Matching Items (3)
Description
The field of Structural Health Monitoring (SHM) has grown significantly over the past few years due to safety and performance enhancing benefits as well as potential life saving capabilities offered by technology. Current advances in SHM systems have lead to a variety of techniques capable of identifying damage. However, few strategies exist for using this information to quickly react to environmental or material conditions needed to repair or protect the system. Rather, current systems simply relay this information to a central processor or human operator who then decides on a course of action, such as altering the mission or scheduling a repair operation. Biological systems exhibit many advanced sensory and healing traits that can be applied to the design of material systems. For instance, bones are the major structural component in vertebrates; however, unlike modern structural materials, bones have many properties that make it effective for arresting the development and propagation of cracks and subsequent healing of the damaged region. Mimicking biological materials, an autonomous material system was developed that uses Shape Memory Polymers (SMPs) with an embedded fiber optic network. This thesis researches a novel system that uses SMPs and employs an optical fiber network as both a damage detection sensor and a network to deliver stimulus to the damage site, initiating active toughening and healing algorithms. In the presence of damage, the fiber optic fractures, which allowed a high power laser diode to deposit a controlled level of thermal energy at the damage site, locally reducing the modulus and blunting the crack tip. The shape memory polymer not only provided a sharp glass transition, but also allowed for the application of an programmed global pre-strain, which under thermal loads induced the shape memory effect to close the crack and adequately heal the polymer to its designed operational conditions recovering full strength. It will be shown that the material can be significantly toughened and that control algorithms combined with the shape memory properties can further increase the toughening and healing effect. The entire system will be able to effectively sense damage, defend its propagation by actively toughening, and subsequently heal the structure, autonomously in a real time operational environment.
ContributorsGarcia, Michael (Author) / Sodano, Henry A (Thesis advisor) / Jiang, Hanqing (Committee member) / Lin, Yirong (Committee member) / Arizona State University (Publisher)
Created2010
Description
Shape Memory Polymers (SMPs) are smart polyurethane thermoplastics that can recover their original shape after undergoing deformation. This shape recovery can be actuated by raising the SMP above its glass transition temperature, Tg. This report outlines a process for repeatedly recycling SMPs using 3D printing. Cubes are printed, broken down into pellets mechanically, and re-extruded into filament. This simulates a recycling iteration that the material would undergo in industry. The samples are recycled 0, 1, 3, and 5 times, then printed into rectangular and dog-bone shapes. These shapes are used to perform dynamic mechanical analysis (DMA) and 3-point bending for shape recovery testing. Samples will also be used for scanning electron microscopy (SEM) to characterize their microstructure.
ContributorsSweeney, Andrew Joseph (Author) / Yekani Fard, Masoud (Thesis director) / Chattopadhyay, Aditi (Committee member) / W.P. Carey School of Business (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Experimental Characterization of Multifunctional Shape Memory Polymers With Carbon-Based Nanofillers
Description
This paper focuses on the fabrication and characterization of shape memory polymer (SMP) with interspersed carbon-based nanofillers which showed significant improvements in quasi-static and dynamic mechanical properties. These composite shape memory polymers have been fabricated using a specialized acetone solvent mixing technique to achieve high dispersion. The effect of individual and hybrid additions of graphene oxide (GO) and carbon nanotubes (CNT) with a total nanofiller content of 2 wt.% was investigated. These high dispersion SMPs showed significant improvements in tensile moduli (up to 25% over baseline), tensile strength (up to 15% over baseline), and strain to failure (up to 75% over baseline), owing to crack propagation hindrance induced by the carbon nanofillers. Further, dynamic mechanical analysis (DMA) showed a minimal reduction in polymer chain mobility and improvements in storage modulus. Dispersion is characterized by micrograph acquisition and subsequent binary image processing.
ContributorsRoman, Jose (Author, Co-author) / Chattopadhyay, Aditi (Thesis director) / Venkatesan, Karthik (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-05