Finite Element Analysis of Buckling Capacity of Conical Steel Tanks Considering Field-measured Initiation Imperfections – A Case Study
Bibliographic record
Abstract
The geometric imperfection in elevated steel conical water tanks is a key factor that influences the buckling capacity of the tank. Current considerations of imperfections in the design of conical tanks are based on theoretical analysis, whereby the imperfection shapes and locations are assumed to have the most critical impact on the capacity. This thesis investigates the initial imperfections of an actual stiffened liquid-filled steel conical tank (LFCT) based on high-resolution laser scan measurement data of the tank geometry.\nIn the first part of this study, detailed analyses of the laser scan data were carried out to extract the global and local initial imperfections of the tank. The global imperfection represents the ovalization of the tank circumferences at difference elevations and shift of the tank central axis from the nominal central axis position. The local imperfection is the difference between the overall and global imperfections. As part of the evaluation of the tank’s structural integrity the imperfections extracted from the laser scan data are compared with specified tolerances recorded in design standards (AWWA D100-11; EN 1993-1-6: 2007, etc.) and with theoretical expressions available in the literature. Analysis results have shown that local & total imperfections exceed the tolerances specified in the design standards at several locations on the tank and the discrepancy between the imperfection wavelengths specified in the standards and observed from the data.\nIn the second part of this study, three-dimensional finite element models of the stiffened conical steel water tank were established. Initial imperfections of various shapes have been incorporated into the models, including patterns extracted from the laser scan data and assumptions from previous studies. Their impacts on the buckling capacity were analyzed by a series of elastoplastic analyses and compared with each other. Conservativeness of assumed imperfection shapes have been verified with more impact than components of field measured imperfections of higher amplitude.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".