Improving the Implementation of Engineering Design Practices in Secondary Science Classrooms

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Description
Various reports produced by the National Research Council suggest that K-12 curricula expand Science, Technology, Engineering, and Mathematics to better help students develop their ability to reason and employ scientific habits rather than simply building scientific knowledge. Every spring, the

Various reports produced by the National Research Council suggest that K-12 curricula expand Science, Technology, Engineering, and Mathematics to better help students develop their ability to reason and employ scientific habits rather than simply building scientific knowledge. Every spring, the Arizona Department of Education (ADE) in conjunction with Arizona State University holds a professional development workshop titled "Engineering Practices in the Secondary Science Classroom: Engineering Training for Grade 6-12 Math and Science School Teams". This workshop provides math and science teachers with the opportunity to either sustain existing engineering proficiency or be exposed to engineering design practices for the first time. To build teachers' proficiency with employing engineering design practices, they follow a two-day curriculum designed for application in both science and math classrooms as a conjoined effort. As of spring 2015, very little feedback has been received concerning the effectiveness of the ASU-ADE workshops. New feedback methods have been developed for future deployment as past and more informal immediate feedback from teachers and students was used to create preliminary changes in the workshop curriculum. In addition, basic laboratory testing has been performed to further link together engineering problem solving with experiments and computer modelling. In improving feedback and expanding available material, the curriculum was analyzed and improved to more effectively train teachers in engineering practices and implement these practices in their classrooms.
Date Created
2015-05
Agent

Experimental procedures and data analysis of orthotropic composites

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Description
Composite materials are widely used in various structural applications, including within the automotive and aerospace industries. Unidirectional composite layups have replaced other materials such as metals due to composites’ high strength-to-weight ratio and durability. Finite-element (FE) models are actively being

Composite materials are widely used in various structural applications, including within the automotive and aerospace industries. Unidirectional composite layups have replaced other materials such as metals due to composites’ high strength-to-weight ratio and durability. Finite-element (FE) models are actively being developed to model response of composite systems subjected to a variety of loads including impact loads. These FE models rely on an array of measured material properties as input for accuracy. This work focuses on an orthotropic plasticity constitutive model that has three components – deformation, damage and failure. The model relies on the material properties of the composite such as Young’s modulus, Poisson’s ratio, stress-strain curves in the principal and off-axis material directions, etc. This thesis focuses on two areas important to the development of the FE model – tabbing of the test specimens and data processing of the tests used to generate the required stress-strain curves. A comparative study has been performed on three candidate adhesives using double lap-shear testing to determine their effectiveness in composite specimen tabbing. These tests determined the 3M DP460 epoxy performs best in shear. The Loctite Superglue with 80% the ultimate stress of the 3M DP460 epoxy is acceptable when test specimens have to be ready for testing within a few hours. JB KwikWeld is not suitable for tabbing. In addition, the Experimental Data Processing (EDP) program has been improved for use in post-processing raw data from composites test. EDP has improved to allow for complete processing with the implementation of new weighted least squares smoothing options, curve averaging techniques, and new functionality for data manipulation.
Date Created
2016
Agent