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College of Engineering and Computing

Faculty and Staff

Austin Downey

Title: Assistant Professor
Department: Mechanical Engineering
College of Engineering and Computing
Email: austindowney@sc.edu
Phone: (803) 777-0239
Resources:
downey

Background

Dr. Downey's research focuses on enhancing the safety and serviceability of structures through structural health monitoring and control. Topics include the investigation of algorithms enabling condition assessment, characterization of sensors, and design and development of structural control systems.

Education

  • Ph.D., Engineering Mechanics; and Wind Energy Science, Engineering, and Policy, Iowa State University, 2018.
  • B.S., Civil Engineering, Iowa State University, 2014.

Recent Publication 

  • Austin Downey, Mohammadkazem Sadoughi, Simon Laflamme and Chao Hu. “Fusion of sensor geometry into additive strain fields measured with sensing skin.” Smart Materials and Structures, May 2018. doi:10.1088/1361-665x/aac4cd.
  • Austin Downey, Simon Laflamme, and Douglas Taylor. “Apparatus, Method, and System for High Capacity Band Brake Type Variable Friction Damping of Movement of Structures.” Patent 9,896,836, February 20th, 2018.
  • Austin Downey, Antonella D’Alessandro, Simon Laflamme, and Filippo Ubertini. “Smart bricks for strain sensing and crack detection in masonry structures.” Smart Materials and Structures, vol. 27, no. 1, November 2017. p. 015009. doi:10.1088/1361-665X/aa98c2.
  • Austin Downey, Antonella D’Alessandro, Simon Laflamme, and Filippo Ubertini. “Smart bricks for strain sensing and crack detection in masonry structures.” Smart Materials and Structures, vol. 27, no. 1, November 2017. p. 015009. doi:10.1088/1361-665X/aa98c2.
  • Austin Downey, Antonella D’Alessandro, Simon Laflamme, and Filippo Ubertini. “Smart bricks for strain sensing and crack detection in masonry structures.” Smart Materials and Structures, vol. 27, no. 1, November 2017. p. 015009. doi:10.1088/1361-665X/aa98c2.
  • Austin Downey, Simon Laflamme, and Filippo Ubertini. “Experimental wind tunnel study of a smart sensing skin for condition evaluation of a wind turbine blade.” Smart Materials and Structures, vol. 26, no. 12, October 2017. p. 125005. doi:10.1088/1361-665X/aa9349.

 

 

 


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