Data Collection Protocols for Adhesive Testing Results Using the Materials Selection and Analysis Tool

Report No. ARL-RP-381
Authors: Daniel DeSchepper; David Flanagan; Jonathan Kaufman; Benjamin Henrie; Wendy Kosik Chaney; Robert Jensen
Date/Pages: June 2012; 20 pages
Abstract: The selection and substitution of materials is the keystone of successful engineering. Armor represents a complex and broad spectrum of possible designs that are continually evolving to meet the protection needs imposed by ever emerging threats. Adhesive selection plays a critical role in armor design. Hence, it is vital to capture, consolidate and organize adhesive data in a meaningful way for both engineering design as well as material advancement. A multitude of adhesives have been available from the commercial market over the years. Those intended for aerospace applications tend to have the highest pedigree engineering criteria defined within existing databases. The Army's adhesive needs push the quest for desirable properties well outside of the aerospace regime, which makes a trial and error selection approach both costly and time consuming. Materials informatics and data mining computational tools are now moving towards the practicality needed for drawing accurate correlations between complex high loading rate response and simpler quasi-static properties. Through a DoD-NASA partnership, the Army Research Laboratory has developed an adhesive database using the ARL tailored Materials Selection and Analysis Tool (MSAT) platform. Leveraging MSAT's real-time data management platform, we have refined our experimental data collection methodology to capture maximum detail, data pedigree, and integrity of non-aerospace adhesives on a large scale. As non-aerospace adhesives represent the dominant sector of the commercial market, streamlining the testing and data collection strategy is critical in achieving a reliable database flexible enough to respond to ever-shifting Army driven property requirements. A key, and often underestimated, factor in the data collection is in the transference process from experimental testing results to digital format, which is focus of this current work.
Distribution: Approved for public release
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Last Update / Reviewed: June 1, 2012