Numerical Investigation of Fluid–Structure Interaction in LNG Storage Tanks under Seismic Loading
Bibliographic record
Abstract
The seismic safety of liquid-filled cylindrical storage tanks is vital for the energy infrastructure, particularly in high seismic zones.This study presents a high-fidelity finite element analysis (FEA) of LNG storage tank system, comprising an inner steel tank and outer reinforced concrete tank.Given the complex nature of fluid-structure interaction (FSI) and the risk of sloshing-induced instability during seismic events, the objective is to provide a comprehensive numerical framework to assess the structural response under realistic earthquake loading conditions.The Arbitrary Lagrangian-Eulerian (ALE) approach is employed to capture the dynamic interaction between the tank structure and the contained fluid, allowing for accurate simulation of sloshing behavior and hydrodynamic pressures.For simplicity, water is used as the infilled liquid.The Concrete Damage Plasticity (CDP) model is adopted for the concrete components to account for nonlinear material degradation under seismic loading.Although the LNG storage system modeled in this study consists of outer reinforced concrete containment, the analysis primarily focuses on the inner tank's seismic response and associated fluid-structure interaction (FSI).The simulation results reveal that while the inner steel tank maintains stable performance under static conditions, dynamic loading produces transient stresses, localized deformation, and significant sloshing wave heights.given that the dynamic loading did not result in significant damage in compression and cracks in tension in the outer tank, detailed discussion on its behavior was omitted to maintain clarity and focus on the more critical inner steel containment.These findings emphasize the critical role of FSI in amplifying structural demands and demonstrate the need to go beyond conventional static or simplified dynamic methods typically used in design codes.This study offers valuable insights into the seismic behavior of LNG tanks and contributes to the advancement of performancebased seismic design practices for critical storage infrastructure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".