Bibliographic record
Abstract
The wide spread use of limit states design procedures in both the Canadian and American steel design codes has created a need for a better understanding of how structures behave. Current design practice, however, allows and often encourages engineers to use an approximate linear analysis to determine the member forces in a structure. This is then followed by an even more approximate amplification of forces through the use of several design equations. It is believed that this practice is no longer acceptible as more accurate second-order computer programs have become a very practical alternative. With this as motivation, this thesis will provide a comparison between a second-order computer program available at the University of British Columbia called ULA (Ultimate Load Analysis) and the Canadian and American building code designs, CAN3-S16.1-M84 and LRFD 1986 respectively. It was felt that ULA should be verified, even though the theory it is based on is well established. Thus, ULA was used to generate a load versus L/r curve for a pin ended column (with the parameters modified slightly to allow direct comparison with the curves available in the codes). ULA was then used to predict load-deflection curves for two existing test frames. The resulting curves compared well with the test data. To ensure simplicity, the building codes make several approximations in the derivation of their design equations. This results in the equations being applicable to a very narrow range of structures. Specifically, the equations apply to rigidly connected frames in which all of the columns reach their critical buckling load simmultaniously. Consequently, the results from ULA were compared to the codes for structures of this type. It was found that the codes were conservative for these structures in relation to the results from ULA, yet the amount of conservatism varied greatly between structures. That is, the codes are not consistant in how conservative they are. Results from ULA were then compared to the codes for structures that do not satisfy all of the code limitations. Alhough using the codes to design structures beyond the limit of applicability is not a recommended practice, engineers do use the codes to design all types of structures, with little appreciation for the applicability limits. Consequently, it was deemed appropriate to extend this study to such structures. Though only a few were investigated, it was found that the codes were unreliable, being highly conservative, very accurate, or in one case highly unconservative when compared to the results from ULA.
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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".