A Stochastic Approach to Structural Health Monitoring of Advanced Composites A Stochastic Approach to Structural Health Monitoring of Advanced Composites C PROJECT ABSTRACT A robust structural health monitoring framework is proposed integrating physics based high fidelity analysis and probabilistic damage and life assessment methodologies. The goal is to derive a fundamental understanding of the physical phenomena that are unique to multiple damage modes and failure mechanisms in composites with significant material/geometric complexity and under complex loading. A stochastic multiscale analysis will be developed to address propagation of uncertainty across the length scales. The effects of uncertainties related to sensor outputs and measurement noise will be investigated. Methodologies for probabilistic life estimation and risk assessment will be developed. Stochastic signal processing will be used for interpretation of the sensor signals and a Bayesian based technique will be used for estimation of residual useful life. The project is organized into three tasks: (1) stochastic multiscale modeling; (2) probabilistic damage state awareness and prognosis; and (3) validation, testing and application. Methodological developments will be steered by a closed-loop validation plan that incorporates both simulation and experimental test data focused on test articles relevant to Army applications. The research output is expected to make a significant impact on life assessment of a number of U.S. Army applications including armored vehicles, rotary wing aircraft, and missiles. Undergraduate Research Opportunity in Understanding the role of variability in modeling heterogenous material systems The Undergraduate Research Apprenticeship Program (URAP), provided through the Army Research Office (ARO), will provide the opportunity to support talented and motivated undergraduate students to work in the PIs research center (Adaptive Intelligent Materials& Systems Center) while promoting interest in engineering and scientific research. The PI has extensive experience in hiring and mentoring high school and undergraduate students. She has collaborated with Peggy Payne Academy at McClintock High School in Tempe, Arizona to offer internship opportunities to high school students. The PI has also granted a number of internship opportunities to ASU undergraduate students in the Barrett Honors College. The selected student(s) will work directly with graduate students on sponsored research. In particular, the student will be assigned to the ARO funded research titled, A Stochastic Approach to Structural Health Monitoring of Advanced Composites. Mentorship and teaching opportunities will take place in a hands-on and interactive manner to directly demonstrate the connection between what the student learns and its direct application to research. The undergraduate student will assist in the optical and mechanical characterization of advanced composites, statistical characterization of microstructures, and finite element modeling development and simulation.
|Effective start/end date||8/6/12 → 8/5/15|
- DOD-ARMY-ARL: Army Research Office (ARO): $370,254.00
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