<figure><img src="image_1.png" /></figure>

# Non-destructive Surface Integrity Evaluation of Nickel-Based Superalloys Using Eddy Current Testing

Jakob LÖTFERING<fnref n="1" />, Martin SCHULZE<fnref n="2" />, Till SCHULZE<fnref n="2" />, Stefan GRÄFE<fnref n="3" />, Markus MEURER<fnref n="1" />, Henning HEUER<fnref n="2" />, Thomas BERGS<fnref n="1" />,<fnref n="3" />

## Abstract

Manufacturing aerospace engine components requires extensive development and rigorous testing, often involving numerous experiments and destructive analyses that lead to high costs and significant material waste. Surface Integrity (SI) in low-pressure aero-engine regions is a critical quality factor, predominantly influenced by thermo-mechanical loads during manufacturing and the prior processing history of semi-finished products. Traditionally, SI assessment relies on destructive post-production testing, limiting efficiency and resource utilization. This paper demonstrates that high-frequency eddy current technology can non-destructively quantify changes in residual stresses and phase contributions in nickel-based superalloys by calibrating electrical conductivity. Controlled variations in SI characteristics were induced using a laser heat treatment process. Calibration of high-frequency eddy current signals against these variations revealed a strong correlation between electrical conductivity and the microstructural changes associated with residual stress and phase alterations. The findings indicate that this non-destructive evaluation method is promising for real-time, in-process monitoring of SI, potentially reducing reliance on costly and wasteful destructive testing in aerospace component manufacturing.

**Keywords:** Aerospace, DA718, material analysis, eddy current

## 1. Introduction

Stringent safety regulations within the aerospace sector are imperative given that the reliability and durability of components have a direct impact on human safety. A case in point is the manufacture of turbine disks which are predominantly constructed from nickel-based superalloys utilized in the low-pressure turbine section. These alloys, known for their resistance to high temperatures, are machined using processes such as face turning. Any alterations to manufacturing processes or parameters require a protracted and expensive approval procedure, which includes thorough assessments of the component's surface integrity (SI). The evaluation of SI necessitates the determination of residual stress depth profiles, typically measured via destructive testing methods like X-ray diffraction with successive material removal or the hole drilling technique [1,2]. To facilitate more adaptable manufacturing process modifications, it is essential to develop non-destructive methods for measuring residual stress depth profiles. Non-destructive testing (NDT) techniques are therefore of significant interest. Among these techniques, high-frequency eddy current methods have the capability to detect residual stresses and other SI characteristics without the need for material removal [3,4]. Correlations between electrical conductivity, microstructural changes, and residual stresses allow for the indirect assessment of SI properties using an eddy current probe after appropriate calibration [5]. The depth of penetration of the primary excitation field from the eddy current sensor is dependent on the excitation frequency, enabling the acquisition of depth information through frequency sweeping [5]. Previous research has demonstrated the feasibility of indirectly measuring residual stress depth profiles in shot-peened samples using conductivity measurements obtained from high-frequency eddy current probes [3,6]. Furthermore, studies have examined the effects of grain size and phase fractions on electrical conductivity in samples subjected to various heat treatments [4]. The current challenge involves applying this methodology to SI alterations resulting from machining processes, which encompass both thermal and mechanical influences. To mitigate the complexity associated with changes in SI, the process has been split into a

<footnote n="1">¹ Manufacturing Technology Institute MTI of RWTH Aachen University, Aachen, Germany;
Phone: +49 24180432; j.loetfering@mti.rwth-aachen.de</footnote>

<footnote n="2">² Fraunhofer IKTS, Dresden, Germany; martin.schulze@ikts.fraunhofer.de</footnote>

<footnote n="3">³Fraunhofer-Institut für Produktionstechnologie IPT, Aachen, Germany; s.graefe@ipt.fraunhofer.de</footnote>
purely thermal procedure via laser heat treatment and a purely mechanical procedure through deep rolling. The current work focuses on the laser heat treatment of cuboid direct aged INCONEL 718 (DA718) samples using a diode laser. The surfaces of the samples are characterized using a high-frequency eddy current probe. For the investigation of correlations between the eddy current signal and surface integrity, electron backscatter diffraction (EBSD) measurements are carried out to determine phase contributions of DA718 that influence the eddy current signal. For correlations with residual stress depth profiles, X-ray diffraction measurements are performed in combination with successive material removal. The Pearson correlation coefficient is calculated for the eddy current signal and the different microstructural and residual stress results.

## 2. Methodology

Three cuboid samples of DA718, with dimensions of 66.5 mm × 45 mm × 20 mm, were cut from a large ring using electrical discharge machining (EDM). Subsequent X-ray diffraction measurements confirmed that the minimal impact of the EDM process resulted in residual stresses confined to a surface layer less than 10 µm in depth. In the following, it is assumed that the influence of the EDM process on the SI is negligible. Next, the three samples were subjected to a laser heat treatment using a high power diode laser of type "Laserline LDF 5000-40" from the company Laserline GmbH, Mühlheim-Kärlich, Germany. The laser is comprised of four wavelengths 910 nm, 940 nm, 980 nm and 1030 nm, has a maximum laser power of 5000 W and a beam parameter product of 40 mm mrad. Furthermore, a Laserline Zoomoptik OTZ-5 was used during the experiments. The laser spot size was set to 1.5 mm at a working distance of 225 mm, which is the distance between optic and part surface. The samples were heat treated with a meandering pattern (see Figure 1 c)) using a step over distance of 0.1 mm and a feed of 4 m/min. The used laser powers were 175 W, 200 W, 225 W, 250 W and 275 W. One of the surfaces was left untreated. The resulting surfaces are shown in Figure 1 b). The samples are in the following denoted by U (untreated), A (175 W), B (200 W), C (225 W), D (250 W) and E (275 W). The corresponding laser power for sample S is denoted by $P_{\text{laser,S}}$. During the heat treatment temperature was measured in the laser focal spot on the surface of the sample using an en2Aix FIRE-3 two-color pyrometer with wavelengths $\lambda_1 = 1.65$ µm and $\lambda_2 = 1.95$ µm (see Figure 1 a)).

<figure><img src="image_2.png" /><figcaption>Figure 1. a) Setup for laser heat treatment. b) Samples after laser heat treatment for different amounts of laser power $P_{\text{laser,S}}$ and roughness measurement positions. c) Meandering pattern used for laser heat treatment.</figcaption></figure>
An optical lens was used to focus the field of view of the pyrometer on the laser focal spot. The sample rate of the measured temperature data was chosen to be 10,000 samples per second. Subsequently, surface roughness descriptors Ra and Rz of the samples were obtained using a Jenoptik Nanoscan 855 tactile measurement device following DIN EN ISO 4287. After the surface roughness measurements, the samples were evaluated metallographically with X-ray diffraction (XRD) using an XStress 3000 from Stresstech, Rennerod, Germany. First, the surface of each sample was scanned in a rectangular grid of 4x4 points to evaluate the surface residual stresses. Then, the samples were cut along their long side to widths of 33 mm to provide samples for the metallographic analysis (see Figure 2 b). One depth profile per sample was measured up to a depth of 200 µm. Additionally, an Electron Backscatter Diffraction (EBSD) analysis of each sample was carried out with a scanning electron microscope type Zeiss Sigma VP 500 (Carl Zeiss AG). For eddy current investigations an EddyCus® Pro-II device from Fraunhofer IKTS was used, which can acquire eddy current sweeps in a frequency range from 100 kHz to 100 MHz. In this frequency range a cable-impedance matching close to the sensor is necessary to reduce noise and machinery interference. Therefore, a preamplifier was integrated into the probe (see Figure 2 a) - black part of probe). The sensing elements are transformer-absolute type coils based on flexible PCB with a diameter of 10 mm. They are mounted close to the preamplifier in the violet body. The measurements are carried out on a rectangular grid of 5x6 points, where the distance of the points in x- and y-direction are 3 mm respectively. Each measurement consists of a frequency sweep from 1 to 100 MHz to capture depth information of the sample's microstructure.

<figure><img src="image_3.png" /><figcaption>Figure 2. a) Setup for eddy current measurement on 5-axis machining center of type DMG DMU 85 FD monoBlock. b) Measurement points for eddy current sweep measurements from 1 to 100 MHz.</figcaption></figure>

### 3. Results and Discussion

A general discoloration of the samples is observed due to an increased laser power (see Figure 1). Discoloration begins to appear in the sample treated with $P_{laser,C} = 225$ W and complete discoloration is observed at $P_{laser,D} = 250$ W. Treated with an even higher laser power of $P_{laser,E} = 275$ W, sample E already shows signs of surface melting. From the time resolved temperature measurements the average and the standard deviation were calculated for each sample, which are shown in Figure 3 a). The parts of the signal when the laser spot left the sample surface were cut off before further calculations. In general, a monotonous increase of temperature with laser power is observed. The standard deviation is the highest for sample E since the temperature does not converge to an equilibrium value but increases over time.
**3.1 Surface Temperature and Surface Roughness**

The surface roughness measurements were carried out at three distinct positions on the surface of each sample in x- and y-direction, respectively (see Fig. 1 b)). The arrows in Figure 1 b) indicate the roughness measurement direction. Mean value and standard deviation of those measurements are shown in Fig. 3 b). In general, the values do not differ by much with a standard deviation of σRa = 0.17 µm and σRz = 0.90 µm (data from x- and y-direction combined). The highest values for Ra and Rz in x-direction occur for sample D which is due to an outlier data point with Ra = 2.05 µm and Rz = 12.7 µm at the edge of the sample. In y-direction the highest value occurs for sample E. The change in roughness can be traced back to the surface melting and rehardening.

<figure><img src="image_4.png" /><figcaption>Figure 3. Results of a) temperature and b) surface roughness measurements. a) shows the temperature average over time during the meandering procedure. The corresponding standard deviations are shown as error bars. In b) surface roughness values Ra and Rz, averaged over three consecutive measurements at different positions on the sample, are shown for x- and y-direction, respectively.</figcaption></figure>

**3.2 Residual Stress**

The surface residual stress measurements in x- and y-direction are shown in Figure 4. The scan of the surface is shown in Figure 4 a) revealing the inhomogeneities of the samples. The inhomogeneities are relatively small as can be seen in Figure 4 b), where the standard deviation of the surface residual stress values is shown as error bars. On average the surface residual stress increases from an average of σ<sub>RS,y</sub> = 200 MPa (σ<sub>RS,x</sub> = 127 MPa) for the untreated sample to an average of σ<sub>RS,y</sub> = 602 MPa (σ<sub>RS,x</sub> = 715 MPa) for sample C. For higher laser powers the surface residual stress decreases to σ<sub>RS,y</sub> = 536 MPa (σ<sub>RS,x</sub> = 520 MPa) and σ<sub>RS,y</sub> = 540 MPa (σ<sub>RS,x</sub> = 419 MPa) for samples D and E, respectively. The relaxation of tensile residual stresses is related to the melting of the surface. This behavior can also be seen in the depth resolved residual stress measurements (see Figure 5). The depth profile was measured until reaching a depth where residual stresses had relaxed. For samples A, B and C a monotonous increase of surface residual stress due to increased laser power can be observed. For higher laser powers P<sub>laser,D</sub> = 250 W and P<sub>laser,E</sub> = 275 W the maximum is shifted towards higher depths around 125 µm and 250 µm, respectively. There is also a monotonous increase from the residuals stresses in y-direction to the residual stresses in x-direction.
<figure><img src="image_5.png" /><figcaption>Figure 4. Surface residual stress in x- and y-direction determined using XRD measurements. a) shows the surface scan and b) the average and standard deviation over the whole surface.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Figure 5. Residual stress depth profile in x-, xy- and y-direction for all samples.</figcaption></figure>

### 3.3 Grain Size and Phase Contributions

The EBSD images showing the phase contributions and the grain sizes are displayed in Figure 6. The δ-phase is denoted by the color yellow, whereas the γ-matrix is denoted by the color red. In general, few differences are found for samples treated with $P_{laser,C}$ = 225 W or less. For samples D and E a melted surface layer with larger grains and a reduced fraction of δ-phase is found at around 30 µm and 70 µm below the surface, respectively. For the calculation of the δ-phase and the average grain size, accumulations of grains seemingly floating above the surface in samples B, D and E were excluded. They stem from a melted surface layer made mostly of Titanium and Aluminium as analyzed with Energy-dispersive X-ray spectroscopy (EDX). They are wrongly classified by the EBSD evaluation software as δ-phase found within the bulk due to similarities in the crystal structure. Moreover, grains with one neighbor or less are not included in the calculation for the fraction of the δ-phase. To get from the fraction of grains to the fraction of the phases, the grain fraction is weighted with the area of the grains. The resulting
$\delta$-phase fraction is displayed in Figure 7 b). The fraction fluctuates between the values of the untreated sample with 0.17 % and sample B with 0.43 %. Notably lower values are observed for samples D and E, where the melting of the surface layer removed the $\delta$-phase almost completely. For the calculation of the mean grain size in addition to excluding the grains above the surface and grains with less than one neighbor, grains with a grain diameter of $d_k = 2$ µm or less are excluded. The resultant average grain sizes and corresponding standard deviations are depicted in Figure 7 a). The average grain size fluctuates between $d_{k,U} = 9.5$ µm and $d_{k,B} = 5.4$ µm for the untreated sample U and sample B. The surface melting of samples D and E leads to larger grain sizes of $d_{k,D,layer 1} = 10.7$ µm and $d_{k,E,layer 1} = 7.5$ µm than in the bulk material with $d_{k,D,layer 2} = 5.9$ µm and $d_{k,E,layer 2} = 4.5$ µm, respectively.

<figure><img src="image_7.png" /><figcaption>Figure 6. EBSD images for the different samples with phase contributions of the γ-phase denoted by the color red and phase contributions of the δ-phase denoted by the color yellow. Where significant grain size changes appear, images are split into layers 1 and 2.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Figure 7. Average grain sizes and phase fraction of the δ-phase calculated from the EBSD images.</figcaption></figure>
### 3.4 Eddy Current

Next, the eddy current signal is going to be evaluated. To interpret the eddy current signal in terms of conductivity and liftoff, i.e. distance from the surface, a calibration procedure is applied to the raw signal. First, a sweep measurement from 1 MHz to 100 MHz of samples with known conductivities and liftoff is performed. The samples have conductivities of 1.259 %IACS, 1.33 %IACS, 1.431 %IACS, 1.5 %IACS and 1.6 %IACS, respectively. The measurement is performed with a liftoff of 0 µm (surface contact), 25 µm, 50 µm, 75 µm and 100 µm each at five different positions. To ensure the correct liftoff distances, Kapton foil with a known thickness was used as a spacer between sensor and sample. The resulting plane spanned by the calibration points for different conductivities and liftoffs can be seen in Figure 8 for an excitation frequency of $f = 2$ MHz. Given the small variation in the impedance plane, data from several samples overlap, rendering some samples visually indistinguishable.

<figure><img src="image_9.png" /><figcaption>Figure 8. Calibration procedure to obtain liftoff and conductivity values from the eddy current data shown for an excitation frequency of $f = 2$ MHz.</figcaption></figure>

Linear interpolation is then used to infer the conductivity and liftoff of any point in between the calibration samples (see Figure 8 a) and b). The inferred conductivity and liftoff values for the eddy current scans at an excitation frequency of $f = 68$ MHz of the laser heat treated samples can be seen in Figure 9.

<figure><img src="image_10.png" /><figcaption>Figure 9. Liftoff and conductivity values obtained from the calibration procedure for the eddy current scans of the different samples at an excitation frequency of $f = 68$ MHz ($\delta_s = 76$ µm).</figcaption></figure>

The independence of the conductivity and liftoff values as obtained from the interpolation procedure can be observed for sample D. The liftoff increases towards the sample edge while the conductivity stays homogeneous. The large liftoff value can be explained by the large
roughness value in x-direction, which is shown in Figure 3 b). Similarly, the differences of samples D and E to the other samples concerning their metallographic properties is visible in the conductivity values in Figure 9. A better overview of the differences between the samples is given in Figure 10, where the average over the whole surface for conductivity and liftoff values is shown. For excitation frequencies larger than f = 90 MHz a sudden decrease of the conductivity value is observed for all samples (see Figure 10 a)). Similarly, a peak appears in the liftoff value in Figure 10 b). Large amounts of fluctuation in the frequency region above f = 90 MHz have been observed during repeated measurements independent of the sample, which probably stem from environmental perturbations. For that reason, frequencies above f = 90 MHz are going to be neglected in the following correlation analyses.

<figure><img src="image_11.png" /><figcaption>Figure 10. Averaged liftoff and conductivity values obtained from the calibration procedure for the eddy current scans of the different samples.</figcaption></figure>

### 3.5 Correlations

As a next step, correlations between different microstructural properties and the inferred conductivity and liftoff from the eddy current signal are evaluated using the Pearson correlation coefficient and a significance level of $\alpha = 0.05$. To correlate the conductivity values with the depth resolved residual stress values the change of the conductivity with respect to the untreated sample U is taken into account. The relative change in conductivity is given by

$$ \Delta\sigma_{el,P_{laser,S}}(f) = \frac{\sigma_{el,P_{laser,S}}(f) - \sigma_{el,U}(f)}{\sigma_{el,U}(f)}, \quad (1) $$

where $\sigma_{el,P_{laser,S}}(f)$ is the frequency resolved conductivity of the sample treated with laser power $P_{laser,S}$ and $\sigma_{el,U}(f)$ is the corresponding conductivity of the untreated sample U. To be able to compare the relative change in conductivity with residual stress values from different depths the excitation frequencies f are converted to depths according to the corresponding skin depth, which is given by

$$ \delta_s = \frac{1}{\sqrt{\pi \cdot \mu_0 \cdot \mu_r \cdot \bar{\sigma}_{el,S} \cdot f}}, \quad (2) $$

where $\mu_0$ is the vacuum permeability, $\mu_r$ is the relative permeability ($\approx 1.0011$ for DA718 [7]) and $\bar{\sigma}_{el,S}$ is the electrical conductivity of sample S averaged over a frequency range, which will be defined later. The integrative behavior of the eddy current measurement is neglected for the purpose of simplicity and it is assumed that $\bar{\sigma}_{el,S}$ as it appears in Eq. 2 corresponds to the conductivity found at depth $\delta_s$. Since the measured depths of the residual stress measurement do not exactly correspond to the depths calculated from the excitation frequency of the eddy current probe, linear interpolation is performed. The correlation of the depth resolved residual stress and the relative conductivity difference as calculated by Eq. 1 is shown in Figure 11.
<figure><img src="image_12.png" /><figcaption>Figure 11. Correlation of residual stress and relative conductivity change σ<sub>el,Plaser,S</sub> for each of the samples and different residual stress directions.</figcaption></figure>

Since Eq. 1 would yield zero for the untreated sample for all frequencies, it is not considered in
the correlation analysis and therefore not shown in Figure 11. The frequency ranges, and
therefore the depths, over which to perform the correlations are chosen as 28-50 MHz (74-99
µm), 28-50 MHz (74-98 µm), 5-90 MHz (55-233 µm), 2-8 MHz (187-418 µm) and 1-4 MHz
(267-458 µm) for samples A, B, C, D and E, respectively. The maximal and minimal frequency
are determined such that they share a common minimum and maximum value with the
corresponding depth of the depth resolved residual stress measurements. The averaging to
obtain the value of σ̄<sub>el,S</sub> is performed over the same frequency ranges. In these frequency ranges,
the measured residual stress correlates linearly with the relative conductivity, but at higher
frequencies the behavior shifts. For samples D and E, this shift results from surface melting.
Overall, at higher frequencies, fluctuations in residual stress versus relative conductivity
increase, likely due to assumptions about penetration depth and the sensor's higher sensitivity.
Therefore, frequencies above 50 MHz were excluded from correlation calculations for samples
A and B. All samples show a significant correlation across all residual stress directions,
strongest in the y-direction and decreasing toward the x-direction. Samples D and E exhibit the
highest correlation coefficients within the chosen frequency range, while sample C shows
correlations over the broadest range. Samples A and B yield the lowest coefficients for the
reasons mentioned above. The correlation with microstructural properties of the samples is
shown in Figure 12. The frequencies are chosen such that they maximize the correlation
coefficient r and minimize the p-value. Significant correlation of the inferred liftoff with the Ra
value in x-direction can be observed with r = 0.92 and p = 0.01. However, for the other
roughness values the correlation is not significant based on a significance level of α = 0.05.
Similarly, no significant correlation of the inferred conductivity with the grain size is found.
For the δ-phase fraction a significant correlation with the conductivity is found with r = 0.85
and p = 0.03.
<figure><img src="image_13.png" /><figcaption>Figure 12. Correlation of roughness values with the liftoff measurements and the grain size and fraction of δ-phase with the conductivity measurements obtained from the calibration procedure, respectively. The excitation frequencies are chosen such that the correlation coefficient *r* is maximized and the *p*-value is minimized. The corresponding penetration depths are 113 µm (22 MHz), 531 µm (1 MHz), 60 µm (79 MHz) and 62 µm (74 MHz).</figcaption></figure>

**4. Summary**

In conclusion a non-destructive strategy for assessing surface integrity (SI) in nickel-based superalloys using high-frequency eddy current testing calibrated against electrical conductivity and liftoff measurements is investigated. A diode laser system offering powers of 175 W to 275 W was employed to induce controlled variations in residual stress and microstructure, using a meandering scan pattern to treat cuboid DA718 samples. During the heat treatment, a two-color pyrometer recorded temperatures, showing that higher laser power correlates with higher peak surface temperatures, as well as melting of the near-surface region at 275 W. Surface roughness (Ra and Rz) was measured following DIN EN ISO 4287, revealing slight but notable increases in roughness at higher laser powers due to localized melting effects. Depth-resolved residual stress profiles were obtained via X-ray diffraction with successive material removal, indicating a pronounced rise in residual stresses up to approximately 600 MPa in certain samples treated at intermediate laser powers, followed by relaxation at the highest power due to surface melting. Microstructural characterization via electron backscatter diffraction (EBSD) revealed that elevating laser power caused changes in grain size and an almost complete dissolution of the δ-phase in the melted surface layers of samples treated at or above 250 W.
High-frequency eddy current sweeps (1–100 MHz) were calibrated using reference samples of known conductivity and controlled sensor liftoff distances, enabling the assessment of electrical conductivity changes within the surface and near-subsurface regions. Notably, the calibrated eddy current signal showed strong correlations with residual stress depth profiles and δ-phase fraction, highlighting the method’s sensitivity to thermal and microstructural modifications induced by the laser treatment. Overall, the study demonstrates the potential of high-frequency eddy current technology as an in-process or real-time monitoring tool that can capture critical SI characteristics, such as residual stress and microstructural alterations, in nickel-based superalloys. In future investigations, it is recommended to perform an eddy current scan on the untreated specimen to enhance measurement sensitivity by providing a direct baseline for comparison with the post-treatment state. Furthermore, to better approximate actual cutting conditions, upcoming experiments will incorporate purely mechanical processing via deep rolling as well as combined mechanical-thermal treatments.

## Acknowledgements

We thank the MTU Aero Engines AG for collaborating on the joint project ManuSafeNextGen within the Production Launch Center Aviation (PLCA). This research is funded by the Federal Ministry for Economic Affairs and Energy (BMWE) under project number 20N2205B (ManuSafeNextGen). Furthermore, we would like to acknowledge Maurice Walther, Bernd Krüger, and Marina Kemperle for their work on the metallographic analysis of samples and help with interpretation of results. We also thank Maurice Echterhoff for his assistance with the experimental execution and data evaluation of eddy current measurements.

## References

[1] Prevéy, P.S., Hornbach, D.J., 2019. X-Ray Diffraction Residual-Stress Techniques, in: ASM International (Ed.), Materials Characterization. ASM International, Materials Park, Ohio, pp. 440–458.

[2] Rossini, N.S., Dassisti, M., Benyounis, K.Y., Olabi, A.G., 2012. Methods of measuring residual stresses in components. Materials & Design 35, 572–588.

[3] Abu-Nabah, B.A., Nagy, P.B., 2007. High-frequency eddy current conductivity spectroscopy for residual stress profiling in surface-treated nickel-base superalloys. NDT & E International 40 (5), 405–418.

[4] Nagarajan, B., Castagne, S., Annamalai, S., Fan, Z., Chan, W.L., 2017. Effect of Microstructure on Electrical Conductivity of Nickel-Based Superalloys. Metall Mater Trans A 48 (8), 3745–3757.

[5] Hillmann, S., Schulze, M.H., Heuer, H., 2018. High-Frequency Eddy Current Techniques, in: Ida, N., Meyendorf, N. (Eds.), Handbook of Advanced Non-Destructive Evaluation. Springer, Cham, pp. 1–28.

[6] Hillmann, S., Heuer, H., Baron, H.-U., Bamberg, J., Yashan, A., Meyendorf, N., 2009. Charakterisierung oberflächennaher Eigenspannungs-Tiefenprofile an Flugzeugturbinenteilen mittels hochfrequenter Wirbelstromtechnik. Materials Testing 51 (10), 705–710.

[7] Special Metals. INCONEL® alloy 718 (UNS N07718/W.Nr. 2.4668). https://www.specialmetals.com/documents/technical-bulletins/inconel/inconel-alloy-718.pdf. Accessed 1 May 2025.