A Nondestructive Testing Method for Wind Turbine Blade Multilayer Composites Based on Inverse Heat Transfer Problem

This study presents a novel methodology that integrates piezoelectric actuation and sensing with regression models and neural networks for high-accuracy detection and localization of multiple delamination and crack defects in composite laminates. An eight-layer graphite/epoxy composite plate, instrumented with piezoelectric patches, is excited using random voltage stimuli, generating structural responses captured by sensors. The proposed framework employs six regression techniques and artificial neural networks, achieving localization accuracy with R^2 values exceeding 99.6%. Additionally, combining five signal decomposition methods with four classifiers enables defect type identification with up to 98.26% accuracy. The methodology demonstrates exceptional precision in detecting previously unseen delamination and crack defects down to the lamina level, optimized through grid search cross-validation. A comparative analysis highlights that piezoelectric sensor voltage signals outperform acceleration signals for defect characterization. This integrated piezoelectric-regression/neural network framework establishes a robust foundation for non-destructive evaluation, offering significant potential for real-time structural health monitoring applications.

Composite materials are of great importance in many industries due to their unique properties, strength and durability, but they also include disadvantages that can affect their use and must be studied. In this article, we simulate the acoustic interference field received by a delay line following an interaction between an acoustic field and a multilayer carbon fibre composite material using the ray approach. In this case, the simulation is performed using carbon fiber composite plates, where some plates have lamination defects such as delamination, while others are free of these defects. Experimental measurements are performed on carbon fiber composite plates with and without delamination defects introduced beforehand, without knowing their thickness. The thickness of each ply is 0.125 mm. The transducer used is a focusing immersion transducer type parametric (V 312) that operates at a frequency of 10 MHz The simulation results almost exactly corroborate those of the experiment. The simulation model was employed to determine the thickness of the induced delamination, which is 0.2 mm, found in the second and third layers.

In this paper, we aim to numerically resolve linear and nonlinear transient heat conduction problems in multilayer composite materials using a deep learning method called multi-domain physics-informed neural networks (MDPINNs). For this purpose, the multilayer media are first divided into independent sub-domains based on domain decomposition technique. The single-layer deep neural networks are first established, and each sub-domain has its corresponding sub-network. Then, each two sub-networks are connected by continuity conditions on the interface to form a MDPINNs’ framework that can directly solve the transient heat conduction problem in multilayer media. The temperature distribution in the computational domain can be obtained by training the MDPINNs, including the temperature values on the interface. A series of numerical experiments are carried out to verify that the proposed framework can achieve satisfactory accuracy, including in micrometer or even nanometer structures. Compared with conventional methods, the MDPINNs have the advantage of directly solving both linear and nonlinear heat conduction problems in multilayer materials in a unified and concise form.

Effects of processing conditions on the solidification and heat-affected zone of 309L stainless steel claddings on carbon steel using wire-directed energy deposition

A comparison is made between conventional (i.e. uniform) and chirped optical fibre Bragg gratings (FBGs) for the detection of matrix cracking damage in composite materials. Matrix cracking damage is generally the first type of visible damage to develop under load in the off-axis plies of laminated composites and is generally the precursor of more serious damage mechanisms, particularly delamination. The detection of this type of damage is thus important, particularly in aerospace applications. Using a uniform FBG, characteristic changes develop in the reflected spectrum which can be used to identify crack development in the composite. The additional advantage of using a chirped grating is that the crack position can also be located.

The components overheating inside an object, such as inside an electric control cabinet, a moving object, and a running machine, can easily lead to equipment failure or fire accident. The infrared remote sensing method is used to inspect the surface temperature of object to identify the overheating components inside the object in recent years. It has important practical application of using infrared thermal imaging surface temperature measurement to identify the internal overheating elements inside an electric control cabinet. In this paper, through the establishment of test bench of electric control cabinet, the experimental study was conducted on the inverse identification technology of internal overheating components inside an electric control cabinet using infrared thermal imaging. The heat transfer model of electric control cabinet was built, and the temperature distribution of electric control cabinet with internal overheating element is simulated using the finite volume method (FVM). The outer surface temperature of electric control cabinet was measured using the infrared thermal imager. Combining the computer image processing technology and infrared temperature measurement, the surface temperature distribution of electric control cabinet was extracted, and using the identification algorithm of inverse heat transfer problem (IHTP) the position and temperature of internal overheating element were identified. The results obtained show that for single element overheating inside the electric control cabinet the identifying errors of the temperature and position were 2.11% and 5.32%. For multiple elements overheating inside the electric control cabinet the identifying errors of the temperature and positions were 3.28% and 15.63%. The feasibility and effectiveness of the method of IHTP and the correctness of identification algorithm of FVM were validated.

Structural damage classification in composite materials using the Wigner-Ville distribution and convolutional neural networks

Carbon fiber epoxy laminates are extensively used in the aerospace industry as they offer a combination of high performance with relatively low weight. However, damage may occur in these materials, either at the manufacturing level or during use, which may affect their structural integrity. Among the type of damage which may occur, delamination is a common defect which causes a reduction in compressive strength and thus limits the life of laminated composites. If undetected, delamination may propagate during use due to mechanical loads and in the worst case may cause fracture of the material. Therefore, delamination in composite materials needs to be efficiently detected and accurately quantified for safety and economic reasons. Because of their heterogeneity, multi-layered structure and anisotropy, the inspection of composite materials remains difficult with conventional NDT methods. A method making use of Foucault currents, and relying on the principle of electromagnetic induction, can be adapted for the detection and characterization of damage in composite materials. The use of Foucault currents in characterizing delaminated areas at interfaces between plies in carbon fiber/epoxy laminates is addressed in this paper. It is demonstrated that Foucault currents can accurately detect and quantify delamination in CFRP materials. Furthermore, the potential of this technique for monitoring defect propagation in composite materials is discussed.

In this work, the Minimum Entropy Deconvolution (MED) method, developed for ultrasonic signals, is used to address the problem of delamination defect detection in Composite Materials. Standard deconvolution techniques suppose that the wavelet is minimum phase but generally make no assumptions about the amplitude distribution of the primary reflection coefficient sequence. For a white reflection sequence the assumption of a Gaussian distribution means that recovery of the true phase of the wavelet is impossible; however, a non-Gaussian distribution in theory allows recovery of the phase. It is generally recognized that primary reflection coefficients typically have a non-Gaussian amplitude distribution. The minimum entropy deconvolution (MED) method supposes whiteness but seek to exploit the non-Gaussianity. This method do not assume minimum phase. The deconvolution filter is defined by the maximization of a function called the objective. The algorithm is tested on simulated data and also tested on real ultrasonic data from multilayered composite materials.

ABSTRACTThe paper investigates the dispersion of quasi‐Lamb waves in a hydro‐elastic system consisting of a plate of multilayer composite material and a compressible, inviscid fluid layer whose flow is confined by a rigid wall. The multilayer composite material is modeled as a transversely isotropic material whose axis of symmetry is aligned along the thickness of the plate. The motion of the plate is described by the exact equations and relations of elastodynamics for anisotropic bodies, but the fluid flow is described by the linearized Euler equations. The analytical solutions of these equations are found and according to these solutions, the dispersion equations are obtained from the corresponding boundary, compatibility, and impermeability conditions. The dispersion equation is solved numerically and the numerical results are obtained for the case where the plate material consists of two alternating layers. Based on these results, a parametric study of the influence of the density ratio of the plate and fluid materials and the ratio of the shear wave propagation velocity in the stiffer material layer of the plate to the sound velocity of the fluid on the dispersion curves concerning the first four subsequent modes (denoted as A0, S0, A1 and S1 modes) of the quasi‐Lamb waves is performed. The influence of the ratio of the shear moduli of the components of the multilayer material and the influence of the contact of the plate with the fluid are investigated.

A multi-layered composite material composed of alternating SUS301 and SUS420J2 steels, prepared by hot-rolling bonding, shows a superior strength and ductility balance than the components. Few researches have been addressed on texture features of structural multi-layered materials during cold-rolling. In the present work, cold-rolling with three reductions (20%, 40% and 65%) in thickness was conducted on both the two monolithic steels (SUS301 and SUS420J2) and the multi-layered material consisting of SUS301 and SUS420J2 components. Texture and microstructure development during the cold-rolling deformation in both the monolithic steels and multi-layered material were investigated by using EBSD technique. It was found that austenite phase in SUS301 component of the multi-layered material showed weaker 〈110〉//ND texture as compared to the monolithic SUS301 steel although the similar texture characteristics appeared in both conditions. On the other hand, the martensite phase in SUS420J2 component of the multi-layered material showed stronger {112}〈110〉 texture components than the 〈111〉//ND and 〈100〉//ND texture components that were dominant in the monolithic SUS420J2 steel. It is considered that the constraint condition and shear stress at component layer interfaces are significant for the formation of Brass component observed as the final stable orientation of austenite phase of the SUS301 steel in the multi-layered samples, and the formation of the {112}〈110〉 texture of martensite phase of the SUS420J2 steel in the multi-layered samples during the cold-rolling deformation.

Porous alumina ceramics was fabricated by direct foaming method using a natural foaming agent shikakai of Acacia Mimosaceae family. Binders affected the foam stability and stable foams were obtained with 2 wt% PVA wrt alumina. The dispersant concentration (0.5%) and the milling time (12 h) were optimized. The slurries for gel casting were prepared by varying solid loading, saponin and surfactant concentration at a constant PVA content. At low saponin content (0.07–0.4%), cracked and drained samples formed. Both cracking and drainage defects were minimized on increasing saponin to 2%. 1.5% Glycerol addition resulted in defect-free samples which could be correlated with the lowering of the shear modulus of the slurry with glycerol addition. The microstructure of the green and sintered samples show that porosity and interconnectivity improved with saponin and glycerol addition. In defect-free samples, the highest total porosity was 51.23 ± 4.25% in 30% solid loading samples. The maximum pore size was 67.16 ± 45.6 µm. Both porosity and pore size decreased with increase in solid loading and saponin content.

В статье рассматриваются возможности повышения эксплуатационных свойств технологического оборудования, в частности аппаратов для тепловой обработки продуктов питания, за счет улучшения теплопередачи на основе использования многослойных металлических композиций. Эта проблема тесна связана с борьбой за энерго- ресурсосбережение в пищевых производствах и снижение экологической нагрузки на окружающую среду. Несанкционированное превышение температуры греющей поверхности одна из серьезных проблем, с которой приходится сталкиваться в промышленных и бытовых условиях тепловой обработки пищевых продуктов. Специалистам известно, какие проблемы представляет собой неравномерный прогрев по площади разнообразных емкостей для приготовления пищи: кастрюль, сковород, противней и других нагреваемых поверхностей. Перегрев одних участков и недостаточная температура других заставляет время от времени перемещать их вдоль греющей поверхности плиты, особенно, если источником тепла является сжигаемое газообразное или жидкое топливо. С одной стороны такая ситуация приводит часто к браку - пригоранию приготавливаемых продуктов питания, а с другой к перерасходу используемой в процессе варки или жарения тепловой энергии. Санитарно-гигиеническая обработка соответствующих емкостей приводит к увеличению общего цикла приготовления пищи, удорожанию технологического процесса, дополнительного расхода воды, которая требует последующей очистки от органических включений при повторном использовании или возвращении в природные водоемы. Предупреждение такой ситуации возможно при использовании нового поколения материалов для изготовления емкостей для тепловой обработки пищи – многослойных композиционных материалов. Такие материалы, сочетая в себе высокую теплопроводность с одной стороны, могут иметь низкую адгезионную способность к органическим веществам с другой. Вместе с тем, одной из серьезных проблем, с которой приходится сталкиваться при производстве емкостей из таких материалов является специфика совместного формования емкостей и соединение разных по физико-механическим свойствам материалов между собой. Проведенные исследования наряду с аналитическими результатами позволяют формулировать практические рекомендации на основе численных в оценок напряженного состояния композиции металлов «сталь+медь+сталь». Экспериментально полученные сваркой взрывом такие материалы хорошо зарекомендовали себя при эксплуатации при нагреве в диапазоне температур 100 – 300 оС.

Cost effective and reliable damage detection is critical for the utilization of composite materials in structural applications. Non-destructive evaluation techniques (e.g. ultrasound, radiography, infra-red imaging) are available for use during standard repair and maintenance cycles, however by comparison to the techniques used for metals these are relatively expensive and time consuming. This paper presents part of an experimental and analytical survey of candidate methods for the detection of damage in composite materials. The experimental results are presented for the application of modal analysis techniques applied to rectangular laminated graphite/epoxy specimens containing representative damage modes, including delamination, transverse ply cracks and through-holes. Changes in natural frequencies and modes were then found using a scanning laser vibrometer, and 2-D finite element models were created for comparison with the experimental results. The models accurately predicted the response of the specimems at low frequencies, but the local excitation and coalescence of higher frequency modes make mode-dependent damage detection difficult and most likely impractical for structural applications. The frequency response method was found to be reliable for detecting even small amounts of damage in a simple composite structure, however the potentially important information about damage type, size, location and orientation were lost using this method since several combinations of these variables can yield identical response signatures.

Defects may be introduced in composites during processing and fabrication. They include contaminants, porosity, inclusions, delaminations, and nonuniform fiber and matrix distributions. Damage induced in service under loading and environmental variations includes matrix cracking, delamination, fiber breakage, and dispersed defects, such as matrix ageing and degradation.