Smart EMI monitoring of thin composite structures

This paper presents a structural health monitoring (SHM) method for in-situ damage detection and localization in carbon fibre reinforced plates (CFRP). The detection is achieved using the electromechanical impedance (EMI) technique employing piezoelectric transducers as high-frequency modal sensors. Numerical simulations based on the finite element method are carried out so as to simulate more than a hundred damage scenarios. Damage metrics are then used to quantify and detect changes between the electromechanical impedance spectrum of a pristine and damaged structure. The localization process relies on artificial neural networks (ANN) whose inputs are derived from a principal component analysis of the damage metrics. It is shown that the resulting ANN can be used as a tool to predict the in-plane position of a single damage in a laminated composite plate

Smart FRP Composite Sandwich Bridge Decks in Cold Regions

INE/AUTC 12.0

Bio-Inspired Aggregation Control of Carbon Nanotubes for Ultra-Strong Composites

High performance nanocomposites require well dispersion and high alignment of the nanometer-sized components, at a high mass or volume fraction as well. However, the road towards such composite structure is severely hindered due to the easy aggregation of these nanometer-sized components. Here we demonstrate a big step to approach the ideal composite structure for carbon nanotube (CNT) where all the CNTs were highly packed, aligned, and unaggregated, with the impregnated polymers acting as interfacial adhesions and mortars to build up the composite structure. The strategy was based on a bio-inspired aggregation control to limit the CNT aggregation to be sub 20--50 nm, a dimension determined by the CNT growth. After being stretched with full structural relaxation in a multi-step way, the CNT/polymer (bismaleimide) composite yielded super-high tensile strengths up to 6.27--6.94 GPa, more than 100% higher than those of carbon fiber/epoxy composites, and toughnesses up to 117--192 MPa. We anticipate that the present study can be generalized for developing multifunctional and smart nanocomposites where all the surfaces of nanometer-sized components can take part in shear transfer of mechanical, thermal, and electrical signals

Active control of strain in a composite plate using shape memory alloy actuators

The present study aims to design an experimental test bench to analyze and control a smart structure system composed of a woven fiberglass laminate plate with shape memory alloy (SMA) actuators instilled on the surface. The aim of this design is to accurately augment the strain of the composite plate. Finite element analysis was employed to model the composite structure and determine the placement of the SMA actuators in order to produce the desired structural response efficiently with minimum power consumption. Due to the nonlinear behavior of the SMA actuator, it will be critical to incorporate a feedback control system that is able to accurately morph the structure by changing the strain of the composite structure. A Proportional–Integral–Derivative (PID) controller was designed to improve its tracking performance. Simulation on the control system showed that the PID controller produced acceptable response and managed to reduce steady state error for different types of input. The PID controller was then implemented in the experimental setup to control the smart composite plate. Results from the experiment illustrates that the smart structure system that has been designed per-formed effectively and the strain value of the composite structure can be controlled accurately

Architectural implications for context adaptive smart spaces

Buildings and spaces are complex entities containing complex social structures and interactions. A smart space is a composite of the users that inhabit it, the IT infrastructure that supports it, and the sensors and appliances that service it. Rather than separating the IT from the buildings and from the appliances that inhabit them and treating them as separate systems, pervasive computing combines them and allows them to interact. We outline a reactive context architecture that supports this vision of integrated smart spaces and explore some implications for building large-scale pervasive systems

Performance prediction of wind turbines utilizing passive smart blades: approaches and evaluation

The induced deformation, because of the presence of elastic coupling in the structure of passive smart blades, is the key parameter that affects the wind turbine aerodynamic performance, namely rotor mechanical power and blade loading. Therefore, in order to determine the aerodynamic performance of these turbines, a structural analyser is also required to bring the effect of the induced deformation into account. When predicting the rotor mechanical power, additional complexity arises when the blades are bend-twist-coupled. In this case, an iterative coupled-aero-structure analysis must be carried out at each given wind speed. Further difficulties in simulation of these turbines are posed by the fact that the current analytical models for analysis of structures made of anisotropic composite materials are not accurate enough. This differentiates the numerical simulation of wind turbines utilizing passive smart blades from the simulation of wind turbines with conventional blades. Different strategies have been proposed and followed by investigators in simulation of wind turbines utilizing passive smart blades. These methods can be categorized by the approach adopted in treating the torsional-induced deformation. In these studies, the induced twist has been predicted, planned or a combination of both. The present paper describes, evaluates and compares these approaches