Results for “Pseudoelasticity” — Page 2

NASA NTRS2015

Computational Modeling and Experimental Characterization of Martensitic Transformations in Nicoal for Self-Sensing Materials

Fundamental changes to aero-vehicle management require the utilization of automated health monitoring of vehicle structural components. A novel method is the use of self-sensing materials, which contain embedded sensory particles (SP). SPs are micron-sized pieces of shape-memory alloy that undergo transformation when the local strain reaches a prescribed threshold. The transformation is a result of a spontaneous rearrangement of the atoms in the crystal lattice under intensified stress near damaged locations, generating acoustic waves of a specific spectrum that can be detected by a suitably placed sensor. The sensitivity of the method depends on the strength of the emitted signal and its propagation through the material. To study the transition behavior of the sensory particle inside a metal matrix under load, a simulation approach based on a coupled atomistic-continuum model is used. The simulation results indicate a strong dependence of the particle's pseudoelastic response on its crystallographic orientation with respect to the loading direction and suggest possible ways of optimizing particle sensitivity. The technology of embedded sensory particles will serve as the key element in an autonomous structural health monitoring system that will constantly monitor for damage initiation in service, which will enable quick detection of unforeseen damage initiation in real-time and during onground inspections.

Wallace, T. A.↗

NASA NTRS2016

A Computationally-Efficient, Multi-Mechanism Based Framework for the Comprehensive Modeling of the Evolutionary Behavior of Shape Memory Alloys

The report summarizes the accomplishments made during the 4-year duration of the project. Here, the major emphasis is placed on the different tasks performed by the two research teams; i.e., the modeling activities by the University of Akron (UA) team and the experimental and neutron diffraction studies conducted by the University of Central Florida (UCF) team, during this 4-year period. Further technical details are given in the upcoming sections by UA and UCF for each of the milestones/years (together with the corresponding figures and captions).The project majorly involved the development, validation, and application of a general theoretical model that is capable of capturing the nonlinear hysteretic responses, including pseudoelasticity, shape memory effect, rate-dependency, multi-axiality, asymmetry in tension versus compression response of shape memory alloys. Among the targeted goals for the SMA model was its ability to account for the evolutionary character response (including transient and long term behavior under sustained cycles) for both conventional and high temperature (HT) SMAs, as well as being able to simulate some of the devices which exploit these unique material systems. This required extensive (uniaxial and multi-axial) experiments needed to guide us in calibrating and characterizing the model. Moreover, since the model is formulated on the theoretical notion of internal state variables (ISVs), neutron diffraction experiments were needed to establish the linkage between the micromechanical changes and these ISVs. In addition, the design of the model should allow easy implementation in large scale finite element application to study the behavior of devices making use of these SMA materials under different loading controls. Summary of the activities, progress/achievements made during this period is given below in details for the University of Akron and the University (Section 2.0) of Central Florida (Section 3.0).

Alloys↗

NASA NTRSDate not supplied

Design and Analysis of Shape Memory Spring Tires for Martian and Lunar Rover Vehicles

Shape memory alloys (SMAs) have played an important role in various innovative engineering and medical applications, such as aerospace actuators, vibration damping devices, and coronary stents. In applications, shape memory alloys are commonly utilized in two fundamentally different ways: (i) making use of the superelasticity/ pseudoelasticity (SE/PE) phenomena, as in applications in biomedical engineering, and (ii) taking advantages of the shape memory effect (SME), as is used for actuators. Their ability to act in such vastly different capacities is mainly due to their unique capability to recover large amounts of deformation produced by either applied stresses or temperature changes. One recent emerging application in use of SMAs has been in the area of non-pneumatic tire designs for Martian or Lunar roving vehicles. These vehicles require tires that are capable of traversing rugged terrain while withstanding extreme temperatures and atmospheric conditions. Inspired by the flexible wire mesh tires used on three Lunar Roving Vehicle (LRV) missions to the Moon on Apollo 15, 16, and 17, a new compliant tire technology was developed by the NASA Glenn Research Center (GRC) and Goodyear Tire & Rubber, known as the Spring Tire. The Spring Tire consists of several hundred coiled springs woven into a flexible mesh and formed into the shape of a tire. Like the LRV wire mesh tires, the original Spring Tires were made from spring steel and were prone to permanent deformation when undergoing high localized loads. Later, a new iteration of this technology was invented, known as the ‘Superelastic Tire’. This new technology incorporated the use of superelastic SMA springs, which could effectively undergo approximately 30 times more reversible deformation than the steel spring. It also provided even greater durability and allowed for more flexibility in design, such as the use of other structural forms to reduce mass or increase load carrying capacity. Because of the unique nature of both the SMA material and the complex interactions between the springs, designing Spring Tires for a specific application requires extensive effort. Historically, design decisions have relied on full-scale empirical testing; however, this is very expensive and time consuming, especially when multiple iterations are needed. Therefore, developing a large-scale, robust, and predictive numerical model entailing complex spring interactions and the shape memory material behavior within a tire construct is the first essential step towards a successful design program. The current work focuses on implementation of the user-defined Shape Memory Alloy (SMA) model, otherwise known as SMA-GVIPs, in the Finite Element analysis (FEA) program ABAQUS for large-scale simulations of the GRC-developed Spring Tires made of SMA. The novelty of this work lies in the thorough, detail-oriented, and computationally efficient finite element analysis of full-scale SMA tires. A well-thought material characterization plan followed by model validation and a systemic sensitivity study on SMA tires has never been reported in the previous literature. The main objective of this study is to help the team improve and optimize the structural design of the SMA tires through in-depth numerical analysis and sensitivity studies. Various design variables (wire diameter, coil diameter, pitch, bead angle, and number of springs) were varied to study their influence on the global load-displacement response of the tire construct. A detailed investigation of the three-dimensional stress states was also carried out to enhance our understanding of the local changes as the tire goes through global deformation. It was concluded that a robust numerical model with a good predictive capability, together with a thoughtfully crafted sensitivity study can result in improved design iterations required to reach a desired tire performance while, significantly reducing manufacturing, labor and testing expenses. A summary of the Finite Element (FE) model construction will be presented together with a description of the user-defined SMA model, characterization process, experimental results, model validation, and numerical sensitivity study results.

shape memory alloys↗