United States Department of Transportation
i
Disaster-Resilient and Self-Assessing Multifunctional Transportation Structures [Supporting Dataset]
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2019-08-01
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Abstract:This research designs and characterizes multifunctional materials, in particular inexpensive shape memory alloys, for transportation structures that possess excellent mechanical properties and self-sensing capabilities for strengthening and health monitoring. The properties are the Fe-SMAs are sensitive to part size in that the grain size of the material, which can be grown to several inches, should exceed the smallest dimension of the part. In the current work, maximum part size of the large dimension Fe-SMA rods were determined through detailed microstructural investigations. Samples were subjected to abnormal grain growth heat treatments and found out that part size be increased up to 4.6 mm. Work to correlate computational and experimental work concerning the magnetic sensing of Fe-SMA transformation was conducted using via tensile loading of Fe-SMA wire. A model was developed to simulate a grain by grain transformation of a wire with large (4mm) grains along the wire, modeled as partitioned segments. The total size of the described zip file is 109 KB. Files with the .xlsx extension are Microsoft Excel spreadsheet files. These can be opened in Excel or open-source spreadsheet programs. Docx files are document files created in Microsoft Word. These files can be opened using Microsoft Word or with an open source text viewer such as Apache OpenOffice.
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Content Notes:National Transportation Library (NTL) Curation Note: As this dataset is preserved in a repository outside U.S. DOT control, as allowed by the U.S. DOT's Public Access Plan (https://doi.org/10.21949/1503647) Section 7.4.2 Data, the NTL staff has performed NO additional curation actions on this dataset. The current level of dataset documentation is the responsibility of the dataset creator. NTL staff last accessed this dataset at its repository URL on 2022-11-11. If, in the future, you have trouble accessing this dataset at the host repository, please email NTLDataCurator@dot.gov describing your problem. NTL staff will do its best to assist you at that time.
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