Performance-Based Assessment of a Guyed Incinerator Stack Using Field Measurements
Bibliographic record
Abstract
Abstract ASME STS-1 provides guidelines for the design, fabrication, and erection of steel stacks, however there are no specific guidelines for the assessment of guyed steel stacks already in service. For example, drift (i.e., displacement) acceptance criteria are only provided for initial installation. Furthermore, existing literature regarding the proper re-tensioning of guy wires is scarce or nonexistent. This procedure is particularly important for stacks that experience significant thermal growth. This effect is further exacerbated by differential wind cooling effects on both the guy wires and on the stack itself. This paper investigates the effect of guy wire spacing, position, tension pattern, and operating and shutdown tension settings on the structural response of a guyed steel stack. Field thermography readings, ultrasonic testing (UT) thickness data, guy wire tension measurements, and laser scans are used to refine a finite element model of the stack. Using elastic-plastic nonlinear “pushover” analyses based on API 579 – 1 Level 3 fitness-for-service methodology and FEMA 356 rehabilitation guidelines, a performance-based methodology resulting in a “watch circle” approach for lateral displacement is provided to guide fitness-for-service assessments and mitigation implementation. Example application of this methodology and recommendations regarding guy wire tensioning are provided for an incinerator stack with 9 guy wires (3 levels – 3 guy wire configuration).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".