When stress in concrete exceeds certain threshold value, microcracks are nucleated, these microcracks can propagate and coalesce forming macrocracks, resulting in the gradual decay of the mechanical properties of concrete and eventual failure of the concrete structures. For safety concerns, one needs to develop suitable nondestructive testing methods capable of detecting past overloads of concrete structures during its service life. In this work, the stress-induced damage in concrete is monitored using ultrasonic techniques, exploiting the coupling between the stress level experienced by concrete and its wave propagation parameters. Cyclic compression tests with increasing maximum load level have been performed on specimens made of concrete with coarse-grained (CG) aggregates. Experimental results have been analyzed by two different ultrasonic methods—the linear and the nonlinear ultrasonic techniques. In linear ultrasonic technique, the stress level experienced by the specimens is related to the variations in signal amplitude and velocity of ultrasonic waves. In nonlinear ultrasonic method, the sideband peak count (SPC) technique is used for revealing the stress-induced damage corresponding to each load step. In comparison to linear ultrasonic parameters, the nonlinear ultrasonic parameter SPC-I appears to be more sensitive to the variations of the internal material structures during both loading and unloading phases. Moreover, the SPC technique has shown to be capable of identifying both the initial damage due to the evolution and nucleation of microcracks at the microscopic scale, and the subsequent damages induced by high overload, resulting in an irreversible degradation of the mechanical properties.

A novel failure model updating methodology is presented in this paper for composite materials. The innovation in the approach presented is found in both the experimental and computational methods used. Specifically, a dominant bottleneck in data-driven failure model development relates to the types of data inputs that could be used for model calibration or updating. To address this issue, nondestructive evaluation data obtained while performing mechanical testing at the laboratory scale are used in this paper to form a damage metric based on a series of processing steps that leverage raw sensing inputs and provide progressive failure curves that are then used to calibrate the damage initiation point computed by full-field three-dimensional finite element simulations of fiber-reinforced composite material that take into account both intra- and interlayer damage. Such curves defined based on nondestructive evaluation data are found to effectively monitor the progressive failure process, and therefore, they could be used as a way to form modeling inputs at different length scales.

As one of the fastest-growing technologies over the past half century, integrated circuit (IC) packaging is getting smaller and more complex. For example, typical silicon wafers in modern IC packaging have thicknesses ranging from several to tens of micrometers, and their coating layers are in the range of a few nanometers. Because the silicon wafer is the main substrate in IC packaging, it is important to accurately measure the geometry of a silicon wafer, especially its coating thickness, for process monitoring and quality control. In this study, an ultrafast ultrasonic measurement system is developed using a femtosecond laser for silicon wafer coating thickness estimation. The proposed technique provides the following unique features: (1) an ultrafast ultrasonic measurement system using a femtosecond laser is developed specifically for silicon wafer coating thickness estimation; (2) the developed system can estimate the thickness of a coating layer in the range of sub-micrometer; (3) except for the wave speed in the coating material, coating thickness can be estimated without any other prior knowledge of the coating material properties or substrate characteristics such as optical constants; and (4) the thermal effects on the ultrasonic waves propagating within a thin coating layer are explicitly considered and minimized for coating thickness estimation. Using the developed system, validation tests were successfully performed on gold-coated silicon wafers with different coating thicknesses.

Nonlinear ultrasonic (NLU) techniques have emerged as a potential solution to improve the resolution of nondestructive measurements to detect microstructural changes of cyclically loaded materials. However, current NLU methods need power-demanding instrumentation that is useful only in the laboratory settings. On the other hand, phased array systems provide the capability of sensing such changes when the later portion of the elastic waveforms, called diffuse field, is analyzed. Moreover, phased array systems are an excellent solution for field test measurement and imaging of material damage. This study explores the use of NLU metrics based on ratios of harmonic amplitudes and frequencies to map the buildup of damage precursors, such as crystal dislocations, under cyclic loading within the microstructure of fatigued 2024-T3 aluminum specimens. The results show that these metrics are highly sensitive to microstructural fatigue damage making them significantly important to measure mechanical properties, such as fracture toughness, that are extremely useful in predicting the remaining useful life of a studied material. A nonlinear metric of elastic energy that encapsulates the nonlinear effects of subharmonic and higher-harmonic generations and frequency ratio is proposed. These effects of spectral energy shifts are combined making this metric highly sensitive to nano- and micro-scale damage within the fatigued medium.

Pipelines are the primary means of land transportation of oil and gas globally, and pipeline integrity is, therefore, of high importance. Failures in pipelines may occur due to internal and external stresses that produce stress concentration zones, which may cause failure by stress corrosion cracking. Early detection of stress concentration zones could facilitate the identification of potential failure sites. Conventional non-destructive testing (NDT) methods, such as magnetic flux leakage, have been used to detect defects in pipelines; however, these methods cannot be effectively used to detect zones of stress concentration. In addition, these methods require direct contact, with access to the buried pipe. Metal magnetic memory (MMM) is an emerging technology, which has the potential to characterize the stress state of underground pipelines from above ground. The present paper describes magnetic measurements performed on steel components, such as bars and tubes, which have undergone changing stress conditions. It was observed that plastic deformation resulted in the modification of measured residual magnetization in steels. In addition, an exponential decrease in signal with the distance of the sensor from the sample was observed. Results are attributed to changes in the local magnetic domain structure in the presence of stress but in the absence of an applied field.

Dual matrix transmit-receive longitudinal (TRL) arrays have been shown to provide an improved signal to noise ratio in the near field zone which makes them the most suitable array configuration for the inspection of near-surface defects. This study aims to compare the performance of different configurations for transmit-receive longitudinal matrix arrays. For this purpose, four matrix configurations of 2 × 32, 4 × 16, 4 × 32, and 8 × 16 elements are investigated using EXTENDE CIVA modeling package. The array operating frequencies investigated are either 5 MHz or 10 MHz. The effect of different natural focal depths, arrays separation distances, dynamic electronic depth focusing, and electronic beam skewing for these TRL arrays are considered in models prepared in CIVA. The inspection of a series of flat bottom holes extended up to a few millimeters under the surface using the selected TRL configurations is also investigated in the study. It is found that the performance of focusing for near-surface areas is more efficient using the 4 × 16 and 8 × 16 elements configurations as compared with the others, and the signal amplitudes of the defects located deeper in the target material are almost independent of the configuration.

Quantitative assessment of fiber characteristics in composite parts is of great significance in order to correlate them with the fiber-induced mechanical properties. X-ray computed tomography (CT) is being successfully used as a three-dimensional nondestructive measuring technique for the analysis of fiber characteristics (mainly the fiber orientation and fiber volume content) in fiber-reinforced composite materials. However, the accuracy of such analyses depends on various factors (e.g., scanning parameters, resolution), which is the motivation for this study. The current work investigates the effect of CT scanning parameters and spatial resolution on the obtained fiber orientation and fiber volume content. First a simulation study is carried out using a computationally generated fiber composite model followed by a validation using a thin-wall injection-molded part. The findings showed that the effect of CT settings is not significant on the measurements, but the resolution affects the estimated fiber volume content adversely. A preliminary error calculation method is proposed for correcting the overestimation in the fiber volume content.

Cyclic loading of mechanical components promotes the formation of dislocation substructures in metals as precursors to crack nucleation leading to final failure of the metallic components. It is well known within the ultrasonic community that the acoustic nonlinearity parameter is a meaningful indicator of the microstructural damage accumulation. However, current nonlinear ultrasonic techniques suffer from response saturation and limited resolution after 50% fatigue life of the metallic medium. The present study investigates the feasibility of incorporating collinear wave mixing interactions into second harmonic assessments to improve the sensitivity of the nonlinear parameter to a microstructural accumulation of damage precursors (DP). To this end, a decomposition technique was explored to obtain higher harmonics from short time-domain pulses propagating through thin metallic components such as jet engine turbine blades. The results demonstrate the effectiveness of the decomposition technique to measure the acoustic nonlinearity parameter as an early and continuous indicator of fatigue damage precursors throughout the service life of critical aircraft components. A micrographic study showed a strong correlation between the nonlinearity parameter and the increase in damage precursors throughout the life of the specimens.

In general, the fatigue life of a safety critical pressure component is estimated using best-fit fatigue life curves (S-N curves). These curves are estimated based on underlying in-air condition fatigue test data. The best-fitting approach requires a large safety factor to accommodate the uncertainty associated with large scatter in fatigue test data. In addition to this safety factor, reactor component fatigue life prognostics requires an additional correction factor that in general is also estimated deterministically. This additional factor known as the environmental correction factor F en is to cater the effect of the harsh coolant environment that severely reduces the life of these components. The deterministic F en factor may also lead to further conservative estimation of fatigue life leading to unnecessary early retirement of costly reactor components. To address the above-mentioned issues, we propose a data-analytics framework which uses Weibull and Bootstrap probabilistic modeling techniques for explicitly quantifying the uncertainty/scatter associated with fatigue life rather than estimating the lives based on a best-fit based deterministic approach. We assume the proposed probabilistic approach would provide the first hand information for assessing the maximum and minimum effects of pressurized water reactor water on the reactor component. In the discussed approach, in addition to the probabilistic fatigue curves, we suggest using a probabilistic environment correction factor F en . We assume the probabilistic fatigue curve and F en would capture the S-N data scatter associated with the bulk effect of material grades, surface finish, strain rate, etc. on the material/component fatigue life.

The manufacturing process of carbon fiber reinforced polymer (CFRP) composite structures can introduce many characteristic defects and flaws such as fiber misorientation, fiber waviness, and wrinkling. Therefore, it becomes increasingly important to detect the presence of these defects at the earliest stages of development. Eddy current testing (ECT) is a nondestructive inspection (NDI) technique that has been proven quite effective in detection of damage in metallic structures. However, NDI of composite structures has mainly relied on other methods such as ultrasonic testing (UT) and X-ray to name a few and not much on ECT. In this paper, the authors explore the possibility of using ECT in NDI of CFRP composites by conducting simulations and experiments thereafter. This research is based on the fact that the CFRP displays some low-level electrical conductivity due to the inherent conductivity of the carbon fibers. This low-level conductivity may permit eddy current pathways to cause the flow of eddy currents in the CFRP composites that can be exploited for nondestructive damage detection. An invention disclosure describing our high-frequency ECT method has also been processed. First, the multiphysics finite element method (FEM) simulation was used to simulate the detection of various types of manufacturing flaws and operational damage in CFRP composites such as fiber misorientation, waviness, wrinkling, and so on. Thereafter, ECT experiments were conducted on CFRP specimens with various manufacturing flaws using the Eddyfi Reddy eddy current array (ECA) system.

This paper presents gamma radiation effects on resonant and antiresonant characteristics of piezoelectric wafer active sensors (PWAS) for structural health monitoring (SHM) applications to nuclear-spent fuel storage facilities. The irradiation test was done in a Co-60 gamma irradiator. Lead zirconate titanate (PZT) and Gallium Orthophosphate (GaPO 4 ) PWAS transducers were exposed to 225 kGy gamma radiation dose. First, 2 kGy of total radiation dose was achieved with slower radiation rate at 0.1 kGy/h for 20; h then the remaining radiation dose was achieved with accelerated radiation rate at 1.233 kGy/h for 192 h. The total cumulative radiation dose of 225 kGy is equivalent to 256 years of operation in nuclear-spent fuel storage facilities. Electro-mechanical impedance and admittance (EMIA) signatures were measured after each gamma radiation exposure. Radiation-dependent logarithmic sensitivity of PZT-PWAS in-plane and thickness modes resonance frequency ( ∂ ( f R ) / ∂ ( log e R d ) ) was estimated as 0.244 kHz and 7.44 kHz, respectively; the logarithmic sensitivity of GaPO 4 -PWAS in-plane and thickness modes resonance frequency was estimated as 0.0629 kHz and 2.454 kHz, respectively. Therefore, GaPO 4 -PWAS EMIA spectra show more gamma radiation endurance than PZT-PWAS. Scanning electron microscope (SEM) and X-ray diffraction method (XRD) was used to investigate the microstructure and crystal structure of PWAS transducers. From SEM and XRD results, it can be inferred that there is no significant variation in the morphology, the crystal structure, and grain size before and after the irradiation exposure.

Peak density is an ultrasound measurement, which has been found to vary according to microstructure, and is defined as the number of local extrema within the resulting power spectrum of an ultrasound measurement. However, the physical factors which influence peak density are not fully understood. This work studies the microstructural characteristics which affect peak density through experimental, computationa,l and analytical means for high-frequency ultrasound of 22–41 MHz. Experiments are conducted using gelatin-based phantoms with glass microsphere scatterers with diameters of 5, 9, 34, and 69 μ m and number densities of 1, 25, 50, 75, and 100 mm −3 . The experiments show the peak density to vary according to the configuration. For example, for phantoms with a number density of 50 mm −3 , the peak density has values of 3, 5, 9, and 12 for each sphere diameter. Finite element simulations are developed and analytical methods are discussed to investigate the underlying physics. Simulated results showed similar trends in the response to microstructure as the experiment. When comparing scattering cross section, peak density was found to vary similarly, implying a correlation between the total scattering and the peak density. Peak density and total scattering increased predominately with increased particle size but increased with scatterer number as well. Simulations comparing glass and polystyrene scatterers showed dependence on the material properties. Twenty-four of the 56 test cases showed peak density to be statistically different between the materials. These values behaved analogously to the scattering cross section.

Active microwave thermography (AMT) is an integrated nondestructive testing (NDT) technique that utilizes a microwave-based thermal excitation and subsequent thermal measurement. AMT has shown potential for applications in the transportation, infrastructure, and aerospace industries. This paper investigates the potential of AMT for detection of defects referred to as flat-bottom holes (FBHs) in composites with high electrical conductivity such as carbon fiber-based composites. Specifically, FBHs of different dimensions machined in a carbon fiber reinforced polymer (CFRP) composite sheet are considered. Simulation and measurement results illustrate the potential for AMT as a NDT tool for inspection of CFRP structures. In addition, a dimensional analysis of detectable defects is provided including a radius-to-depth ratio threshold for successful detection.

Shockwave is a high pressure and short duration pulse that induce damage and lead to progressive collapse of the structure. The shock load excites high-frequency vibrational modes and causes failure due to large deformation in the structure. Shockwave experiments were conducted by imparting repetitive localized shock loads to create progressive damage states in the structure. Two-phase novel damage detection algorithm is proposed, that quantify and segregate perturbative damage from microscale damage. The first phase performs dimension reduction and damage state segregation using principal component analysis (PCA). In the second phase, the embedding dimension was reduced through empirical mode decomposition (EMD). The embedding parameters were derived using singular system analysis (SSA) and average mutual information function (AMIF). Based, on Takens theorem and embedding parameters, the response was represented in a multidimensional phase space trajectory (PST). The dissimilarity in the multidimensional PST was used to derive the damage sensitive features (DSFs). The DSFs namely: (i) change in phase space topology (CPST) and (ii) Mahalanobis distance between phase space topology (MDPST) are evaluated to quantify progressive damage states. The DSFs are able to quantify the occurrence, magnitude, and localization of progressive damage state in the structure. The proposed algorithm is robust and efficient to detect and quantify the evolution of damage state for extreme loading scenarios.

A computational damage model, which is driven by material, mechanical behavior, and nondestructive evaluation (NDE) data, is presented in this study. To collect material and mechanical behavior damage data, an aerospace grade precipitate-hardened aluminum alloy was mechanically loaded under monotonic conditions inside a scanning electron microscope, while acoustic and optical methods were used to track the damage accumulation process. In addition, to obtain experimental information about damage accumulation at the laboratory scale, a set of cyclic loading experiments was completed using three-point bending specimens made out of the same aluminum alloy and by employing the same nondestructive methods. The ensemble of recorded data for both cases was then used in a postprocessing scheme based on outlier analysis to form damage progression curves, which were subsequently used as custom damage laws in finite element (FE) simulations. Specifically, a plasticity model coupled with stiffness degradation triggered by the experimentally defined damage curves was used in custom subroutines. The results highlight the effect of the data-driven damage model on the simulated mechanical response of the geometries considered and provide an information workflow that is capable of coupling experiments with simulations that can be used for remaining useful life (RUL) estimations.

Composite materials find wide range of applications due to their high strength-to-weight ratio. Due to this increasing dependence on composite materials, there is a need to study their mechanical behavior in case of damage. There are several extended nondestructive testing (ENDT) and structural health-monitoring (SHM) methods for the assessment of the mechanical properties each with their set of advantages and disadvantages. This paper presents a comparative study of three distinct damage detection methods (infrared thermography (IRT), neutral axis (NA) method based on optical strain sensor measurements, and terahertz spectroscopy) for the detection of delamination and temperature-induced damage in a simple glass fiber reinforced polymer (GFRP) beamlike structure. The terahertz spectroscopy is a specialized technique suitable for detecting deterioration inside the structure but has limited application for in-service performance monitoring. Similarly, the IRT technique in the active domain may be used for in situ monitoring but not in in-service assessment. Both methods allow the visualization of the internal structure and hence allow identification of the type and the extent of damage. Fiber optic sensors (especially fiber Bragg grating (FBG)) due to their small diameter and no need of calibration can be permanently integrated within the sample and applied for continuous dynamic strain measurements. The measured strain is treated as an input for neutral axis (NA) method, which as a damage-sensitive feature may be used for in-service monitoring but gives absolutely no information about the type and extent of damage. The results for damage detection based on proposed comparative studies give a complete description of the analyzed structure.

An in-process cure monitoring technique based on “guided wave” concept for carbon fiber reinforced polymer (CFRP) composites was developed. Key parameters including physical properties (viscosity and degree of cure) and state transitions (gelation and vitrification) during the cure cycle were clearly identified experimentally from the amplitude and group velocity of guided waves, validated via the semi-empirical cure process modeling software RAVEN . Using the newly developed cure monitoring system, an array of high-temperature piezoelectric transducers acting as an actuator and sensors were employed to excite and sense guided wave signals, in terms of voltage, through unidirectional composite panels fabricated from Hexcel ® IM7/8552 prepreg during cure in an oven. Average normalized peak voltage, which pertains to the wave amplitude, was selected as a metric to describe the guided waves phenomena throughout the entire cure cycle. During the transition from rubbery to glassy state, the group velocity of the guided waves was investigated for connection with degree of cure, T g , and mechanical properties. This work demonstrated the feasibility of in-process cure monitoring and continued progress toward a closed-loop process control to maximize composite part quality and consistency.

Composite materials are becoming ever more popular in an increasing number of applications. This because of their many advantages, amongst others the possibility to create a new material of given characteristics in a quite simple way by changing either the type of matrix, or reinforcement, and/or rearranging the reinforcement in a different way. Of course, once a new material is created, it is necessary to characterize it to verify its suitability for a specific exploitation. In this context, infrared thermography (IRT) represents a viable means since it is noncontact, nonintrusive, and can be used either for nondestructive evaluation to detect manufacturing defects, or fatigue-induced degradation, or else for monitoring the inline response to applied loads. In this work, IRT is used to investigate different types of composite materials, which involve carbon fibers embedded in a thermoset matrix and either glass or jute fibers embedded in a thermoplastic matrix, which may be neat, or modified by the addition of a percentage of a specific compatibilizing agent. IRT is used with a twofold function. First, for nondestructive evaluation, with the lock-in technique, before and after loading to either assure absence of manufacturing defects, or discover the damage caused by the loads. Second, for visualization of thermal effects, which develop when the material is subjected to impact. The obtained results show that it is possible to follow inline what happens to the material (bending, delamination, and eventual failure) under impact and get information, which may be valuable to deepen the complex impact damaging mechanisms of composites.