Oct.18, 2018
The U.S. Department of Transportation awarded a $300,000 grant to Associate Professor Salvatore Salamone in the Department of Civil, Architectural and Environmental Engineering for his pipeline safety research.
The Pipeline and Hazardous Materials Safety Administration (PHMSA) awarded the grant for Salamone’s research on pipeline corrosion, which could help prevent environmental disasters such as oil spills. Overall, PHMSA awarded a total of $3.8 million to 11 universities as part of its Competitive Academic Agreement Program (CAAP) for pipeline safety research and innovation.
Established in 2013, the CAAP, through cooperative agreement awards, has invested in research, and is responsible for introducing science and engineering students to pipeline design, mitigation, and corrosion issues.
Salamone is a leading researcher in detecting and estimating pipeline corrosion using high-frequency waves. He said the success of the research could reduce the large cost of pipeline maintenance as well as detect corrosion, one of the leading causes of pipeline failure.
Salamone and his Smart Structures Research Group at UT Austin are designing and implementing an innovative monitoring system for corrosion-damage assessment of pipelines.
The grant also covers graduate student funding in the UT Austin study. Postdoctoral researcher Arvin Ebrahimkhanlou said this funding has a direct impact on the students participating in the research.
“The award sponsors important research and also has a positive educational component,” Ebraimkhanlou said. “The people who are working on the project are able to continue their education and become experts in this area so that in the future they can be hired by the industries who are going to use and implement these types of technologies.”
“Through the PHMSA award, our team will be able to perform in-depth studies and experiments to develop a state-of-the-art structural health monitoring system for pipeline corrosion inspection,” said Stylianos Livadiotis, research assistant and civil engineering graduate student. “This system will have the key characteristics of being economic, automated and capable to diagnose the early stages of corrosion damage.”
