Space shuttle experience is topic for Cornell astronaut-alum Daniel Barry in Oct. 7 talk

 

NASA astronaut Daniel T. Barry, a 1975 engineering graduate of Cornell, will describe his experience aboard space shuttle flight STS-72 in a School of Electrical Engineering colloquium planned for Tuesday, Oct. 7, at 4:30 p.m. in 101 Phillips Hall on the Cornell campus.

A reception and refreshments at 4 p.m. in the Phillips Hall Lounge will precede the colloquium, which is open to the public at no charge. The topic for Barry, whose shuttle flight lasted from Jan. 11-20, 1996, will be "An Electrical Engineer at Mach 25."

Describing the shuttle's re-entry to Earth's atmosphere at 25 times the speed of sound, Barry said, "We were surrounded by a gray fog, then orange fireballs started popping off the tail, shaking the whole orbiter. Eventually, the gray fog turned a bright orange surrounding us and spooky neon St. Elmo's fire ran around inside the window frames, between the multiple panes."

But the highlight of the flight came earlier, on day 5, Barry said, when he successfully completed all the assigned tasks of his space walk -- and had a few minutes for sightseeing. "I was standing on the orbiter's robot arm and my crewmate, Koichi Wakata, flew the robot arm high above the shuttle's payload bay," Barry recalled. "I was about 30 feet over the bay looking down on the shuttle, with my friends waving out the overhead windows and the entire Earth below." The purpose of his space walk was to evaluate assembly techniques for the planned international space station.

After graduating from the Cornell College of Engineering, Barry went on to earn master of engineering and master of arts degrees (1977) and a Ph.D. in electrical engineering and computer science (1980) from Princeton University, as well as an M.D. (1982) from the University of Miami.

Before joining NASA as a mission specialist in 1992, Barry taught in the Department of Physical Medicine and Rehabilitation at the University of Michigan. His research involves biological signal processing, including signal processing theory, algorithms and applications to specific biological systems.

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