Date of Award
Fall 2022
Access Type
Thesis - Open Access
Degree Name
Master of Science in Aerospace Engineering
Department
Aerospace Engineering
Committee Chair
Daewon Kim
Committee Co-Chair
Foram Madiyar
First Committee Member
Sirish Namilae
Abstract
NASA maintains the ability to track a large majority of objects in Earth’s orbit, however lack the ability to track objects smaller than five centimeters in diameter. These untrackable objects represent a significant danger to inflatable structures. This work seeks to synthesize and fabricate a self-healable, passive, dielectric elastomer impact sensor for structural health monitoring on inflatable space structures subject to impact by micrometeoroids and orbital debris. In a setting in which impact repairs can be extremely costly, the implementation of such a technology would not only alert personnel of such an event but would also serve to decrease the cost and time of repairs. This investigation synthesizes an intrinsically self-healing poly(dimethylsiloxane) via a supra-molecular network of multi-strength hydrogen bonds. The modified poly(dimethylsiloxane) network must be effective in harsh environments, particularly extremely low temperatures, as well as retain the dielectric properties of poly(dimethylsiloxane). Self-healing efficiency, stretchability and flexibility are also desirable properties to attain. Integration of the manufactured sensor arrays around a layer of woven ceramic fiber with conductive fabric electrodes, hypervelocity impact testing, and self-healing efficiency tests are performed and confirm the sensors capabilities. The performed tests demonstrate a measurable change in capacitance associated with impact damage and location. Success is represented by passive operation and the penetrated sensors’ ability to self-repair without compromising the sensors impact detection capabilities.
Scholarly Commons Citation
Smith, Nicholas, "Passive, Self-Healable, Dielectric Elastomers for Structural Health Monitoring" (2022). Doctoral Dissertations and Master's Theses. 709.
https://commons.erau.edu/edt/709