Subir Patra

Material State Awareness for Composites Part II: Precursor Damage Analysis and Quantification of Degraded Material Properties Using Quantitative Ultrasonic Image Correlation (QUIC)

Material state awareness of composites using conventional Nondestructive Evaluation (NDE) method is limited by finding the size and the locations of the cracks and the delamination in a composite structure. To aid the progressive failure models using the slow growth criteria, the awareness of the precursor damage state and quantification of the degraded material properties is necessary, which is challenging using the current NDE methods. To quantify the material state, a new offline NDE method is reported herein. The new method named Quantitative Ultrasonic Image Correlation (QUIC) is devised, where the concept of microcontinuum mechanics is hybrid with the experimentally measured Ultrasonic wave parameters. This unique combination resulted in a parameter called Nonlocal Damage Entropy for the precursor awareness. High frequency (more than 25 MHz) scanning acoustic microscopy is employed for the proposed QUIC. Eight woven carbon-fiber-reinforced-plastic composite specimens were tested under fatigue up to 70% of their remaining useful life. During the first 30% of the life, the proposed nonlocal damage entropy is plotted to demonstrate the degradation of the material properties via awareness of the precursor damage state. Visual proofs for the precursor damage states are provided with the digital images obtained from the micro-optical microscopy, the scanning acoustic microscopy and the scanning electron microscopy.

Material State Awareness for Composites Part I: Precursor Damage Analysis Using Ultrasonic Guided Coda Wave Interferometry (CWI)

Detection of precursor damage followed by the quantification of the degraded material properties could lead to more accurate progressive failure models for composite materials. However, such information is not readily available. In composite materials, the precursor damages—for example matrix cracking, microcracks, voids, interlaminar pre-delamination crack joining matrix cracks, fiber micro-buckling, local fiber breakage, local debonding, etc.—are insensitive to the low-frequency ultrasonic guided-wave-based online nondestructive evaluation (NDE) or Structural Health Monitoring (SHM) (~100–~500 kHz) systems. Overcoming this barrier, in this article, an online ultrasonic technique is proposed using the coda part of the guided wave signal, which is often neglected. Although the first-arrival wave packets that contain the fundamental guided Lamb wave modes are unaltered, the coda wave packets however carry significant information about the precursor events with predictable phase shifts. The Taylor-series-based modified Coda Wave Interferometry (CWI) technique is proposed to quantify the stretch parameter to compensate the phase shifts in the coda wave as a result of precursor damage in composites. The CWI analysis was performed on five woven composite-fiber-reinforced-laminate specimens, and the precursor events were identified. Next, the precursor damage states were verified using high-frequency Scanning Acoustic Microscopy (SAM) and optical microscopy imaging.

Subsurface pressure profiling: a novel mathematical paradigm for computing colony pressures on substrate during fungal infections

Colony expansion is an essential feature of fungal infections. Although mechanisms that regulate hyphal forces on the substrate during expansion have been reported previously, there is a critical need of a methodology that can compute the pressure profiles exerted by fungi on substrates during expansion; this will facilitate the validation of therapeutic efficacy of novel antifungals. Here, we introduce an analytical decoding method based on Biot’s incremental stress model, which was used to map the pressure distribution from an expanding mycelium of a popular plant pathogen, Aspergillus parasiticus. Using our recently developed Quantitative acoustic contrast tomography (Q-ACT) we detected that the mycelial growth on the solid agar created multiple surface and subsurface wrinkles with varying wavelengths across the depth of substrate that were computable with acousto-ultrasonic waves between 50 MHz–175 MHz. We derive here the fundamental correlation between these wrinkle wavelengths and the pressure distribution on the colony subsurface. Using our correlation we show that A. parasiticus can exert pressure as high as 300 KPa on the surface of a standard agar growth medium. The study provides a novel mathematical foundation for quantifying fungal pressures on substrate during hyphal invasions under normal and pathophysiological growth conditions.

Peri-Elastodynamic Simulations of Guided Ultrasonic Waves in Plate-Like Structure with Surface Mounted PZT

Peridynamic based elastodynamic computation tool named Peri-elastodynamics is proposed herein to simulate the three-dimensional (3D) Lamb wave modes in materials for the first time. Peri-elastodynamics is a nonlocal meshless approach which is a scale-independent generalized technique to visualize the acoustic and ultrasonic waves in plate-like structure, micro-electro-mechanical systems (MEMS) and nanodevices for their respective characterization. In this article, the characteristics of the fundamental Lamb wave modes are simulated in a sample plate-like structure. Lamb wave modes are generated using a surface mounted piezoelectric (PZT) transducer which is actuated from the top surface. The proposed generalized Peri-elastodynamics method is not only capable of simulating two dimensional (2D) in plane wave under plane strain condition formulated previously but also capable of accurately simulating the out of plane Symmetric and Antisymmetric Lamb wave modes in plate like structures in 3D. For structural health monitoring (SHM) of plate-like structures and nondestructive evaluation (NDE) of MEMS devices, it is necessary to simulate the 3D wave-damage interaction scenarios and visualize the different wave features due to damages. Hence, in addition, to simulating the guided ultrasonic wave modes in pristine material, Lamb waves were also simulated in a damaged plate. The accuracy of the proposed technique is verified by comparing the modes generated in the plate and the mode shapes across the thickness of the plate with theoretical wave analysis.

Ultrasonic measurement and detection of precursor delamination damage in composite under tension-torsion loading

Precursor to Damage state quantification in composite material is extremely challenging in the field of structural health monitoring (SHM). Conventional ultrasonic technique is not able to predict the early damage state; this could lead to catastrophic failure of the structure. So, early state damage detection is very imperative for safety and operation of structure. Composite materials experience different type of loading condition (e.g., Tension, torsion bending, etc.) during its operation in extreme environment. Precursor to damage in the composite material can appear in the form matrix cracking, fiber breakage and delamination. In this work, we presented an on board damage detection technique for precursor damage state quantification of Carbon fiber composite material (CFRP). An American society of testing and materials (ASTM) standard specimen was tested under tensor-torsion fatigue lading. Pitch-catch experiments were performed at a regular interval of 10,000 cycles and ultrasonic imaging were performed by using scanning acoustic microscope (SAM) to examine the onset of damage on surface as well as inside the material. Optical microscopy was also performed to examine the damage onset on the surface of the material. Advance signal processing techniques such as Discrete Fourier Transform (DFT), Short-time Fourier transform (STFT) and Continuous Wavelet Transform (CWT) were performed to analyze the sensor signal for extract information of damage growth with fatigue loading to prove that the precursor damage quantification is possible in online SHM.

Nonlocal and Coda Wave Quantification of Damage Precursors in Composite from Nonlinear Ultrasonic Response

Materials state awareness using conventional nondestructive evaluation (NDE) at the early stage of service life is extremely challenging because of the inherent material nonlinearity that initiates at the lower scales. Conventional NDE methods are limited by reporting location, size, and shape of the material discontinuities, e.g., cracks, voids, delamination, etc. In the past, several nonlinear ultrasonic methods are developed to detect the small discrete damages, whereas quantification of degraded material properties and detection of embryonic precursor damage in materials is currently challenging. Understanding the early stage of precursor damages using ultrasonic method inherently is to understand the material nonlinearity that arise from the bottom-up scales, which further requires to evaluate the ultrasonic signals with subtle nonlinearity in an innovative way that are essentially ignored in conventional ultrasonic NDE methods. Hence, in this chapter, it is hypothesized that such nonlinear effects at the early stage of damage at the lower scale are actually sensed by the ultrasonic NDE probes/sensors and hidden in the ultrasonic signals. Such hidden features are required to be extracted from the signals using innovative signal analysis method integrated with the microcontinuum physics. In this chapter defying the conventional nonlinear ultrasonic techniques, a newly formulated nonlocal approach is presented to quantify the damage precursor in materials at its early stage of the service life. Nonlocal parameter that carries information from the lower scale has a nonlinear dependency on the ultrasonic wave velocity at any particular frequency, which is assumed to be a constant in linear ultrasonics and no information could be extracted. Here, it should be noted that the nonlinear function of nonlocal parameter from a material that can be extracted from the material degradation state is not necessarily associated with the material discontinuities like cracks or delamination at the macroscale but due to distributed nonlocal effect of lower scale defects and damages. Thus, a new term called nonlocal damage entropy (NLDE) was coined by the authors in their recent publications to quantify the multiscale damage state in materials while exploiting the high-frequency ultrasonic (≥10 MHz) with microcontinuum field theory. In this chapter, first, a review of different “bottom-up” multiscale modeling approaches is discussed followed by the need of a “top-down” precursor quantification method is justified. Further, a review of the existing methods for quantifying damage precursor is presented followed by a mathematical and experimental derivation of NLDE is presented. To justify the findings with additional information from different scales, low-frequency (≤500 kHz) Guided wave ultrasonic NDE was performed. It is further hypothesized that the lower frequency ultrasonic guided wave signal that carries the nonlinear effect from the lower scale is essentially manifested but can only be extracted from the coda part of the signals and thus in this chapter the coda part of the signals were analyzed. Frequency transformation of the signals could result very low and almost undetectable higher harmonics due to the very early stage of damage and may not be useful for precursor quantification. Hence, a time domain analysis is required to find this information on the nonlinearity that could be manifested but are buried deep inside the signal. Thus, Guided coda wave interferometry (CWI) for composite is formulated for the first time using high-speed Taylor series expansion method. Precursor damage index is then formulated to quantify the damage state. Precursor damage index from Guided CWI and high-frequency NLDE are then correlated to evaluate the equivalency of information. To prove the positive indication of precursor damage from the newly coined NLDE, a set of benchmark studied are presented using optical microscopy and scanning electron microscopy (SEM). As metallic structures are well studied by many researchers, in this chapter the example study of precursor damage is restricted to the composite specimens under fatigue.

Precursor to damage state quantification in composite materials (Conference Presentation)

Nonlinear damage in the composite materials is developed with the growth of damages in the material under fatigue loading. Nonlinear ultrasonic techniques are sensitive to early stage damages such as, fiber breakages, matrix micro-cracking, and deboning etc. Here, in this work, early stage damages are detected in Unidirectional (UD) carbon fiber composite under fatigue loading. Specimens are prepared according to American Society for Testing and Materials (ASTM) standard. Specimens are subjected to low cycle high load (LCHL) fatigue loading until 150,000 cycles. Sensors are mounted on the specimen used for actuation and sensing. A five count tone burst with low frequency (fc =375 kHz) followed by high frequency (fc =770 kHz) signal, was used as actuation signal. Pitch-catch experiments are collected at the interval of 5,000 cycles. Sensor signals are collected for various excitation voltage (from 5V to 20V, with 5V interval). First Fourier Transform (FFT) of the sensor signals are performed and side band frequencies are observed at around 770 kHz. Severity of damages in the material is quantified from the ratio of amplitude of side band frequencies with the central frequency. Nonlinearity in the material due to damage development is also investigated from the damage growth curve obtained at various excitation amplitude. Optical Microcopy imaging were also performed at the interval of 5,000 to examine developments of damages inside the material. This study has a good potential in detection of early stage damages in composite materials.

Progressive damage state evolution and quantification in composites

Precursor damage state quantification can be helpful for safety and operation of aircraft and defense equipment’s. Damage develops in the composite material in the form of matrix cracking, fiber breakages and deboning, etc. However, detection and quantification of the damage modes at their very early stage is not possible unless modifications of the existing indispensable techniques are conceived, particularly for the quantification of multiscale damages at their early stage. Here, we present a novel nonlocal mechanics based damage detection technique for precursor damage state quantification. Micro-continuum physics is used by modifying the Christoffel equation. American society of testing and materials (ASTM) standard woven carbon fiber (CFRP) specimens were tested under Tension-Tension fatigue loading at the interval of 25,000 cycles until 500,000 cycles. Scanning Acoustic Microcopy (SAM) and Optical Microscopy (OM) were used to examine the damage development at the same interval. Surface Acoustic Wave (SAW) velocity profile on a representative volume element (RVE) of the specimen were calculated at the regular interval of 50,000 cycles. Nonlocal parameters were calculated form the micromorphic wave dispersion curve at a particular frequency of 50 MHz. We used a previously formulated parameter called “Damage entropy” which is a measure of the damage growth in the material calculated with the loading cycle. Damage entropy (DE) was calculated at every pixel on the RVE and the mean of DE was plotted at the loading interval of 25,000 cycle. Growth of DE with fatigue loading cycles was observed. Optical Imaging also performed at the interval of 25,000 cycles to investigate the development of damage inside the materials. We also calculated the mean value of the Surface Acoustic Wave (SAW) velocity and plotted with fatigue cycle which is correlated further with Damage Entropy (DE). Statistical analysis of the Surface Acoustic Wave profile (SAW) obtained at different fatigue cycles was performed to extract the useful information about the damage state. This study has potential to investigate progressive damage evolution and to quantify at different fatigue cycles.

Precursor Damage Inception Quantification

Quantification of precursor of damage initiation in composite materials is extremely challenging using an on-board Structural health Monitoring (SHM) system. Here we present the recent advancement in online ultrasonic sensing methodology for precursor damage quantification. Present SHM techniques are incapable of detecting the damage stage at sub wave length scale. In this paper, first we have studied a simple but novel off-board approach for precursor damage state quantification using high frequency ultrasonic image correlation technique. Further proper sensing methodology is established from the information extracted from proposed off-board technique. To correlate the on-board SHM technique with the off-board understanding, high frequency piezoelectric sensors were mounted on the specimen and lamb wave interaction with stiffness reduction is studies to excerpt information of damage incubation. Here, we investigated damage state of Carbonfiber- reinforced polymer (CFRP) composite. Precursor damage states are generally in the form of matrix cracking, deboning and fiber breakage in composites. Here in this work we performed tensile-tensile fatigue testing on ASTM standard specimen at an interval of 10000 cycles until cracks / delamination are developed. At each interval of loading, volumetric ultrasonic scans are performed on the gage area of the specimen using Scanning Acoustic Microscope (SAM). The stiffness degradation is calculated at each pixel points of the selected gage area using nonlocal elastoplasticity theory. We used our novel observable parameter called ‘’Damage Entropy” (DE) which is a measure of material damage, are calculated, and plotted with fatigue loading cycle until visible damage incubates. Damage incubation in the specimen was clearly observed from the Z-scan images from SAM. Advance signal processing technique and sensor selection is used for this process. This study has the potential to correlate the DE from SAM and Damage index (DI) from online Sensor Data for online precursor damage quantification. doi: 10.12783/SHM2015/322