Search Results (46)

This study comprehensively compares the performance of two non-destructive testing (NDT) techniques—active thermography (AT) and digital shearography (DS)—for identifying various damage types in composite structures. Three distinct composite specimens were inspected: a carbon-fiber-reinforced polymer (CFRP) plate with flat-bottom holes, an aluminum honeycomb core sandwich plate with a circular skin-core disbond, and a CFRP plate with two low-energy impacts damage. The research highlights the significant role of post-processing methods in enhancing damage detectability. For AT, algorithms such as fast Fourier transform (FFT) for temperature phase extraction and principal component thermography (PCT) for identifying significant temperature components were employed, generally making anomalies brighter and easier to locate and size. For DS, a novel band-pass filtering approach applied to phase maps, followed by summing the filtered maps, remarkably improved the visualization and precision of damage-induced anomalies by suppressing background noise. Qualitative image-based comparisons revealed that DS consistently demonstrated superior performance. The sum of DS filtered phase maps provided more detailed and precise information regarding damage location and size compared to both pulsed thermography (PT) and lock-in thermography (LT) temperature phase and amplitude. Notably, DS effectively identified shallow flat-bottom holes and subtle imperfections that AT struggled to clearly resolve, and it provided a more comprehensive representation of the impacts damage location and extent. This enhanced capability of DS is attributed to the novel phase map filtering approach, which significantly improves damage identification compared to the thermogram post-processing methods used for AT. Full article

Many pipelines are buried and operated underground in nuclear and chemical plants. Since these pipelines are welded on-site and subsequently coated, ensuring the integrity of these coatings is crucial. Over time, rubber coatings can disbond due to factors such as soil pressure, creating gaps that lead to defects and may expose weld joints to electrolytes locally. Thus, effective detection of coating defects in buried pipelines is crucial for maintaining pipelines’ structural integrity and preventing corrosion. This study examines the shielding effect of rubber disbond on DCVG signal magnitude using the Direct Current Voltage Gradient (DCVG) technique. Simulations conducted with COMSOL Multiphysics^®, considering variables such as soil resistivity (1–19 kΩ·cm), defect exposure size (100 cm² and 1 cm²), detection electrode distance, and applied voltage, show that the DCVG signal generally increases as soil resistivity decreases and as defect size and electrode spacing increase. This is due to a stronger current distribution resulting from the higher applied voltages. However, shielded defects consistently produce lower DCVG signals than unshielded ones, a phenomenon that stems from the insulating shielding layer around the defect, which restricts the flow of the inspection current. These findings highlight how the shielding layer significantly influences the distribution of the inspection current. Full article

This study presents a novel approach to evaluate the galvanic corrosion risk of mild steel coated with graphene-embedded epoxy coatings. The potential for graphene platelets to promote anodic dissolution of the underlying steel substrate via galvanic corrosion mechanisms was systematically assessed through the accelerated alternating current-direct current-alternating current (AC-DC-AC) technique and cathodic disbondment testing. The possible risk of displacing cathodic reactions from the coating–steel interface to the dispersed graphene platelets within the epoxy matrix was investigated by evaluating the degradation trend of the graphene-containing coating under the AC-DC-AC test. The degradation behaviour of both pure epoxy and graphene-embedded epoxy coatings during accelerated aging was characterized using electrochemical impedance spectroscopy (EIS) measurements. The finding highlighted the negligible catalytic effect of incorporated graphene platelets on the anodic dissolution of steel substrate. On the other hand, as an inert filler, graphene platelets contributed to the enhancement of the structural integrity of the epoxy matrix during the AC-DC-AC test and natural immersion in NaCl 3.5 wt % solution by enhancing the barrier performance of the coating. Despite their spectacular barrier performance, damaged graphene-containing coatings performed inferiorly against corrosion-induced delamination compared to pure epoxy. Samples underwent the cathodic disbondment test to eliminate the effect of substrate anodic dissolution from corrosion-induced delamination. The accelerated delamination of graphene-embedded epoxy coatings was attributed to the destructive impact of graphene platelets on the interfacial adhesion of the epoxy matrix to the steel substrate. Full article

Adhesively bonded joints are crucial to the aeronautical industry, contributing to weight reduction and more sustainable flights. However, certifying these joints is still a topic of debate due to the lack of reliable inspection methods to determine their strength. Additionally, prediction models for crack growth under fatigue loading are still being developed. This manuscript describes the implementation and validation of a cohesive zone model to evaluate high cycle fatigue disbonding under mode I opening. This model was integrated into the commercial finite element analysis software Abaqus using user-defined subroutines, specifically a UMAT. The experimental data from the literature on the effect of adhesive thickness during fatigue loading of a double cantilever beam were used for model validation. Three modelling techniques were explored, including substitution of the adhesive with the cohesive zone (2D and 3D) and the addition of a cohesive layer in the mid-plane of the adhesive (2D only). The results have confirmed that the model is effective in accurately predicting fatigue crack growth in all the simulated cases. Additionally, it has been shown that the adhesive’s thickness has an impact on the simulation results, particularly with thicker bondlines and low strain energy release rates. Full article

The volume fractions of martensite and ferrite in dual-phase steel affect its strength and plasticity. In this study, the effect of heat treatment on the structure morphology and volume fractions of martensitic and ferrite was studied in rare earth, micro-alloyed dual-phase steel, and the strain-hardening behaviour of the experimental steel under various process conditions was determined. The results show that a uniform structure with an alternating distribution of ferrite and martensite could be obtained by complete quenching before critical annealing, and the martensitic phase content increased from 60% to 93% with a rise in annealing temperature. With the growth in the martensitic phase content, the strength of dual-phase (DP) steel gradually increased, and elongation gradually decreased. However, the strength–plasticity product remained at approximately 17 GPa∙%, showing good comprehensive mechanical properties, and the mechanical properties were better at 780 and 820 °C annealing temperatures. When the martensite content was higher, the strain-hardening ability of the DP steel was stronger. The results show that the failure mode of the DP steel was a typical ductile fracture, and only a small amount of cleavage pattern was observed in the samples annealed at 840 °C. No obvious interfacial disbonding was seen in the tensile fracture, and only a few cracks formed. By optimizing the heat treatment process, the microstructural uniformity was improved, and the ferrite phase was strengthened to some extent, which better coordinated the deformation of ferrite and martensite, thereby delaying fracture. The modification effect of rare earth elements on inclusions in the DP steel was obvious. Full article

Adhesively bonded joints are essential in the aeronautical industry, offering benefits such as weight reduction and enhanced sustainability. However, certifying these joints is challenging due to unreliable methods for assessing their strength and the development of predictive models for fatigue-driven disbonding remains an ongoing effort. This manuscript presents the implementation and validation of a cohesive zone model for studying high-cycle fatigue disbonding under Mode I and Mixed-Mode loading. The model was integrated into the commercial finite element analysis software Abaqus using user-defined material subroutine (UMAT). Two modelling approaches were investigated: one replacing the adhesive with a cohesive layer, and the other incorporating a cohesive layer at the adhesive’s mid-plane while modelling its entire thickness, using both 2D and 3D techniques. Validation was conducted against experimental data from the literature that examined the influence of adhesive thickness on fatigue behaviour in DCB and CLS tests. The findings of this study confirm that the model accurately predicts fatigue disbonding across all cases examined. Additionally, the analysis reveals that modelling adhesive thickness plays a critical role in the simulation’s outcomes. Variations in adhesive thickness can significantly alter the crack growth behaviour, highlighting the importance of carefully considering this parameter in future assessments and applications. Full article

Adhesive joining has the severe limitation that damages/defects developed in the bondline are difficult to assess. Conventional non-destructive examination (NDE) techniques are adequate to reveal disbonding defects in fabrication and delamination near the end of service life but are not helpful in detecting and monitoring in-service degradation of the joint. Several techniques suitable for long-term joint integrity monitoring are proposed. Fiber Bragg grating (FBG) sensors embedded in the joint are one of the promising candidates. It has the advantages of being close to the damage and immune to environmental attack and electromagnetic interference. Damage and disbonding inside an adhesive joint will give rise to a non-uniform strain field that may bring about peak splitting and chirping of the FBG spectrum. It is shown that the evolution of the full spectral responses can closely reveal the development of damages inside the adhesive joints during tensile and fatigue failures. However, recording and comparing the successive full spectra in the course of damage is tedious and can be subjective. An energy modulation interrogation technique is proposed using a pair of tunable optical filters. Changes in the full FBG spectral responses are modulated by the filters and converted into a conveniently measurable voltage output by photodiodes. Monitoring damage development can then be easily automated, and the technique is well-suited for practical applications. Filter spectrum width of 5 nm and initial overlap with the FBG spectrum to give 40% of the maximum output voltage is found to be optimal for measurement. The technique is tested on embedded FBGs from different adhesive lap-joint specimens and successfully reflected the severity of changes in the full spectral shapes during the course of tensile failure. Moreover, the trends in these PD outputs corroborate with the V value previously proposed to describe the qualitative change in FBG spectral shape. Full article

An experimental investigation of interlaminar toughness for post-cured through-thickness reinforcement (PTTR) skin–stringer sub-element is presented. The improvement in the crack resistance capability of skin–stringer samples was shown through experimental testing and finite element analysis (FEA) modeling. The performance of PTTR was evaluated on a pristine and initial-disbond of the skin–stringer specimen. A macro-scale pin–spring modeling approach was employed in FEA using a non-linear spring to capture the pin failure under the mixed-mode load. The experimental results showed a 15.5% and 20.9% increase in strength for the pristine-PTTR and initial-disbond PTTR specimens, respectively. The modeling approach accurately represents the overall structural response of PTTR laminate, including stiffness, adhesive strength, crack extension scenarios and progressive pin failure modes. This modeling approach can be beneficial for designing damage-tolerant structures by exploring various PTTR arrangements for achieving improved structural responses. Full article

With the advent of bonded composites in today’s aircraft, there is a need to verify the structural integrity of the bonded joints that comprise their structure. To produce adequate joint integrity, strict process control is required during bonding operations. The latest non-destructive joint inspection techniques cannot quantify the strength of the bond and only indicate the presence of disbonds or delaminations. Expensive and timely proof-load testing of the joints is required to demonstrate structural performance. This work focuses on experimentally evaluating joint-health monitoring with piezoelectric sensors exposed to repeated loadings until failure. Single-lap-shear composite joints are structurally tested while using sensor electromechanical impedance response as a health indicator. Based on these experiments, validation of this novel method is achieved through detailed evaluation of the sensor impedance response characteristics during loading, which enable initial and prognostic joint health assessments. The experimental results indicate that the embedded piezoelectric sensors are able to measure the sensor impedance radial and thickness resonance response changes prior to joint failure, without sacrificing the joints’ structural performance. Full article

This paper deals with joining dissimilar materials using thermal drilling technology as well as the combination of thermal drilling and adhesive bonding. The base materials for the experimental work were deep-drawn low-carbon steel DC04, HSLA steel TL 1550-220 + Z, and structural aluminum alloy EN AW-6082 T6 (AlSi1MgMn). The geometry of the formed joints was tested metallographically as the load-bearing shear capacity under the tensile shear test of single-lapped joints and the resistance of the joints against corrosion-induced disbonding in a climate chamber. The energy dissipated by the joints up to fracture was calculated from the load–displacement curves. The hybrid joints were compared with the bonded joints with the same overlap area in terms of the load-bearing capacity and energy dissipated at joint failure. The hybrid joints formed by thermal drilling and adhesive bonding with a rubber-based adhesive confirmed the synergistic effect—the adhesive provides the high load-bearing capacity of the joint, and the bushing formed by thermal drilling increases the dissipated energy of the joint at failure. The exposure of the joints in the climatic chamber did not cause a relevant reduction in the characteristics of the joints. Full article

Welded lap joints play a vital role in a wide range of engineering structures such as pipelines, storage tanks, pressure vessels, and ship hulls. This study aims to investigate the propagation of ultrasonic guided waves in steel welded lap joints for the baseline-free inspection of joint defects using the mode conversion of Lamb waves. The finite element method was used to simulate a single lap joint with common defects such as corrosion and disbonding. To identify the propagating wave modes, a wavenumber–frequency analysis was conducted using the 2D fast Fourier transform. The power loss of the transmitted modes was also determined to identify damage in the lap joints. The results indicate that the A0 incident in pristine conditions experienced significant transmission losses of about 9.5 dB compared to an attenuation of 2.8 dB for the S0 incident. The presence of corrosion was found to reduce these transmission losses by more than 28%. In contrast, introducing disbonding in the lap joint increased the transmission loss of the S0 incident, while a negligible loss was observed for the A0 incident. The mode-converted S0 (MC-S) and mode-converted A0 (MC-A0) incidents were found to exhibit a unique sensitivity to the presence of corrosion and disbonding. The results indicate that MC-S0 and MC-A0 as well as Lamb mode incidents interact differently in terms of corrosion and disbonding, providing a means to identify damage without relying on baseline signals. Full article

Marine propellers work under severe service conditions, where they commonly suffer from mechanical, electrochemical, and biological corrosion damage. The major mechanical corrosion involves cavitation, erosion, and impingement corrosion. On the other hand, the major electrochemical corrosion involves galvanic corrosion and electrolysis. As a result, consideration of both desired mechanical and electrochemical properties is necessary when designing a marine propeller coating. In this study, a PVB (polyvinyl butyral) and an epoxy coating were formulated without corrosion inhibitors to investigate the desired coating properties for marine propeller applications. The two coatings were compared with a Cr-containing commercial marine propeller coating to investigate the advantages and disadvantages of using PVB and epoxy for marine propeller coatings. It was found that it is desirable for marine propeller coatings to be flexible to avoid cracking and flaking; to be able to withstand high pH in order to resist cathodic disbondment (electrolysis); to have adequate primer–substrate adhesion; and, ideally, to be able to self-heal when the coating is damaged (cavitation). It was found that the PVB-ZO coating has more desirable properties, and introducing self-healing properties could be one of the options for further optimization in the future. Full article

This paper presents a baseline-free damage imaging technique using a parallel array of piezoelectric sensors and a control board that facilitates custom combinations of sensor selection. This technique incorporates an imaging algorithm that uses parallel beams for generation and reception of ultrasonic guided waves in a pitch–catch configuration. A baseline-free reconstruction algorithm for probabilistic inspection of defects (RAPID) algorithm is adopted. The proposed RAPID method replaces the conventional approach of using signal difference coefficients with the maximum signal envelope as a damage index, ensuring independence from baseline data. Additionally, conversely to the conventional RAPID algorithm which uses all possible sensor combinations, an innovative selection of combinations is proposed to mitigate attenuation effects. The proposed method is designed for the inspection of lap joints. Experimental measurements were carried out on a composite lap joint, which featured two dissimilar-sized disbonds positioned at the lap joint’s borderline. A 2D correlation coefficient was used to quantitatively determine the similarity between the obtained images and a reference image with correct defect shapes and locations. The results demonstrate the effectiveness of the proposed damage imaging method in detecting both defects. Additionally, parametric studies were conducted to illustrate how various parameters influence the accuracy of the obtained imaging results. Full article

Complex engineering models are typically computationally demanding and defined by a high-dimensional parameter space challenging the comprehensive exploration of parameter effects and design optimization. To overcome this curse of dimensionality and to minimize computational resource requirements, this research demonstrates a user-friendly approach to formulating a reduced-dimension surrogate model that represents a high-dimensional, high-fidelity source model. This approach was developed specifically for a non-expert using commercially available tools. In this approach, the complex physical behavior of the high-fidelity source model is separated into individual, interacting physical behaviors. A separate reduced-dimension surrogate model is created for each behavior and then all are summed to formulate the reduced-dimension surrogate model representing the source model. In addition to a substantial reduction in computational resources and comparable accuracy, this method also provides a characterization of each individual behavior providing additional insight into the source model behavior. The approach encompasses experimental testing, finite element analysis, surrogate modeling, and sensitivity analysis and is demonstrated by formulating a reduced-dimension surrogate model for the damage tolerance of an aluminum plate reinforced with a co-cured bonded E-glass/epoxy composite laminate under four-point bending. It is concluded that this problem is difficult to characterize and breaking the problem into interacting mechanisms leads to improved information on influential parameters and efficient reduced-dimension surrogate modeling. The disbond damage at the interface between the resin and metal proved the most difficult mechanism for reduced-dimension surrogate modeling as it is only engaged in a small subspace of the full parameter space. A binary function was successful in engaging this damage mechanism when applicable based on the values of the most influential parameters. Full article

Structural health monitoring is a popular inspection method that utilizes acoustic emission (AE) signals for fault detection in engineering infrastructures. Diagnosis based on the propagation of AE signals along any surface material offers an attractive solution for fault identification. However, the classification of AE signals originating from failure events, especially coating failure (coating disbondment), is a challenging task given the AE signature of each material. Thus, different experimental settings and analyses of AE signals are required to classify the various types of coating failures, and they are time-consuming and expensive. Hence, to address these issues, we utilized machine learning (ML) classification models in this work to evaluate epoxy-based-protective-coating disbondment based on the AE principle. A coating disbondment experiment consisting of coated carbon steel test panels for the collection of AE signals was implemented. The obtained AE signals were then processed to construct the final dataset to train various state-of-the-art ML classification models to divide the failure severity of coating disbondment into three classes. Consequently, methods for the extraction of useful features, the handling of data imbalance, and a reduction in the bias of ML models were also effectively utilized in this study. Evaluations of state-of-the-art ML classification models on the AE signal dataset in terms of standard metrics revealed that the decision forest classification model outperformed the other state-of-the-art models, with accuracy, precision, recall, and F1 score values of 99.48%, 98.76%, 97.58%, and 98.17%, respectively. These results demonstrate the effectiveness of utilizing ML classification models for the failure severity prediction of protective-coating defects via AE signals. Full article