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Analysis of the potential use of the passive magnetic method for detecting defects in welded joints made of X2CrNiMo17-12-2 steel

  • Tomasz Mucha EMAIL logo , Maciej Roskosz , Arkadiusz Złocki and Jerzy Kwaśniewski
Published/Copyright: June 7, 2025
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Open Engineering
From the journal Open Engineering Volume 15 Issue 1

Abstract

This study aims to analyze the feasibility of using the passive magnetic method for detecting welding defects in tubular joints made of X2CrNiMo17-12-2 steel, with dimensions of an outside diameter 48.30 mm and a wall thickness of 2.77 mm, manufactured using the tungsten inert gas arc welding technique. The tests included preparing welded joints meeting the quality level B criteria according to EN-ISO 5817 standards, as well as joints containing defects such as lack of fusion, excessive penetrations, poor restarts, gas pores, and tungsten inclusions. Radiographic tests and measurements of the components of the self-magnetic flux leakage (SMFL) were performed. A comparison of the radiographic and magnetic test results demonstrated a correlation between the presence of defects in tubular welded joints and the values of the magnetic signal generated at their locations. SMFL measurements showed significant differences between joints meeting quality requirements and those with welding defects. This confirms the effectiveness of this method as a screening method for non-destructive testing of welded joints.

Keywords: non-destructive testing; austenitic steel; TIG welding; welding defects; delta ferrite; residual magnetic field

1 Introduction and research objective

X2CrNiMo17-12-2 steel, an austenitic grade, is widely used in chemical, refinery, energy, pharmaceutical, and food industries due to its excellent mechanical properties and exceptional corrosion resistance [1,2]. It is a key material for installations requiring high strength and tightness, such as pipelines for chemical transportation or devices operating in aggressive environments. Its properties make it the preferred choice for applications where reliability and durability are paramount [1,3,4].

Welding processes for austenitic steels, including X2CrNiMo17-12-2, particularly tubular joints, are crucial for ensuring structural strength and tightness. Tungsten inert gas (TIG) welding is one of the most commonly used methods, allowing for high-quality welds through precise control of process parameters such as welding current and sequence of bead deposition, which significantly minimize distortions. Orbital welding further enables durable connections while ensuring repeatability and aesthetic joint appearance, as presented by Dak et al. [5], Akowua et al. [6], Widyianto et al. [7], and Tabrizi et al. [8]. Moreover, Górka et al. [2] demonstrated that orbital welding without the use of filler material allows for the production of welds that meet quality criteria and contain a sufficient amount of delta ferrite, which prevents hot cracking and maintains optimal mechanical properties.

Assessing the efficiency of material bonding primarily depends on the effectiveness of detecting defects formed during or after welding. Traditional volumetric diagnostic methods, such as radiographic and ultrasonic techniques, dominate but are time-consuming, require specialized equipment, and do not allow for the determination of stress conditions. Therefore, the search for alternative non-destructive methods with high sensitivity and low operating costs is particularly important for the industry. In this context, methods utilizing magnetic signals offer a valuable solution [9,10,11,12].

In austenitic steels, such as X2CrNiMo17-12-2, residual stresses and phase martensitic transformations contribute to changes in the magnetic field distribution. Although austenitic steels are typically non-magnetic, they can exhibit magnetic properties due to plastic deformation, welding processes, or cooling, leading to the formation of martensitic phase or delta ferrite. Dubov et al. [13] demonstrated that this phenomenon can affect the microstructure and mechanical properties of welds, as well as the material’s response in non-destructive testing. The transformation of austenite into martensite under stress generates magnetic signals that can be utilized for defect detection in the early stages of material fatigue [14,15].

The aforementioned delta ferrite directly affects the weld’s resistance to hot cracking, its mechanical properties, and corrosion resistance [2]. It is determined using magnetic methods, such as ferrite meter measurements or microstructural analysis via optical and electron microscopy or by means of stereological methods, for example, using the Schaeffler diagram [16]. It is widely used in materials engineering to predict the microstructure of welds based on their chemical composition. It relies on chromium and nickel equivalents to determine the balance between austenite and ferrite in the weld metal. This diagram has been crucial for understanding and controlling delta ferrite content in welds, influencing mechanical properties and corrosion resistance. Its developments, such as the DeLong and WRC-1992 diagrams, also enable predictions of material behavior during welding and operation [17,18].

Non-destructive testing of welded joints using the passive magnetic method for both ferromagnetic and austenitic steels has gained significance due to its ability to detect stress concentration areas and micro-defects without magnetizing the elements. This method utilizes the residual magnetic field (RMF) intensity of the tested object as a diagnostic signal. Roskosz [19], in previous research studies, demonstrated that RMF measurements do not guarantee the same effectiveness in detecting discrepancies at the production stage as the radiographic method used as the reference technique. However, it is more effective for detecting defects in already operational welds. Weld imperfections that concentrate stresses from operational loads cause magnetic anomalies. Dubov and Kolokolnikov [11] proved that the presence of welding inconsistencies such as lack of fusion, gas pores, or tungsten inclusions in newly formed welds can be a factor causing magnetic anomalies. This method has potential for quickly detecting potentially hazardous areas, including microstructural inhomogeneities and residual stresses post-welding, making it a valuable tool in industrial diagnostics of welded joints [4,20,21].

The objective of this article is to analyze the potential application of the passive magnetic method for detecting defects in tubular joints made of X2CrNiMo17-12-2 steel. The research focuses on evaluating the relationship between the results obtained through the magnetic method and traditional radiographic tests, allowing the determination of the effectiveness and limitations of this new approach under industrial conditions.

2 Methods and experimental

The research was conducted on tubular welded joints with dimensions of an outside diameter of 48.30 mm and a wall thickness of 2.77 mm, made of X2CrNiMo17-12-2 (316L) steel, an austenitic grade. The chemical composition of the steel is presented in Table 1. The welding samples were manufactured using the TIG arc welding technique (process 141 according to EN-ISO 4063) with a filler rod supplied by Certilas under the trade name Ceweld 316LSi Tig (designation per EN-ISO 14343-A: W 19 12 3 LSi). The welded joints tested included those meeting the quality level B criteria of EN-ISO 5817 and those with defects such as lack of fusion (401 per EN-ISO 6520-1), poor restarts (517 per EN-ISO 6520-1), gas pores (2011 per EN-ISO 6520-1), excessive penetrations (504 per EN-ISO 6520-1), and tungsten inclusions (3041 per EN-ISO 6520-1).

Table 1

Chemical composition of X2CrNiMo17-12-2 steel according to the material certificate

Chemical composition (%)
Steel type Number C Cr Mn Mo N Ni P S Si
X2CrNiMo17-12-2 1.4404 0.019 16.770 1.250 2.040 0.031 11.130 0.036 0.009 0.460

Radiographic testing was conducted following the guidelines outlined in EN-ISO 17636-2:2022 using a Teledyne ICM/Site-X CP200DS X-ray machine, Carestream INDUSTREX Flex XL Blue image plates (100 × 480 mm), a Carestream Industrex HPX-1 scanner, and a Carestream INDUSTREX HP Z4 Workstation. The evaluation was performed using a double-wall penetration and double-image technique with the source and detector located outside the object (diagram 11 of EN-ISO 17636-2:2022). For each welded joint, two exposures were performed approximately 90° apart. The exposures were labeled A and B, and the symbols are visible on the radiogram along the pipe’s longitudinal axis. On the radiographs, the measurement locations for the image quality indicator (W) and the SNR are marked using green arrows. An example set of radiograms for one weld is shown in Figure 1.

Figure 1 Example set of radiograms ((a) exposures A and (b) B) for the weld marked as S2.1.
Figure 1

Example set of radiograms ((a) exposures A and (b) B) for the weld marked as S2.1.

Delta ferrite content on the weld surface was determined following the guidelines of EN-ISO 8249:2018-11 using the FMP30 ferrite content measuring instrument and the FGAB1.3-Fe probe from Fischer. The measurement range of the ferrite meter was 0.1 to 80% Fe or 0.1 to 110 ferrite number (FN). On the prepared surface, 24 readings (every 15° around the pipe’s circumference) were taken along the longitudinal axis of the weld bead. The measurement point corresponding to 0° on the diagrams was assumed to be at the position of exposure A. The measured value was expressed as an FN.

The obtained results were compared with values determined analytically using the Schaeffler diagram, assuming a weld metal contribution of 60% in the welded joint, and through the metallographic method. The value calculated based on the Schaeffler diagram is presented in Figure 2. The measurement of delta ferrite content by the metallographic method was conducted on photomicrographs representative of a given weld section using a Zeiss Neophot 32 microscope, following the guidelines outlined in ASTM E 562. The chemical reagent used for etching – 20% NaOH – selectively stained delta ferrite dark, while other structural components remained unexposed. The microstructures and masks from the conducted studies at optical magnifications of parent material and weld face of ×200 are presented in Figure 3 and confirmed the presence of delta ferrite in the weld joint. The amount of delta ferrite in the microstructure of the parent material (Figure 3a and b) is on a much lower level than in the weld face (Figure 3c and d).

Figure 2 Schaeffler diagram for X2CrNiMo17-12-2 steel with 60% weld metal contribution.
Figure 2

Schaeffler diagram for X2CrNiMo17-12-2 steel with 60% weld metal contribution.

Figure 3 Visualization of delta ferrite content in parent material and weld face of welded joint of X2CrNiMo17-12-2 steel using the metallographic method: (a) parent material microstructure mag. ×200; (b) parent material mask mag. ×200; (c) weld face microstructure mag. ×200; and (d) weld face mask mag. ×200.
Figure 3

Visualization of delta ferrite content in parent material and weld face of welded joint of X2CrNiMo17-12-2 steel using the metallographic method: (a) parent material microstructure mag. ×200; (b) parent material mask mag. ×200; (c) weld face microstructure mag. ×200; and (d) weld face mask mag. ×200.

Self-magnetic flux leakage (SMFL) measurements were conducted using a TSC-1M-4 magnometer with 12-channel measurement sensor No. 6-12M-206 with a maximum scanning speed of 1 m/s, manufactured by Energodiagnostika Co. Ltd., Moscow (Russia). The range of the sensor is ±2,000 A/m with a resolution of 1 A/m. The instrument was calibrated in the Earth’s magnetic field, with a value assumed to be 40 A/m. Magnetic field measurements were performed in 1 mm increments along lines parallel to the weld axis, spaced 7 mm apart. The examined area included the weld and heat-affected zone, with measurements taken from the weld bead’s face. During the tests, the sensor remained stationary while the sample was rotated. A special holder designed for the geometry of the tested object was constructed and used for measurements. The holder and measurement setup are shown in Figure 4. The background values of magnetic field components were subtracted from the obtained results.

Figure 4 Measurement setup equipped with 12-channel sensor No. 6-12M-206. Description of measurement station: 1 – base, 2 – lower support for the measurement sensor, 3 – mounting bracket for the lower springs and measurement sensors, 4 – mounting bracket for the upper springs, 5 – measurement sensors, 6 – springs, 7 – screw for setting the position in the horizontal direction, 8 – screw for setting the position in the vertical direction, 9 – screws for fixing the positions of the brackets, 10 – measurement trolley on wheels, 11 – pipe with an external diameter of 48.30 mm, and 12 – pipe with an external diameter of 60.30 mm.
Figure 4

Measurement setup equipped with 12-channel sensor No. 6-12M-206. Description of measurement station: 1 – base, 2 – lower support for the measurement sensor, 3 – mounting bracket for the lower springs and measurement sensors, 4 – mounting bracket for the upper springs, 5 – measurement sensors, 6 – springs, 7 – screw for setting the position in the horizontal direction, 8 – screw for setting the position in the vertical direction, 9 – screws for fixing the positions of the brackets, 10 – measurement trolley on wheels, 11 – pipe with an external diameter of 48.30 mm, and 12 – pipe with an external diameter of 60.30 mm.

3 Results and analysis

This section presents the results of the conducted research, including the analysis of weld quality based on ferrite content measurements, radiographic testing, and SMFL measurements. The results are discussed separately for welds meeting the EN-ISO 5817 quality level B criteria and those containing welding defects. Additionally, a comparative assessment of radiographic and magnetic test results is provided to evaluate the effectiveness of the passive magnetic method in detecting welding discontinuities.

3.1 Weld samples meeting the quality level B criteria according to EN-ISO 5817

Figures 5–7 present the results of radiographic tests. Fragments of yellow letters and numbers are excerpts from full-size radiograms and describe measurement data. From the perspective of assessing the location of welding inconsistencies, they have no impact; however, they have been retained to avoid interference with the original radiographic image.

Figure 5 Radiogram of the welded joint S22: (a) exposure A and (b) exposure B.
Figure 5

Radiogram of the welded joint S22: (a) exposure A and (b) exposure B.

Figure 6 Radiogram of the welded joint S23: (a) exposure A and (b) exposure B.
Figure 6

Radiogram of the welded joint S23: (a) exposure A and (b) exposure B.

Figure 7 Radiogram of the welded joint S24: (a) exposure A and (b) exposure B.
Figure 7

Radiogram of the welded joint S24: (a) exposure A and (b) exposure B.

In Figures 8–10, the results of delta ferrite content measurements, expressed as FN, are presented.

Figure 8 Distribution of FN along the circumference of the welded joint S22.
Figure 8

Distribution of FN along the circumference of the welded joint S22.

Figure 9 Distribution of FN along the circumference of the welded joint S23.
Figure 9

Distribution of FN along the circumference of the welded joint S23.

Figure 10 Distribution of FN along the circumference of the welded joint S24.
Figure 10

Distribution of FN along the circumference of the welded joint S24.

Figures 11–13 present the results of measurements of the normal component H N (green), the tangential component H T (red), and their gradients.

Figure 11 Distributions of (a) RMF component values and (b) their gradients for the welded joint S22.
Figure 11

Distributions of (a) RMF component values and (b) their gradients for the welded joint S22.

Figure 12 Distributions of (a) RMF component values and (b) their gradients for the welded joint S23.
Figure 12

Distributions of (a) RMF component values and (b) their gradients for the welded joint S23.

Figure 13 Distributions of (a) RMF component values and (b) their gradients for the welded joint S24.
Figure 13

Distributions of (a) RMF component values and (b) their gradients for the welded joint S24.

3.2 Weld samples with imperfections

Figures 14–19 present the results of radiographic tests. The fragments of green arrows are excerpts from full-size radiographs and indicate the measurement location of the SNR. From the perspective of assessing the location of welding discontinuities, they have no impact; however, they have been retained to avoid any interference with the original radiographic image.

Figure 14 Radiogram of the welded joint S2.1: (a) exposure A and (b) exposure B.
Figure 14

Radiogram of the welded joint S2.1: (a) exposure A and (b) exposure B.

Figure 15 Radiogram of the welded joint S2.2: (a) exposure A and (b) exposure B.
Figure 15

Radiogram of the welded joint S2.2: (a) exposure A and (b) exposure B.

Figure 16 Radiogram of the welded joint S2.3: (a) exposure A and (b) exposure B.
Figure 16

Radiogram of the welded joint S2.3: (a) exposure A and (b) exposure B.

Figure 17 Radiogram of the welded joint S2.4: (a) exposure A and (b) exposure B.
Figure 17

Radiogram of the welded joint S2.4: (a) exposure A and (b) exposure B.

Figure 18 Radiogram of the welded joint S2.5: (a) exposure A and (b) exposure B.
Figure 18

Radiogram of the welded joint S2.5: (a) exposure A and (b) exposure B.

Figure 19 Radiogram of the welded joint S2.6: (a) exposure A and (b) exposure B.
Figure 19

Radiogram of the welded joint S2.6: (a) exposure A and (b) exposure B.

Figures 20–25 present the results of delta ferrite content measurements, represented by the FN, in the form of its distribution along the circumference of the welded joint.

Figure 20 Distribution of FN along the circumference of the welded joint S2.1.
Figure 20

Distribution of FN along the circumference of the welded joint S2.1.

Figure 21 Distribution of FN along the circumference of the welded joint S2.2.
Figure 21

Distribution of FN along the circumference of the welded joint S2.2.

Figure 22 Distribution of FN along the circumference of the welded joint S2.3.
Figure 22

Distribution of FN along the circumference of the welded joint S2.3.

Figure 23 Distribution of FN along the circumference of the welded joint S2.4.
Figure 23

Distribution of FN along the circumference of the welded joint S2.4.

Figure 24 Distribution of FN along the circumference of the welded joint S2.5.
Figure 24

Distribution of FN along the circumference of the welded joint S2.5.

Figure 25 Distribution of FN along the circumference of the welded joint S2.6.
Figure 25

Distribution of FN along the circumference of the welded joint S2.6.

Figures 26–31 present the results of measurements of the normal component H N (green), the tangential component H T (red), and their gradients.

Figure 26 Distributions of RMF component values and their gradients for the welded joint S2.1: (a) distributions of components and (b) distributions of gradients.
Figure 26

Distributions of RMF component values and their gradients for the welded joint S2.1: (a) distributions of components and (b) distributions of gradients.

Figure 27 Distributions of RMF component values and their gradients for the welded joint S2.2: (a) distributions of components and (b) distributions of gradients.
Figure 27

Distributions of RMF component values and their gradients for the welded joint S2.2: (a) distributions of components and (b) distributions of gradients.

Figure 28 Distributions of RMF component values and their gradients for the welded joint S2.3: (a) distributions of components and (b) distributions of gradients.
Figure 28

Distributions of RMF component values and their gradients for the welded joint S2.3: (a) distributions of components and (b) distributions of gradients.

Figure 29 Distributions of RMF component values and their gradients for the welded joint S2.4: (a) distributions of components and (b) distributions of gradients.
Figure 29

Distributions of RMF component values and their gradients for the welded joint S2.4: (a) distributions of components and (b) distributions of gradients.

Figure 30 Distributions of RMF component values and their gradients for the welded joint S2.5: (a) distributions of components and (b) distributions of gradients.
Figure 30

Distributions of RMF component values and their gradients for the welded joint S2.5: (a) distributions of components and (b) distributions of gradients.

Figure 31 Distributions of RMF component values and their gradients for the welded joint S2.6: (a) distributions of components and (b) distributions of gradients.
Figure 31

Distributions of RMF component values and their gradients for the welded joint S2.6: (a) distributions of components and (b) distributions of gradients.

3.3 Analysis of test results

3.3.1 Analysis of FN

The FN measurement results shown in Figures 8–10 for welded joints meeting the quality requirements of level B, as well as the results for joints with welding inconsistencies, do not show any differences. This indicates that ferrite number measurements cannot serve as a diagnostic indicator for assessing weld quality in terms of the presence of surface and volumetric welding inconsistencies.

3.3.2 Analysis of RMF component values and their gradients

In Table 2, the minimum and maximum values of the normal component H N and tangential component H T, as well as the maxima of their gradients, are summarized. Based on the obtained results, it was found that for samples with welding defects, the values of individual parameters are significantly higher than for samples meeting the quality level B criteria according to EN-ISO 5817.

Table 2

Minimum and maximum values of the normal component H N and tangential component H T, as well as the maxima of their gradients

Sample number H N (A/m) H T (A/m) Max gradient H N (A/m/mm) Max gradient H T (A/m/mm)
Min Max Min Max
22 −19 30 −20 15 14 12
23 −31 28 −19 17 14 11
24 −29 14 −23 10 9 10
S2.1 −595 215 −293 237 182 146
S2.2 −897 346 −438 325 189 194
S2.3 −860 369 −481 324 317 211
S2.4 −789 237 −332 385 153 161
S2.5 −38 37 −18 31 17 20
S2.6 −87 121 −36 43 50 25

For samples meeting the quality level B criteria, the range of the normal component H N varies from −31 to 30 A/m, the tangential component H T from −23 to 17 A/m, and the maximum gradients for the normal component H N reach 14 A/m/mm, while for the tangential component H T, they reach −12 A/m/mm. For samples with defects, the variability range of the components is always greater than for the compliant samples. This is particularly evident for samples S2.1–S2.4, where the difference is an order of magnitude larger. A similar relationship exists for the gradient values. For samples S2.5 and S2.6, the variability range of the H N and H T components is also greater than in compliant samples, but the changes are significantly smaller compared to samples S2.1–S2.4.

Considering the component field values and gradient values as diagnostic signals, a clear boundary can be drawn between compliant samples and those with defects. This boundary can be treated as a criterion for assessing the quality of welded joints.

3.3.3 Comparison of the locations of welding inconsistencies and magnetic anomalies

In non-destructive testing of welded joints, the objective, in addition to determining the quality class of the weld joint, is also to identify the location of inconsistencies that determine the weld quality level. This is because a non-conforming welded joint may undergo repair, and the repair site should be precisely located. In Table 3, the locations of welding defects detected using the radiographic method, areas of magnetic anomaly concentration with the highest values for each weld, and the ranges of magnetic indications recorded in individual welds are summarized.

Table 3

Comparison of the locations of welding defects detected using the radiographic method, areas of magnetic anomaly concentration with the highest values for each weld, and the ranges of magnetic indications recorded in individual welds

Sample number Radiographic test Magnetic test Magnetic test
Location of defects (in °, where 0° corresponds to the upper part of the weld in line with the letter A) Maximum values from component and gradient distributions Range of magnetic anomalies potentially related to the presence of defects
S2.1 90–100 90 330–30, 50–150
S2.2 150–160 195 90–255
S2.3 30–45 30 0–360
S2.4 170–190 345 270–45
S2.5 115–145, 195–225 75 285–90
S2.6 345–15 240 0–360

In two cases, for welds S2.1 and S2.3, where the identified welding defects were excessive penetrations (504 according to EN-ISO 6520-1), the defect locations on the radiogram coincide with the maximum recorded magnetic signal values for the respective welds. In weld S2.2, the maximum recorded value is located in a different position than the welding defect of poor restart (517 according to EN-ISO 6520-1) identified on the radiogram. However, the values measured at the defect location reach 70–80% of the maximum magnetic signal value. In welds S2.4 and S2.5, where gas pores (2011 according to EN-ISO 6520-1) and tungsten inclusions (3041 according to EN-ISO 6520-1) were, respectively, detected, significant magnetic signal values were practically not recorded at the defect locations, or they were at a minimal level. In weld S2.6, where a lack of fusion (401 according to EN-ISO 6520-1) was detected, the highest recorded magnetic signal value is also located in a different position. Based on the analyzed results, we cannot definitively conclude that the maximum magnetic anomaly occurs at the location of the defect. However, at the defect location, the signal value reaches 60–70% of the maximum magnetic signal value.

4 Conclusions

The analysis results, derived from both the Schaeffler diagram and ferrite meter measurements, indicate the presence of delta ferrite in the structure of welded joints. Delta ferrite, due to its magnetic properties, can serve as a carrier of diagnostic information, offering potential for its application in the non-destructive quality assessment of welded joints. Its detection and analysis can provide the basis for early identification of potential defects.

Despite differences in the quality of welded joints, the FN for samples meeting quality criteria and for joints containing welding defects remains at a comparable level. This suggests that FN, as a single diagnostic parameter, may not be sufficient to unequivocally distinguish compliant joints from those with defects. This underscores the need to combine this method with other testing techniques.

SMFL, which appears in the welded joint due to the presence of delta ferrite, revealed significant differences between joints meeting quality requirements and those with welding defects. This confirms the effectiveness of this method in detecting local anomalies associated with welding defects such as excessive penetrations, lack of fusion, or poor restart. This method can be particularly useful in industrial applications, where speed and diagnostic accuracy are critical.

A comparative analysis of magnetograms and radiograms revealed certain similarities in the locations of some types of welding defects. However, the lack of complete correlation highlights the complexity of interpreting the results of both methods. Magnetic anomalies do not always precisely coincide with the locations of welding defects visible on radiograms, suggesting the need for further research to improve detection accuracy in both techniques.

Although it is not always possible to precisely locate defects in a weld in every examined case, a clear difference in the values of magnetic signals recorded in welds with defects and those meeting quality criteria is evident. This supports the use of magnetic testing as a screening method to identify welds with potential defects.

SMFL and its anomalies appeared on the surface of the austenitic welded joint due to the existence of delta ferrite in the microstructure. Roskosz [19] highlights the potential of magnetic measurements in assessing welded joints during their operational phase. Over time, welding inconsistencies may develop in welded joints (either those that initially met quality criteria during manufacturing or those undetectable due to the sensitivity of a given method). Combining these findings, it can be assumed that SMFL measurements in operational austenitic joints could be a promising diagnostic method. However, further research is required to confirm this potential.

,

Acknowledgments

This article was developed under the “Implementation Doctorate” programme funded by the Ministry of Science and Higher Education of the Republic of Poland.

  1. Funding information: Authors state no funding involved.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and consented to its submission to the journal, reviewed all the results and approved the final version of the manuscript. TM: data acquisition, methodology, writing, visualization, and interpretation; MR: methodology, conceptualization, writing – reviewing and editing, guidance, critical revision, and interpretation; AZ: methodology, visualization, validation, and interpretation, JK: methodology and critical revision.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Data availability statement: All data generated or analyzed during this study are included in this published article.

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Received: 2025-01-23
Revised: 2025-03-16
Accepted: 2025-03-28
Published Online: 2025-06-07

© 2025 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/eng-2025-0116
Keywords for this article
non-destructive testing; austenitic steel; TIG welding; welding defects; delta ferrite; residual magnetic field
Creative Commons
BY 4.0

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