This work presents a first investigation of the small punch test (SPT) as a possible method to identify material parameters for shape memory alloy (SMA) behavior. In comparison to more common tests, the SPT has advantages in setup simplicity, small sample size, uncomplicated shape, and the possibility of specimen clamping, while offering controlled multi axial loading. Different loading scenarios are described and executed. The parameters of an established SMA model are subsequently (partially) calibrated from the measured SPT force-deflection curves. For some loading regimes, the effective response curves suggest the occurrence of damage events. To investigate the underlying microscale failure mechanisms, a first SEM study was conducted. These first results underline that the SPT is a promising efficient and inexpensive characterization method to support SMA constitutive model development under multiaxial loading — including aspects of damage, fracture and fatigue.

Shape memory alloys (SMAs) are unique materials capable of undergoing a thermo-mechanically induced, reversible, crystallographic phase transformation. As SMAs are utilized across a variety of applications, it is necessary to understand the internal changes that occur throughout the lifetime of SMA components. One of the key limitations to the lifetime of a SMA component is the response of SMAs to fatigue. SMAs are subject to two kinds of fatigue, namely structural fatigue due to cyclic mechanical loading which is similar to high cycle fatigue, and functional fatigue due to cyclic phase transformation which typical is limited to the low cycle fatigue regime. In cases where functional fatigue is due to thermally induced phase transformation in contrast to being mechanically induced, this form of fatigue can be further defined as actuation fatigue. Utilizing X-ray computed microtomography, it is shown that during actuation fatigue, internal damage such as cracks or voids, evolves in a non-linear manner. A function is generated to capture this non-linear internal damage evolution and introduced into a SMA constitutive model. Finally, it is shown how the modified SMA constitutive model responds and the ability of the model to predict actuation fatigue lifetime is demonstrated.

Bridge management and maintenance work is an important part for the assessment the health state of bridge. The conventional management and maintenance work mainly relied on experienced engineering staffs by visual inspection and filling in survey forms. However, the human-based visual inspection is a difficult and time-consuming task and its detection results significantly rely on subjective judgement of human inspectors. To address the drawbacks of human-based visual inspection method, this paper proposes an image-based comprehensive maintenance and inspection method for bridges using deep learning. To classify the types of bridges, a convolutional neural network (CNN) classifier established by fine-turning the AlexNet is trained, validated and tested using 3832 images with three types of bridges (arch, suspension and cable-stayed bridge). For the recognition of bridge components (tower and deck of bridges), a Faster Region-based Convolutional Neural Network (Faster R-CNN) based on modified ZF-net is trained, validated and tested by utilizing 600 bridge images. To implement the strategy of a sliding window technique for the crack detection, another CNN from fine-turning the GoogLeNet is trained, validated and tested by employing a databank with cropping 1455 raw concrete images into 60000 intact and cracked images. The performance of the trained CNNs and Faster R-CNN is tested on some new images which are not used for training and validation processes. The test results substantiate the proposed method can indeed recognize the types and components and detect cracks for a bridges.

An identification module is designed and studied to detect and evaluate the cracks at the welding joint area using a new smart coating sensor and entropy measurement. A new piezoelectric composite coating is applied at a welding joint to possibly charge the wireless data transmission module as an energy harvester. It also sends warning and dynamic signals for crack evaluation when the crack damage occurs. More specifically, entropy calculation is introduced to quantify the weak perturbations, which is caused by the material nonlinearity and crack breathing at the crack tip and hidden in the signal. In this paper, a finite element model (FEM) of a welded beam experiencing dynamic base motion is established as an example. The effects of material nonlinearity and crack breathing on structural dynamics response are simulated by creating nonlinear material property around the crack area and contact pair of crack walls, respectively. After obtaining the time domain vibration signal, crack severity is quantified using Sample Entropy. It is concluded that, even at very early stages of 5% of the beam thickness for the crack depth, the entropy variation is significant for a damaged beam compared with the healthy one.

Fracture behavior in nickel-titanium (NiTi) shape memory alloys (SMAs) subjected to mode-I, isothermal loading is studied using finite element analysis (FEA). Compact tension (CT) SMA specimen is modeled in Abaqus finite element suite and crack growth under displacement boundary condition is investigated for plane strain and plane stress conditions. Parameters for the SMA material constitutive law implemented in the finite element setup are acquired from characterization tests conducted on near-equiatomic NiTi SMA. Virtual crack closure technique (VCCT) is implemented where crack is assumed to extend when the energy release rate at the crack-tip becomes equal to the experimentally obtained material-specific critical value. Load-displacement curves and mechanical fields near the crack-tip in plane strain and plane stress cases are examined. Moreover, a discussion with respect to the crack resistance R-curves calculated using the load-displacement response for plane strain and plane stress conditions is presented.

This paper presents the development process of an electrically insulating and liquid-impermeable coating for piezoelectric actuators. Against the background of flow investigations of an adaptive airfoil in a water tunnel the adaptive lip including PZT-ceramics for the active lip deformation must be insulated and sealed up against the ingress of moisture. Due to high electric field strength of 2 kV/mm between electrodes of multilayer actuators any ingress of moisture would lead to a reduction of the dielectric strength and may cause a short circuit. In order to prevent failure of the adaptive lip the electrical connections of the actuators have to be insulated by a waterproof coating. A service life of at least 10 7 load cycles at a frequency of 100 Hz is required for the actuators. Therefore the coating should be as ductile as possible otherwise it could crack and water could diffuse into the actuators. That is why the yield strength of the coating has to be higher than of the actuators, which is 0.3 %. For the investigation of the waterproofness several samples are coated with different materials in various processes. First the actuators are moulded in epoxy resin and then a diffusion-resistant PVF-foil is applied. After a screening of different materials, an additional coating with a two-component tar-epoxy resin in combination with a gold coating applied by a PVD process seems to be the most suitable process. Another promising waterproof coating is the atomic layer deposition (ALD). It is a slightly changed chemical vapor deposition (CVD) and referring to the studies of Abdulagatov et al. an ALD of aluminum oxide (Al 2 O 3 ) and titanium dioxide (TiO 2 ) can slow down the corrosion of static copper specimens in water for ∼80 days [1]. Through a redrying procedure during test intermissions an increased underwater service life of the piezoelectric actuators is achieved.

Self-healing materials have emerged as an alternative solution to the repair of damage in fibre-reinforced composites. Recent developments have largely focused on a vascular approach, due to the ability to transport healing agents over long distances and continually replenish from an external source. However fracture of the vascular network is required to enable the healing agents to infiltrate the crack plane, ceasing its primary function in transporting fluid and preventing the repair of any further damage events. Here we present a novel approach to vascular self-healing through the development and integration of 3D printed, porous, thermoplastic networks into a thermoset matrix. This concept exploits the inherently low surface chemistry of thermoplastic materials, which results in adhesive failure between the thermoplastic network and thermoset matrix on arrival of a propagating crack, thus exposing the radial pores of the network and allowing the healing agents to flow into the damage site. We investigate the potential of two additive manufacturing techniques, fused deposition modeling (FDM) and stereolithography, to fabricate free-standing, self-healing networks. Furthermore, we assess the interaction of a crack with branched network structures under static indentation in order to establish the feasibility of additive manufacture for multi-dimensional 3D printed self-healing networks.

Self-healing material structures with the inherent capability to mend damage will lead to a paradigm shift in design as fracture may no longer constitute a failure. Generally, there are two techniques of self-healing that operate at different scales, require different approaches and often are dealt with separately; geometric restoration and crack filling/bonding. Geometric restoration uses shape memory materials that can mechanically close fractures after they occur. Crack filling and bonding fills and chemically bonds fractured parts in place. Materials capable of recovering from complete fractures, that have propagated across the entire component, have typically taken a sparse fiber composite form with a structural matrix encapsulating shape memory fibers. This form of self-healing material has demonstrated the ability recover original bulk geometry. However, lacking bonding, the healed structures have not had the ability to resist subsequent externally applied loads without re-opening the crack. A new approach of pre-straining the shape memory fibers before curing them in a matrix in the pre-strained state is presented in this paper with basic theory and experimental results. Pre-straining the shape memory fibers before casting them in the matrix causes them to undergo constrained recovery upon activation. Thus, the samples create closing loads across the crack which are capable of withstanding external loads without re-opening.

Damage nucleation and growth can be complex in hybrid structures composed of layers of metal and laminated composites. Presently there are limited reliable damage growth analytical and empirical methods to evaluate the bond integrity of such structures and to quantify the state of bonding in such joints. Depending on the geometry and accessibility of hybrid joints, ultrasonic nondestructive testing (NDT) techniques are available for inspection of these structures. However there are some limitations for the usage of typical bulk or guided waves to quantify the integrity of bondline in hybrid structures. This work suggests the use of specific forms of ultrasonic guided waves that propagate along the bondline of these hybrid structures. This study is dedicated to modeling of interface guided waves for the purpose of disbond crack damage assessment. The nature of interface waves is discussed and the numerical simulation based on the material properties and geometries of hybrid interfaces as well as composite stacking sequence is verified. A finite element model of a hybrid structure with isotropic and anisotropic multilayer composites is constructed. The behavior of interface guided waves influenced by disbond cracks at free edges of hybrid bonded joints is numerically studied. The propagation characteristics of interface waves is shown to be sensitive to the size of disbond cracks. The velocity of interface waves is shown to have an inverse relation to the disbond damage size. Results show the speed is also a function of the interfacing ply orientation at the bondline. These results suggest that interface waves can be used to monitor the condition of bonded joints in hybrid structures.

Some of The Great Wall relics are destroyed or even disappeared. The existing studies relied on field surveys are costly and time consuming. So a new cloud monitoring system based on smart phones is proposed. The system, which consists of three modules, image acquisition, questionnaire and real-time location, can realize rapid acquisition of information. Firstly, using smart phones, some photos of the Great Wall can be obtained. Then, the typical integrity damage information and location information can be obtained, including structure crack, human-caused destruction, the vegetation growth, etc. Secondly, analyzing the typical integrity damage information, the evaluation results are obtained. Then, the Great Wall information in the form of questionnaire is posted on the Great Wall integrity monitoring system. Mobile phone users who logged in the system can upload photos, and fill in the questionnaires. Through taking pictures and filling in the questionnaires, the required information can be obtained.

The main objective of this work is to develop a non-contact, non-invasive, structural health monitoring technique for surface and sub-surface damage detection in structures such as composite helicopter rotor blades. In many cases, composite structures are prone to damage in the form of cracks, delamination, and manufacturing defects, which can propagate beneath structural surfaces and cause severe component or catastrophic structural failure. The damage detection technique in this study works on the principle of electrical capacitance tomography. Different patterns of electrical field are propagated in a pre-defined sensing area. Using measurements of electrical response along boundaries of the sensing area, the permittivity distribution within that space can be reconstructed. First, a series of numerical simulations was performed by altering the electrical permittivity at different locations to simulate damage. The shapes and locations of permittivity changes were captured by the proposed technique. Second, to demonstrate its validity, an experimental test setup was built with a set of boundary electrodes. The system was connected to a function generator that supplied an electrical signal and induced electrical fields between electrodes. Capacitance between pairs of electrodes were then measured, which were used as inputs for solving the inverse permittivity reconstruction problem. Various test cases with different objects placed in the sensing area were conducted for validating this technique. The preliminary results show that the system was able to reconstruct spatial permittivity distributions and detect the presence, shapes, and locations of objects, thereby suggesting potential for damage detection.

Thermally responsive self-healing polyurethanes (1DA1T, 1.5DA1T, and 2DA1H) with shape memory property were developed and the fully reversible Diels-Alder (DA) and retro Diels-Alder (rDA) reactions were employed for the healing mechanism. The transition temperatures of the DA and rDA reactions were confirmed through a differential scanning calorimetry and the molecular level of analysis on the reversibility and the repeatability between the DA and rDA reactions were completed though a variable temperature proton nuclear magnetic resonance at the reaction temperatures. Also, compact tension specimens were made to observe the healing efficiencies. These specimens were healed without the use of external forces to close the crack surfaces after testing for the repeatable healing ability with three cycles. As a result, the average first healing cycle efficiencies of 80%, 84%, and 96% for 1DA1T, 1.5DA1T and 2DA1H, respectively, were achieved and small drops for the second and third healing cycles were observed. Then, using two of the self-healing polyurethanes as resins, continuous carbon fiber fabric reinforced polymer matrix composites (C1.5DA1T and C2DA1H) were fabricated and short beam shear testing was conducted to determine the healing capability on the delamination. Accordingly, the first healing efficiencies of 88% and 85% were measured without any additional treatments on the fibers; however, an external pressure was applied during the composite healing process.

In this work, the effect of a crack on the vibrational properties of a shaft-disc system has been studied applying a generalized harmonic balance method. In the reviewed literature, the reported methods to find the unbalance response of a continuous shaft-disc system provide only the first harmonic component of the response; whereas, the presented method gives the super-harmonic components as well. The shaft-disk system consists of a flexible shaft with a single rigid disc mounted on rigid short bearing supports. The shaft contains a transverse breathing crack (fatigue crack). The main concept for crack detection in vibration-based methods is basically the investigation of crack-induced changes in the selected vibrational properties. Shaft critical speeds and harmonic and super-harmonic components of the unbalance lateral response have been used as typical vibrational properties for crack detection in a rotating shaft system. A generalized harmonic balance method has been developed to efficiently investigate changes in vibrational properties due to the effect of crack properties, depth and location. The results of the developed analytical model have been compared with those obtained from the finite element model and close agreement has been observed.

Impedance-based structural health monitoring (SHM) is a non-destructive, active technique for real-time structural damage assessment. Conventional impedance-based SHM practices apply a sinusoidal signal of fixed amplitude to excite the piezoceramic patch and obtain the impedance signature over a certain frequency range. Damage is then detected by comparing the measured impedance signature to a baseline measurement taken at the pristine state. In this work, the amplitude of the driving signal, which is directly related to the magnitude of the excitation force acting on the structure, is introduced as an additional variable, and sweeps over both frequencies and amplitudes are performed. Several structural defects, such as cracks and loose joints, are nonlinear in nature. Therefore, changing the excitation force will allow the detection of such damage induced nonlinearities and track their evolution. Numerical simulations are carried out to study the effects of nonlinearities on the impedance signature using a single mode model. Several types of structural nonlinearities, such as hardening, softening, and nonlinear damping are studied with the assumption that the piezoelectric actuator stays in its linear regime. Experiments are conducted on a single beam and a lap joint, and impedance signatures in the range of 12–15 KHz are measured at different levels of excitation. Nonlinear damping and softening behavior are detected experimentally by examining the measured impedance signatures. Numerical and experimental findings suggest the possibility of detecting and tracking structural nonlinearities using impedance measurements.

A new Structural Health Monitoring system was developed to allow a faster introduction of 3D printed components into safety critical applications. Additive manufacturing techniques are used to embed capillaries in a 3D printed structure that are then pressurized. Continuous monitoring of the capillary pressure allows the system to indicate the existence of a crack when the pressure deviates from the initial pressure level. A specifically developed experimental set-up enables the study of the impact of different parameters on the leak flow behavior and the occurring Negative Pressure Waves. Negative Pressure Waves are analyzed to demonstrate the crack localization and crack size estimation feasibility. It will first be theoretically proven that the size and location of the crack can be derived from the Negative Pressure Waves. Secondly, measurements will validate the crack localization and size estimation feasibility of the new Structural Health Monitoring system.

This conceptual research focuses on identifying damage precursors in carbon fiber reinforced polymer laminates. By coupling integrated in situ sensing elements (magnetostrictive particles) and multi-scale ultrasonic inspection (Quantitative Ultrasonic Imaging) with minimum hardware the authors are able to capture and gain an understanding of damage precursors. Preliminary damage precursors can be identified and quantified and correlated to a particular failure mode(s) and/or fabrication process accelerating the need for a sensing/repair strategy that could be implemented to capture the specific precursor prior to the onset of cracks. Capturing and mitigating damage precursors ahead of micro-crack formulation will slow the evolution of the damage precursors to micro-cracks, mitigate adverse loading environment, and develop techniques to reduce stress and loading below the endurance limit to keep it from being fatigued.

This paper proposes an effective statistical based vibration health monitoring technique using Auto Regressive (AR) parameters and Support Vector Machine (SVM) for truss type structures. The finite element method has been utilized to obtain acceleration response signals of a space truss structure under random excitations. The signals are then processed to extract their AR parameters as the feature vectors in which the AR parameters of the healthy structure are considered to be the reference baseline data. A Damage Index is then defined to be the standard deviation of the feature vectors from the baseline data. The proposed index provides an effective tool to detect the damage in the structure. It is shown that using only one sensor, it is still possible to accurately detect the damage. To locate the damage, data classification technique based on Support Vector Machine (SVM) has been employed. It is shown that SVM can successfully classify different signals extracted from the structure. Finally extensive sensitivity analysis has been performed to study the effect of different parameter such as crack size, number of sensors and AR parameter numbers on the accuracy of detection and localization processes.

A method for detecting fatigue cracks has been explored at NASA Langley Research Center. Microscopic NiTi shape memory alloy (sensory) particles were embedded in a 7050 aluminum alloy matrix to detect the presence of fatigue cracks. Cracks exhibit an elevated stress field near their tip inducing a martensitic phase transformation in nearby sensory particles. Detectable levels of acoustic energy are emitted upon particle phase transformation such that the existence and location of fatigue cracks can be detected. To test this concept, a fatigue crack was grown in a mode-I single-edge notch fatigue crack growth specimen containing sensory particles. As the crack approached the sensory particles, measurements of particle strain, matrix-particle debonding, and phase transformation behavior of the sensory particles were performed. Full-field deformation measurements were performed using a novel multi-scale optical 3D digital image correlation (DIC) system. This information will be used in a finite element-based study to determine optimal sensory material behavior and density.

Incorporation of multifunctionality to fibre reinforced polymer composite materials delivers many benefits. One example includes improved longevity of components through increasing permissible temperatures of operation, which could be achieved via in-situ cooling. As the temperature of composite components approaches the glass transition temperature (T g ) of the matrix, thermal stress induced ageing greatly increases [1], [2], thus the incentive for integrated cooling. In order to assess the damage, which could be caused by exposure to elevated temperatures, isothermal ageing was performed at a temperature 15°C lower than the materials T g (2200 hours at 110°C). Material used in this study is a carbon/epoxy prepreg system (Gurit, SE70), with a T g of 126°C when cured at 110°C. Results have shown a significant drop in Short Beam Shear (SBS) Strength starting after exposure for 1700h and increase in fibre bridging seen in mode I Double Cantilever Beam (DCB) testing. Fracture surface analysis using SEM indicated that fibres were generally less well bonded to the matrix, with visible changes began occurring as early as 1000h exposure. These results indicate that extended exposure of a material at near T g temperatures has a detrimental effect on material properties. To mitigate against this phenomenon, a series of tests were performed on SBS and DCB specimens in a raised temperature (110°C) environment, which incorporated in-situ cooling. The specimens were placed in an oven at 110°C and were cooled down to a constant temperature of 60°C via the internal vascular cooling arrangement. Further testing is underway to assess the inhibition of ageing and maintenance of the original composite material by active cooling using embedded vascular networks.

Highly cross-linked polyurethanes have a high elastic modulus and creep resistance, but they undergo a brittle fracture below the glass transition temperature. Unfortunately, a large number of glassy polyurethanes are prone to brittle fracture without undergoing large elastic deformations; in particular, brittle failure is common under conditions such as low temperature and high strain rates. While the rigidity in polymers is required for practical applications, the lack of resistance against crack propagation is essential to avoid catastrophic failures. The toughening of polymers is a crucial aspect of improving the strength and ductility at specific temperatures and deformation rates. One method that has shown promise in recent years is the creation of local regions of reduced modulus that absorb strain energy and toughen the polymer. For instance, rubbers are typically added to epoxy which phase separate upon polymerization and create local elastic regions that significantly toughen the polymer. In this study, a variety of two-phase transparent polyurethanes in the form of single inclusions is designed to study the toughening mechanism of the local regions of reduced modulus with an embedded crack. Synthesized heterogeneous polyurethanes show a transition from brittle to ductile behavior in addition to a drastic increase in the maximum load that the polymer can withstand. Compact tension experiments demonstrate that a small reduction in the inclusion’s Young’s modulus (∼10%) leads to an increase in the toughness by factor of 7 (∼700%). Moreover, digital image correlation is performed to map the strain distribution around the crack in order to visualize possible toughening mechanism. Comparison between the induced strain field in samples with inclusion and samples without inclusion reveals an efficient toughening mechanism of the polymers.