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Since laser powder bed fusion (PBF-LB/M) is prone to the formation of defects during the building process, a fundamental requirement for widespread application is to find ways to assure safety and reliability of the additively manufactured parts. A possible solution for this problem lies in the usage of in-situ thermographic monitoring for defect detection. In this contribution we investigate possibilities and limitations of the VIS/NIR wavelength range for defect detection. A VIS/NIR camera can be based on conventional silicon-based sensors which typically have much higher spatial and temporal resolution in the same price range but are more limited in the detectable temperature range than infrared sensors designed for longer wavelengths. To investigate the influence, we compared the thermographic signatures during the creation of artificially provoked defects by local parameter variations in test specimens made of a nickel alloy (UNS N07208) for two different wavelength ranges (~980 nm and ~1600 nm).
The integration of additive manufacturing with traditional processes, termed hybrid additive manufacturing, has expanded its application domain, particularly in the repair of gas turbine blade tips. However, process-related defects in additively manufactured materials, interface formation, and material property mismatches in dual-material structures can significantly impact the fatigue performance of components. This investigation examines the low cycle fatigue and fatigue crack growth behaviors in dual-material specimens of nickel-based alloys, specifically the additively manufactured STAL15 and the cast alloy 247DS, at elevated temperatures. Low cycle fatigue experiments were conducted at temperatures of 950 °C and 1000 °C under a range of strain levels (0.3%–0.8%) and fatigue crack growth tests were conducted at 950 °C with stress ratios of 0.1 and −1. Fractographic and microscopic analyses were performed to comprehend fatigue crack initiation and crack growth mechanisms in the dual-material structure. The results consistently indicated crack initiation and fatigue fracture in the additively manufactured STAL15 material. Notably, fatigue crack growth retardation was observed near the interface when the crack extended from the additively manufactured STAL15 material to the perpendicularly positioned interface. This study highlights the importance of considering yield strength mismatch, as well as the potential effects of residual stresses and grain structure differences, in the interpretation of fatigue crack growth behavior at the interface.
Additive manufacturing techniques, such as laser powder bed fusion (PBF-LB), are well known for their exceptional freedom in part design. However, these techniques are also characterized by the development of large thermal gradients during production and thus residual stress (RS) formation in produced parts. In this context, neutron diffraction enables the non-destructive characterization of the bulk RS distribution. By control of the thermal gradients in the powder-bed plane by scan strategy variation we study the impact of in-process scan strategy variations on the microstructure and the three-dimensional distribution of RS. Microstructural analysis by means of electron backscatter diffraction reveals sharp microstructure transitions at the interfaces ranging from 100-200 µm. The components of the RS tensor are determined by means of neutron diffraction and the principal stress directions and magnitudes are determined by eigenvalue decomposition. We find that the distribution of RS in the powder-bed plane corresponds to the underlying scan strategy. When the alternating scan vectors align with the x- and y sample coordinate axes, the principal stress directions co-align. In the present geometry, nearly transverse isotropic stress states develop when the scan vectors are either aligned 45° between x and y or continuously rotated by 67° between each layer.
This work provides an investigation of the influence of low temperature heat treatments on the fatigue behavior of a PBF-LB AlSi10Mg alloy. Fatigue specimens are produced in form of round bars on a build platform preheated at 200 ◦C. The specimens have been tested in three different conditions: as-built, and after heat treatments at 265 ◦C for 1 h and 300 ◦C for 2 h. Prior to the fatigue testing, the defect distribution is analyzed by means of micro computed tomography. Subsequently, the peak over threshold method is successfully applied to provide a prediction of the size of killer defect. The defect population was of gas porosity type. No clear improvement of the fatigue performance is observed after the heat treatments. The fatigue strength predicted using fracture mechanics-based approaches is in good agreement with the experimental data. Among the studied approaches, short crack models provided the most conservative predictions.
This article presents a method to use the dispersive behavior of ultrasonic guided waves and neural networks to determine the isotropic elastic constants of plate-like structures through dispersion images. Therefore, two different architectures are compared: one using convolutions and transfer learning based on the EfficientNetB7 and a Vision Transformer-like approach. To accomplish this, simulated and measured dispersion images are generated, where the first is applied to design, train, and validate and the second to test the neural networks. During the training of the neural networks, distinct data augmentation layers are employed to introduce artifacts appearing in measurement data into the simulated data. The neural networks can extrapolate from simulated to measured data using these layers. The trained neural networks are assessed using dispersion images from seven known material samples. Multiple variations of the measured dispersion images are tested to guarantee the prediction stability. The study demonstrates that neural networks can learn to predict the isotropic elastic constants from measured dispersion images using only simulated dispersion images for training and validation without needing an initial guess or manual feature extraction, independent of the measurement setup. Furthermore, the suitability of the different architectures for generating information from dispersion images in general is discussed.
Defect reconstruction is essential in non-destructive testing and structural health monitoring with guided ultrasonic waves. This paper presents an algorithm for reconstructing notches in steel plates, which can be seen as artificial defects representing cracks by comparing measured results with those from a simulation model. The model contains a parameterized notch, and its geometrical parameters are to be reconstructed. While the algorithm is formulated and presented in a general notation, a special case of guided wave propagation is used to investigate one of the simplest possible simulation models that discretizes only the cross section of the steel plate. An efficient simulation model of the plate cross section is obtained by the semi-analytical scaled boundary finite element method. The reconstruction algorithm applied is gradient-based, and algorithmic differentiation calculates the gradient. The dedicated experimental setup excites nearly plane wave fronts propagating orthogonal to the notch. A scanning laser Doppler vibrometer records the velocity field at certain points on the plate surface as input to the reconstruction algorithm. Using two plates with notches of different depths, it is demonstrated that accurate geometry reconstruction is possible.
Additively manufactured components are characterized by heterogeneous mechanical properties due to variations of the microstructure, flaws and residual stresses resulting from the inhomogeneous fabrication process. The large number of influencing factors poses a further challenge in understanding the correlation between material properties, process parameters and component geometry. Therefore, the qualification of components based on witness specimens produced within the same job is questionable. This work aims to present a new strategy for the characterization of PBF-LB/M components based on representative specimens. The key assumption is the feasibility of a transfer of the thermal history from a component to a specimen. It is assumed that similar material properties are determined for components and specimens produced adopting a similar thermal history. After the definition of a region of interest in the component, a combination of thermal analyses by means of finite elements and in-situ experimental determination of the thermal history through infrared thermography is used to produce test coupons with a similar thermal history. The effectiveness of the procedure is demonstrated on a pressure vessel for applications in the chemical industry.
Quantitative microstructural analysis of XCT 3D images is key for quality assurance of materials and components. In this paper we implement a Graph Convolutional Neural Network (GCNN) architecture to segment a complex Al-Si Metal Matrix composite XCT volume (3D image). We train the model on a synthetic dataset and we assess its performance on both synthetic and experimental, manually-labeled, datasets. Our simple GCNN shows a comparable performance, measured via the Dice score, to more standard machine learning methods, but uses a greatly reduced number of parameters (less than 1/10 of parameters), features low training time, and needs little hardware resources. Our GCNN thus achieves a cost-effective reliable segmentation.
Self-healing polymers have been developed to improve durability and reduce costs associated with maintenance during service. The addition of thermoplastics to thermosets to produce mendable polymers appears as a promising selfhealing technique. In this study, poly (ethylene-co-methacrylic acid) (EMAA) was added to epoxy resin and the effects of EMAA addition on epoxy properties were evaluated. Specimens with two different contents of thermoplastic and particles sizes were manufactured. A two-level full factorial experimental design was used to evaluate the effect of particle size and particle content on properties of epoxy modified with addition of EMAA. Tensile tests and dynamic mechanical analysis (DMA) were used and the evaluated responses were tensile strength, modulus of elasticity, and glass transition temperature (Tg). X-ray computed tomography (XCT) was used to investigate particle size and concentration after manufacturing. It was found that the particle concentration has greater effects on stress–strain behavior of epoxy while Tg was not significantly affected by neither of the analyzed entrance variables.
Relation of craze to crack length during slow crack growth phenomena in high‐density polyethylene
(2024)
The craze‐crack mechanism occurring in high‐density polyethylene (HDPE) causing slow crack growth and environmental stress cracking is investigated in detail with respect to the relation of crack length and the related craze zone. This is essential for the understanding of the resulting features of the formed fracture surface and their interpretation in the context of the transition from crack propagation to ductile shear deformation. It turns out that an already formed craze zone does not inevitably result in formation of a propagating crack, but could also undergo ductile failure. For the examination, the full notch creep test (FNCT) was employed with a subsequent advanced fracture surface analysis that was performed using various imaging techniques: light microscopy, laser scanning microscopy, scanning electron microscopy, and X‐ray micro computed tomography scan. FNCT specimens were progressively damaged for increasing durations under standard test conditions applying Arkopal, the standard surfactant solution, and biodiesel as test media were used to analyze the stepwise growth of cracks and crazes. From considerations based on well‐established fracture mechanics approaches, a theoretical correlation between the length of the actual crack and the length of the preceding craze zone was established that could be evidenced and affirmed by FNCT fracture surface analysis. Moreover, the yield strength of a HDPE material exposed to a certain medium as detected by a classic tensile test was found to be the crucial value of true stress to induce the transition from crack propagation due to the craze‐crack mechanism to shear deformation during FNCT measurements.
Highlights
- Progress of crack formation in high‐density polyethylene is analyzed by different imaging techniques
- Determined growth rates depend on distinction between craze zone and crack
- The ratio of the present crack to the anteceding craze zone is validated theoretically
- The transition from crack propagation to ductile shear deformation is identified
- An already formed craze zone may still fail by ductile mechanisms