Bibliographic record
Abstract
This thesis presents a study of the efficiency and economy of post-tensioned concrete bridges.It is an initial step towards a broader goal of providing designers with a rational basis for assessing the efficiency of designs and for linking efficiency in design with economy. The approach consisted first of establishing a set of parameters defining the primary characteristics of the bridge type considered, simply-supported slab and multiple-T systems. Within a defined range of parameter values, designs were generated and checked against applicable safety and serviceability criteria. Over 10^13 combinations of geometric parameters were considered, each of which defined a feasible bridge. From these bridges, two efficient sets were extracted according to two separate measures of efficiency: (1) minimum quantity of concrete, measured by reference depth, the ratio of the cross-sectional area and deck width, and (2) minimum quantity of prestressing steel, measured by the ratio of the prestressing steel cross-section and deck width. From these bridges, an economical set was also extracted based on minimum total construction cost. These sets were examined to determine their most significant characteristics to identify parameters most closely associated with efficiency and economy. The number of webs in all three sets is approximately equal to deck width divided by 3.5 m. Span to depth ratio lies between 18 and 25 for minimum concrete, and is approximately 8 for minimum prestressing steel. The intersection of the two efficient sets is empty. This research identified circumstances under which efficiency also results in economy in a design. Two design strategies were identified for the bridge type considered in this study: (1) minimizing reference depth to within 10% of the minimum established in this research, (2) set span-to-depth ratio to a value between approximately 20 and 30, and minimize the quantity of prestressing steel to within 10% of the minimum established in this research for the given span, width, and span-to-depth ratio. The efficient sets have lower quantities of concrete and prestressing steel than comparable recently built bridges. Number of webs and span-to-depth ratios of the efficient and economical sets differ from published recommendations from eminent designers.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".