Avalanches, Icy Explosions, and Dunes: NASA Is Tracking New Year on Mars - UNIVERSE

 

It’s a new year on Mars, and while New Year’s means winter in Earth’s northern hemisphere, it’s the start of spring in the same region of the Red Planet. And that means ice is thawing, leading to all sorts of interesting things. JPL research scientist Serina Diniega explains. NASA/JPL-Caltech

Instead of a winter wonderland, the Red Planet’s northern hemisphere goes through an active — even explosive — spring thaw.

While New Year’s Eve is around the corner here on Earth, Mars scientists are ahead of the game: The Red Planet completed a trip around the Sun on Nov. 12, 2024, prompting a few researchers to raise a toast.

But the Martian year, which is 687 Earth days, ends in a very different way in the planet’s northern hemisphere than it does in Earth’s northern hemisphere: While winter’s kicking in here, spring is starting there. That means temperatures are rising and ice is thinning, leading to frost avalanches crashing down cliffsides, carbon dioxide gas exploding from the ground, and powerful winds helping reshape the north pole.

“Springtime on Earth has lots of trickling as water ice gradually melts. But on Mars, everything happens with a bang,” said Serina Diniega, who studies planetary surfaces at NASA’s Jet Propulsion Laboratory in Southern California.

Mars’ wispy atmosphere doesn’t allow liquids to pool on the surface, like on Earth. Instead of melting, ice sublimates, turning directly into a gas. The sudden transition in spring means a lot of violent changes as both water ice and carbon dioxide ice — dry ice, which is much more plentiful on Mars than frozen water — weaken and break.

“You get lots of cracks and explosions instead of melting,” Diniega said. “I imagine it gets really noisy.”

Using the cameras and other sensors aboard NASA’s Mars Reconnaissance Orbiter (MRO), which launched in 2005, scientists study all this activity to improve their understanding of the forces shaping the dynamic Martian surface. Here’s some of what they track.

Frost Avalanches

In 2015, MRO’s High-Resolution Imaging Science Experiment (HiRISE) camera captured a 66-foot-wide (20-meter-wide) chunk of carbon dioxide frost in freefall. Chance observations like this are reminders of just how different Mars is from Earth, Diniega said, especially in springtime, when these surface changes are most noticeable.

Martian spring involves lots of cracking ice, which led to this 66-foot-wide (20-meter-wide) chunk of carbon dioxide frost captured in freefall by the HiRISE camera aboard NASA’s Mars Reconnaissance Orbiter in 2015

NASA/JPL-Caltech/University of Arizona

“We’re lucky we’ve had a spacecraft like MRO observing Mars for as long as it has,” Diniega said. “Watching for almost 20 years has let us catch dramatic moments like these avalanches.”

Gas Geysers

Diniega has relied on HiRISE to study another quirk of Martian springtime: gas geysers that blast out of the surface, throwing out dark fans of sand and dust. These explosive jets form due to energetic sublimation of carbon dioxide ice. As sunlight shines through the ice, its bottom layers turn to gas, building pressure until it bursts into the air, creating those dark fans of material.

As light shines through carbon dioxide ice on Mars, it heats up its bottom layers, which, rather than melting into a liquid, turn into gas. The buildup gas eventually results in explosive geysers that toss dark fans of debris on to the surface.

NASA/JPL-Caltech/University of Arizona

But to see the best examples of the newest fans, researchers will have to wait until December 2025, when spring starts in the southern hemisphere. There, the fans are bigger and more clearly defined.

Spiders

Another difference between ice-related action in the two hemispheres: Once all the ice around some northern geysers has sublimated in summer, what’s left behind in the dirt are scour marks that, from space, look like giant spider legs. Researchers recently re-created this process in a JPL lab.

Sometimes, after carbon dioxide geysers have erupted from ice-covered areas on Mars, they leave scour marks on the surface. When the ice is all gone by summer, these long scour marks look like the legs of giant spiders.

NASA/JPL-Caltech/University of Arizona

Powerful Winds

For Isaac Smith of Toronto’s York University, one of the most fascinating subjects in springtime is the Texas-size ice cap at Mars’ north pole. Etched into the icy dome are swirling troughs, revealing traces of the red surface below. The effect is like a swirl of milk in a café latte.

“These things are enormous,” Smith said, noting that some are a long as California. “You can find similar troughs in Antarctica but nothing at this scale.”

As temperatures rise, powerful winds kick up that carve deep troughs into the ice cap of Mars’ north pole. Some of these troughs are as long as California, and give the Martian north pole its trademark swirls. This image was captured by NASA’s now-inactive Mars Global Surveyor.

NASA/JPL-Caltech/MSSS

Fast, warm wind has carved the spiral shapes over eons, and the troughs act as channels for springtime wind gusts that become more powerful as ice at the north pole starts to thaw. Just like the Santa Ana winds in Southern California or the Chinook winds in the Rocky Mountains, these gusts pick up speed and temperature as they ride down the troughs — what’s called an adiabatic process.

Wandering Dunes

The winds that carve the north pole’s troughs also reshape Mars’ sand dunes, causing sand to pile up on one side while removing sand from the other side. Over time, the process causes dunes to migrate, just as it does with dunes on Earth.

This past September, Smith coauthored a paper detailing how carbon dioxide frost settles on top of polar sand dunes during winter, freezing them in place. When the frost all thaws away in the spring, the dunes begin migrating again.

Surrounded by frost, these Martian dunes in Mars’ northern hemisphere were captured from above by NASA’s Mars Reconnaissance Orbiter using its HiRISE camera on Sept. 8, 2022.

NASA/JPL-Caltech/University of Arizona

Each northern spring is a little different, with variations leading to ice sublimating faster or slower, controlling the pace of all these phenomena on the surface. And these strange phenomena are just part of the seasonal changes on Mars: the southern hemisphere has its own unique activity.

More About MRO

The University of Arizona, in Tucson, operates HiRISE, which was built by Ball Aerospace & Technologies Corp., in Boulder, Colorado. NASA’s Jet Propulsion Laboratory, a division of Caltech in Pasadena, California, manages the Mars Reconnaissance Orbiter Project for NASA’s Science Mission Directorate, Washington.

For more information, visit:

https://science.nasa.gov/mission/mars-reconnaissance-orbiter  

By: Jet Propulsion Laboratory

Source: Avalanches, Icy Explosions, and Dunes: NASA Is Tracking New Year on Mars - NASA

Virus that threatened humanity opens the future

Professor Sangmin Lee from POSTECH’s Department of Chemical Engineering, in collaboration with 2024 Nobel Chemistry Laureate Professor David Baker from the University of Washington, has developed an innovative therapeutic platform by mimicking the intricate structures of viruses using artificial intelligence (AI). Their pioneering research was published in Nature on December 18 (local time).

Viruses are uniquely designed to encapsulate genetic material within spherical protein shells, enabling them to replicate and invade host cells, often causing disease. Inspired by these complex structures, researchers have been exploring artificial proteins modeled after viruses. These “nanocages” mimic viral behavior, effectively delivering therapeutic genes to target cells. However, existing nanocages face significant challenges: their small size restricts the amount of genetic material they can carry, and their simple designs fall short of replicating the multifunctionality of natural viral proteins.

To address these limitations, the research team used AI-driven computational design. While most viruses display symmetrical structures, they also feature subtle asymmetries. Leveraging AI, the team recreated these nuanced characteristics and successfully designed nanocages in tetrahedral, octahedral, and icosahedral shapes for the first time.

The resulting nanostructures are composed of four types of artificial proteins, forming intricate architectures with six distinct protein-protein interfaces. Among these, the icosahedral structure, measuring up to 75 nanometers in diameter, stands out for its ability to hold three times more genetic material than conventional gene delivery vectors, such as adeno-associated viruses (AAV^*1), marking a significant advancement in gene therapy.

Electron microscopy confirmed the AI-designed nanocages achieved precise symmetrical structures as intended. Functional experiments further demonstrated their ability to effectively deliver therapeutic payloads to target cells, paving the way for practical medical applications.

“Advancements in AI have opened the door to a new era where we can design and assemble artificial proteins to meet humanity’s needs,” said Professor Sangmin Lee. “We hope this research not only accelerates the development of gene therapies but also drives breakthroughs in next-generation vaccines and other biomedical innovations.”

Professor Lee previously worked as a postdoctoral researcher in Professor Baker’s laboratory at the University of Washington for nearly three years, from February 2021 to late 2023, before joining POSTECH in January 2024.

Source: https://www.postech.ac.kr/eng/virus-that-threatened-humanity-opens-the-future/

Journal article: https://www.nature.com/articles/s41586-024-07814-1 

Source: Virus that threatened humanity opens the future – Scents of Science

Crossing the Uncanny Valley: Breakthrough in technology for lifelike facial expressions in androids

Even if an android’s appearance is so realistic that it could be mistaken for a human in a photograph, watching it move in person can feel a bit unsettling. It can smile, frown, or display other various, familiar expressions, but finding a consistent emotional state behind those expressions can be difficult, leaving you unsure of what it is truly feeling and creating a sense of unease.

Until now, when allowing robots that can move many parts of their face, like androids, to display facial expressions for extended periods, a ‘patchwork method’ has been used. This method involves preparing multiple pre-arranged action scenarios to ensure that unnatural facial movements are excluded while switching between these scenarios as needed.

However, this poses practical challenges, such as preparing complex action scenarios beforehand, minimizing noticeable unnatural movements during transitions, and fine-tuning movements to subtly control the expressions conveyed.

In this study, lead author Hisashi Ishihara and his research group developed a dynamic facial expression synthesis technology using “waveform movements,” which represents various gestures that constitute facial movements, such as “breathing,” “blinking,” and “yawning,” as individual waves. These waves are propagated to the related facial areas and are overlaid to generate complex facial movements in real time. This method eliminates the need for the preparation of complex and diverse action data while also avoiding noticeable movement transitions.

Furthermore, by introducing “waveform modulation,” which adjusts the individual waveforms based on the robot’s internal state, changes in internal conditions, such as mood, can be instantly reflected as variations in facial movements.”

“Advancing this research in dynamic facial expression synthesis will enable robots capable of complex facial movements to exhibit more lively expressions and convey mood changes that respond to their surrounding circumstances, including interactions with humans,” says senior author Koichi Osuka. “This could greatly enrich emotional communication between humans and robots.”

Ishihara adds, “Rather than creating superficial movements, further development of a system in which internal emotions are reflected in every detail of an android’s actions could lead to the creation of androids perceived as having a heart.”

By realizing the function to adaptively adjust and express emotions, this technology is expected to significantly enhance the value of communication robots, allowing them to exchange information with humans in a more natural, humanlike manner. 

Source: https://resou.osaka-u.ac.jp/en/research/2024/20241223_2

Image Credit: Hisashi Ishihara 

Source: Crossing the Uncanny Valley: Breakthrough in technology for lifelike facial expressions in androids – Scents of Science  

Ready, Set, Action! Our Sun is the Star in Dazzling Simulation - UNIVERSE

 

A 3D simulation showing the evolution of turbulent flows in the upper layers of the Sun. The more saturated and bright reds represent the most vigorous upward or downward twisting motions. Clear areas represent areas where there are only relatively slow up-flows, with very little twisting.

NASA/Irina Kitiashvili and Timothy A. Sandstrom

NASA supercomputers are shedding light on what causes some of the Sun’s most complex behaviors. Using data from the suite of active Sun-watching spacecraft currently observing the star at the heart of our solar system, researchers can explore solar dynamics like never before. 

The animation shows the strength of the turbulent motions of the Sun’s inner layers as materials twist into its atmosphere, resembling a roiling pot of boiling water or a flurry of schooling fish sending material bubbling up to the surface or diving it further down below. 

“Our simulations use what we call a realistic approach, which means we include as much as we know to-date about solar plasma to reproduce different phenomena observed with NASA space missions,” said Irina Kitiashvili, a scientist at NASA’s Ames Research Center in California’s Silicon Valley who helped lead the study. 

Using modern computational capabilities, the team was able for the first time to reproduce the fine structures of the subsurface layer observed with NASA’s Solar Dynamics Observatory.

“Right now, we don’t have the computational capabilities to create realistic global models of the entire Sun due to the complexity,” said Kitiashvili. “Therefore, we create models of smaller areas or layers, which can show us structures of the solar surface and atmosphere – like shock waves or tornado-like features measuring only a few miles in size; that’s much finer detail than any one spacecraft can resolve.”

Scientists seek to better understand the Sun and what phenomena drive the patterns of its activity. The connection and interactions between the Sun and Earth drive the seasons, ocean currents, weather, climate, radiation belts, auroras and many other phenomena. Space weather predictions are critical for exploration of space, supporting the spacecraft and astronauts of NASA’s Artemis campaign. Surveying this space environment is a vital part of understanding and mitigating astronaut exposure to space radiation and keeping our spacecraft and instruments safe.

This has been a big year for our special star, studded with events like the annular eclipse, a total eclipse, and the Sun reaching its solar maximum period. In December 2024, NASA’s Parker Solar Probe mission – which is helping researchers to understand space weather right at the source – will make its closest-ever approach to the Sun and beat its own record of being the closest human-made object to reach the Sun. 

“The Sun keeps surprising us. We are looking forward to seeing what kind of exciting events will be organized by the Sun."

Irina Kitiashvili

NASA Scientist

“The Sun keeps surprising us,” said Kitiashvili. “We are looking forward to seeing what kind of exciting events will be organized by the Sun.”

These simulations were run on the Pleaides supercomputer at the NASA Advanced Supercomputing facility at NASA Ames over several weeks of runtime, generating terabytes of data. 

NASA is showcasing 29 of the agency’s computational achievements at SC24, the international supercomputing conference, Nov. 17-22, 2024, in Atlanta, Georgia. For more technical information, visit: ​https://www.nas.nasa.gov/sc24  

By: Rachel Hoover

Source: Ready, Set, Action! Our Sun is the Star in Dazzling Simulation - NASA  

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NASA’s Parker Solar Probe Makes History With Closest Pass to Sun - UNIVERSE

Operations teams have confirmed NASA’s mission to “touch” the Sun survived its record-breaking closest approach to the solar surface on Dec. 24, 2024.

Breaking its previous record by flying just 3.8 million miles above the surface of the Sun, NASA’s Parker Solar Probe hurtled through the solar atmosphere at a blazing 430,000 miles per hour — faster than any human-made object has ever moved. A beacon tone received late on Dec. 26 confirmed the spacecraft had made it through the encounter safely and is operating normally.

This pass, the first of more to come at this distance, allows the spacecraft to conduct unrivaled scientific measurements with the potential to change our understanding of the Sun.

“Flying this close to the Sun is a historic moment in humanity’s first mission to a star,” said Nicky Fox, who leads the Science Mission Directorate at NASA Headquarters in Washington. “By studying the Sun up close, we can better understand its impacts throughout our solar system, including on the technology we use daily on Earth and in space, as well as learn about the workings of stars across the universe to aid in our search for habitable worlds beyond our home planet.” 

NASA’s Parker Solar Probe survived its record-breaking closest approach to the solar surface on Dec. 24, 2024. Breaking its previous record by flying just 3.8 million miles above the surface of the Sun, the spacecraft hurtled through the solar atmosphere at a blazing 430,000 miles per hour — faster than any human-made object has ever moved.
Credits: NASA

Parker Solar Probe has spent the last six years setting up for this moment. Launched in 2018, the spacecraft used seven flybys of Venus to gravitationally direct it ever closer to the Sun. With its last Venus flyby on Nov. 6, 2024, the spacecraft reached its optimal orbit. This oval-shaped orbit brings the spacecraft an ideal distance from the Sun every three months — close enough to study our Sun’s mysterious processes but not too close to become overwhelmed by the Sun’s heat and damaging radiation. The spacecraft will remain in this orbit for the remainder of its primary mission.

“Parker Solar Probe is braving one of the most extreme environments in space and exceeding all expectations,” said Nour Rawafi, the project scientist for Parker Solar Probe at the Johns Hopkins Applied Physics Laboratory (APL), which designed, built, and operates the spacecraft from its campus in Laurel, Maryland. “This mission is ushering a new golden era of space exploration, bringing us closer than ever to unlocking the Sun’s deepest and most enduring mysteries.”

Close to the Sun, the spacecraft relies on a carbon foam shield to protect it from the extreme heat in the upper solar atmosphere called the corona, which can exceed 1 million degrees Fahrenheit. The shield was designed to reach temperatures of 2,600 degrees Fahrenheit — hot enough to melt steel — while keeping the instruments behind it shaded at a comfortable room temperature. In the hot but low-density corona, the spacecraft’s shield is expected to warm to 1,800 degrees Fahrenheit.

The spacecraft’s record close distance of 3.8 million miles may sound far, but on cosmic scales it’s incredibly close. If the solar system was scaled down with the distance between the Sun and Earth the length of a football field, Parker Solar Probe would be just four yards from the end zone — close enough to pass within the tenuous outer atmosphere of the Sun known as the corona. NASA/APL

“It’s monumental to be able to get a spacecraft this close to the Sun,” said John Wirzburger, the Parker Solar Probe mission systems engineer at APL. “This is a challenge the space science community has wanted to tackle since 1958 and had spent decades advancing the technology to make it possible.”

By flying through the solar corona, Parker Solar Probe can take measurements that help scientists better understand how the region gets so hot, trace the origin of the solar wind (a constant flow of material escaping the Sun), and discover how energetic particles are accelerated to half the speed of light.

“The data is so important for the science community because it gives us another vantage point,” said Kelly Korreck, a program scientist at NASA Headquarters and heliophysicist who worked on one of the mission’s instruments. “By getting firsthand accounts of what’s happening in the solar atmosphere, Parker Solar Probe has revolutionized our understanding of the Sun.”

Previous passes have already aided scientists’ understanding of the Sun. When the spacecraft first passed into the solar atmosphere in 2021, it found the outer boundary of the corona is wrinkled with spikes and valleys, contrary to what was expected. Parker Solar Probe also pinpointed the origin of important zig-zag-shaped structures in the solar wind, called switchbacks, at the visible surface of the Sun — the photosphere.

Since that initial pass into the Sun, the spacecraft has been spending more time in the corona, where most of the critical physical processes occur.

This conceptual image shows Parker Solar Probe about to enter the solar corona. NASA/Johns Hopkins APL/Ben Smith

“We now understand the solar wind and its acceleration away from the Sun,” said Adam Szabo, the Parker Solar Probe mission scientist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “This close approach will give us more data to understand how it’s accelerated closer in.”

Parker Solar Probe has also made discoveries across the inner solar system. Observations showed how giant solar explosions called coronal mass ejections vacuum up dust as they sweep across the solar system, and other observations revealed unexpected findings about solar energetic particles. Flybys of Venus have documented the planet’s natural radio emissions from its atmosphere, as well as the first complete image of its orbital dust ring.

So far, the spacecraft has only transmitted that it’s safe, but soon it will be in a location that will allow it to downlink the data it collected on this latest solar pass.

“The data that will come down from the spacecraft will be fresh information about a place that we, as humanity, have never been.”

Joe Westlake  Heliophysics Division Director, NASA Headquarters

“The data that will come down from the spacecraft will be fresh information about a place that we, as humanity, have never been,” said Joe Westlake, the director of the Heliophysics Division at NASA Headquarters. “It’s an amazing accomplishment.”

The spacecraft’s next planned close solar passes come on March 22, 2025, and June 19, 2025.

For more information source: NASA’s Parker Solar Probe Makes History With Closest Pass to Sun - NASA Science

NASA 2025: To the Moon, Mars, and Beyond

 

Want to design the car of the future? Here are 8,000 designs to get you started

In a new dataset that includes more than 8,000 car designs, MIT engineers simulated the aerodynamics for a given car shape, which they represent in various modalities, including "surface fields." Credit: Mohamed Elrefaie

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. The study is published on the arXiv preprint server.

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 2024 conference in December in Vancouver. 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.

Credit: Massachusetts Institute of Technology

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.

In a new dataset that includes more than 8,000 car designs, MIT engineers simulate the aerodynamics for a given car shape, which they represent in various modalities, including "surface fields" (left) and "streamlines" (right). Credit: Mohamed Elrefaie

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 more than 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." 

by Jennifer Chu, Massachusetts Institute of Technology

Source: Want to design the car of the future? Here are 8,000 designs to get you started