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    High-speed videos show what happens when a droplet splashes into a pool

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    Rain can freefall at speeds of up to 25 miles per hour. If the droplets land in a puddle or pond, they can form a crown-like splash that, with enough force, can dislodge any surface particles and launch them into the air.Now MIT scientists have taken high-speed videos of droplets splashing into a deep pool, to track how the fluid evolves, above and below the water line, frame by millisecond frame. Their work could help to predict how spashing droplets, such as from rainstorms and irrigation systems, may impact watery surfaces and aerosolize surface particles, such as pollen on puddles or pesticides in agricultural runoff.The team carried out experiments in which they dispensed water droplets of various sizes and from various heights into a pool of water. Using high-speed imaging, they measured how the liquid pool deformed as the impacting droplet hit the pool’s surface.Across all their experiments, they observed a common splash evolution: As a droplet hit the pool, it pushed down below the surface to form a “crater,” or cavity. At nearly the same time, a wall of liquid rose above the surface, forming a crown. Interestingly, the team observed that small, secondary droplets were ejected from the crown before the crown reached its maximum height. This entire evolution happens in a fraction of a second.

    “This cylinder-like wall of rising liquid, and how it evolves in time and space, is at the heart of everything,” Lydia Bourouiba says. GIF has been edited down to 5 frames per second.

    Image: Courtesy of the researchers; edited by MIT News

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    Scientists have caught snapshots of droplet splashes in the past, such as the famous “Milk Drop Coronet” — a photo of a drop of milk in mid-splash, taken by the late MIT professor Harold “Doc” Edgerton, who invented a photographic technique to capture quickly moving objects.The new work represents the first time scientists have used such high-speed images to model the entire splash dynamics of a droplet in a deep pool, combining what happens both above and below the surface. The team has used the imaging to gather new data central to build a mathematical model that predicts how a droplet’s shape will morph and merge as it hits a pool’s surface. They plan to use the model as a baseline to explore to what extent a splashing droplet might drag up and launch particles from the water pool.“Impacts of drops on liquid layers are ubiquitous,” says study author Lydia Bourouiba, a professor in the MIT departments of Civil and Environmental Engineering and Mechanical Engineering, and a core member of the Institute for Medical Engineering and Science (IMES). “Such impacts can produce myriads of secondary droplets that could act as carriers for pathogens, particles, or microbes that are on the surface of impacted pools or contaminated water bodies. This work is key in enabling prediction of droplet size distributions, and potentially also what such drops can carry with them.”Bourouiba and her mentees have published their results in the Journal of Fluid Mechanics. MIT co-authors include former graduate student Raj Dandekar PhD ’22, postdoc (Eric) Naijian Shen, and student mentee Boris Naar.Above and belowAt MIT, Bourouiba heads up the Fluid Dynamics of Disease Transmission Laboratory, part of the Fluids and Health Network, where she and her team explore the fundamental physics of fluids and droplets in a range of environmental, energy, and health contexts, including disease transmission. For their new study, the team looked to better understand how droplets impact a deep pool — a seemingly simple phenomenon that nevertheless has been tricky to precisely capture and characterize.Bourouiba notes that there have been recent breakthroughs in modeling the evolution of a splashing droplet below a pool’s surface. As a droplet hits a pool of water, it breaks through the surface and drags air down through the pool to create a short-lived crater. Until now, scientists have focused on the evolution of this underwater cavity, mainly for applications in energy harvesting. What happens above the water, and how a droplet’s crown-like shape evolves with the cavity below, remained less understood.“The descriptions and understanding of what happens below the surface, and above, have remained very much divorced,” says Bourouiba, who believes such an understanding can help to predict how droplets launch and spread chemicals, particles, and microbes into the air.Splash in 3DTo study the coupled dynamics between a droplet’s cavity and crown, the team set up an experiment to dispense water droplets into a deep pool. For the purposes of their study, the researchers considered a deep pool to be a body of water that is deep enough that a splashing droplet would remain far away from the pool’s bottom. In these terms, they found that a pool with a depth of at least 20 centimeters was sufficient for their experiments.They varied each droplet’s size, with an average diameter of about 5 millimeters. They also dispensed droplets from various heights, causing the droplets to hit the pool’s surface at different speeds, which on average was about 5 meters per second. The overall dynamics, Bourouiba says, should be similar to what occurs on the surface of a puddle or pond during an average rainstorm.“This is capturing the speed at which raindrops fall,” she says. “These wouldn’t be very small, misty drops. This would be rainstorm drops for which one needs an umbrella.”Using high-speed imaging techniques inspired by Edgerton’s pioneering photography, the team captured videos of pool-splashing droplets, at rates of up to 12,500 frames per second. They then applied in-house imaging processing methods to extract key measurements from the image sequences, such as the changing width and depth of the underwater cavity, and the evolving diameter and height of the rising crown. The researchers also captured especially tricky measurements, of the crown’s wall thickness profile and inner flow — the cylinder that rises out of the pool, just before it forms a rim and points that are characteristic of a crown.“This cylinder-like wall of rising liquid, and how it evolves in time and space, is at the heart of everything,” Bourouiba says. “It’s what connects the fluid from the pool to what will go into the rim and then be ejected into the air through smaller, secondary droplets.”The researchers worked the image data into a set of “evolution equations,” or a mathematical model that relates the various properties of an impacting droplet, such as the width of its cavity and the thickness and speed profiles of its crown wall, and how these properties change over time, given a droplet’s starting size and impact speed.“We now have a closed-form mathematical expression that people can use to see how all these quantities of a splashing droplet change over space and time,” says co-author Shen, who plans, with Bourouiba, to apply the new model to the behavior of secondary droplets and understanding how a splash end-up dispersing particles such as pathogens and pesticides. “This opens up the possibility to study all these problems of splash in 3D, with self-contained closed-formed equations, which was not possible before.”This research was supported, in part, by the Department of Agriculture-National Institute of Food and Agriculture Specialty Crop Research Initiative; the Richard and Susan Smith Family Foundation; the National Science Foundation; the Centers for Disease Control and Prevention-National Institute for Occupational Safety and Health; Inditex; and the National Institute of Allergy and Infectious Diseases of the National Institutes of Health. 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      To design better water filters, MIT engineers look to manta rays

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      Filter feeders are everywhere in the animal world, from tiny crustaceans and certain types of coral and krill, to various molluscs, barnacles, and even massive basking sharks and baleen whales. Now, MIT engineers have found that one filter feeder has evolved to sift food in ways that could improve the design of industrial water filters.In a paper appearing this week in the Proceedings of the National Academy of Sciences, the team characterizes the filter-feeding mechanism of the mobula ray — a family of aquatic rays that includes two manta species and seven devil rays. Mobula rays feed by swimming open-mouthed through plankton-rich regions of the ocean and filtering plankton particles into their gullet as water streams into their mouths and out through their gills.The floor of the mobula ray’s mouth is lined on either side with parallel, comb-like structures, called plates, that siphon water into the ray’s gills. The MIT team has shown that the dimensions of these plates may allow for incoming plankton to bounce all the way across the plates and further into the ray’s cavity, rather than out through the gills. What’s more, the ray’s gills absorb oxygen from the outflowing water, helping the ray to simultaneously breathe while feeding.“We show that the mobula ray has evolved the geometry of these plates to be the perfect size to balance feeding and breathing,” says study author Anette “Peko” Hosoi, the Pappalardo Professor of Mechanical Engineering at MIT.The engineers fabricated a simple water filter modeled after the mobula ray’s plankton-filtering features. They studied how water flowed through the filter when it was fitted with 3D-printed plate-like structures. The team took the results of these experiments and drew up a blueprint, which they say designers can use to optimize industrial cross-flow filters, which are broadly similar in configuration to that of the mobula ray.“We want to expand the design space of traditional cross-flow filtration with new knowledge from the manta ray,” says lead author and MIT postdoc Xinyu Mao PhD ’24. “People can choose a parameter regime of the mobula ray so they could potentially improve overall filter performance.”Hosoi and Mao co-authored the new study with Irmgard Bischofberger, associate professor of mechanical engineering at MIT.A better trade-offThe new study grew out of the group’s focus on filtration during the height of the Covid pandemic, when the researchers were designing face masks to filter out the virus. Since then, Mao has shifted focus to study filtration in animals and how certain filter-feeding mechanisms might improve filters used in industry, such as in water treatment plants.Mao observed that any industrial filter must strike a balance between permeability (how easily fluid can flow through a filter), and selectivity (how successful a filter is at keeping out particles of a target size). For instance, a membrane that is studded with large holes might be highly permeable, meaning a lot of water can be pumped through using very little energy. However, the membrane’s large holes would let many particles through, making it very low in selectivity. Likewise, a membrane with much smaller pores would be more selective yet also require more energy to pump the water through the smaller openings.“We asked ourselves, how do we do better with this tradeoff between permeability and selectivity?” Hosoi says.As Mao looked into filter-feeding animals, he found that the mobula ray has struck an ideal balance between permeability and selectivity: The ray is highly permeable, in that it can let water into its mouth and out through its gills quickly enough to capture oxygen to breathe. At the same time, it is highly selective, filtering and feeding on plankton rather than letting the particles stream out through the gills.The researchers realized that the ray’s filtering features are broadly similar to that of industrial cross-flow filters. These filters are designed such that fluid flows across a permeable membrane that lets through most of the fluid, while any polluting particles continue flowing across the membrane and eventually out into a reservoir of waste.The team wondered whether the mobula ray might inspire design improvements to industrial cross-flow filters. For that, they took a deeper dive into the dynamics of mobula ray filtration.A vortex keyAs part of their new study, the team fabricated a simple filter inspired by the mobula ray. The filter’s design is what engineers refer to as a “leaky channel” — effectively, a pipe with holes along its sides. In this case, the team’s “channel” consists of two flat, transparent acrylic plates that are glued together at the edges, with a slight opening between the plates through which fluid can be pumped. At one end of the channel, the researchers inserted 3D-printed structures resembling the grooved plates that run along the floor of the mobula ray’s mouth.The team then pumped water through the channel at various rates, along with colored dye to visualize the flow. They took images across the channel and observed an interesting transition: At slow pumping rates, the flow was “very peaceful,” and fluid easily slipped through the grooves in the printed plates and out into a reservoir. When the researchers increased the pumping rate, the faster-flowing fluid did not slip through, but appeared to swirl at the mouth of each groove, creating a vortex, similar to a small knot of hair between the tips of a comb’s teeth.“This vortex is not blocking water, but it is blocking particles,” Hosoi explains. “Whereas in a slower flow, particles go through the filter with the water, at higher flow rates, particles try to get through the filter but are blocked by this vortex and are shot down the channel instead. The vortex is helpful because it prevents particles from flowing out.”The team surmised that vortices are the key to mobula rays’ filter-feeding ability. The ray is able to swim at just the right speed that water, streaming into its mouth, can form vortices between the grooved plates. These vortices effectively block any plankton particles — even those that are smaller than the space between plates. The particles then bounce across the plates and head further into the ray’s cavity, while the rest of the water can still flow between the plates and out through the gills.The researchers used the results of their experiments, along with dimensions of the filtering features of mobula rays, to develop a blueprint for cross-flow filtration.“We have provided practical guidance on how to actually filter as the mobula ray does,” Mao offers.“You want to design a filter such that you’re in the regime where you generate vortices,” Hosoi says. “Our guidelines tell you: If you want your plant to pump at a certain rate, then your filter has to have a particular pore diameter and spacing to generate vortices that will filter out particles of this size. The mobula ray is giving us a really nice rule of thumb for rational design.”This work was supported, in part, by the U.S. National Institutes of Health, and the Harvey P. Greenspan Fellowship Fund.  More

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      in Environment

      Study: Marshes provide cost-effective coastal protection

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      Images of coastal houses being carried off into the sea due to eroding coastlines and powerful storm surges are becoming more commonplace as climate change brings a rising sea level coupled with more powerful storms. In the U.S. alone, coastal storms caused $165 billion in losses in 2022.Now, a study from MIT shows that protecting and enhancing salt marshes in front of protective seawalls can significantly help protect some coastlines, at a cost that makes this approach reasonable to implement.The new findings are being reported in the journal Communications Earth and Environment, in a paper by MIT graduate student Ernie I. H. Lee and professor of civil and environmental engineering Heidi Nepf. This study, Nepf says, shows that restoring coastal marshes “is not just something that would be nice to do, but it’s actually economically justifiable.” The researchers found that, among other things, the wave-attenuating effects of salt marsh mean that the seawall behind it can be built significantly lower, reducing construction cost while still providing as much protection from storms.“One of the other exciting things that the study really brings to light,” Nepf says, “is that you don’t need a huge marsh to get a good effect. It could be a relatively short marsh, just tens of meters wide, that can give you benefit.” That makes her hopeful, Nepf says, that this information might be applied in places where planners may have thought saving a smaller marsh was not worth the expense. “We show that it can make enough of a difference to be financially viable,” she says.While other studies have previously shown the benefits of natural marshes in attenuating damaging storms, Lee says that such studies “mainly focus on landscapes that have a wide marsh on the order of hundreds of meters. But we want to show that it also applies in urban settings where not as much marsh land is available, especially since in these places existing gray infrastructure (seawalls) tends to already be in place.”The study was based on computer modeling of waves propagating over different shore profiles, using the morphology of various salt marsh plants — the height and stiffness of the plants, and their spatial density — rather than an empirical drag coefficient. “It’s a physically based model of plant-wave interaction, which allowed us to look at the influence of plant species and changes in morphology across seasons,” without having to go out and calibrate the vegetation drag coefficient with field measurements for each different condition, Nepf says.The researchers based their benefit-cost analysis on a simple metric: To protect a certain length of shoreline, how much could the height of a given seawall be reduced if it were accompanied by a given amount of marsh? Other ways of assessing the value, such as including the value of real estate that might be damaged by a given amount of flooding, “vary a lot depending on how you value the assets if a flood happens,” Lee says. “We use a more concrete value to quantify the benefits of salt marshes, which is the equivalent height of seawall you would need to deliver the same protection value.”They used models of a variety of plants, reflecting differences in height and the stiffness across different seasons. They found a twofold variation in the various plants’ effectiveness in attenuating waves, but all provided a useful benefit.To demonstrate the details in a real-world example and help to validate the simulations, Nepf and Lee studied local salt marshes in Salem, Massachusetts, where projects are already underway to try to restore marshes that had been degraded. Including the specific example provided a template for others, Nepf says. In Salem, their model showed that a healthy salt marsh could offset the need for an additional seawall height of 1.7 meters (about 5.5 feet), based on satisfying a rate of wave overtopping that was set for the safety of pedestrians.However, the real-world data needed to model a marsh, including maps of salt marsh species, plant height, and shoots per bed area, are “very labor-intensive” to put together, Nepf says. Lee is now developing a method to use drone imaging and machine learning to facilitate this mapmaking. Nepf says this will enable researchers or planners to evaluate a given area of marshland and say, “How much is this marsh worth in terms of its ability to reduce flooding?”The White House Office of Information and Regulatory Affairs recently released guidance for assessing the value of ecosystem services in planning of federal projects, Nepf explains.  “But in many scenarios, it lacks specific methods for quantifying value, and this study is meeting that need,” she says.The Federal Emergency Management Agency also has a benefit-cost analysis (BCA) toolkit, Lee notes. “They have guidelines on how to quantify each of the environmental services, and one of the novelties of this paper is quantifying the cost and the protection value of marshes. This is one of the applications that policymakers can consider on how to quantify the environmental service values of marshes,” he says.The software that environmental engineers can apply to specific sites has been made available online for free on GitHub. “It’s a one-dimensional model accessible by a standard consulting firm,” Nepf says.“This paper presents a practical tool for translating the wave attenuation capabilities of marshes into economic values, which could assist decision-makers in the adaptation of marshes for nature-based coastal defense,” says Xioaxia Zhang, a professor at Shenzen University in China who was not involved in this work. “The results indicate that salt marshes are not only environmentally beneficial but also cost-effective.”The study “is a very important and crucial step to quantifying the protective value of marshes,” adds Bas Borsje, an associate professor of nature-based flood protection at the University of Twente in the Netherlands, who was not associated with this work. “The most important step missing at the moment is how to translate our findings to the decision makers. This is the first time I’m aware of that decision-makers are quantitatively informed on the protection value of salt marshes.”Lee received support for this work from the Schoettler Scholarship Fund, administered by the MIT Department of Civil and Environmental Engineering. More

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      in Environment

      Microscopic defects in ice influence how massive glaciers flow, study shows

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      As they seep and calve into the sea, melting glaciers and ice sheets are raising global water levels at unprecedented rates. To predict and prepare for future sea-level rise, scientists need a better understanding of how fast glaciers melt and what influences their flow.Now, a study by MIT scientists offers a new picture of glacier flow, based on microscopic deformation in the ice. The results show that a glacier’s flow depends strongly on how microscopic defects move through the ice.The researchers found they could estimate a glacier’s flow based on whether the ice is prone to microscopic defects of one kind versus another. They used this relationship between micro- and macro-scale deformation to develop a new model for how glaciers flow. With the new model, they mapped the flow of ice in locations across the Antarctic Ice Sheet.Contrary to conventional wisdom, they found, the ice sheet is not a monolith but instead is more varied in where and how it flows in response to warming-driven stresses. The study “dramatically alters the climate conditions under which marine ice sheets may become unstable and drive rapid rates of sea-level rise,” the researchers write in their paper.“This study really shows the effect of microscale processes on macroscale behavior,” says Meghana Ranganathan PhD ’22, who led the study as a graduate student in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS) and is now a postdoc at Georgia Tech. “These mechanisms happen at the scale of water molecules and ultimately can affect the stability of the West Antarctic Ice Sheet.”“Broadly speaking, glaciers are accelerating, and there are a lot of variants around that,” adds co-author and EAPS Associate Professor Brent Minchew. “This is the first study that takes a step from the laboratory to the ice sheets and starts evaluating what the stability of ice is in the natural environment. That will ultimately feed into our understanding of the probability of catastrophic sea-level rise.”Ranganathan and Minchew’s study appears this week in the Proceedings of the National Academy of Sciences.Micro flowGlacier flow describes the movement of ice from the peak of a glacier, or the center of an ice sheet, down to the edges, where the ice then breaks off and melts into the ocean — a normally slow process that contributes over time to raising the world’s average sea level.In recent years, the oceans have risen at unprecedented rates, driven by global warming and the accelerated melting of glaciers and ice sheets. While the loss of polar ice is known to be a major contributor to sea-level rise, it is also the biggest uncertainty when it comes to making predictions.“Part of it’s a scaling problem,” Ranganathan explains. “A lot of the fundamental mechanisms that cause ice to flow happen at a really small scale that we can’t see. We wanted to pin down exactly what these microphysical processes are that govern ice flow, which hasn’t been represented in models of sea-level change.”The team’s new study builds on previous experiments from the early 2000s by geologists at the University of Minnesota, who studied how small chips of ice deform when physically stressed and compressed. Their work revealed two microscopic mechanisms by which ice can flow: “dislocation creep,” where molecule-sized cracks migrate through the ice, and “grain boundary sliding,” where individual ice crystals slide against each other, causing the boundary between them to move through the ice.The geologists found that ice’s sensitivity to stress, or how likely it is to flow, depends on which of the two mechanisms is dominant. Specifically, ice is more sensitive to stress when microscopic defects occur via dislocation creep rather than grain boundary sliding.Ranganathan and Minchew realized that those findings at the microscopic level could redefine how ice flows at much larger, glacial scales.“Current models for sea-level rise assume a single value for the sensitivity of ice to stress and hold this value constant across an entire ice sheet,” Ranganathan explains. “What these experiments showed was that actually, there’s quite a bit of variability in ice sensitivity, due to which of these mechanisms is at play.”A mapping matchFor their new study, the MIT team took insights from the previous experiments and developed a model to estimate an icy region’s sensitivity to stress, which directly relates to how likely that ice is to flow. The model takes in information such as the ambient temperature, the average size of ice crystals, and the estimated mass of ice in the region, and calculates how much the ice is deforming by dislocation creep versus grain boundary sliding. Depending on which of the two mechanisms is dominant, the model then estimates the region’s sensitivity to stress.The scientists fed into the model actual observations from various locations across the Antarctic Ice Sheet, where others had previously recorded data such as the local height of ice, the size of ice crystals, and the ambient temperature. Based on the model’s estimates, the team generated a map of ice sensitivity to stress across the Antarctic Ice Sheet. When they compared this map to satellite and field measurements taken of the ice sheet over time, they observed a close match, suggesting that the model could be used to accurately predict how glaciers and ice sheets will flow in the future.“As climate change starts to thin glaciers, that could affect the sensitivity of ice to stress,” Ranganathan says. “The instabilities that we expect in Antarctica could be very different, and we can now capture those differences, using this model.”  More

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      in Environment

      Study: Heavy snowfall and rain may contribute to some earthquakes

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      When scientists look for an earthquake’s cause, their search often starts underground. As centuries of seismic studies have made clear, it’s the collision of tectonic plates and the movement of subsurface faults and fissures that primarily trigger a temblor.But MIT scientists have now found that certain weather events may also play a role in setting off some quakes.In a study appearing today in Science Advances, the researchers report that episodes of heavy snowfall and rain likely contributed to a swarm of earthquakes over the past several years in northern Japan. The study is the first to show that climate conditions could initiate some quakes.“We see that snowfall and other environmental loading at the surface impacts the stress state underground, and the timing of intense precipitation events is well-correlated with the start of this earthquake swarm,” says study author William Frank, an assistant professor in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). “So, climate obviously has an impact on the response of the solid earth, and part of that response is earthquakes.”The new study focuses on a series of ongoing earthquakes in Japan’s Noto Peninsula. The team discovered that seismic activity in the region is surprisingly synchronized with certain changes in underground pressure, and that those changes are influenced by seasonal patterns of snowfall and precipitation. The scientists suspect that this new connection between quakes and climate may not be unique to Japan and could play a role in shaking up other parts of the world.Looking to the future, they predict that the climate’s influence on earthquakes could be more pronounced with global warming.“If we’re going into a climate that’s changing, with more extreme precipitation events, and we expect a redistribution of water in the atmosphere, oceans, and continents, that will change how the Earth’s crust is loaded,” Frank adds. “That will have an impact for sure, and it’s a link we could further explore.”The study’s lead author is former MIT research associate Qing-Yu Wang (now at Grenoble Alpes University), and also includes EAPS postdoc Xin Cui, Yang Lu of the University of Vienna, Takashi Hirose of Tohoku University, and Kazushige Obara of the University of Tokyo.Seismic speedSince late 2020, hundreds of small earthquakes have shaken up Japan’s Noto Peninsula — a finger of land that curves north from the country’s main island into the Sea of Japan. Unlike a typical earthquake sequence, which begins as a main shock that gives way to a series of aftershocks before dying out, Noto’s seismic activity is an “earthquake swarm” — a pattern of multiple, ongoing quakes with no obvious main shock, or seismic trigger.The MIT team, along with their colleagues in Japan, aimed to spot any patterns in the swarm that would explain the persistent quakes. They started by looking through the Japanese Meteorological Agency’s catalog of earthquakes that provides data on seismic activity throughout the country over time. They focused on quakes in the Noto Peninsula over the last 11 years, during which the region has experienced episodic earthquake activity, including the most recent swarm.With seismic data from the catalog, the team counted the number of seismic events that occurred in the region over time, and found that the timing of quakes prior to 2020 appeared sporadic and unrelated, compared to late 2020, when earthquakes grew more intense and clustered in time, signaling the start of the swarm, with quakes that are correlated in some way.The scientists then looked to a second dataset of seismic measurements taken by monitoring stations over the same 11-year period. Each station continuously records any displacement, or local shaking that occurs. The shaking from one station to another can give scientists an idea of how fast a seismic wave travels between stations. This “seismic velocity” is related to the structure of the Earth through which the seismic wave is traveling. Wang used the station measurements to calculate the seismic velocity between every station in and around Noto over the last 11 years.The researchers generated an evolving picture of seismic velocity beneath the Noto Peninsula and observed a surprising pattern: In 2020, around when the earthquake swarm is thought to have begun, changes in seismic velocity appeared to be synchronized with the seasons.“We then had to explain why we were observing this seasonal variation,” Frank says.Snow pressureThe team wondered whether environmental changes from season to season could influence the underlying structure of the Earth in a way that would set off an earthquake swarm. Specifically, they looked at how seasonal precipitation would affect the underground “pore fluid pressure” — the amount of pressure that fluids in the Earth’s cracks and fissures exert within the bedrock.“When it rains or snows, that adds weight, which increases pore pressure, which allows seismic waves to travel through slower,” Frank explains. “When all that weight is removed, through evaporation or runoff, all of a sudden, that pore pressure decreases and seismic waves are faster.”Wang and Cui developed a hydromechanical model of the Noto Peninsula to simulate the underlying pore pressure over the last 11 years in response to seasonal changes in precipitation. They fed into the model meteorological data from this same period, including measurements of daily snow, rainfall, and sea-level changes. From their model, they were able to track changes in excess pore pressure beneath the Noto Peninsula, before and during the earthquake swarm. They then compared this timeline of evolving pore pressure with their evolving picture of seismic velocity.“We had seismic velocity observations, and we had the model of excess pore pressure, and when we overlapped them, we saw they just fit extremely well,” Frank says.In particular, they found that when they included snowfall data, and especially, extreme snowfall events, the fit between the model and observations was stronger than if they only considered rainfall and other events. In other words, the ongoing earthquake swarm that Noto residents have been experiencing can be explained in part by seasonal precipitation, and particularly, heavy snowfall events.“We can see that the timing of these earthquakes lines up extremely well with multiple times where we see intense snowfall,” Frank says. “It’s well-correlated with earthquake activity. And we think there’s a physical link between the two.”The researchers suspect that heavy snowfall and similar extreme precipitation could play a role in earthquakes elsewhere, though they emphasize that the primary trigger will always originate underground.“When we first want to understand how earthquakes work, we look to plate tectonics, because that is and will always be the number one reason why an earthquake happens,” Frank says. “But, what are the other things that could affect when and how an earthquake happens? That’s when you start to go to second-order controlling factors, and the climate is obviously one of those.”This research was supported, in part, by the National Science Foundation. More

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      in Environment

      MIT-derived algorithm helps forecast the frequency of extreme weather

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      To assess a community’s risk of extreme weather, policymakers rely first on global climate models that can be run decades, and even centuries, forward in time, but only at a coarse resolution. These models might be used to gauge, for instance, future climate conditions for the northeastern U.S., but not specifically for Boston.

      To estimate Boston’s future risk of extreme weather such as flooding, policymakers can combine a coarse model’s large-scale predictions with a finer-resolution model, tuned to estimate how often Boston is likely to experience damaging floods as the climate warms. But this risk analysis is only as accurate as the predictions from that first, coarser climate model.

      “If you get those wrong for large-scale environments, then you miss everything in terms of what extreme events will look like at smaller scales, such as over individual cities,” says Themistoklis Sapsis, the William I. Koch Professor and director of the Center for Ocean Engineering in MIT’s Department of Mechanical Engineering.

      Sapsis and his colleagues have now developed a method to “correct” the predictions from coarse climate models. By combining machine learning with dynamical systems theory, the team’s approach “nudges” a climate model’s simulations into more realistic patterns over large scales. When paired with smaller-scale models to predict specific weather events such as tropical cyclones or floods, the team’s approach produced more accurate predictions for how often specific locations will experience those events over the next few decades, compared to predictions made without the correction scheme.

      Play video

      This animation shows the evolution of storms around the northern hemisphere, as a result of a high-resolution storm model, combined with the MIT team’s corrected global climate model. The simulation improves the modeling of extreme values for wind, temperature, and humidity, which typically have significant errors in coarse scale models. Credit: Courtesy of Ruby Leung and Shixuan Zhang, PNNL

      Sapsis says the new correction scheme is general in form and can be applied to any global climate model. Once corrected, the models can help to determine where and how often extreme weather will strike as global temperatures rise over the coming years. 

      “Climate change will have an effect on every aspect of human life, and every type of life on the planet, from biodiversity to food security to the economy,” Sapsis says. “If we have capabilities to know accurately how extreme weather will change, especially over specific locations, it can make a lot of difference in terms of preparation and doing the right engineering to come up with solutions. This is the method that can open the way to do that.”

      The team’s results appear today in the Journal of Advances in Modeling Earth Systems. The study’s MIT co-authors include postdoc Benedikt Barthel Sorensen and Alexis-Tzianni Charalampopoulos SM ’19, PhD ’23, with Shixuan Zhang, Bryce Harrop, and Ruby Leung of the Pacific Northwest National Laboratory in Washington state.

      Over the hood

      Today’s large-scale climate models simulate weather features such as the average temperature, humidity, and precipitation around the world, on a grid-by-grid basis. Running simulations of these models takes enormous computing power, and in order to simulate how weather features will interact and evolve over periods of decades or longer, models average out features every 100 kilometers or so.

      “It’s a very heavy computation requiring supercomputers,” Sapsis notes. “But these models still do not resolve very important processes like clouds or storms, which occur over smaller scales of a kilometer or less.”

      To improve the resolution of these coarse climate models, scientists typically have gone under the hood to try and fix a model’s underlying dynamical equations, which describe how phenomena in the atmosphere and oceans should physically interact.

      “People have tried to dissect into climate model codes that have been developed over the last 20 to 30 years, which is a nightmare, because you can lose a lot of stability in your simulation,” Sapsis explains. “What we’re doing is a completely different approach, in that we’re not trying to correct the equations but instead correct the model’s output.”

      The team’s new approach takes a model’s output, or simulation, and overlays an algorithm that nudges the simulation toward something that more closely represents real-world conditions. The algorithm is based on a machine-learning scheme that takes in data, such as past information for temperature and humidity around the world, and learns associations within the data that represent fundamental dynamics among weather features. The algorithm then uses these learned associations to correct a model’s predictions.

      “What we’re doing is trying to correct dynamics, as in how an extreme weather feature, such as the windspeeds during a Hurricane Sandy event, will look like in the coarse model, versus in reality,” Sapsis says. “The method learns dynamics, and dynamics are universal. Having the correct dynamics eventually leads to correct statistics, for example, frequency of rare extreme events.”

      Climate correction

      As a first test of their new approach, the team used the machine-learning scheme to correct simulations produced by the Energy Exascale Earth System Model (E3SM), a climate model run by the U.S. Department of Energy, that simulates climate patterns around the world at a resolution of 110 kilometers. The researchers used eight years of past data for temperature, humidity, and wind speed to train their new algorithm, which learned dynamical associations between the measured weather features and the E3SM model. They then ran the climate model forward in time for about 36 years and applied the trained algorithm to the model’s simulations. They found that the corrected version produced climate patterns that more closely matched real-world observations from the last 36 years, not used for training.

      “We’re not talking about huge differences in absolute terms,” Sapsis says. “An extreme event in the uncorrected simulation might be 105 degrees Fahrenheit, versus 115 degrees with our corrections. But for humans experiencing this, that is a big difference.”

      When the team then paired the corrected coarse model with a specific, finer-resolution model of tropical cyclones, they found the approach accurately reproduced the frequency of extreme storms in specific locations around the world.

      “We now have a coarse model that can get you the right frequency of events, for the present climate. It’s much more improved,” Sapsis says. “Once we correct the dynamics, this is a relevant correction, even when you have a different average global temperature, and it can be used for understanding how forest fires, flooding events, and heat waves will look in a future climate. Our ongoing work is focusing on analyzing future climate scenarios.”

      “The results are particularly impressive as the method shows promising results on E3SM, a state-of-the-art climate model,” says Pedram Hassanzadeh, an associate professor who leads the Climate Extremes Theory and Data group at the University of Chicago and was not involved with the study. “It would be interesting to see what climate change projections this framework yields once future greenhouse-gas emission scenarios are incorporated.”

      This work was supported, in part, by the U.S. Defense Advanced Research Projects Agency. More

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      in Environment

      Artificial reef designed by MIT engineers could protect marine life, reduce storm damage

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      The beautiful, gnarled, nooked-and-crannied reefs that surround tropical islands serve as a marine refuge and natural buffer against stormy seas. But as the effects of climate change bleach and break down coral reefs around the world, and extreme weather events become more common, coastal communities are left increasingly vulnerable to frequent flooding and erosion.

      An MIT team is now hoping to fortify coastlines with “architected” reefs — sustainable, offshore structures engineered to mimic the wave-buffering effects of natural reefs while also providing pockets for fish and other marine life.

      The team’s reef design centers on a cylindrical structure surrounded by four rudder-like slats. The engineers found that when this structure stands up against a wave, it efficiently breaks the wave into turbulent jets that ultimately dissipate most of the wave’s total energy. The team has calculated that the new design could reduce as much wave energy as existing artificial reefs, using 10 times less material.

      The researchers plan to fabricate each cylindrical structure from sustainable cement, which they would mold in a pattern of “voxels” that could be automatically assembled, and would provide pockets for fish to explore and other marine life to settle in. The cylinders could be connected to form a long, semipermeable wall, which the engineers could erect along a coastline, about half a mile from shore. Based on the team’s initial experiments with lab-scale prototypes, the architected reef could reduce the energy of incoming waves by more than 95 percent.

      “This would be like a long wave-breaker,” says Michael Triantafyllou, the Henry L. and Grace Doherty Professor in Ocean Science and Engineering in the Department of Mechanical Engineering. “If waves are 6 meters high coming toward this reef structure, they would be ultimately less than a meter high on the other side. So, this kills the impact of the waves, which could prevent erosion and flooding.”

      Details of the architected reef design are reported today in a study appearing in the open-access journal PNAS Nexus. Triantafyllou’s MIT co-authors are Edvard Ronglan SM ’23; graduate students Alfonso Parra Rubio, Jose del Auila Ferrandis, and Erik Strand; research scientists Patricia Maria Stathatou and Carolina Bastidas; and Professor Neil Gershenfeld, director of the Center for Bits and Atoms; along with Alexis Oliveira Da Silva at the Polytechnic Institute of Paris, Dixia Fan of Westlake University, and Jeffrey Gair Jr. of Scinetics, Inc.

      Leveraging turbulence

      Some regions have already erected artificial reefs to protect their coastlines from encroaching storms. These structures are typically sunken ships, retired oil and gas platforms, and even assembled configurations of concrete, metal, tires, and stones. However, there’s variability in the types of artificial reefs that are currently in place, and no standard for engineering such structures. What’s more, the designs that are deployed tend to have a low wave dissipation per unit volume of material used. That is, it takes a huge amount of material to break enough wave energy to adequately protect coastal communities.

      The MIT team instead looked for ways to engineer an artificial reef that would efficiently dissipate wave energy with less material, while also providing a refuge for fish living along any vulnerable coast.

      “Remember, natural coral reefs are only found in tropical waters,” says Triantafyllou, who is director of the MIT Sea Grant. “We cannot have these reefs, for instance, in Massachusetts. But architected reefs don’t depend on temperature, so they can be placed in any water, to protect more coastal areas.”

      MIT researchers test the wave-breaking performance of two artificial reef structures in the MIT Towing Tank.Credit: Courtesy of the researchers

      The new effort is the result of a collaboration between researchers in MIT Sea Grant, who developed the reef structure’s hydrodynamic design, and researchers at the Center for Bits and Atoms (CBA), who worked to make the structure modular and easy to fabricate on location. The team’s architected reef design grew out of two seemingly unrelated problems. CBA researchers were developing ultralight cellular structures for the aerospace industry, while Sea Grant researchers were assessing the performance of blowout preventers in offshore oil structures — cylindrical valves that are used to seal off oil and gas wells and prevent them from leaking.

      The team’s tests showed that the structure’s cylindrical arrangement generated a high amount of drag. In other words, the structure appeared to be especially efficient in dissipating high-force flows of oil and gas. They wondered: Could the same arrangement dissipate another type of flow, in ocean waves?

      The researchers began to play with the general structure in simulations of water flow, tweaking its dimensions and adding certain elements to see whether and how waves changed as they crashed against each simulated design. This iterative process ultimately landed on an optimized geometry: a vertical cylinder flanked by four long slats, each attached to the cylinder in a way that leaves space for water to flow through the resulting structure. They found this setup essentially breaks up any incoming wave energy, causing parts of the wave-induced flow to spiral to the sides rather than crashing ahead.

      “We’re leveraging this turbulence and these powerful jets to ultimately dissipate wave energy,” Ferrandis says.

      Standing up to storms

      Once the researchers identified an optimal wave-dissipating structure, they fabricated a laboratory-scale version of an architected reef made from a series of the cylindrical structures, which they 3D-printed from plastic. Each test cylinder measured about 1 foot wide and 4 feet tall. They assembled a number of cylinders, each spaced about a foot apart, to form a fence-like structure, which they then lowered into a wave tank at MIT. They then generated waves of various heights and measured them before and after passing through the architected reef.

      “We saw the waves reduce substantially, as the reef destroyed their energy,” Triantafyllou says.

      The team has also looked into making the structures more porous, and friendly to fish. They found that, rather than making each structure from a solid slab of plastic, they could use a more affordable and sustainable type of cement.

      “We’ve worked with biologists to test the cement we intend to use, and it’s benign to fish, and ready to go,” he adds.

      They identified an ideal pattern of “voxels,” or microstructures, that cement could be molded into, in order to fabricate the reefs while creating pockets in which fish could live. This voxel geometry resembles individual egg cartons, stacked end to end, and appears to not affect the structure’s overall wave-dissipating power.

      “These voxels still maintain a big drag while allowing fish to move inside,” Ferrandis says.

      The team is currently fabricating cement voxel structures and assembling them into a lab-scale architected reef, which they will test under various wave conditions. They envision that the voxel design could be modular, and scalable to any desired size, and easy to transport and install in various offshore locations. “Now we’re simulating actual sea patterns, and testing how these models will perform when we eventually have to deploy them,” says Anjali Sinha, a graduate student at MIT who recently joined the group.

      Going forward, the team hopes to work with beach towns in Massachusetts to test the structures on a pilot scale.

      “These test structures would not be small,” Triantafyllou emphasizes. “They would be about a mile long, and about 5 meters tall, and would cost something like 6 million dollars per mile. So it’s not cheap. But it could prevent billions of dollars in storm damage. And with climate change, protecting the coasts will become a big issue.”

      This work was funded, in part, by the U.S. Defense Advanced Research Projects Agency. More

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      in Environment

      New tool predicts flood risk from hurricanes in a warming climate

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      Coastal cities and communities will face more frequent major hurricanes with climate change in the coming years. To help prepare coastal cities against future storms, MIT scientists have developed a method to predict how much flooding a coastal community is likely to experience as hurricanes evolve over the next decades.

      When hurricanes make landfall, strong winds whip up salty ocean waters that generate storm surge in coastal regions. As the storms move over land, torrential rainfall can induce further flooding inland. When multiple flood sources such as storm surge and rainfall interact, they can compound a hurricane’s hazards, leading to significantly more flooding than would result from any one source alone. The new study introduces a physics-based method for predicting how the risk of such complex, compound flooding may evolve under a warming climate in coastal cities.

      One example of compound flooding’s impact is the aftermath from Hurricane Sandy in 2012. The storm made landfall on the East Coast of the United States as heavy winds whipped up a towering storm surge that combined with rainfall-driven flooding in some areas to cause historic and devastating floods across New York and New Jersey.

      In their study, the MIT team applied the new compound flood-modeling method to New York City to predict how climate change may influence the risk of compound flooding from Sandy-like hurricanes over the next decades.  

      They found that, in today’s climate, a Sandy-level compound flooding event will likely hit New York City every 150 years. By midcentury, a warmer climate will drive up the frequency of such flooding, to every 60 years. At the end of the century, destructive Sandy-like floods will deluge the city every 30 years — a fivefold increase compared to the present climate.

      “Long-term average damages from weather hazards are usually dominated by the rare, intense events like Hurricane Sandy,” says study co-author Kerry Emanuel, professor emeritus of atmospheric science at MIT. “It is important to get these right.”

      While these are sobering projections, the researchers hope the flood forecasts can help city planners prepare and protect against future disasters. “Our methodology equips coastal city authorities and policymakers with essential tools to conduct compound flooding risk assessments from hurricanes in coastal cities at a detailed, granular level, extending to each street or building, in both current and future decades,” says study author Ali Sarhadi, a postdoc in MIT’s Department of Earth, Atmospheric and Planetary Sciences.

      The team’s open-access study appears online today in the Bulletin of the American Meteorological Society. Co-authors include Raphaël Rousseau-Rizzi at MIT’s Lorenz Center, Kyle Mandli at Columbia University, Jeffrey Neal at the University of Bristol, Michael Wiper at the Charles III University of Madrid, and Monika Feldmann at the Swiss Federal Institute of Technology Lausanne.

      The seeds of floods

      To forecast a region’s flood risk, weather modelers typically look to the past. Historical records contain measurements of previous hurricanes’ wind speeds, rainfall, and spatial extent, which scientists use to predict where and how much flooding may occur with coming storms. But Sarhadi believes that the limitations and brevity of these historical records are insufficient for predicting future hurricanes’ risks.

      “Even if we had lengthy historical records, they wouldn’t be a good guide for future risks because of climate change,” he says. “Climate change is changing the structural characteristics, frequency, intensity, and movement of hurricanes, and we cannot rely on the past.”

      Sarhadi and his colleagues instead looked to predict a region’s risk of hurricane flooding in a changing climate using a physics-based risk assessment methodology. They first paired simulations of hurricane activity with coupled ocean and atmospheric models over time. With the hurricane simulations, developed originally by Emanuel, the researchers virtually scatter tens of thousands of “seeds” of hurricanes into a simulated climate. Most seeds dissipate, while a few grow into category-level storms, depending on the conditions of the ocean and atmosphere.

      When the team drives these hurricane simulations with climate models of ocean and atmospheric conditions under certain global temperature projections, they can see how hurricanes change, for instance in terms of intensity, frequency, and size, under past, current, and future climate conditions.

      The team then sought to precisely predict the level and degree of compound flooding from future hurricanes in coastal cities. The researchers first used rainfall models to simulate rain intensity for a large number of simulated hurricanes, then applied numerical models to hydraulically translate that rainfall intensity into flooding on the ground during landfalling of hurricanes, given information about a region such as its surface and topography characteristics. They also simulated the same hurricanes’ storm surges, using hydrodynamic models to translate hurricanes’ maximum wind speed and sea level pressure into surge height in coastal areas. The simulation further assessed the propagation of ocean waters into coastal areas, causing coastal flooding.

      Then, the team developed a numerical hydrodynamic model to predict how two sources of hurricane-induced flooding, such as storm surge and rain-driven flooding, would simultaneously interact through time and space, as simulated hurricanes make landfall in coastal regions such as New York City, in both current and future climates.  

      “There’s a complex, nonlinear hydrodynamic interaction between saltwater surge-driven flooding and freshwater rainfall-driven flooding, that forms compound flooding that a lot of existing methods ignore,” Sarhadi says. “As a result, they underestimate the risk of compound flooding.”

      Amplified risk

      With their flood-forecasting method in place, the team applied it to a specific test case: New York City. They used the multipronged method to predict the city’s risk of compound flooding from hurricanes, and more specifically from Sandy-like hurricanes, in present and future climates. Their simulations showed that the city’s odds of experiencing Sandy-like flooding will increase significantly over the next decades as the climate warms, from once every 150 years in the current climate, to every 60 years by 2050, and every 30 years by 2099.

      Interestingly, they found that much of this increase in risk has less to do with how hurricanes themselves will change with warming climates, but with how sea levels will increase around the world.

      “In future decades, we will experience sea level rise in coastal areas, and we also incorporated that effect into our models to see how much that would increase the risk of compound flooding,” Sarhadi explains. “And in fact, we see sea level rise is playing a major role in amplifying the risk of compound flooding from hurricanes in New York City.”

      The team’s methodology can be applied to any coastal city to assess the risk of compound flooding from hurricanes and extratropical storms. With this approach, Sarhadi hopes decision-makers can make informed decisions regarding the implementation of adaptive measures, such as reinforcing coastal defenses to enhance infrastructure and community resilience.

      “Another aspect highlighting the urgency of our research is the projected 25 percent increase in coastal populations by midcentury, leading to heightened exposure to damaging storms,” Sarhadi says. “Additionally, we have trillions of dollars in assets situated in coastal flood-prone areas, necessitating proactive strategies to reduce damages from compound flooding from hurricanes under a warming climate.”

      This research was supported, in part, by Homesite Insurance. More

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      in Environment

      Studying rivers from worlds away

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      Rivers have flowed on two other worlds in the solar system besides Earth: Mars, where dry tracks and craters are all that’s left of ancient rivers and lakes, and Titan, Saturn’s largest moon, where rivers of liquid methane still flow today.

      A new technique developed by MIT geologists allows scientists to see how intensely rivers used to flow on Mars, and how they currently flow on Titan. The method uses satellite observations to estimate the rate at which rivers move fluid and sediment downstream.

      Applying their new technique, the MIT team calculated how fast and deep rivers were in certain regions on Mars more than 1 billion years ago. They also made similar estimates for currently active rivers on Titan, even though the moon’s thick atmosphere and distance from Earth make it harder to explore, with far fewer available images of its surface than those of Mars.

      “What’s exciting about Titan is that it’s active. With this technique, we have a method to make real predictions for a place where we won’t get more data for a long time,” says Taylor Perron, the Cecil and Ida Green Professor in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). “And on Mars, it gives us a time machine, to take the rivers that are dead now and get a sense of what they were like when they were actively flowing.”

      Perron and his colleagues have published their results today in the Proceedings of the National Academy of Sciences. Perron’s MIT co-authors are first author Samuel Birch, Paul Corlies, and Jason Soderblom, with Rose Palermo and Andrew Ashton of the Woods Hole Oceanographic Institution (WHOI), Gary Parker of the University of Illinois at Urbana-Champaign, and collaborators from the University of California at Los Angeles, Yale University, and Cornell University.

      River math

      The team’s study grew out of Perron and Birch’s puzzlement over Titan’s rivers. The images taken by NASA’s Cassini spacecraft have shown a curious lack of fan-shaped deltas at the mouths of most of the moon’s rivers, contrary to many rivers on Earth. Could it be that Titan’s rivers don’t carry enough flow or sediment to build deltas?

      The group built on the work of co-author Gary Parker, who in the 2000s developed a series of mathematical equations to describe river flow on Earth. Parker had studied measurements of rivers taken directly in the field by others. From these data, he found there were certain universal relationships between a river’s physical dimensions — its width, depth, and slope — and the rate at which it flowed. He drew up equations to describe these relationships mathematically, accounting for other variables such as the gravitational field acting on the river, and the size and density of the sediment being pushed along a river’s bed.

      “This means that rivers with different gravity and materials should follow similar relationships,” Perron says. “That opened up a possibility to apply this to other planets too.”

      Getting a glimpse

      On Earth, geologists can make field measurements of a river’s width, slope, and average sediment size, all of which can be fed into Parker’s equations to accurately predict a river’s flow rate, or how much water and sediment it can move downstream. But for rivers on other planets, measurements are more limited, and largely based on images and elevation measurements collected by remote satellites. For Mars, multiple orbiters have taken high-resolution images of the planet. For Titan, views are few and far between.

      Birch realized that any estimate of river flow on Mars or Titan would have to be based on the few characteristics that can be measured from remote images and topography — namely, a river’s width and slope. With some algebraic tinkering, he adapted Parker’s equations to work only with width and slope inputs. He then assembled data from 491 rivers on Earth, tested the modified equations on these rivers, and found that the predictions based solely on each river’s width and slope were accurate.

      Then, he applied the equations to Mars, and specifically, to the ancient rivers leading into Gale and Jezero Craters, both of which are thought to have been water-filled lakes billions of years ago. To predict the flow rate of each river, he plugged into the equations Mars’ gravity, and estimates of each river’s width and slope, based on images and elevation measurements taken by orbiting satellites.

      From their predictions of flow rate, the team found that rivers likely flowed for at least 100,000 years at Gale Crater and at least 1 million years at Jezero Crater — long enough to have possibly supported life. They were also able to compare their predictions of the average size of sediment on each river’s bed with actual field measurements of Martian grains near each river, taken by NASA’s Curiosity and Perseverance rovers. These few field measurements allowed the team to check that their equations, applied on Mars, were accurate.

      The team then took their approach to Titan. They zeroed in on two locations where river slopes can be measured, including a river that flows into a lake the size of Lake Ontario. This river appears to form a delta as it feeds into the lake. However, the delta is one of only a few thought to exist on the moon — nearly every viewable river flowing into a lake mysteriously lacks a delta. The team also applied their method to one of these other delta-less rivers.

      They calculated both rivers’ flow and found that they may be comparable to some of the biggest rivers on Earth, with deltas estimated to have a flow rate as large as the Mississippi. Both rivers should move enough sediment to build up deltas. Yet, most rivers on Titan lack the fan-shaped deposits. Something else must be at work to explain this lack of river deposits.

      In another finding, the team calculated that rivers on Titan should be wider and have a gentler slope than rivers carrying the same flow on Earth or Mars. “Titan is the most Earth-like place,” Birch says. ”We’ve only gotten a glimpse of it. There’s so much more that we know is down there, and this remote technique is pushing us a little closer.”

      This research was supported, in part, by NASA and the Heising-Simons Foundation. More