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.

Timber poles are widely used in electricity transmission and telecommunication sectors throughout the world. The stress wave propagation for the condition assessment of timber poles is identified as a promising non-destructive testing (NDT) technique due to its simplicity and cost-effectiveness compared to other traditional methods. In this paper, a novel damage severity evaluation criterion for timber poles is proposed on the basis of short-time wavelet entropy of the reflected stress waves. The stress waves are generated by transverse impacts close to the ground level of the pole. The reflected stress waves are recorded and processed in the time frequency domain using the discrete wavelet transform. The decomposed signal components using discrete wavelet analysis are used to determine the wavelet entropy. The wavelet entropies of intact and damaged poles are compared to obtain the relative wavelet entropy (RWE) for damage severity estimation. Further, a numerical model for an in situ pole system is developed to simulate the transverse stress wave propagation and to evaluate the capability of the proposed defect severity estimation method. The developed numerical model is validated with experimental data from controlled testing and the data from field tests. The validated numerical model is then used to simulate different defect scenarios. The wavelet entropy is sensitive to the damage severity in timber poles and can be used as an effective tool to evaluate the severity of damages.

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.

Rolling bearings accomplishes a smoother force transmission between relative components of high production volume systems. An impending fault may cause system malfunction and its maturation lead to a catastrophic failure of the system that increases the possibility of unscheduled maintenance or an expensive shutdown. These critical states demand a robust failure diagnosis scheme for bearings. The present paper demonstrates a novel way to develop a dynamic model for the rotor-bearing system using dimensional analysis (DA) considering significant geometric, operating, and thermal parameters of the system. The vibration responses of faulty spherical roller bearings are investigated under various operating conditions for validation of the developed model. Multivariable regression analysis is performed to expose the potential of the approach in the detection of the bearing failure. Results obtained unveil the simple and reliable nature of the dynamic modeling using DA.

Bearing defects are major causes for rotary machine breakdown; hence, the dynamic behavior of bearing is crucial and important. This paper aims to present the dynamic response of bearing due to various localized defects. To study the parametric effect, three factors such as load, speed, and defect size are chosen. The Box–Behnkan method has been used to get trials to plot response surfaces. A bearing test rig has been used for experimentation with high speed, which is capable of high loading to introduce and simulate industrial application environment. Vibration and torque data have been acquired using high-precision sensors and data acquisition system. Fast Fourier transform (FFT) vibration peak and torque peak-to-peak (P2P) have been taken as the output parameter. It is observed that speed has a significant effect on both outputs and affects the bearing performance more than load. Response surfaces show that a change in load has less impact on vibration amplitude, while small variation of speed considerably increases vibration values. On the other hand, both parameters, load and speed, has a strong impact on peak-to-peak torque.

The understanding of strength recovery behavior under a dynamic loading environment provides a guidance for optimizing the design of composite structures for in-service applications. Although established for metals, the quantification of strength recovery in carbon fiber-reinforced viscoelastic composites is still an area under active research. This study aims to understand the effects of fatigue loading rates on the damage behaviors of stress-relaxed carbon fiber-based composites. Hence, the time-dependent strength recovery in woven composites is quantified experimentally using two mutually exclusive approaches under identical fatigue loading environments. In the first approach, the strength recovery is quantified by the dissipated non-linearity in Lamb wave propagation due to the damage state of the composite materials. This is quantified and shown coupled with second- and third-order non-linear parameters. In the second approach, ultrasonic acoustic pressure waves are utilized to quantify the fatigue-induced internal stress and the damage accumulation. A comparison of these two approaches leads to the assessment of strength reduction which is experimentally validated with the remaining strength of the specimens.

This article presents a numerical formulation and the experimental validation of the dynamic interaction between highly nonlinear solitary waves generated along a mono-periodic array of spherical particles and rails in a point contact with the array. A general finite element model of rails was developed and coupled to a discrete particle model able to predict the propagation of the solitary waves along a L-shaped array located perpendicular and in contact with the web of the rail. The models were validated experimentally by testing a 0.9-m long and a 2.4-m long rail segments subjected to compressive load. The scope of the study was the development of a new nondestructive evaluation technique able to estimate the stress in continuous welded rails and eventually to infer the temperature at which the longitudinal stress in the rail is zero. The numerical findings presented in this article demonstrate that certain features, such as the amplitude and time of flight, of the solitary waves are affected by the axial stress. The experimental results validated the numerical predictions and warrant the validation of the nondestructive evaluation system against real rails.

The correlation between the nonlinear acousto-ultrasonic response and the progressive accumulation of fatigue damage is investigated for an additively manufactured aluminum alloy AlSi7Mg and compared with the behavior of a conventional wrought aluminum alloy 6060-T5. A dual transducer and wedge setup is employed to excite a 30-cycle Hann-windowed tone burst at a center frequency of 500 kHz in plate-like specimens that are 7.2 mm thick. This choice of frequency-thickness is designed to excite the symmetric Lamb mode s 1 , which, in turn, generates a second-harmonic s 2 mode in the presence of distributed material nonlinearity. This s 1 -s 2 mode pair satisfies the conditions for internal resonance, thereby leading to a cumulative build-up of amplitude for the second-harmonic s 2 mode with increasing propagation distance. Measurements of a nonlinearity parameter β derived from the second-harmonic amplitude are plotted against propagation distance at various fractions of fatigue life under constant amplitude loading, for three different stress levels corresponding to low-cycle fatigue (LCF), high-cycle fatigue (HCF), and an intermediate case. The results show both qualitative and quantitative differences between LCF and HCF, and between the additively manufactured specimens and the wrought alloy. The potential use of this nonlinearity parameter for monitoring the early stages of fatigue damage accumulation, and hence for predicting the residual fatigue life, is discussed, as well as the potential for quality control of the additive manufacturing (AM) process.

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.

Devices mounted on printed circuit boards (PCBs) are subject to temperature variations resulting from power switching and ambient temperature changes, and may be subject to random dynamic load histories from sources such as vibration. Since solder material is mechanically the most ductile part, fatigue failure may occur in solder joints. Health monitoring for fatigue life under field conditions is a key issue for improving availability and serviceability for maintenance. We have developed a failure precursor detection technology and a fatigue life estimation method for ball grid array (BGA) solder joints, based on a canary circuit. This method estimates fatigue failure life of an actual circuit by detecting failure connections in a canary circuit (a dummy circuit of daisy-chained solder joints). The canary circuit is designed to fail before the actual circuit under the same failure mode by using accelerated reliability testing and inelastic stress simulation. A feasibility study of the failure probability estimation method is conducted by applying the method to a PCB on which a BGA component is mounted. It is confirmed that the fatigue life under a thermal cyclic load can be estimated from a canary circuit, that estimation of fatigue life under a random dynamic load is feasible, and that the estimation results are consistent with results from actual random vibration tests. The proposed method is found to be useful for prognostic health monitoring of solder joint fatigue failure.

This investigation determined the effect of specimen out-of-plane movement on the accuracy of strain measurement made applying two-dimensional (2D) and three-dimensional (3D) measurement approaches using the representative, state-of-the-art digital image correlation (DIC)-based tool ARAMIS . DIC techniques can be used in structural health monitoring (SHM) by measuring structural strains and correlating them to structural damage. This study was motivated by initially undetected damage at low strains in connections of a real-world bridge, whose detection would have prevented its propagation, resulting in lower repair costs. This study builds upon an initial investigation that concluded that out-of-plane specimen movement results in noise in DIC-based strain measurements. The effect of specimen out-of-plane displacement on the accuracy of strain measurements using the 2D and 3D measurement techniques was determined over a range of strain values and specimen out-of-plane displacements. Based upon the results of this study, the 2D system could measure strains as camera focus was being lost, and the effect of the loss of focus became apparent at 1.0 mm beam out-of-plane displacement while measuring strain of the order of magnitude of approximately 0.12%. The corresponding results for the 3D system demonstrate that the beam out-of-plane displacement begins to affect the accuracy of the strain measurements at approximately 0.025% strain for all magnitudes of out-of-plane displacement, and the 3D ARAMIS system can make accurate strain measurements at up to 2.5 mm amplitude at this strain. Finally, based upon the magnitudes of strain and out-of-plane displacement amplitudes that typically occur in real steel bridges, it is advisable to use the 3D system for SHM of stiff structures instead of the 2D system.

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.