Mr. Aaron Misla Profile

Aaron Misla

at New Mexico Institute of Mining and Technology

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Proceedings Article | 28 March 2019 Paper

Autonomous structural composites for self-powered strain sensing-enabled damage detection

Alfred Mongare, Jordan Ulibarri-Sanchez, Aaron Misla, YoungHo Park, Andrei Zagrai, Donghyeon Ryu

Proceedings Volume 10970, 1097015 (2019) https://doi.org/10.1117/12.2514360

KEYWORDS: Composites, Damage detection, Fiber reinforced polymers, Unmanned aerial vehicles, Analytical research, Directed self assembly, Zinc, Molybdenum, System identification, Sensors

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In this study, autonomous composites (AutoCom) are suggested by embedding multifunctional mechano-luminescenceoptoelectronic (MLO) composites into fiber reinforced polymer (FRP) structural composites. The AutoCom is designed for next generation unmanned aerial vehicles to enhance self-sustainability by benefiting from the self-powered strain sensing damage detection capability. The MLO composites generate direct current (DC) in response to mechanical stimuli, and the generated DC varies with magnitude of strain and strain rate. The DC-based strain sensing capability of MLO composites enables AutoCom to measure strain by itself without any external electrical source. The strain sensing data produced from the AutoCom can be potentially used to detect damage using vibration-based damage detection scheme. First, the MLO composites are fabricated by assembling two functional building blocks, such as mechanooptoelectronic (MO) poly(3-hexylthiophene) (P3HT)-based sensing thin films and mechano-luminescent (ML) copperdoped zinc sulfide (ZnS:Cu)-based elastomeric composites. The MLO composites’ self-powered strain sensing capability is validated by subjecting the MLO composites to cyclic tensile strains. Second, AutoCom specimen is fabricated and tested for validating its self-powered strain sensing capability using four-point bending test. Third, mechanical properties of the AutoCom are assessed through theoretical study by comparing to FRP composites without MLO embedment. Last, strain-based system identification methodology is proposed and used for performing system identification of FRP composites.

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