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Filtering by: Academic Affiliation Wood Science and Engineering Subject Loblolly pine

Data from: Methodology for comparing wood adhesive bond load transfer using digital volume correlation

Creator:

Ching, Daniel J., McKinley, Paige E., Kamke, Fred A., Zauner, Michaela, and Xiao, Xianghui

Abstract:

There is a lack of fundamental knowledge about the role which adhesive flow and infiltration plays in the micro-mechanical performance of wood adhesive bonds. This data set, for the first time, provides a way to study directly the relationship between adhesive flow and the micro-mechanics of wood adhesive bonds. Specimens...

Resource Type:

Dataset

Date Created: