Yingtao Liu

Hydrothermal synthesis of vertically aligned lead zirconate titanate nanowire arrays

A hydrothermal method is employed for the growth of single crystal vertically aligned lead zirconate titanate (PZT) nanowire arrays. The resulting PZT nanowires were grown from a TiO2 film and are shown to be single crystal with growth in the [110] axis. PZT has a coupling coefficient up to two orders of magnitude higher than ZnO, which should provide many opportunities for the creation of active nanodevices and systems.

Damage assessment of CFRP composites using a time–frequency approach

A damage assessment methodology using a time–frequency signal processing technique is presented in this article. Delaminations are detected in composite structures with multiple stiffeners. Because Lamb waves are complex in nature, due to wave dispersion and scattering, a robust signal processing technique is required to extract features from Lamb wave signals. In this article, the matching pursuit decomposition algorithm is used for extracting wavelets from the Lamb wave signals in the time–frequency domain. A small time–frequency atom dictionary is defined to avoid the exhaustive search over the time–frequency domain and to reduce the computation costs. The propagation characteristics of Lamb waves in stiffened composite panels are investigated. The delaminations are detected by identifying the converted Lamb wave modes introduced by the structural imperfection. A two-step damage detection approach, which uses both pulse-echo and pitch-catch active sensing schemes, is developed for the identification of delaminations. The delamination is quantified using a signal energy-based damage index. The matching pursuit decomposition algorithm is further used to localize the delamination position by solving a set of nonlinear equations. The results show that the matching pursuit decomposition algorithm can be used to identify and localize the seeded delaminations in composite structures with complex geometries and material properties.

Characterization of Epoxy Resin Including Strain Rate Effects Using Digital Image Correlation System

AbstractThe mechanical response of epoxy resin Epon E 863 has been studied in tension, compression, and flexure. The epoxy resins have been tested at different strain rates ranging from 5.9×10-5 to 0.03  s-1. Two types of dog-bone geometries have been used in the tension tests. Small sized cubic, prismatic, and cylindrical samples were used in compression tests. Beams with quarter deep notches or grooves were tested at their midpoints in flexural tests. Strains were measured by using a digital image correlation technique, extensometer, strain gages, and actuator. Observation of sample geometry during tension tests at constant elongation rate shows necking and crazing in Epon E 863. Cubic, prismatic, and cylindrical compression samples undergo a stress drop at yield, but only cubic samples experience strain hardening before failure. Characteristic points of tensile and compressive stress strain relation and load deflection curve in flexure, such as proportional elastic limit stress (PEL), ultimate tensile ...

Application of System-Identification Techniquest to Health Monitoring of On-Orbit Satellite Boom Structures

The integration of composites into spacecraft is challenged by the risk of damage initiation andpropagation during storage, launch, and service life. Elastically deployable composite booms are being developed for space utility.Matrix cracks are considered a primary form of damage caused by packaging before launch. However, while on orbit, most damages are induced by the environmental effects on the polymers. A well-developed structural health monitoring system will provide information for the dynamic control of the satellite and the condition of the deployable mechanisms on the space vehicle. A structural health monitoring methodology, based on the system-identification techniques, is proposed to identify the structural degradation in laminated composite booms. Nondestructive evaluation techniques, frequency-response analysis and autoregressive with exogenous input models are used to approximate the transfer functions between input and output sensing signals. Structural degradation is identified by examining the change of transfer functions at different storage states. A single-input/single-output approach is adopted in this paper. The proposed methodology is validated through experimentation in which matrix cracking is gradually induced by packaging the sample.

Low-velocity impact damage monitoring of a sandwich composite wing:

Impact damage has been identified as a critical form of defect that constantly threatens the reliability of composite structures, such as those used in aircrafts and naval vessels. Low-energy impacts can introduce barely visible damage and cause structural degradation. Therefore, efficient structural health monitoring methods, which can accurately detect, quantify, and localize impact damage in complex composite structures, are required. In this article, a novel damage detection methodology is demonstrated for monitoring and quantifying the impact damage propagation. Statistical feature matrices, composed of features extracted from the time and frequency domains, are developed. Kernel principal component analysis is used to compress and classify the statistical feature matrices. Compared with traditional principal component analysis algorithm, kernel principal component analysis method shows better feature clustering and damage quantification capabilities. A new damage index, formulated using the Mahalanobis distance, is defined to quantify impact damage. The developed methodology has been validated using low-velocity impact experiments with a sandwich composite wing.

Analytical Solution for Flexural Response of Epoxy Resin Materials

AbstractA piecewise linear parametric uniaxial stress-strain approach has been used to obtain the closed form nonlinear moment curvature response on the basis of strain compatibility in bending for epoxy resin materials. The stress-strain curves, consisting of a bilinear ascending curve followed by strain softening and constant plastic flow in tension and compression, are described by two main parameters, with an additional five nondimensional tensile and seven nondimensional compressive parameters. The main parameters are the modulus of elasticity and strain at the proportional elastic limit point in tension. Parametric studies show that ultimate tensile stress and compressive yield stresses and tension and compression flow stresses have the highest effects on flexural load carrying capacity. Moment curvature equations, in conjunction with softening localization and static equilibrium conditions, were used to simulate the flexural load-deflection response of a beam under three-point bending (3PB) conditi...

An optimized cross-linked network model to simulate the linear elastic material response of a smart polymer

This article presents a novel approach to model the mechanical response of smart polymeric materials. A cyclobutane-based mechanophore, named “smart particle” in this article, is embedded in an epoxy polymer matrix to form the self-sensing smart material. A spring–bead model is developed based on the results from molecular dynamics simulation at the nanoscale to represent bond clusters of a smart polymer. The spring–bead network model is developed through parametric studies and mechanical equivalence optimization to represent the microstructure of the material. A statistical network model is introduced, which is capable of bridging the high-accuracy molecular dynamics model at the nanoscale and the computationally efficient finite element model at the macroscale. A comparison between experimental and simulation results shows that the multiscale model can capture global mechanical response and local material properties.

Study of glass transition temperature (Tg) of novel stress-sensitive composites using molecular dynamic simulation

This study investigates the glass transition temperature (Tg) of novel stress-sensitive composites capable of detecting a damage precursor using molecular dynamics (MD) simulations. The molecular structures of a cross-linked epoxy network (which consist of epoxy resin, hardener and stress-sensitive material) have been simulated and experimentally validated. The chemical constituents of the molecular structures are di-glycidyl ether of bisphenol F (DGEBF: epoxy resin), di-ethylene tri-amine (DETA: hardener) and tris-(cinnamoyloxymethyl)-ethane (TCE: stress-sensitive material). The cross-linking degree is varied by manipulating the number of covalent bonds through tuning a cutoff distance between activated DGEBF and DETA during the non-equilibrium MD simulation. A relationship between the cross-linking degree and Tgs has been studied numerically. In order to validate a proposed MD simulation framework, MD-predicted Tgs of materials used in this study have been compared to the experimental results obtained by the differential scanning calorimetry (DSC). Two molecular models have been constructed for comparative study: (i) neat epoxy (epoxy resin with hardener) and (ii) smart polymer (neat epoxy with stress-sensitive material). The predicted Tgs show close agreement with the DSC results.

Early damage detection in epoxy matrix using cyclobutane-based polymers

Identification of early damage in polymer composites is of great importance. We have incorporated cyclobutane-containing cross-linked polymers into an epoxy matrix, studied the effect on thermal and mechanical properties, and, more importantly, demonstrated early damage detection through mechanically induced fluorescence generation. Two cinnamate derivatives, 1,1,1-tris(cinnamoyloxymethyl) ethane (TCE) and poly(vinyl cinnamate) (PVCi), were photoirradiated to produce cyclobutane-containing polymer. The effects on the thermal and mechanical properties with the addition of cyclobutane-containing polymer into epoxy matrix were investigated. The emergence of cracks was detected by fluorescence at a strain level just beyond the yield point of the polymer blends, and the fluorescence intensified with accumulation of strain. Overall, the results show that damage can be detected through fluorescence generation along crack propagation.

A novel statistical spring-bead based network model for self-sensing smart polymer materials

This paper presents a multiscale modeling approach to simulating the self-sensing behavior of a load sensitive smart polymer material. A statistical spring-bead based network model is developed to bridge the molecular dynamics simulations at the nanoscale and the finite element model at the macroscale. Parametric studies are conducted on the developed network model to investigate the effects of the thermoset crosslinking degree on the mechanical response of the self-sensing material. A comparison between experimental and simulation results shows that the multiscale framework is able to capture the global mechanical response with adequate accuracy and the network model is also capable of simulating the self-sensing phenomenon of the smart polymer. Finally, the molecular dynamics simulation and network model based simulation are implemented to evaluate damage initiation in the self-sensing material under monotonic loading.