Jun 9, 2016 | By Tess
When we think of storms, such as Hurricane Sandy in 2012 or Hurricane Katrina in 2005, we immediately think of the impact they have made, the destruction they have left behind. The traces of the storm can be plainly seen through destroyed homes, flooded streets, and terrified people. There are, however, also traces that we don’t see, which could actually help scientists to better understand and thus better predict how storms of that magnitude happen. The traces I am referring to are called ripple bedforms, and now, thanks to an advanced algorithm and 3D printing technologies, scientists are able to read and understand them better than ever before.
Ripple bedforms are essentially small swells that are formed on the seafloor caused by waves and currents. The subtle formations have even been likened to fingerprints, in that they are unique rippled traces left by the storms that occur. For instance, ripples are said to be more spread apart if the distance of waves is larger. Currently, a team of researchers from the University of Delaware is studying these ripple bedforms at Redbird Reef, a manmade reef made up of old subway cars, tires, and sunken tugboats, located only 16 miles from the coast of the Indian River Inlet in Delaware.
A study based off the research, authored by oceanography PhD student Carter DuVal, Art Trembanis, and Adam Skarke, was recently published in the journal of Continental Shelf Research. The paper details how the researchers have employed a novel fingerprint algorithm to understand and better predict what types and what scale of bedforms could be made by a superstorm like Hurricane Sandy. As Trembanis explains, “At practical levels, if we are going to appropriately predict and model how storms are going to behave, we need to be able to determine ripple parameters, such as wavelength and orientation to the shoreline, with accuracy. Until we began using a fingerprint algorithm, we didn’t have strong enough tools to do this.”
The fingerprint algorithm, which is actually based off of fingerprint reading technologies, is capable of a number of things. First, it has the ability to focus directly on parts of the seabed that are textured and rippled, while filtering out areas that are featureless. Importantly, it can also process the nature of the ripples and their appearance (whether they are straight, curved, etc.), which could greatly help in determining how the ripple bedforms change over time.
The scientists have also been able to recreate 3D printed models of the seabeds they are analyzing, which gives them a tactile perspective on the terrain they are researching. The 3D models were created based on bathymetric sonar images and other data taken after the storm. DuVal explains of the 3D model, “It gives you a perspective that you cannot get by looking at a two- or three-dimensional map on a screen. Not only can we look at the surface, but also the texture.” The fingerprint algorithm has helped them to analyze the distinct ripple formations.
With 3D printing and the advanced algorithm, the researchers are hoping that they will be able to link certain ripple patterns to their respective storms, which could in the long run help them to predict the outcome of future storms, such as how much beachfront erosion they might cause, or how strong of a storm surge there might be. Additionally, by conducting their research in the same area of the continental shelf, the scientists will seek to gain a better understanding of how the area evolves over time.
Considering the number of superstorms the east coast of the United States has seen in the past decade, the research development comes at a crucial time, especially with the U.S. Environmental Protection Agency expecting an increase in the frequency, strength, and length of these extreme weather events.
Posted in 3D Printing Application
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