In recent years, there has been a significant increase in the use of Unmanned Aerial Vehicles (UAV). UAVs are expected to fly a large number of long (48 or more hours) missions, and operate without failure. Furthermore, in order to increase the durability of these vehicles and to decrease weight, composite materials are currently experiencing a widespread adoption in applications related both to military and civilian aerospace structures. As a result, in order to decrease costs associated with the operation, maintenance, and, in some cases, loss of these vehicles, it is desirable to have a Dynamically Data-Driven Applications Systems framework that can reliably predict the onset and progressions of structural damage in geometrically and materially complex aerospace composite structures operating in the environments typical of UAVs. In this chapter we present a multiscale DDDAS Interactive Structure Composite Element Relation Network (DISCERN) framework. The proposed multiscale DISCERN framework is successfully deployed on a full-scale laminated composite structure to predict the damage onset, evolution, and the structure remaining fatigue life.
Multiscale DDDAS Framework for Damage Prediction in Aerospace Composite Structures
Handbook of Dynamic Data Driven Applications Systems ; Chapter : 30 ; 693-712
2021-06-12
20 pages
Article/Chapter (Book)
Electronic Resource
English
DDDAS Interactive Structure Composite Element Relation Network (DISCERN) , Continuum Damage Mechanics (CDM) , Isogeometric Analysis (IGA) , Structural health model , Classical Laminated Plate Theory (CLPT) , Non-Uniform Rational B-Splines (NURBS) , Airfoil , Piezoelectric transducers , Self-aware UAV Computer Science , Simulation and Modeling , Computer Applications
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