Earthquake Resistance Optimization and Evaluation of Bridge Piers Structural Form and Dimensions Based on Demand to Capacity Ratio and Yielding Points of Force-Displacement
Bibliographic record
Abstract
The evaluation of structural safety must be taken after each earthquake. The importance losses of life and materials carries the significance of the works in the field of earthquake engineering. The purpose of this study was to optimize and evaluate the earthquake resistance of bridge piers by adopting different cross-section forms and dimensions for bridge supports under earthquake action. Two methods of seismic design were used in the optimization and evaluation process. These methods were demand to capacity ratio (DCR) and yielding point. The results of demand to capacity ratio shown that the values of DCR for all piers forms models were increased when the dimension of pier cross section were increased and the values of DCR became less than 1.0, indicating that the increasing in dimensions leading to rise the capacity of bridge supports to carry the earthquake loads in transverse and longitudinal direction. Comparing with models, solid wall pier form had the lower value of DCR, indicating that solid wall piers were suitable in the design of bridge supports to resist the lateral loads of earthquake and it has enough stiffness and capacity under earthquake action. The results of performance points shown that the yielding points were increased when the dimensions of piers were increased for all piers form in transverse and longitudinal direction. The maximum values were appeared within support No. 1 and support No. 4. Solid wall form of pier had the higher values of yielding points, meaning that this type of piers form had higher seismic capacity and it will resist the earthquake action more than others piers form. This study recommended that to use third model for each pier form in the design of bridges structures to resist the earthquake load. Also this study was recommended to use solid wall piers as supports in construction of bridge structure within areas had earthquake action.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".