ASME J Nondestructive Evaluation. 2019;2(1):010201-010201-2. doi:10.1115/1.4042482.

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Commentary by Dr. Valentin Fuster

Research Papers

ASME J Nondestructive Evaluation. 2018;2(1):011001-011001-12. doi:10.1115/1.4041068.

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 (GaPO4) 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 ((fR)/(logeRd)) was estimated as 0.244 kHz and 7.44 kHz, respectively; the logarithmic sensitivity of GaPO4-PWAS in-plane and thickness modes resonance frequency was estimated as 0.0629 kHz and 2.454 kHz, respectively. Therefore, GaPO4-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.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2018;2(1):011002-011002-11. doi:10.1115/1.4041122.

In recent years, nonlinear vibro-acoustic methods have shown potential to identify defects which are difficult to detect using linear ultrasonic methods. However, these methods come with their own challenges such as frequency dependence, requirement for a high excitation amplitude, and difficulties in distinguishing nonlinearity from defect with nonlinearity from other sources to name a few. This paper aims to study the dependence of nonlinear vibro-acoustic methods for detection of delaminations inside a composite laminate, on the excitation methods and excitation frequencies. It is shown that nonlinear vibro-acoustic methods are highly frequency dependent and commonly used excitation signals which utilize particular values of excitation frequencies might not always lead to a clear distinction between intact and delaminated regions of the specimen. To overcome the frequency dependence, signals based on frequency sweep are used. Interpretation of output response to sweep signals to identify damage is demonstrated using an earlier available approach, and a simpler approach is proposed. It is demonstrated that the damage detection with sweep signal excitations is relatively less dependent on excitation frequency than the conventional excitation methods. The proposed interpretation technique is then applied to specimens with delamination of varying sizes and with delaminations at different depths inside the laminate to demonstrate its effectiveness.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2018;2(1):011003-011003-6. doi:10.1115/1.4041567.

A linear sensor arrangement is presented as a means of measuring the three-dimensional grain angle of wood. The measurement principle is based on an optical characteristic of a wood surface where the microscopic cell structure causes preferential reflection of light perpendicular to the wood grain. This response is notable among the several other techniques for measuring wood grain angle in that it enables identification of diving (out-of-plane) angle in addition to the surface (within-plane) angle. The basic measurement principle has been previously investigated using a circular array of light sensors to measure the spatial distribution of the light reflected from a wood surface. That procedure works reasonably well for surface points near the center of the circle and for modest dive angles. The linear sensor arrangement investigated here is designed to extend measurement functionality so as to be able to measure grain angle at any point along a central line and over a greater range of dive angle. A prototype scanner system is presented together with example experimental results for clear wood samples and for a face knot sample.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2018;2(1):011004-011004-8. doi:10.1115/1.4041717.

Sometimes, nondestructive evaluation (NDE) or structural health monitoring methods commonly used in engineering structures are used for the betterment of consumer goods. A classic example is the use of sensor systems to monitor the pressure and the quality of car tires. In this paper, we present a nondestructive method to characterize tennis balls. The International Tennis Federation (ITF) specifies which characteristics a tennis ball must have in order to be commercialized. One of these characteristics is bounciness and the standardized method to measure it is the rebound test, where a ball is released from 2.54 m onto a smooth rigid surface and, in order to be approved, the ball must bounce within a certain range. This test can be staged by manufacturers and testing authorities but the equipment necessary to perform it is not readily available to the average consumer. In the study presented in this paper, an empirical method based on the propagation of highly nonlinear solitary waves (HNSWs) is proposed to establish whether a given ball conforms the specifications set by the ITF in terms of bounciness and allowed deformation. The experiments conducted in this study aim to discover a correlation between some features of the waves and the values obtained with the rebound test and the compression test in which the deformation of the ball under a known load is measured. The presence of such correlations could represent a viable alternative to establish the conformity of tennis balls. Based on the empirical evidences collected in this study, a possible new standard is suggested.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2019;2(1):011005-011005-9. doi:10.1115/1.4042176.

This research investigates the application of sum-of-squares (SOS) optimization method on finite element model updating through minimization of modal dynamic residuals. The modal dynamic residual formulation usually leads to a nonconvex polynomial optimization problem, the global optimality of which cannot be guaranteed by most off-the-shelf optimization solvers. The SOS optimization method can recast a nonconvex polynomial optimization problem into a convex semidefinite programming (SDP) problem. However, the size of the SDP problem can grow very large, sometimes with hundreds of thousands of variables. To improve the computation efficiency, this study exploits the sparsity in SOS optimization to significantly reduce the size of the SDP problem. A numerical example is provided to validate the proposed method.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2019;2(1):011006-011006-8. doi:10.1115/1.4042259.

Heat-resistant composites, such as ceramic matrix composites and heat-resistant carbon fiber reinforced plastics (CFRPs), are expected to be used for aircraft engine parts. The development of reliable heat-resistant composite materials requires the use of nondestructive test techniques for evaluating the progression of damage during material testing at elevated temperatures. Furthermore, structural health monitoring (SHM) technologies that operate under harsh environments are expected to be realized for monitoring heat-resistant composite structures. To provide potential solutions for the establishment of such technologies, this research developed a heat-resistant ultrasonic sensor based on a regenerated fiber-optic Bragg grating (RFBG). First, we fabricated an RFBG by annealing a normal fiber-optic Bragg gratings (FBG) sensor. Because the RFBG exhibits high heat resistance at temperatures of 1000 °C, the sensor achieved stable ultrasonic detection at an elevated temperature. In addition, we attempted to use a π-phase-shifted FBG (PSFBG) as the seed grating to construct an ultrasonic sensor with enhanced performance. As a result, the regenerated phase-shifted fiber-optic Bragg grating (R(PS)FBG) sensor possessed a very short effective gauge length and achieved a broad frequency response to ultrasonic waves with frequencies greater than 1.5 MHz. The broadband detectability enables the R(PS)FBG sensor to acquire an accurate response to ultrasonic waves. Hence, we believe the regenerated Bragg grating-based ultrasonic sensors can contribute to establishing an effective nondestructive evaluation method for composite materials, thereby enabling a structural health monitoring system for a composite-made structure operating under extreme high-temperature environments.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2019;2(1):011007-011007-8. doi:10.1115/1.4042397.

In this study, we develop a modeling and experimental framework for multiscale identification of the biomechanical properties of the human Achilles tendon (AT). For this purpose, we extend our coarse-grained model of collagen fibrous materials with a chemomechanical model of collagen type I decomposition. High-temperature degradation of molecular chains of collagen in a water environment was simulated using a reactive molecular dynamics (MD) method. The results from MDs simulations allowed us to define the Arrhenius equation for collagen degradation kinetics and calculate the energy of activation together with the frequency factor. Kinetic coefficients obtained from a MD simulations were further used to provide better calibration of the a coarse grained (CG) model of collagen denaturation. For the experimental part of our framework, we performed a uniaxial tensile test of the human AT with additional use of digital image correlation (DIC) for ex vivo strain tracking. Using a different path of strain tracking, we were able to include the inhomogeneity of deformation and, therefore, regional variations in tissue stiffness. Our results, both in modeling and the experimental part of the study, are in line with already existing reports and thus provide an improved approach for multiscale biomechanical and chemomechanical studies of the human AT.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2019;2(1):011008-011008-10. doi:10.1115/1.4042177.

Aiming at characterizing interfacial roughness of thin coatings with unknown sound velocity and thickness, we derive a full time-domain ultrasonic reflection coefficient phase spectrum (URCPS) as a function of interfacial roughness based on the phase screen approximation theory. The constructed URCPS is used to determine the velocity, thickness, and interfacial roughness of specimens through the cross-correlation algorithm. The effect of detection frequency on the roughness measurement is investigated through the finite element method. A series of simulations were implemented on Ni-coating specimens with a thickness of 400 μm and interfacial roughness of 1.9–39.8 μm. Simulation results indicated that the measurement errors of interfacial roughness were less than 10% when the roughness satisfies the relationship of Rq = 1.6–10.0%λ. The measured velocity and thicknesses were in good agreement with those imported in simulation models with less than 9.3% error. Ultrasonic experiments were carried out on two Ni-coating specimens through a flat transducer with an optimized frequency of 15 MHz. Compared with the velocities measured by time-of-flight (TOF) method, the relative errors of inversed velocities were all less than 10%. The inversed thicknesses were in good agreement with those observed by optical microscopy with less than 10.9% and 7.6% error. The averaged interfacial roughness determined by the ultrasonic inversion method was 16.9 μm and 30.7 μm, respectively. The relative errors were 5.1% and 2.0% between ultrasonic and confocal laser scanning microscope (CLSM) method, respectively.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2019;2(1):011009-011009-9. doi:10.1115/1.4042260.

Ultrasonic metal welding is used in the automotive industry for a wide variety of joining applications, including batteries and automotive wire harnessing. During electric vehicle battery pack assembly, the battery cell tab and busbar are ultrasonically welded. Quality inspection of these welds is important to ensure durable packs. A method for inspection of ultrasonic welds is proposed using pulsed infrared (IR) thermography in conjunction with electrical resistance measurements to assess the structural and electrical weld integrity. The heat source distribution (HSD) was calculated to obtain thermal images with high temporal and spatial resolution. All defective welds were readily identifiable using three postprocess analyses: pixel counting, gradient image, and knurl pattern assessment. A positive relationship between pixel count and mechanical strength was observed. The results demonstrate the potential of pulsed thermography for inline inspection to assess weld integrity.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2019;2(1):011010-011010-19. doi:10.1115/1.4042261.

A wireless nondestructive fault detection test for loose or damaged connectors is demonstrated. An architecture known as the conditioned multiclassification of stimulated emissions (CMSE) is pretrained on simulated and empirical radar outputs, and transfer learning is applied to classify connected and disconnected coaxial interconnections. The two main data conditioning methods of this architecture, a statistical signal analysis tool and a convolutional filter bank, are evaluated in order to determine the cost-value proposition of each component. Novel contributions of this technique include the use of two simulation-aided convolutional filter banks to generate a multinetwork ensemble and transfer learning from artificial neural networks trained on two primitive datasets revolving around the electromagnetic phenomena of reflection and filtering. A total of 560 different neural network topologies across four different signal conditioning configurations are considered, with all results compared against the current standard for measurement of cable and connection faults, time-domain reflectometry. Metrics used for comparison are time (training and evaluation), detection (connector engagement at state change detection), and clustering (projection space performance, used as a measure of transfer learning potential). It is determined that the full CMSE architecture performs best, with nearly any neural network topology of this configuration displaying an early detection improvement of 113% and requiring 30% less time to execute an individual classification versus the current standard, all while meeting the most stringent definitions of nondestructive evaluation (NDE).

Commentary by Dr. Valentin Fuster

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