Auburn Engineering received national visibility when faculty members Prabhakar Clement and Joel Hayworth in the Department of Civil Engineering were featured in National Geographic daily news to discuss finding traces of the Deepwater Horizon oil spill on the sands of Orange Beach, Ala., as recently as February. The researchers have been investigating the effects of the oil spill on Alabama’s Gulf coast since 2010. “We could have collected as many tar balls as we wanted, from less than one centimeter up to four centimeters — or .4 to 1.6 inches — in diameter,” Clement told National Geographic. “And these are really soft tar balls that are decaying, so there are probably also millions of tiny fragments that we can’t even see. I collected over 1,000 tar balls within [an area of] about 10 miles in five hours. What does that mean? I don’t know. What are the health ramifications? I don’t know. But this clearly demonstrates the magnitude of the [ongoing] problem attributable to Deepwater Horizon.”
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AUBURN ENGINEERING NEWS
- Aerospace engineering students earn top honors at AIAA regional student conference June 5, 2025Auburn Engineering continued its streak of excellence at the 76th annual Southeastern Regional Student Conference of the American Institute of Aeronautics and Astronautics (AIAA), where three students brought home awards.
- NextPAVE Challenge to showcase cutting-edge asphalt innovations at NCAT June 5, 2025NCAT, NAPA, and MnROAD have launched the NextPAVE Challenge, a competition aimed at validating innovative technologies for longer-lasting flexible pavements. By leveraging cutting-edge modeling, laboratory tests, and closely-controlled field experiments in hot and cold climates, the challenge will accelerate the adoption of pavement technologies for better-performing and more efficient highways for generations to come.
- Associate professor in ECE shares thoughts on data significance as conference keynote speaker June 5, 2025At the 2025 WiOpt conference in Linkoping, Sweden, Yin Sun introduced a framework for quantifying data significance using information-theoretic metrics.