A time‐domain seismic SSI analysis method for inelastic bridge structures through the use of a frequency‐dependent lumped parameter model
Bibliographic record
Abstract
Summary It is highlighted in the past that the soil–structure interaction phenomenon can produce a significant alteration on the response of a bridge structure. A variety of approaches has been developed in the past, which is capable of tackling the soil–structure interaction problem from different perspectives. The popular approach of a discretized truncated finite element model of the soil domain is not always a numerically viable solution, especially for computationally demanding simulations such as the probabilistic fragility analysis of a bridge structure or the real time hybrid simulation. This paper aims to develop a complete modeling procedure that is capable of coping with the soil–structure interaction problem of inelastic bridge structures through the use of a frequency dependent lumped parameter assembly. The proposed procedure encounters accuracy and global stability issues observed on past methods while maintaining the broad applicability of the method by any commercial FEM software. A case study of an overpass bridge structure under earthquake excitations is illustrated in order to verify the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".