PLANNING AND DESIGN OF INTEGRAL ABUTMENT BRIDGES UNDER SERVICE AND SEISMIC LOADS
Bibliographic record
Abstract
This course is composed of two parts. The first part will provide general information on the planning and design of integral bridges under service and seismicloads and the second part will cover dynamic analysis and seismic design of integral bridges. Integral bridges are rigid frame structures where the superstructure is connected monolithically to a flexible abutment-pile system composed of thin, stub abutments supported on a single row of piles. Therefore, the behavior of integral abutment bridges under thermal, gravitational, and seismic loads is different than that of regular jointed bridges. The first part of this course introduces (i) general planning and design considerations, (ii) implementing proper abutment backfill interaction behavior in the structural model under thermal effects, (iii) calculation of length limits of integral abutment bridges to evade low cycle fatigue failure of the steel piles (iv) estimation of live load effects in the superstructure, abutments and piles considering the continuity of the bridge and soil-structure interaction, (v) important soil-structure modeling considerations for the seismic analysis and design of integral abutment bridges. The second part of this short course will focus on explaining the dynamic behaviors of structures. The main objectives of this part are to identify dynamic problems, determine the natural frequencies of structures, establish the equations of motion, stiffness, and mass for structures and introduce the seismic analysis methods for structures. Seismic analyses and design methods adopted inthe Canadian codes and standards will be presented and applied to integral abutment bridges. Critical parameters impacting seismic design for new bridges and rehabilitation of existing structures will be introduced and discussed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".