A Hybrid Approach for Nonlinear Soil-Structure Interaction Analysis of Pile- Supported Bridges
Bibliographic record
Abstract
The large-diameter reinforced concrete pile shafts are commonly designed as an economical solution for foundation of highway bridges in soft soils.The substructure method is a widely used technique for seismic SSI analysis of pile-supported bridges due to its remarkable computational efficiency.In the substructure modelling, the complexvalued impedance functions are used to represent the stiffness and energy dissipation characteristics of the soil-pile interaction system.While characteristics of the pile head impedance functions have been decently determined for linear soil-pile interaction, the effects of inelastic interaction on the impedance function still remain unclear.In fact, this study is an attempt to overcome the limitations of linear elastic soil and rigid soil-pile interface bonding assumptions that have been used in substructure analysis.This thesis aims to develop numerical and analytical frameworks to (i) investigate seismic response of a representative bridge superstructure supported by a large-diameter pile shaft under fully coupled inelastic soil-pile-structure interaction, and (ii) compute the equivalent-linear (EL) pile head impedance functions under the controlled dynamic and earthquake loading modes.Hence, a three-dimensional finite element (FE) model of the soil-pile system, as a rigorous direct method of SSI analysis is developed.The pile shaft lateral capacity is designed following to the AASHTO LRFD guidelines.The developed model is verified using data from centrifuge tests.In order to compute EL impedance functions from the continuum FE model, an algebraic solution is derived for the system of dynamic equilibrium equations in substructure analysis.In this frequency-domain solution, the Fourier transform of the force and displacement values obtained from the time-domain ii FE analysis are inserted, while the closed-form solution for the pile head impedance matrix is derived in terms of infinite series.Results of parametric FE analyses indicate that except for the extreme near-fault motions, the residual structural drift and the pile bending moment of the system would hardly exceed the design limits.The computed EL impedances provide insight into the damping evolution and stiffness reduction due to inelastic interaction over a frequency range of interest.As a key conclusion, it is shown that soil and interface inelasticity can drastically alter the impedance values compared to their fully elastic counterpart.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".