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Low Cost Fabrication of Carbon-Carbon (C-C) Aeroshells for Hypersonic Weapon Systems

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-07-M-5057
Agency Tracking Number: F071-136-2573
Amount: $99,969.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF071-136
Solicitation Number: 2007.1
Timeline
Solicitation Year: 2007
Award Year: 2007
Award Start Date (Proposal Award Date): 2007-04-30
Award End Date (Contract End Date): 2008-05-30
Small Business Information
450 Lindbergh Avenue
Livermore, CA 94551
United States
DUNS: 008645624
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Scott Brown
 Vice President, R & D
 (916) 955-6646
 sbrown@ocellusinc.com
Business Contact
 Michael Droege
Title: President
Phone: (925) 606-6540
Email: mdroege@ocellusinc.com
Research Institution
N/A
Abstract

In future conflicts, it is projected that there will be a need for new weapon types that can strike targets around the globe within minutes. The development of hypersonic vehicles is one response to this need. Future requirements for hypersonic vehicles demand advanced thermal and structural materials. Significant effort has been invested in developing an array of composite materials for use in aircraft, spacecraft, and hypersonic vehicles. For high temperature applications like hypersonic vehicles, carbon-carbon is a composite material of choice. Although, the origins of carbon-carbon composites can be traced back to the 1960’s, many critical problem areas still exist which have limited their application. Many of these problems can be traced to manufacturing process-induced defects and failures. Despite clear advantage in physical properties, a robust, low-cost manufacturing approach will be required to enable the use of carbon-carbon composite structures in hypersonic vehicles. To meet this need for reliable, efficient, and cost-effective carbon-carbon manufacturing, we propose the development of a carbon-carbon manufacturing method that relies on the integration of a process environment model that can be used to both predict optimum processing parameters as well as provide real-time control of the process operation.

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

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