The goal of this Challenge is to optimize petrochemical assets by using Linear Programming. We use Linear Programming…
New tool predicts flood risk from hurricanes in a warming climate
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.
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New model predicts how shoe properties affect a runner’s performance
A good shoe can make a huge difference for runners, from career marathoners to couch-to-5K first-timers. But every runner is unique, and a shoe that works for one might trip up another. Outside of trying on a rack of different designs, there’s no quick and easy way to know which shoe best suits a person’s particular running style.
MIT engineers are hoping to change that with a new model that predicts how certain shoe properties will affect a runner’s performance.
The simple model incorporates a person’s height, weight, and other general dimensions, along with shoe properties such as stiffness and springiness along the midsole. With this input, the model then simulates a person’s running gait, or how they would run, in a particular shoe.
Using the model, the researchers can simulate how a runner’s gait changes with different shoe types. They can then pick out the shoe that produces the best performance, which they define as the degree to which a runner’s expended energy is minimized.
While the model can accurately simulate changes in a runner’s gait when comparing two very different shoe types, it is less discerning when comparing relatively similar designs, including most commercially available running shoes. For this reason, the researchers envision the current model would be best used as a tool for shoe designers looking to push the boundaries of sneaker design.
“Shoe designers are starting to 3D print shoes, meaning they can now make them with a much wider range of properties than with just a regular slab of foam,” says Sarah Fay, a postdoc in MIT’s Sports Lab and the Institute for Data, Systems, and Society (IDSS). “Our model could help them design really novel shoes that are also high-performing.”
The team is planning to improve the model, in hopes that consumers can one day use a similar version to pick shoes that fit their personal running style.
“We’ve allowed for enough flexibility in the model that it can be used to design custom shoes and understand different individual behaviors,” Fay says. “Way down the road, we imagine that if you send us a video of yourself running, we could 3D print the shoe that’s right for you. That would be the moonshot.”
The new model is reported in a study appearing this month in the Journal of Biomechanical Engineering. The study is authored by Fay and Anette “Peko” Hosoi, professor of mechanical engineering at MIT.
Running, revamped
The team’s new model grew out of talks with collaborators in the sneaker industry, where designers have started to 3D print shoes at commercial scale. These designs incorporate 3D-printed midsoles that resemble intricate scaffolds, the geometry of which can be tailored to give a certain bounce or stiffness in specific locations across the sole.
“With 3D printing, designers can tune everything about the material response locally,” Hosoi says. “And they came to us and essentially said, ‘We can do all these things. What should we do?’”
“Part of the design problem is to predict what a runner will do when you put an entirely new shoe on them,” Fay adds. “You have to couple the dynamics of the runner with the properties of the shoe.”
Fay and Hosoi looked first to represent a runner’s dynamics using a simple model. They drew inspiration from Thomas McMahon, a leader in the study of biomechanics at Harvard University, who in the 1970s used a very simple “spring and damper” model to model a runner’s essential gait mechanics. Using this gait model, he predicted how fast a person could run on various track types, from traditional concrete surfaces to more rubbery material. The model showed that runners should run faster on softer, bouncier tracks that supported a runner’s natural gait.
Though this may be unsurprising today, the insight was a revelation at the time, prompting Harvard to revamp its indoor track — a move that quickly accumulated track records, as runners found they could run much faster on the softier, springier surface.
“McMahon’s work showed that, even if we don’t model every single limb and muscle and component of the human body, we’re still able to create meaningful insights in terms of how we design for athletic performance,” Fay says.
Gait cost
Following McMahon’s lead, Fay and Hosoi developed a similar, simplified model of a runner’s dynamics. The model represents a runner as a center of mass, with a hip that can rotate and a leg that can stretch. The leg is connected to a box-like shoe, with springiness and shock absorption that can be tuned, both vertically and horizontally.
They reasoned that they should be able to input into the model a person’s basic dimensions, such as their height, weight, and leg length, along with a shoe’s material properties, such as the stiffness of the front and back midsole, and use the model to simulate what a person’s gait is likely to be when running in that shoe.
But they also realized that a person’s gait can depend on a less definable property, which they call the “biological cost function” — a quality that a runner might not consciously be aware of but nevertheless may try to minimize whenever they run. The team reasoned that if they can identify a biological cost function that is general to most runners, then they might predict not only a person’s gait for a given shoe but also which shoe produces the gait corresponding to the best running performance.
With this in mind, the team looked to a previous treadmill study, which recorded detailed measurements of runners, such as the force of their impacts, the angle and motion of their joints, the spring in their steps, and the work of their muscles as they ran, each in the same type of running shoe.
Fay and Hosoi hypothesized that each runner’s actual gait arose not only from their personal dimensions and shoe properties, but also a subconscious goal to minimize one or more biological measures, yet unknown. To reveal these measures, the team used their model to simulate each runner’s gait multiple times. Each time, they programmed the model to assume the runner minimized a different biological cost, such as the degree to which they swing their leg or the impact that they make with the treadmill. They then compared the modeled gait with the runner’s actual gait to see which modeled gait — and assumed cost — matched the actual gait.
In the end, the team found that most runners tend to minimize two costs: the impact their feet make with the treadmill and the amount of energy their legs expend.
“If we tell our model, ‘Optimize your gait on these two things,’ it gives us really realistic-looking gaits that best match the data we have,” Fay explains. “This gives us confidence that the model can predict how people will actually run, even if we change their shoe.”
As a final step, the researchers simulated a wide range of shoe styles and used the model to predict a runner’s gait and how efficient each gait would be for a given type of shoe.
“In some ways, this gives you a quantitative way to design a shoe for a 10K versus a marathon shoe,” Hosoi says. “Designers have an intuitive sense for that. But now we have a mathematical understanding that we hope designers can use as a tool to kickstart new ideas.”
This research is supported, in part, by adidas.
What’s the Environmental Impact of Your Website?
The web was once commonly thought to be a “green” platform. That makes sense, given the times. Electronic documents weren’t as popular. Using a website could save lots of printer paper and ink.
Yes, websites often eliminate the need for physical copies of documents. But there was much we didn’t consider in those days.
We didn’t think about massive server farms and the electricity required to run them. Nor did we consider the resources needed to load every image, video, and passage of text in a browser. And what about the costs associated with creating content?
Websites have an impact on our environment. Every site is an offender to some degree. The good news is that we can always do better.
Let’s examine the relationship between the web and the planet. Along the way, we’ll show you how to measure your website’s impact. And we’ll offer tips for reducing its carbon footprint.
The Importance of Sustainable Web Design
Web design is a multifaceted process. We create beautiful user interfaces. But there are other areas of focus. Websites also need to be usable and accessible.
We should now add sustainability to the equation. The world has moved online. Power consumption continues to grow. Thus, it’s worth considering how our decisions impact the environment.
Sustainable web design may sound scary – like it will require drastic measures. Eliminating the use of images due to their carbon footprint, for example. However, it may be more familiar than we think.
Sustainability and performance can go hand-in-hand. Performant practices can also be a win for the planet. It stands to reason that a page that loads quickly will also require fewer resources.
There are areas where the two may diverge, though. Web hosting is a prime example. Using a beefed-up server benefits performance. But that also comes with higher energy usage.
The path to being gentler on Mother Earth isn’t always a straight line. Doing right by your clients and the environment takes careful thought. Web designers must now view these processes through a different lens.
Perhaps you’re now wondering about your website’s environmental impact. So, how can you measure it?
Several web applications are available to help. We’ll choose Website Carbon Calculator for our example. The service has developed a methodology for calculating a site’s carbon footprint.
It measures the amount of site data, energy source, and related metrics. From there, you’ll receive a score based on this formula.
Enter your URL into the calculator and see where your website ranks. The results offer usage examples based on the number of monthly pageviews.
For instance, you’ll see how many trees it takes to absorb the carbon from your website. Or how far an electric vehicle can travel on the energy used. You can change the monthly pageviews to see how it impacts the resources required.
The numbers provided may not be exact. It does offer a glimpse of how eco-friendly your website is (or isn’t), though. You’ll have a better idea if you’re on the right path.
We hope your website scored well! If not, that’s OK. That means there is plenty of room for improvement. And you’ll find quite a few places to look.
Here are a few ways you can reduce your website’s carbon footprint.
Use an Environmentally Friendly Web Host
No two web hosts are the same. And that includes their sustainability policies.
Website Carbon Calculator takes this into account when testing your website. You receive a higher score if your host uses “green” energy or carbon offsets. For reference, you can find this data on The Green Web Directory.
Yes, changing hosts can be a pain. However, switching to an environmentally conscious provider might be worth it. You’ll be rewarding them for their efforts. And it’s something you can promote to clients.
Clean Up Your CSS & JavaScript
Websites can become bloated with CSS and JavaScript. Unused styles and scripts eat up precious resources. They’ll slow you down and place an extra strain on your server.
Here’s where performance and sustainability intersect. Loading only the necessary items improves both areas.
Your browser’s developer tools can help. They’ll allow you to assess each page load. From there, you can eliminate anything that isn’t needed.
Optimize Your Site’s Media
Your site’s images, audio, and video are ripe for optimization. And a little effort here can go a long way.
Make sure to use the latest codecs and formats. For example, WebP images can save space while maintaining quality.
It may not seem like much on a per-file basis. But saving a few kilobytes (KB) here and there adds up. You’ll use less bandwidth, less energy, and increase performance.
You might also consider efficiencies like content delivery networks (CDN). Or by hosting your videos on a service like Vimeo or YouTube. These providers fine-tune their servers for specific tasks. All while removing the burden from your web host.
Inspect Your Custom Code
Inefficient code can be costly. It may result in extra hits to your site’s database. Or require more CPU cycles to run. You could also chew up your server’s available memory.
All of this leads to more power consumption. The good news is that there are opportunities to trim the fat.
Spend some time reviewing any code you’ve written. Ensure that it runs as needed and that it does so efficiently. Run performance tests to gauge the effectiveness of your changes.
Third-party code might also be an issue. WordPress plugins can be a culprit. Use software that is actively maintained and supported. Remove or replace anything that’s hurting performance.
Get a Handle on Bot Traffic
Bots from search engines and other services visit your site often. Perhaps more than you might imagine. And that’s not counting the many brute-force attempts from malicious actors.
However, most websites don’t benefit from frequent bot traffic. It’s likely overkill unless your content is frequently updated.
All of this adds up to more carbon emissions. But it’s possible to keep these bots at bay.
WordPress users can turn to the Yoast SEO plugin. Its crawl optimization features allow you to reduce bot traffic. It’s an easy way to turn off features that you aren’t using.
There are other options. A CDN can help you limit bot traffic. Use security apps to ban hackers. And you can still use a robots.txt file to create custom indexing rules.
Small Steps to Creating a Greener Web
Every website we build has a carbon footprint. The worst offenders tend to be outdated websites and those with sloppy code. However, using modern best practices can make a world of difference.
Going further, consider the environmental cost of your design decisions. That means you’ll be building a greener website from the start.
You’ll not only reduce the emissions produced by your site. You might also save some money and improve the user experience.
So, take a moment to measure your site’s environmental impact. Then, look for areas of improvement. The steps you take will benefit everyone.
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