Through‐Thickness Residual Stresses, Microstructure, and Mechanical Properties of Electron Beam‐Welded CA6NM Martensitic Stainless Steel after Postweld Heat Treatment
Bibliographic record
Abstract
In this study, the integrity of electron beam‐ (EB‐) welded CA6NM—a grade of 13% Cr‐4% Ni martensitic stainless steel—was assessed through the entire joint thickness of 90 mm after postweld heat treatment (PWHT). The joints were characterized by examining the microstructure, residual stresses, global mechanical properties (static tensile, Charpy impact, and bend), and local properties (yield strength and strain at fracture) in the metallurgically modified regions of the EB welds. The applied PWHT tempered the “fresh” martensite present in the microstructure after welding, which reduced sufficiently the hardness (<280 HV) and residual stresses (<100 MPa) to meet the requirements for hydroelectric turbine assemblies. Also, the properties of the EB joints after PWHT passed the minimum acceptance criteria specified in ASME sections VIII and IX. Specifically, measurement of the global tensile properties indicated that the tensile strengths of the EB welds in the transverse and longitudinal directions were on the same order as that of the base metal (BM). Evaluation of the local tensile properties using a digital image correlation (DIC) methodology showed higher local yield strengths in the fusion zone (FZ) and heat‐affected zone (HAZ) of 727 MPa and 740 MPa, respectively, relative to the BM value of 663 MPa. Also, the average impact energies for the FZ and HAZ were 63 J and 148 J, respectively, and attributed to the different failure mechanisms in the HAZ (dimples) versus the FZ (quasi‐cleavage consisting of facets and dimples). This study shows that the application of PWHT plays an important role in improving the weld quality and performance of EB‐welded CA6NM and provides the essential data for validating the design and manufacturing process for next‐generation hydroelectric turbine products.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".