charging stations caused customer spending increases, the researchers compared data from businesses within 500 meters of new charging stations before and after their installation. They also analyzed transactions from similar businesses in the same time frame that weren’t near charging stations.
Supercharging nearby businesses
The researchers found that installing a charging station boosted annual spending at nearby establishments by an average of 1.4 percent in 2019 and 0.8 percent from January 2021 to June 2023.
While that might sound like a small amount per business, it amounts to thousands of dollars in overall consumer spending increases. Specifically, those percentages translate to almost $23,000 in cumulative spending increases in 2019 and about $3,400 per year from 2021 through June 2023.
Zheng says the decline in spending increases over the two time periods might be due to a saturation of EV chargers, leading to lower utilization, as well as an overall decrease in spending per business after the Covid-19 pandemic and a reduced number of businesses served by each EV charging station in the second period. Despite this decline, the annual impact of a charging station on all its surrounding businesses would still cover approximately 11.2 percent of the average infrastructure and installation cost of a standard charging station.
Through both time frames, the spending increases were highest for businesses within about a football field’s distance from the new stations. They were also significant for businesses in disadvantaged and low-income areas, as designated by California and the Justice40 Initiative.
“The positive impacts of EV charging stations on businesses are not constrained solely to some high-income neighborhoods,” Wang says. “It highlights the importance for policymakers to develop EV charging stations in marginalized areas, because they not only foster a cleaner environment, but also serve as a catalyst for enhancing economic vitality.”
Zheng believes the findings hold a lesson for charging station developers seeking to improve the profitability of their projects.
“The joint gas station and convenience store business model could also be adopted to EV charging stations,” Zheng says. “Traditionally, many gas stations are affiliated with retail store chains, which enables owners to both sell fuel and attract customers to diversify their revenue stream. EV charging providers could consider a similar approach to internalize the positive impact of EV charging stations.”
Zheng also says the findings could support the creation of new funding models for charging stations, such as multiple businesses sharing the costs of construction so they can all benefit from the added spending.
Those changes could accelerate the creation of charging networks, but Zheng cautions that further research is needed to understand how much the study’s findings can be extrapolated to other areas. She encourages other researchers to study the economic effects of charging stations and hopes future research includes states beyond California and even other countries.
“A huge number of studies have focused on retail sales effects from traditional transportation infrastructure, such as rail and subway stations, bus stops, and street configurations,” Zhao says. “This research provides evidence for an important, emerging piece of transportation infrastructure and shows a consistently positive effect on local businesses, paving the way for future research in this area.”
The research was supported, in part, by the Singapore-MIT Alliance for Research and Technology (SMART) and the Singapore National Research Foundation. Diao was partially supported by the Natural Science Foundation of Shanghai and the Fundamental Research Funds for the Central Universities of China.
© Image: iStock
Although critical to the nation’s food security, farm work is potentially hazardous, farmworkers receive lower wages when compared with nonsupervisory workers outside agriculture, and many hired farm workers lack legal work authorization and access to basic public services. For the United States to remain competitive as a producer of fruit, vegetables, and other labor-intensive commodities both private and government institutions will need to accelerate adaptation to a changing landscape of farm labor.
An upcoming conference on farm labor seeks to strengthen ongoing farm labor research by convening and developing a network of researchers and stakeholders. The Changing Landscape of Farm Labor Conditions in the United States: What the Future Holds and How to Prepare for It conference will take place September 17 to 19, 2024, in Santa Cruz, California.
The conference is presented by the USDA Economic Research Service and Farm Foundation. It will cover four key themes: trends in the farm labor force, including worker migration and the H-2A Temporary Agricultural Program; labor costs, farm worker conditions, and workforce development.
Visit https://farmfoundation.swoogo.com/farmlabor for more information and to register.
The post Upcoming Farm Labor Conference Tackles Critical Issues appeared first on Farm Foundation.
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