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Ground Loads Predictive Analysis

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9302-06-M-0015
Agency Tracking Number: F061-320-3206
Amount: $99,998.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF06-320
Solicitation Number: 2006.1
Timeline
Solicitation Year: 2006
Award Year: 2006
Award Start Date (Proposal Award Date): 2006-05-08
Award End Date (Contract End Date): 2007-02-09
Small Business Information
566 Glenbrook Drive
Palo Alto, CA 94306
United States
DUNS: 172390481
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Thuan Lieu
 Research Scientist
 (650) 283-8401
 cmsoft_inc_thuan@yahoo.com
Business Contact
 Charbel Farhat
Title: President
Phone: (650) 353-0540
Email: cmsoftinc@yahoo.com
Research Institution
N/A
Abstract

The use of a reliable analysis tool for predicting aircraft ground loads during high-speed taxi can expedite ground loads testing during the certification of military aircraft. Therefore, the ultimate objective of this proposal is to develop GLAT, a state-of-the-art simulation tool for ground load analysis capable of: (a) modeling the tire and tire/runway interaction along with the landing gear dynamics during landing, rollout, and taxiing, (b) modeling the aerodynamic ground effects during landing and rollout, and (c) coupling both models to perform ground load analyses. The runway condition, tire characteristics, and their interaction are of great importance to the prediction of ground loads during high-speed rollout/taxi and low-speed taxi. Hence, a significant component of the proposed work focuses on characterizing the runway condition and identifying the modeling details needed for accuracy. The proposed research effort also includes the development of computational methods for transferring the reaction forces from the runway to the aircraft through the tire, and the aerodynamic and gravitational loads from the airframe to the landing gear. Phase I focuses on a feasibility study of the integration process. Phase II will focus on refining the key models, tightening their integration into GLAT, and validating this simulation capability.

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

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