Predicting Requirements for instructional Environment Design to Improve Critical Training (PREDICT)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-12-G-05460002
Agency Tracking Number: N071-099-0687a
Amount: $298,166.00
Phase: Phase II
Program: SBIR
Awards Year: 2012
Solicitation Year: 2007
Solicitation Topic Code: N07-099
Solicitation Number: 2007.1
Small Business Information
12 Gill Street, Suite 1400, Woburn, MA, -
DUNS: 967259946
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Emily Wiese
 Associate Director, Human
 (781) 496-2449
Business Contact
 Thomas McKenna
Title: Chief Financial Officer
Phone: (781) 395-3966
Research Institution
Phase II.5 proposal, extension of Phase II contract N00014-09-C-0079: Aircraft carrier landings are one of the most difficult and safety critical tasks Naval Aviators must master in the course of their training. In light of continuing training resource and budgetary constraints, there has been interest on the part of the USN to investigate the potential for increased flight simulator utilization for aircraft carrier landing training. In particular, there is initial interest in augmenting F-18 Fleet Replacement Squadron (FRS) carrier qualification (CQ) training which accounts for the largest CQ training requirement. Current F-18 flight simulators do not support CQ training due to a lack of fidelity, particularly with regard to visual display capabilities and aircraft motion representation. In order to advance flight simulator capabilities such that they may support future CQ training, it will be necessary to investigate current simulator fidelity shortfalls and determine the necessary upgrades. In support of that objective the current effort proposes to: (1) develop objective measures of pilot performance during aircraft carrier landings; (2) design experiments to assess the impact of varying levels of simulator fidelity on pilot performance during aircraft carrier landings; and (3) to collect objective data to identify the appropriate level of simulator fidelity required for CQ training.

* Information listed above is at the time of submission. *

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