The increasing number of electric vehicles on roads has led to concerns about their safety signals. A recent study from Chalmers University of Technology in Sweden has found that one of the most common signal types is difficult for humans to locate, especially when multiple similar vehicles are moving simultaneously.

Researchers conducted a study involving 52 test subjects who were placed at the center of anechoic chambers and surrounded by loudspeakers. Three types of simulated vehicle sounds were played on the loudspeakers, corresponding to signals from one, two or more electric and hybrid vehicles, plus an internal combustion engine. The test subjects had to mark the direction they thought the sound was coming from as quickly as possible.

The results showed that all signal types were harder to locate than the sound of an internal combustion engine. One type of signal, which consisted of two tones, was particularly difficult for the test subjects to distinguish, with many unable to determine whether it was one or multiple vehicles emitting the sound.

This study highlights a hidden flaw in electric vehicle safety and emphasizes the need for further research into how people react in traffic situations involving electric vehicles. The researchers suggest that new signal types may be needed to improve detection and localization, while minimizing negative impacts on non-road users.

The study’s findings have implications for policymakers and car manufacturers, who must balance the need for effective safety signals with the potential consequences of noisy environments.

As the number of electric vehicles on roads continues to grow, it is essential that safety considerations are prioritized. This study serves as a reminder of the importance of continued research into the acoustic properties of electric vehicle safety signals.

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.”