Grating-based X-ray dark-field computed tomography for the characterization of friction stir welds: A feasibility study

Schaff, Florian; Bachmann, Andreas; Zens, Amanda; Zaeh, Michael F.; Pfeiffer, Franz; Herzen, Julia

doi:10.1016/j.matchar.2017.04.023

“…Based on the investigations of SCHAFF ET AL. [17], it was presumed that a significant change in microstructure induced by the welding process could lead to a detectable change of the attenuation of X-rays when passing through a sample. As part of a preliminary experimental series, weld specimens were examined using a µCT device with respect to material qualification.…”

Section: Discussionmentioning

confidence: 99%

“…X-ray dark-field CT was used to investigate microstructural changes induced in macroscopically homogeneous materials during friction stir welding. The imaging technique provided threedimensional information about the microstructure of the welds on a macroscopic scale [17].…”

Section: Offline Characterization Of the Weld Seam Geometry And Weld Defectsmentioning

confidence: 99%

A Novel Approach to the Holistic 3D Characterization of Weld Seams – Paving the Way for Deep Learning-Based Process Monitoring

Schmoeller

¹

,

Stadter

²

,

Kick

³

et al. 2021

Preprint

3

0

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In an industrial environment, the quality assurance of weld seams requires extensive efforts. The most commonly used methods for that are expensive and time-consuming destructive tests, since quality assurance procedures are difficult to integrate into production processes. Beyond that, available test methods allow only the assessment of a very limited set of characteristics. They are either suitable for determining selected geometric features or for locating and evaluating internal seam defects. The presented work describes an evaluation methodology based on microfocus X-ray computed tomography scans (µCT scans) which enable the 3D characterization of weld seams, including internal defects such as cracks and pores. A 3D representation of the weld contour, i.e., the complete geometry of the joint area in the component with all quality-relevant geometric criteria, is an unprecedented novelty. Both the dimensions of the weld seam and internal defects can be revealed, quantified with a resolution down to a few micrometers and precisely assigned to the welded component. On the basis of the methodology developed within the framework of this study, the results of the scans performed on the alloy AA 2219 can be transferred to other aluminum alloys. In this way, the data evaluation framework can be used to obtain extensive reference data for the calibration and validation of inline process monitoring systems employing Deep Learning-based data processing.

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“…Since titanium and aluminum possess different linear attenuation coefficients, the XCT is used to visualize the distribution of different phases [21], such as Ti and Al, in the scanned area of the weld sample. For example, in the FSW of Al to Ti with a niobium (Nb) interlayer, Kar et al [4] used XCT techniques to demarcate the distribution and morphology of Ti and Nb.…”

Section: X-ray Computed Tomographymentioning

confidence: 99%

A new method to elucidate fracture mechanism and microstructure evolution in titanium during dissimilar friction stir welding of aluminum and titanium

Kar

¹

,

Malopheyev

²

,

Mironov

³

et al. 2021

Materials Characterization

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In the friction stir welding (FSW) of dissimilar materials, the weld nugget exhibits composite properties and is composed of hard particles (high-strength material) distributed in a soft matrix material. The distribution of these particles influences the properties of the weld. Therefore, it is useful to characterize the deformation and fragmentation of the high-strength material from which they originate. In the current study, FSW of aluminum (Al) to titanium (Ti) was performed and a new technique was introduced to remove Al from the post-weld sample to characterize the deformation and fragmentation of Ti in the weld nugget. The post-weld sample showed that Ti particles were inhomogeneously distributed. It was understood that the plastic deformation of the Ti depends on its location of the weld. A detailed investigation revealed a number of fracture zones in titanium. A systematic analysis revealed the evolution of twins in Ti in the thermos-mechanically affected zone (TMAZ), whereas notwins and recrystallized grains were noticed on the Ti flake that was consolidated in the weld nugget. The Xray computed tomography (XCT) showed that Ti flakes were subjected to deformation and bending. Furthermore, it was noticed that the width of the flakes was not identical along their length and that the flakes were broken at the middle region into two parts. It can be concluded that Ti, at the interface and as flakes, was subjected to severe deformation at a lower homologous temperature that leads to the formation of adiabatic shear bands (ASBs). The local evolution of temperature within the ASBs was much higher than the general weld temperature, leading to the recrystallization of Ti at the interface. Moreover, ASBs are prone to crack nucleation and propagation; hence, particles with different morphology and sizes were noticed in the nugget zone. The distribution of particles was inhomogeneous due to variation in the particle size and complex mechanical mixing. The distribution of particles varied with location across the weld nugget. A homogeneous mechanical mixing was noticed at the center of the weld nugget due to complex material flow and distribution of finer particles. With this understanding of the deformation and fracture mechanism of titanium during dissimilar FSW of Al to Ti, it is possible to engineer the developed composites and/or weld nuggets of dissimilar materials to achieve the required combination of mechanical properties.

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“…X-ray dark-field CT was used to investigate microstructural changes induced in macroscopically homogeneous materials during friction stir welding. The imaging technique provided three-dimensional information about the microstructure of the welds on a macroscopic scale [17].…”

Section: State Of the Art 21 Offline Characterization Of The Weld Seam Geometry And Weld Defectsmentioning

confidence: 99%

“…Figure 4). The materials were evaluated to determine the extent to which changes in the microstructure caused by welding resulted in a detectable change in the attenuation of the radiation from the µCT, according to the investigations of Schaff et al [17]. The alloy AA 2219 was selected for further analyses as it allowed a complete visuali-zation of the weld geometry inside the specimens.…”

Section: Materials and Experimental Set-upmentioning

confidence: 99%

A Novel Approach to the Holistic 3D Characterization of Weld Seams—Paving the Way for Deep Learning-Based Process Monitoring

Schmoeller

¹

,

Stadter

²

,

Kick

³

et al. 2021

View full text Add to dashboard Cite

In an industrial environment, the quality assurance of weld seams requires extensive efforts. The most commonly used methods for that are expensive and time-consuming destructive tests, since quality assurance procedures are difficult to integrate into production processes. Beyond that, available test methods allow only the assessment of a very limited set of characteristics. They are either suitable for determining selected geometric features or for locating and evaluating internal seam defects. The presented work describes an evaluation methodology based on microfocus X-ray computed tomography scans (µCT scans) which enable the 3D characterization of weld seams, including internal defects such as cracks and pores. A 3D representation of the weld contour, i.e., the complete geometry of the joint area in the component with all quality-relevant geometric criteria, is an unprecedented novelty. Both the dimensions of the weld seam and internal defects can be revealed, quantified with a resolution down to a few micrometers and precisely assigned to the welded component. On the basis of the methodology developed within the framework of this study, the results of the scans performed on the alloy AA 2219 can be transferred to other aluminum alloys. In this way, the data evaluation framework can be used to obtain extensive reference data for the calibration and validation of inline process monitoring systems employing Deep Learning-based data processing in the scope of subsequent work.

show abstract

Grating-based X-ray dark-field computed tomography for the characterization of friction stir welds: A feasibility study

Cited by 13 publications

References 29 publications

A Novel Approach to the Holistic 3D Characterization of Weld Seams – Paving the Way for Deep Learning-Based Process Monitoring

A Novel Approach to the Holistic 3D Characterization of Weld Seams – Paving the Way for Deep Learning-Based Process Monitoring

A new method to elucidate fracture mechanism and microstructure evolution in titanium during dissimilar friction stir welding of aluminum and titanium

A Novel Approach to the Holistic 3D Characterization of Weld Seams—Paving the Way for Deep Learning-Based Process Monitoring

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