ASMADA—A tool for automatic analysis of shape memory alloy thermal cycling data under constant stress Academic Article uri icon

abstract

  • Abstract The authors present the automatic shape memory alloy data analyzer (ASMADA). ASMADA is capable of rapid, robust, and consistent processing of shape memory alloy thermal cycling data acquired under constant stress. This seeks to address two primary issues: the lack of unified analysis procedures in relevant standards and the near-universal manual analysis of such data. ASMADA is compliant with the definitions provided in ASTM standards and calculates up to twenty-three (23) material properties/parameters at speeds ranging from 5 to 35 cycles s−1. These parameters include the four transformation start/finish temperature thresholds, which are calculated using the tangent line method; the transformation region tangent lines are determined using a modified sigmoid function, whereas the single-phase region tangent lines are determined based on the geometry of the cycle data. Additionally, a graphical user interface is provided to make the tool readily accessible and easy to navigate. The capabilities of ASMADA have been tested on experimental data from four different research groups; results from five of these tests are presented to demonstrate the tool’s robustness. This tool was developed in Python and is publicly available at https://github.com/matthewkuner/ASMADA

published proceedings

  • Smart Materials and Structures

author list (cited authors)

  • Kuner, M. C., Karakalas, A. A., & Lagoudas, D. C

citation count

  • 0

complete list of authors

  • Kuner, Matthew C||Karakalas, Anargyros A||Lagoudas, Dimitris C

publication date

  • December 2021