Effect of β-Phase on Deformation and Stress Partitioning in Zr-2.5Nb Pressure Tubes
Bibliographic record
Abstract
Abstract Zr-2.5Nb alloy is widely used in nuclear pressure tubes due to its favorable mechanical properties. The alloy consists of α-zirconium with hexagonal close-packed (HCP) crystals and a minor β-zirconium phase with body-centered cubic (BCC) crystals, mainly located between the α-grains. This study investigates the effect of β-phase grains on deformation behavior and stress partitioning in Zr-2.5Nb using crystal plasticity finite element (CPFE) modeling. The higher yield stress of β-phase grains compared to α-phase grains significantly influences stress redistribution under high plastic deformation. Two cases were analyzed: a material with random texture and a material with a preferred grain orientation (textured). The textured material exhibited anisotropic mechanical behavior, leading to greater variations in stress compared to the random texture. As plastic strain increases, the β-phase grains experience higher stresses than the surrounding α-grains. The study also examines residual stresses after unloading, showing that as macrostrain increases, the variation in residual stresses approaches that seen in the loaded state. Additionally, for a given macrostrain, hydrostatic stresses are higher in textured materials compared to randomly oriented ones when loaded along the direction of maximum material strength. These findings not only offer insights into the stress and deformation behavior of Zr-2.5Nb but also have important implications for hydrogen embrittlement, as hydrogen distribution is closely linked to the state of stress. Understanding these relationships is essential for improving the mechanical reliability and safety of nuclear pressure tube applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".