The University of Michigan has developed a groundbreaking prototype that could revolutionize the way we design and navigate underwater vehicles. By taking inspiration from the humble golf ball, researchers have created a spherical prototype with adjustable surface dimples that can drastically reduce drag while eliminating the need for protruding appendages like fins or rudders.

Anchal Sareen, U-M assistant professor of naval architecture and marine engineering, led the research team in developing the smart morphable sphere. The team formed the prototype by stretching a thin layer of latex over a hollow sphere dotted with holes, resembling a pickleball. A vacuum pump depressurizes the core, pulling the latex inwards to create precise dimples when switched on.

To test how the dimples affected drag, the sphere was put through its paces within a 3-meter-long wind tunnel. The researchers found that for high wind speeds, shallower dimples cut the drag more effectively while deeper dimples were more efficient at lower wind speeds. By adjusting dimple depth, the sphere reduced drag by 50% compared to a smooth counterpart for all conditions.

Moreover, the adaptive skin setup was able to notice changes in the speed of the incoming air and adjust dimples accordingly to maintain drag reductions. This concept could be applied to underwater vehicles, reducing both drag and fuel consumption.

The smart morphable sphere can also generate lift, allowing for controlled movement. By designing the inner skeleton with holes on only one side, the researchers created asymmetric flow separation on the two sides of the sphere, deflecting the wake toward the smooth side. This effectively pushed the sphere in the direction of the dimples, enabling precise steering by selectively activating dimples on the desired side.

The team tested the new sphere in the same wind tunnel setup with varying wind velocity and dimple depth. With the optimal dimple depth, the half rough/half smooth sphere generated lift forces up to 80% of the drag force. This is comparable to the Magnus effect, but instead of using rotation, it was created entirely by modifying the surface texture.

The implications of this research are vast and exciting. For example, compact spherical robotic submarines that prioritize maneuverability over speed for exploration and inspection could benefit from this mechanism, reducing the need for multiple propulsion systems.

Anchal Sareen anticipates collaborations that combine expertise in materials science and soft robotics, further advancing the capabilities of this dynamic skin technology. She believes that this smart dynamic skin technology could be a game-changer for unmanned aerial and underwater vehicles, offering a lightweight, energy-efficient, and highly responsive alternative to traditional jointed control surfaces.

Ultimately, this innovation promises to enhance maneuverability, optimize performance, and unlock new possibilities for vehicle design. As researchers continue to explore and refine this technology, we can expect to see significant advancements in the field of underwater vehicles and beyond.

Satellite Data from Ship Captures Landslide-Generated Tsunami: A Breakthrough in Early Warning Systems

Landslide-generated tsunamis pose a significant threat to coastal communities, particularly within narrow fjords where tall cliffs can trap and amplify waves. Scientists have traditionally relied on earthquake-based observation systems to issue tsunami warnings, but these methods often fail to capture localized ground movement caused by landslides.

In a groundbreaking study published in Geophysical Research Letters, researchers from the University of Colorado Boulder’s Cooperative Institute for Research in Environmental Sciences (CIRES) and the University of Alaska Fairbanks have successfully detected tsunami waves generated by a landslide using data from a ship’s satellite receiver. This achievement has significant implications for improving early warning systems and saving lives.

On May 8, 2022, a landslide near the port city of Seward, Alaska, sent debris tumbling into Resurrection Bay, creating a series of small tsunami waves. The R/V Sikuliaq, a research ship owned by the National Science Foundation and operated by the University of Alaska Fairbanks, was moored 650 meters (0.4 miles) away from the landslide site. Fortunately, it was equipped with an external Global Navigation Satellite System (GNSS) receiver previously installed by Ethan Roth, the ship’s science operations manager.

Researchers took advantage of this unique opportunity to analyze data from the ship’s GNSS receiver and open-source software to calculate changes in the vertical position of the R/V Sikuliaq down to the centimeter level. They created a time series showing the ship’s height before, during, and after the landslide. By comparing the data to a landslide-tsunami model, they confirmed that the ship’s vertical movement was consistent with the event, marking the first detection of a landslide-generated tsunami from a ship’s satellite navigation system.

This breakthrough has significant implications for early warning systems. As researcher Adam Manaster noted, “If we process the data fast enough, warnings can be sent out to those in the affected area so they can evacuate and get out of harm’s way.” The study builds upon previous CIRES-led research demonstrating how GPS data from commercial shipping vessels could be used to improve tsunami early warning systems.

To implement this approach on a larger scale, researchers emphasize the need for collaboration with the shipping industry to make onboard data accessible to scientists. As researcher Anne Sheehan noted, “The science shows that this approach works. So many ships now have real-time GPS, but if we want to implement on a larger scale, we need to collaborate with the shipping industry.”

The University of Washington-led team has developed a system called ProxiCycle that logs when a passing car comes too close to a cyclist (within four feet). This small, inexpensive sensor plugs into bicycle handlebars and tracks the passes, sending them to the rider’s phone. The team tested the system for two months with 15 cyclists in Seattle and found a significant correlation between the locations of close passes and other indicators of poor safety, such as collisions.

“The threat of cars is the biggest deterrent to cycling,” said lead author Joseph Breda, a UW doctoral student in the Paul G. Allen School of Computer Science & Engineering. “We want to help novice cyclists navigate safer bike routes through cities.”

The team surveyed 389 people in Seattle and found that respondents of all cycling experience levels ranked the threat of cars as the factor which most discouraged them from cycling. They also said they’d be very likely to use a map that helps navigate for safety.

To create ProxiCycle, the team built a small sensor system that plugs into a bike’s left handlebar. The system consists of a 3D printed plastic casing that houses a pair of sensors and a Bluetooth antenna. The antenna transmits data to the rider’s phone, where the team’s algorithm susses out what’s a passing car rather than a person, or another cyclist, or a tree.

The team validated the system both by testing it in a parking lot, with a car passing at different distances, and with seven cyclists riding through Seattle with GoPro cameras on their handlebars. Researchers watched the footage from these rides and compared this to the sensor output.

In the future, researchers hope to scale the study up and potentially account for other risk factors, such as cyclists being hit by opening car doors, and deploy ProxiCylce in other cities. With enough data, existing bike mapping apps might include safer route suggestions for cyclists.

“One study participant found out that there’s a great bike lane on a quieter street just one block north,” said Breda. “It’s these minor adjustments that can make a big difference in safety.”