Bibliographic record
Abstract
Section 6.5.2 of N283.3-10 of the CSA Standard [1] describes analytical methods for seismic qualification of nuclear components. Clause 6.5.2.2 of this Section instructs how to prepare seismic input for the time history method, specifically it states: “Time-histories of support point motion (displacement, velocity, or acceleration) may be used as dynamic inputs to components. To take into account the effects of possible frequency variations of component and structure, the analysis shall be carried out using three different time-history excitations. These time-histories shall be obtained by varying time scale of the original support point time-history by (a) 1.0; (b) 1 - Δfj/fj; and (c) 1 + Δfj/fj, where fj = the dominant structural frequency; Δfj = a parameter defining the frequency variation due to uncertainties in structural soil properties. The most severe effects obtained from these three time history analyses shall be considered in the design of the components. Notes: (1) A value of 15% for Δfj/fj may be used for the time-history analysis specified in this Clause; (2) For structures directly on bedrock, a value of Δfj/fj = 0% may be used”. This paper identifies some ambiguities in the approach described above. It shows, by theory and examples, that significantly different responses are obtained depending on which form of excitation is used (acceleration, velocity or displacement). In a typical acceleration excitation approach, the response may be over or under estimated. To remove this ambiguity, the paper proposes a simple modification of the broadening procedure described in [1]. The problem discussed in this paper may also be meaningful for the broadening time history described in Appendix N of ASME Code [2].
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.071 | 0.017 |
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".