An Extended Process-Zone Modeling Framework for Overload Crack Initiation in Zr-2.5Nb Pressure Tubes
Bibliographic record
Abstract
Abstract Flaws found during in-service inspection of Zr-2.5Nb pressure tubes include fuel bundle scratches, debris fretting flaws, fuel bundle bearing pad fretting flaws and crevice corrosion flaws. These flaws are volumetric and blunt in nature. Crack initiation from these in-service flaws can be caused by the presence of hydrogen in operating pressure tubes and resultant formation of hydrided regions at the flaw tips during reactor heat-up and cool-down cycles. There are two known hydride induced crack initiation mechanisms. One is delayed hydride cracking (DHC) that refers to the situations in which hydride formation and fracture occur at the same applied loads. The second crack initiation mechanism is known as overload crack initiation in a hydrided region. In this case, crack initiation occurs in the course of reactor transients when the applied stress acting on hydrided regions at flaw tips exceeds the stress at which these hydrided regions have been formed. The process-zone model was previously established to predict DHC initiation. There has been recent work to extend the process-zone model for predicting overload crack initiation in hydrided regions ahead of flaw tips. Efforts were made to identify appropriate modeling approaches for the two sequential and distinct physical stages of overload crack initiation: formation of hydrided regions with thermal cycles under constant load, and crack initiation from the pre-existing, fixed hydrided regions ahead of flaw tips under rising load (i.e. overload). The established process-zone methodology is used to model formation of hydrided regions at flaw tips with thermal cycles under constant load. A Weibull stress approach is proposed to predict fracture of the preexisting, flaw-tip hydrided regions during overload. This paper describes the extended process-zone modeling framework for overload crack initiation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".