Nondestructive Evaluation Results Research Articles

Understanding the performance of bridge decks through full-scale accelerated testing

Understanding the long-term performance of bridges plays a major role in the selection of appropriate asset-management strategies, which eventually reduce life-cycle costs and extend the service life of a bridge. To understand bridge performance better, the Federal Highway Administration initiated a research project utilising accelerated testing of full-scale bridge superstructure systems subjected to cyclic moving wheel loads and freeze–thaw environmental conditions. As part of the research project, complementary non-destructive evaluation (NDE) techniques were used to assess the performance of a full-scale bridge deck during the curing and loading period. NDE results, shortly after construction, revealed a smaller cover depth of rebars in the middle section of the deck. This has likely created a preferential path for the subsequent deterioration of the deck. It was suggested to use a scaled version of the electrical resistivity (ER) values to improve the consistency between temporal ER measurements of the deck, and it was shown that combining construction information with NDE results can improve the interpretation of results. Overall, the results showed the importance of NDE for quality assurance of new construction and provided a better understating of the long-term bridge deck performance.

A unifying review of NDE models towards optimal decision support

Non-destructive evaluation (NDE) inspections are an integral part of asset integrity management. The relationship between the condition of interest and the quantity measured by NDE is described with probabilistic models such as PoD or ROC curves. These models are used to assess the quality of the information provided by NDE systems, which is affected by factors such as the experience of the inspector, environmental conditions, ease of access, and the precision of the measurement device. In this paper, we review existing probabilistic models of NDE andshow how they are connected within a unifying framework. This frameworkprovides insights into how these models should be learned, calibrated, and applied. We investigate and highlighthow the choice of the model can affect the maintenance decisions taken on the basis of NDE results. In addition, we analyze the impact of experimental design on the performance of a given NDE system in a decision-making context.

Nondestructive Evaluation of Electroplating-Induced Hydrogen Embrittlement in Cadmium-Coated High-Strength Steel Using Ultrasonic Surface Waves

Development of a nondestructive evaluation (NDE) method to detect nascent hydrogen embrittlement (HE) in electroplated high-strength steel parts is becoming important for the aerospace industry. This research investigates the feasibility of surface acoustic waves (SAWs) measurements to distinguish between cadmium (Cd) plated SAE 4340 steel samples with low and high HE susceptibilities. SAWs were generated with a 10 MHz piezoelectric transducer and detected by line scans via a laser Doppler vibrometer setup. Using signal processing algorithms in MATLAB, SAW velocities as well as attenuation coefficients were estimated. Depth profiles of steel hardness near coatings were also evaluated using Vickers microindentation tests. Average steel hardness in not-baked samples was slightly increased. Cd coatings were characterized by laser and optical microscopy methods. Small variations found in thickness and surface roughness of the Cd coatings among the samples did not significantly affect the NDE results. On average, samples in the not-baked condition (high HE risk) exhibited lower SAW attenuation coefficients compared to immediately baked and late-baked conditions (low HE risk). However, it was not possible to distinguish between the manufacturing conditions of individual samples due to overlaps in attenuation measurement results. SAW velocities as estimated by the cross-correlation method were found to be not sensitive to manufacturing conditions.

Fusion and Visualization of Bridge Deck Nondestructive Evaluation Data via Machine Learning

To maintain infrastructure safety and integrity, nondestructive evaluation (NDE) technologies are often used for detection of subsurface defects and for holistic condition assessment of structures. While the rapid advances in data collection and the diversity of available sensing technologies provide new opportunities, the ability to efficiently process data and combine heterogeneous data sources to make robust decisions remains a challenge. Heterogeneous NDE measurements often conflict with one another and methods to visualize integrated results are often developed ad hoc. In this work, we present a framework to support fusion of multiple NDE techniques in order to improve both detection and quantification accuracy while also improving the visualization of NDE results. For data sources with waveform representations, the discrete wavelet transform (DWT) is used to extract salient features and facilitate fusion with scalar-valued NDE measurements. The description of a signal in terms of its salient features using a wavelet transform allows for capturing the significance of the original data, while suppressing measurement noise. The complete set of measurements is then fused using nonparametric machine learning so as to relax the need for Bayesian assumptions regarding statistical distributions. A novel visualization schema based on classifier confidence intervals is then employed to support holistic visualization and decision making. To validate the capabilities of the proposed methodology, an experimental prototype system was created and tested from NDE measurements of laboratory-scale bridge decks at Turner-Fairbank highway research center (TFHRC). The laboratory decks exhibit various types of artificial defects and several non-destructive tests have already been carried out by research center technicians to characterize the mechanical properties of the materials and the existing damages. The behaviors of several different data fusion approaches are compared here. Based on the presented analyses, it is demonstrated that fusion via support vector machines provided the most robust and consistent data fusion and defect detection capabilities.

Application of advanced volumetric non-destructive evaluation methods for the analysis of friction welded tube-to-tube plates using an external tool

Friction welding of tube-to-tube plate using external tool (FWTPET) is a novel variant of friction welding process for joining tubes to tube plates. This process has the capability of producing leak proof joints between similar or dissimilar materials. Being a solid state welding process FWTPET has a significant advantage that it is free from fusion related defects usually seen in conventional tube to tube plate joining alternatives which use fusion welding methods. Hence this process offers a strong potential for applications in several sectors including automotive, marine, aerospace etc. However, in order to establish FWTPET for industrial applications it is required to develop suitable Non-Destructive Evaluation (NDE) methods for detection and characterization of the defects. In this study, the defects in FWTPET joints welded between 6 mm thick AA 6061 plate and 2 mm thick AA 1060 tube under various conditions are investigated using two advanced volumetric NDE methods, namely Digital Radiography (DR) and Phased Array Ultrasonic Testing (PAUT). This study shows the capability of these volumetric NDE methods to assess the quality of FWTPET joints, and to reveal significant information about the conditions which lead to defect formation. This work also brings out the effect of the parameters of FWTPET using theoretical model and NDE results, and in turn suggests the parametric combinations which could offer defect free joints.

Numerical and Experimental Studies of Porosity on Aerospace Grade Advanced Composites

Porosity is one of the innate factors and may not be completely eliminated during the manufacturing process of composite parts of aircraft, while produced in large numbers. The effect of porosity has been studied by developing different levels of porosity laminates, evolving a cure system called as Diverse Cure System (DCS) which occur during production. Further assessment of porosity levels by Non Destructive Evaluation (NDE) methods, microscopic studies and numerical model have been achieved in a Carbon Fiber Epoxy resin system laminates. The porosity effects are evaluated in terms of Non Destructive Test attenuation coefficient. Correlations are obtained on the different levels for porosity laminates of two different thicknesses. Assessment of porosity effect is verified with numerical analysis and categorized as good, medium and high porous based on the studies. Classification of porosity is based on NDE results and numerical studies.

Comparison of Dynamic Young’s Modulus of Thin Concrete Disks to Stress Wave–Based Nondestructive Evaluation Findings

Stress wave–based nondestructive evaluation (NDE) techniques are frequently used for in-situ evaluation of concrete. Stress wave velocity in a material is related to Young’s modulus of elasticity. Cores for in-situ compressive strength are subject to a minimum length-to-diameter ratio requirement that enforce large specimen sizes. Thin circular disks sawn from cylinders or cores are widely used in measurement of chloride or air permeability of concrete. While these methods provide useful information on concrete properties with depth, the capability of measuring changes in mechanical properties such as elastic Young’s modulus in small depth increments is of value to both researchers and consulting engineers conducting condition assessment or NDE, particularly when damage gradients exist. Changes in properties over relatively small depths may be undetected otherwise due to limitations of test method, equipment, or imposed specimen size. This study presents applications of Young’s modulus of thin concrete disks to structural assessment projects involving damage and damage gradients. In-situ nondestructive ultrasonic pulse velocity (UPV) testing was used in identification of affected areas. Young’s modulus of thin concrete disks was used in interpretation of the NDE results and provided an improved understanding of the extent of damage that was indicated using NDE. Two different case studies are discussed: exposure to fire and exposure to thermal shock and cryogenic temperatures. The use of thin disks enabled determination of mechanical properties of relatively thin layers of concrete and, therefore, provided a means to quantitatively assess the extent of damage gradients. Confirmation of NDE results using modulus data and analytical modeling using the relationship between Young’s modulus and pulse velocity provided improved understanding of NDE findings reducing uncertainty in engineering analysis and improving repair recommendations.

High-Tcplanar SQUID gradiometer for eddy current non-destructive evaluation

This paper reports the fabrication and test of a high-T-c SQUID planar gradiometer which is patterned from YBCO thin film deposited on a SrTiO3 bicrystal substrate. The measurement of noise spectrum at 77K shows that the white noise at 200 Hz is about 1 x 10(-4)Phi(0)/root Hz. The minimal magnetic gradient is measured and the results suggest that the minimal magnetic gradient is 94 pT/m. The planar gradiometer is used in non-destructive evaluation (NDE) experiments to detect the artifacts in conducting aluminium plates by performing eddy current testing in an unshielded environment. The effect of the exciting coil dimension on the NDE results is investigated. By mapping out the induced field distribution, flaws about 10mm below the plate surface can be clearly identified.

Embedded Non-destructive Evaluation for Structural Health Monitoring, Damage Detection, and Failure Prevention

In this paper we review the state of the art in an emerging new technology: embedded ultrasonic non-destructive evaluation (NDE). Embedded ultrasonic NDE permits active structural health monitoring, i.e. the on-demand interrogation of the structure to determine its current state of structural health. The enabling element of embedded ultrasonic NDE is the piezoelectric wafer active sensor (PWAS). We begin by reviewing the guided wave theory in plate, tube, and shell structures, with special attention to Lamb waves. The mechanisms of Lamb wave excitation and detection with embeddable PWAS transducers is presented. It is shown analytically and verified experimentally that Lamb wave mode tuning can be achieved by the judicious combination of PWAS dimensions, frequency value, and Lamb mode characteristics. Subsequently, we address in turn the use of pitch-catch, pulse-echo, and phased array ultrasonic methods for Lambwave damage detection. In each case, the conventional ultrasonic NDE results are contrasted with embedded NDE results. Detection of cracks, disbonds, delaminations, and diffuse damage in metallic and composite structures are exemplified. Other techniques, such as the time reversal method and the migration technique, are also presented. The paper ends with conclusions and suggestions for further work.

Accurate Crack Sizing of Land-Based Gas Turbine Blades by Eddy-Current Techniques

Japanese utilities are increasing their use of gas turbines for generation of electricity. In order to maintain competitive electricity rates, the utilities need to find ways to reduce maintenance costs. There is a need to develop nondestructive evaluation (NDE) methods that can be applied to gas turbine blades in situ during periodic turbine maintenance, and to be able to use the NDE results and operating history to predict future degradation. This paper describes the development of methods for detecting cracks right under MCrAlY overlay coatings, and entimating crack depths from the results of eddy current testing. For these purposes, an eddy-current measurement system has been developed, and Ni-base superalloy specimens with the CoCrAlY coatings have been prepared for the eddy-current measurements. Notches simulating the cracks right under the coatings can be detected, discriminating from surface-breaking notches in the phase angles of their eddy-current responses. The proposed flaw-sizing approach can provide more accurately the estimated depths of the cracks, irrespective of their lengths.