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Novel Multi-scale/Multi-physics Integrated Tool for the Prediction of Manufacturing-Induced Defects in Autoclave Composite Airframe Parts

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-17-C-0110
Agency Tracking Number: N15A-003-0115
Amount: $249,979.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: N15A-T003
Solicitation Number: 15.A
Timeline
Solicitation Year: 2015
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-02-07
Award End Date (Contract End Date): 2021-02-22
Small Business Information
3190 Fairview Park Drive Suite 650
Falls Church, VA 22042
United States
DUNS: 010983174
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Nicole Apetre Nicole Apetre
 Senior Engineer
 (703) 226-4076
 napetre@tda-i.com
Business Contact
 Patty Walk
Phone: (703) 226-4064
Email: pwalk@tda-i.com
Research Institution
 Wichita State University
 Monica Calhoun Monica Calhoun
 
National Institute for Aviation Research 1845 Fairmount, Box 93
Wichita, KS 67260
United States

 (316) 978-6899
 Nonprofit College or University
Abstract

Composite materials have emerged as the materials of choice for increasing the performance and reducing the weight and cost of military aircraft. Nevertheless, manufacture of composite parts still poses numerous difficulties which can result in premature curing, degradation in thin cross-sections, incomplete curing in thick counterparts or build-up of internal stresses. Experimental investigations of the cure and rheology of the composites can be effective for understanding how a manufacturing process can result in the highest quality components. This empirical approach can be very complex to set-up and time consuming to execute. Numerical modeling and simulations are much more cost effective alternatives to in-situ empirical trials for such processes. In this STTR effort, TDA team and its university partner, Wichita State University (Dr. Waruna Seneviratne) will be focusing on building a virtual autoclave which will (a) ease the burden of experiments, (b) provide the evolution of volumetric changes, residual stresses and process-induced distortions and (c) include optimization features. The required analytical solutions are developed in the framework of finite element model by suitable fluid-structure interaction modeling, micromechanical computations and stochastic methodologies. Lessons learned in the laboratory will be used to model manufacturing defects in a virtual environment.

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

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