Composite materials are ideal for many weight-conscious applications such as aerospace and automotive structures because of their exceptionally high specific properties. However, composite materials are susceptible to complex damage and difficult-to-predict damage growth. This necessitates the application of structural health monitoring (SHM) for in-operation monitoring of damage formation and accumulation. Self-sensing materials are strong candidates for composite SHM because they do not suffer from limitations associated with traditional, point-based sensors. A common approach to self-sensing is the piezoresistive effect in nanofiller-modified materials. To date, work in the area of self-sensing via the piezoresistive effect has focused overwhelmingly on the direct current (DC) response of these materials. This is an important limitation because alternating current (AC) effects inherently provide more information by relating both impedance and phase to damage. Therefore, this work explores the effect of high-cycle fatigue loading on the AC response of carbon nanofiber (CNF)-modified glass fiber/epoxy laminates. Specifically, impedance magnitude and phase angle are both measured through the thickness and along the length of a tension-tension fatigue-loaded specimen with an open-hole stress concentration as a function of load cycle and up to 10 MHz. The collected impedance data is then fit to an equivalent circuit model and correlated to stiffness changes. This means that changes in equivalent circuit behavior can be used to track fatigue-induced softening in self-sensing composites. In light of these promising preliminary results, AC effects appear to have considerable potential for real-time tracking of damage accumulation.

The excellent piezoelectric properties of Polyvinyl Fluoride (PVDF), its low cost, ease of workability and high chemical resistance, make it very useful to develop sensing devices for structural health monitoring applications (SHM). However, challenges occur when the devices need to be embedded into a hosting material or structure which could instead be damaged. In this study, the PVDF device is transformed into an ultralight and porous piezoelectric mat formed by ultra-long and randomly distributed micro fibers. The piezoelectric mat is embedded into a glass fiber (GF) composite by intercalating it with the GF layers during the lay-up process. This approach allows the realization of an intelligent composite that is capable to self-monitor its strain or vibrations during inservice life.

Helicopters suffer from a number of problems raised from the high vibratory loads, noise generation, load capacity limitations, forward speed limitation etc. Especially unsteady aerodynamic conditions due to the different aerodynamic environment between advised and retreating side of the rotor cause most of these problems. Researchers study on passive and active methods to eliminate negative effects of aerodynamic loads. Nowadays, active methods such as Higher Harmonic Control (HHC), Individual Blade Control (IBC), Active Control of Structural Response (ACSR), Active Twist Blade (ATB), and Active Trailing-edge Flap (ATF) gain importance to vibration and noise reduction. In this paper, strain-induced blade twist control is studied integrated by Macro Fiber Composite (MFC) actuator. 3D model is presented to analyze the twisting of a morph and bimorph helicopter rotor blade comprising MFC actuator which is generally applied vibration suppression, shape control and health monitoring. The helicopter rotor blade is modeling with NACA23012 airfoil type and consists of D-spar made of unidirectional fiberglass, ±45° Glass Fiber Reinforced Polymer (GFRP) and foam core. Two-way fluid-structure interaction (FSI) method is used to simulate loop between fluid flow and physical structure to enable the behavior of the complex system. To develop piezoelectric effects, thermal strain analogy based on the similarities between thermal and piezo strains. The optimization results are obtained to show the influence of different design parameters such as web length, spar circular fitting, MFC chord length on active twist control. Also, skin thickness, spar thickness, web thickness are used to optimization parameters to illustrate effects on torsion angle by applying response surface methodology. Selection of correct design parameters can then be determined based on this system results.

The adaptation of a wing contour is important for most aircraft, because of the different flight states. That’s why an enormous number of mechanisms exists and reaches from conventional slats and flaps to morphing mechanisms, which are integrated in the wing. Especially integrated mechanisms reduce the number of gaps at the wing skin and produce less turbulent flow. However these concepts are located at a certain section of the wing. This leads to morphing and fixed wing sections, which are located next to each other. Commonly, the transition between these sections is not designed or a wing fence is used. If the transition is not designed, the wing has a step with an activated morphing mechanism and that produces additional vortices. A new skin design will be presented in order to smooth the contour between a fixed wing and a morphing wing. Here the transition between a droop nose and a fixed wing is considered. The skin material is a mix of ethylene propylene diene monomer rubber and glass-fiber reinforced plastic. The rubber is the baseline material, while the glass-fiber is added as stripes in chord-wise direction. In span-wise direction the glass fiber is connected with the rubber. The rubber carries the loads in span-wise direction and reduces the required actuation force. The glass fiber stiffens the skin locally in chord wise direction and keeps the basic contour of the skin. Some geometrical parameters within the skin layup can be varied to change the transition along the span or to reduce the maximum strain within the skin. The local strain maximum is a result of the material transition with different modules. One design of a leading edge was manufactured with an existing mold and it has a span of 200 mm. There are two essential aspects from a structural point of view. One is a nearly continuous deformation along the span and the second is the maximum strain in the rubber. Both aspects are investigated in an experiment and the results are compared with a simulation model. The results show a reliable concept and its numerical model, which will be assigned to a full scale demonstrator. This demonstrator will have a span of 1000 mm and will show the smooth skin transition between a droop nose and a fixed wing.

The main goal of this study is the optimization of vibration reduction on helicopter blade by using macro fiber composite (MFC) actuator under pressure loading. Due to unsteady aerodynamic conditions, vibration occurs mainly on the rotor blade during forward flight and hover. High level of vibration effects fatigue life of components, flight envelope, pleasant for passengers and crew. In this study, the vibration reduction phenomenon on helicopter blade is investigated. 3D helicopter blade model is used to perform the aeroelastic behavior of a helicopter blade. Blade design is created by Spaceclaim and finite element analysis is conducted by ANSYS 19.0. Generated model are solved via Fluent by using two-way fluid-solid coupling analysis, then the analyzed results (all aerodynamic loads) are directly transferred to the structural model. Mechanical results (displacement etc.) are also handed over to the Fluent analysis by helping fluid-structure interaction interface. Modal and harmonic analysis are performed after FSI analysis. Shark 120 unmanned helicopter blade model is used with NACA 23012 airfoil. The baseline of the blade structure consists of D spar made of unidirectional Glass Fiber Reinforced Polymer +45°/−45° GFRP skin. MFC, which was developed by NASA’s Langley Research Center for the shaping of aerospace structures, is applied on both upper and lower surfaces of the blade to reduce the amplitude in the twist mode resonant frequency. D33 effect is important for elongation and to observe twist motion. To foresee the behavior of the MFC, thermo-elasticity analogy approach is applied to the model. Therefore, piezoelectric voltage actuation is applied as a temperature change on ANSYS. The thermal analogy is validated by using static behavior of cantilever beam with distributed induced strain actuators. Results for cantilever beam are compared to experimental results and ADINA code results existing in the literature. The effects of fiber orientation of MFC actuator and applied voltage on vibration reduction on helicopter blade are represented. The study shows that torsion mode determines the optimum placement of actuators. Fiber orientation of the MFC has few and limited influences on results. Additionally, the voltage applied on MFC has strong effects on the results and they must be selected according to applied model.

Glass Fiber Reinforced Polymer (GFRP) beams have shown over a 20% decrease in weight compared to more traditional materials without affecting system performance or fatigue life. These beams are being studied for use in automobile leaf-spring suspension systems to reduce the overall weight of the car therefore increasing fuel efficiency. These systems are subject to large amplitude mechanical vibrations at relatively constant frequencies, making them an ideal location for potential energy scavenging applications. This study analyses the effect on performance of GFRP beams by substituting various composite layers with piezoelectric fiber layers and the results on deflection and stiffness. Maximum deflection and stress in the beam is calculated for varying the piezoelectric fiber layer within the beam. Initial simulations of a simply supported multimorph beam were run in ABAQUS/CAE. The beam was designed with symmetric piezoelectric layers sandwiching a layer of S2-glass fiber reinforced polymer and modeled after traditional mono leaf-spring suspension designs with total dimensions 1480 × 72 × 37 mm 3 , with 27 mm camber. Both piezoelectric and GFRP layers had the same dimensions and initially were assumed to have non-directional bulk behavior. The loading of the beam was chosen to resemble loading of a leaf spring, corresponding to the stresses required to cycle the leaf at a stress ratio between R = 0.2 and 0.4, common values in heavy-duty suspension fatigue analysis. The maximum stresses accounted for are based on the monotonic load required to set the bottom leaf surface under tension. These results were then used in a fiber orientation optimization algorithm in Matlab. Analysis was conducted on a general stacking sequence [0°/45°] s , and stress distributions for cross ply [0°/90°] s , and angle ply [+45°/−45°] s were examined. Fiber orientation was optimized for both the glass fiber reinforced polymer layer to maximize stiffness, and the piezoelectric fiber layers to simultaneously minimize the effect on stiffness while minimizing deflection. Likewise, these fibers could be activated through the application of electric field to increase or decrease the stiffness of the beam. The optimal fiber orientation was then imported back into the ABAQUS/CAE model for a refined simulation taking into account the effects of fiber orientation on each layer.

The hair cell is a biological sensor that uses microscopic hair-like structures to detect delicate motions of surrounding fluid. Inspired by this principle, we have created an artificial hair cell (AHC) sensory method based on biomolecular transduction for sensing spatial variations in air flow. The key feature of this method is the use of one-dimensional arrays built from modular AHC units which measure local velocity at different points in a flow profile. Each of the AHC units uses thinly extruded glass fibers as mechanical receptors of air velocity. Hair vibrations are converted to current via hydrogel-supported lipid bilayer membranes through their mechanocapacitive properties. Preliminary tests with linear arrays of three AHC units attempt to measure the air source profile with varying position and intensity. Each unit was fabricated with a hair of different length, giving it a unique vibrational response. This technique was inspired by how organisms use hair cells with tuned responses to mechanically process flow stimuli. A significant challenge in processing the sensors’ output was the limitation of one input channel on the current measurement unit, thus each sensor output had to be sent over the same channel. When several AHC units are excited simultaneously by an airflow, the resulting signal is a superposition of each sensor’s individual response. To separate the signals back into their individual measurements, the Hair Frequency Response Decomposition method is developed, which maps the spectral content of a combined output to the location of excitation in the array. This method takes advantage of the AHC’s high signal-to-noise ratio (compared to other membrane-based AHCs) and linear output response to flow velocity. Results show that the bilayers’ consistent spectral responses allow for an accurate localization of sensor excitation within the array. However, temporal variations in bilayer size affect sensitivity properties and make accurate flow velocity estimation difficult. Nevertheless, under stable bilayer conditions the measured velocity profiles matched closely with theoretical predictions. The implementation of the array sensing method demonstrates the sensory capability of bilayer-based AHC arrays, but highlights the difficulties of achieving consistent performance with bio-molecular materials.

Utilizing conductivity changes to locate matrix damage in glass fiber reinforced polymers (GFRPs) manufactured with nanocomposite matrices is a promising avenue of composite structural health monitoring (SHM) with the potential to ensure unprecedented levels of safety. Nanocomposites depend on the formation of well-connected nanofiller networks for electrical conductivity. Therefore, matrix damage that severs the connection between nanofillers will manifest as a local change in conductivity. This research advances state of the art conductivity-based SHM by employing electrical impedance tomography (EIT) to locate damage-induced conductivity changes in a glass fiber/epoxy laminate manufactured with carbon black (CB) filler. EIT for damage detection is characterized by identifying the lower threshold of through-hole detection and demonstrating the capability of EIT to accurately resolve multiple through holes. It is found that through holes as small as 3.18 mm in diameter can be detected, and EIT can detect multiple through holes. However, sensitivity to new through holes is diminished in the presence of existing through holes unless a damaged baseline is used. These research findings demonstrate the considerable potential of conductivity-based health monitoring for GFRP laminates with conductive networks of nanoparticles in the matrix.

Performance demands of future unmanned air vehicles will require rapid autonomous responses to changes in environment. Towards this goal, we expect that the next generation flight control systems will include advanced sensors beyond the contemporary array. One promising scenario correlates measurements of flow footprints over aircraft surfaces with aerodynamic data to aid navigation and feedback control algorithms. As a sensor for this concept, we construct artificial hair sensors (AHSs) based on glass microfibers enveloped in an annular, radially-aligned piezoresistive carbon nanotube (CNT) forest to measure air flow in boundary layers. This study includes an analysis of the sensitivity based on laboratory scale electromechanical testing. The sensors in this work utilize nine micron diameter S2 glass fibers as the sensing mechanism for coupling to boundary layer air flows. The annular CNT forest resides in a fused silica microcapillary with electrodes at the entrance. The sensor electrical transduction mechanism relies on the resistance change of the CNT forest due to changes in both the bulk and contact resistance as a function of mechanical loading on the fiber. For the electromechanical analysis, the sensors are controllably loaded to measure both the force and moment acting at the base of the hair and the resulting deflection of the CNT forest inside of the microcapillary is measured to estimate the stress on the forest and the pressure between the forest and the electrode. The electrical responses of the sensors are compared to the mechanical state of the CNT forest. This work represents the development of a characterization tool to better understand and control the response of CNT based AHSs.

In nature, both material and structure are formed according to the principles of biologically controlled self-assembly, a process defined as the spontaneous and reversible ordering of small molecular building blocks under the influence of non-covalent, static interactions. The orientation and distribution of reinforcing entities in engineering composites is key to enabling structural efficiency, yet the architecture remains simplistic when compared to the distinctive and unique hierarchies found in Nature. These biological ‘composite’ materials achieve such configurations by accurately controlling the orientation of anisotropic nano- and micro-sized ‘building blocks’, thereby reinforcing the material in specific directions to carry the multidirectional external loads at different length scales. Capturing the design principles underlying the exquisite architecture of such biological materials will overcome many of the mechanical limitations of current engineering composites. The scientific vision for this study is the development of a novel and highly ordered complex architecture fibrous material for additive layer manufacturing. Using novel chemistry and controlled field-effect assembly, functionally graded, stiffness modulated architectures, analogous to those found in nature, are synthesised to realise enhanced mechanical performance, multi-dimensional composite structures. To achieve this, both hierarchical discontinuous fibres (glass fibres with ZnO nanrods) and a new type of ultrasonic device has been developed. The two studies reported here have been successfully employed to manufacture and mechanically characterise the fibres and aligned discontinuous fibres. A 43 % improvement in strength was observed for samples tested parallel to the direction of the fibre reinforcement over those strained normal to the fibre direction, despite the relatively low volume percentage of the reinforcement phase. This technique shows great potential for the low cost instantaneous alignment of structural reinforcement to generate the light-weight high performance structures required for the future.

Electromechanical impedance (EMI) method is an effective and powerful technique in structural health monitoring (SHM) which couples the mechanical impedance of host structure with the electrical impedance measured at the piezoelectric wafer active sensor (PWAS) transducer terminals. Due to the electromechanical coupling in piezoelectric materials, changes in structural mechanical impedance are reflected in the electrical impedance measured at the PWAS. Therefore, the structural mechanical resonances are reflected in a virtually identical spectrum of peaks and valleys in the real part of the measured EMI. Multi-physics based finite element method (MP-FEM) has been widely used for the analysis of piezoelectric materials and structures. It uses finite elements taking both electrical and mechanical DOF’s into consideration, which allows good differentiation of complicated structural geometries and damaged areas. In this paper, MP-FEM was then used to simulate PWAS EMI for the goal of SHM. EMI of free PWAS was first simulated and compared with experimental result. Then the constrained PWAS was studied. EMI of both metallic and glass fiber composite materials were simulated. The first case is the constrained PWAS on aluminum beam with various dimensions. The second case studies the sensitivity range of the EMI approach for damage detection on aluminum beam using a set of specimens with cracks at different locations. In the third case, structural damping effects were also studied in this paper.. Our results have also shown that the imaginary part of the impedance and admittance can be used for sensor self-diagnosis.

A novel Lewis acid-catalysed self-healing system is investigated for implementation in epoxy-based fibre reinforced polymer (FRP) composite materials. The catalyst, scandium(III) triflate, is selected using a qualitative approach and subsequently embedded with pre-synthesised epoxy-solvent loaded microcapsules, into an epoxy resin. Healing is initiated when microcapsules are ruptured at the onset of crack propagation. The epoxy monomer healing agent contained within, actively undergoes ring-opening polymerisation (ROP) on contact with the locally placed catalyst, forming a new polymer to bridge the two fractured crack surfaces. Self-healing performance is quantified using tapered double cantilever beam (TDCB) epoxy resin test specimens and the effects of microcapsule loading, microcapsule content and healing temperature are all independently considered. As an initial proof of concept study, results show that a material recovery value of greater than 80% fracture strength is achieved for this novel Lewis acid-catalysed self-healing epoxy resin. The same self-healing agent system was subsequently demonstrated in a larger scale FRP component by incorporating both a microcapsule and hollow glass fibre (HGF) delivery system within an FRP laminate using a End-Notched Flexure (ENF) test configuration.

The trend towards higher reliance on fiber-reinforced composites for structural components has led to the need to rethink current nondestructive evaluation (NDE) strategies. In principle, embeddable sensor schemes are desired for green-light/red-light structural health monitoring systems that do not negatively affect the properties and performance of the host structure. However, there are still numerous challenges that need to be overcome before these embedded sensing technologies can be realized for real-world structural systems. For example, some of these issues and challenges include the damage detection sensitivity/threshold, reliability of the system, transportability of the system to multiple configurations and different types of structural components, and signal processing/interpretation. The objective of this study is to develop a novel, embedded sensing system that can accurately quantify damage to composites without interfering with structural performance and functionality. In particular, this study will utilize multi-walled carbon nanotube (MWNT)-polyelectrolyte (PE) thin films deposited on a glass fiber substrate for in situ composite structural monitoring. A layer-by-layer (LbL) film fabrication methodology is employed for depositing piezoresistive nanocomposites directly onto glass fiber fabrics, and the resulting film exhibits excellent strain sensing performance, homogeneity, and exhibits no phase segregation. Specifically, the LbL fabrication process will employ polycationic poly(vinyl alcohol) (PVA) and polyanionic poly(sodium 4-styrene sulfonate) (PSS) doped with MWNTs for fabricating the electrically-conductive and piezoresistive thin films. Upon film deposition, the glass fiber substrates are infused with an epoxy matrix via wet-layup to fabricate self-sensing glass fiber-reinforced polymer (GFRP) composite specimens for testing. A frequency-domain approach, based on electrical impedance spectroscopy, is used to characterize the electromechanical response of the GFRP-MWNT-based thin film samples when subjected to complex uni-axial tensile load patterns. A resistor connected to a parallel resistor-capacitor circuit model is proposed for fitting experimental impedance spectroscopic measurements. It has been found that the series resistor models the bulk thin film piezoresistive performance accurately. In addition, these impedance measurements shed light on the glass fiber-thin film interaction electromechanical behavior. Bi-functional strain sensitivity is observed for all GFRP specimens, and the transition point of bilinear strain sensitivity is utilized as a possible metric for GFRP damage detection.