Icy runway

June 2019

Q. You’ve been asked to review a new horror movie. In the closing scene, a passenger jet is ready for takeoff at the head of a runway that’s very wide and completely covered in ice. The zombies are slipping and sliding toward the plane, so the pilot has no choice but to open the throttle. Will the plane take off?

Submitted by Jeff Eldredge, professor of mechanical and aerospace engineering at the University of California, Los Angeles.

Draft a response of 250 words or fewer and email it by midnight Eastern time June 6 to aeropuzzler@aiaa.org.

CALL FOR HELP: We challenged you to tell us why the engineer among a group of castaways implored the person with a VHF radio to wait for a forecast temperature inversion before expending the last bit of battery power on a mayday call.

Your responses were reviewed by space systems consultant Chris Hoeber and Dave Jenn of the Naval Postgraduate School in California. Here is the top submission:

WINNING RESPONSE: VHF radio waves are a part of the electromagnetic spectrum. All EM waves bend when they move from a denser to a less dense substance. This is known as refraction. Refraction is responsible for rainbows, mirages, halos and sundogs. When the weather is calm and there is a strong temperature inversion, a layer of high-density cold air is blanketed above by a layer of low-density hot air. This forms an ideal condition for VHF signals to refract and be transmitted over large distances (1,000-3,000 miles). This is called tropospheric ducting, and the engineer hopes to tap into this phenomenon. Under ideal weather, VHF signals do not refract substantially to be transmitted over a longer distance. Stranded on a tropical island, it is less likely that the pilot can signal for help using the VHF radio. Instead, if they wait for tomorrow, the temperature inversion will benefit them. The VHF signal can then travel for a long distance. This will increase their chances of their mayday call being picked up by someone.

Niladri Das
Graduate assistant researcher
Intelligent Systems Research Laboratory
Texas A&M University, College Station
niladridas@tamu.edu