Updating Standard Shape Material Properties Database for Design and Reliability
Bibliographic record
Abstract
This paper summarizes the mechanical properties of ASTM A992 steel as determined by tests of 207 flatstrap tensile test specimens at the University of Minnesota and the University of Western Ontario carried out in accordance with ASTM A370. Samples were obtained from 38 heats of steel from eight different shapes provided by three producers. The objectives of the study were to quantify statistical parameters for the mechanical properties of A992 steel and to investigate the necessity of updating the resistance factor for steel in the AISC LRFD Specification (AISC, 1999). The lower tail of the yield strength data is accurately represented by the lognormal distribution reported by Dexter, Graeser, Saari, Pascoe, Gardner, and Galambos (2000). The ratio of the observed yield stress to the corresponding value reported on the Mill Test Report averaged 1.002, with a coefficient of variation of 0.044. The ratio of the flange yield strength to web yield strength averaged 0.95. The difference between the static yield strength and the yield strength recorded at ASTM A370 strain rates averaged 4.4 ksi. It is concluded that A992 steel has smaller bias coefficients and smaller coefficients of variation compared to the parameters for A36 steel used in the original calibration that have increased the reliability index slightly. At the AISC LRFD calibration point of a live-to-dead ratio of three, the reliability index for a braced compact beam with a resistance factor of 0.9 increases from 2.5 to 2.6 if the discretization factor is ignored or to 2.8 if the discretization factor is included. However, an increase of resistance factor from 0.90 to 0.95 is not recommended without further study.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.036 |
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".