Settlement Analysis of a Large Pile Group Supporting an LNG Storage Tank
Bibliographic record
Abstract
ABSTRACT Liquefied natural gas (LNG) storage tanks are often supported by large pile groups (>100 piles). The design of such foundations is generally governed by settlement rather than bearing capacity. However, minimal information is available regarding the settlement performance of the LNG tank foundations. This article first presents a comprehensive program of the settlement analysis for an LNG tank foundation comprising 1600 driven concrete piles. The field test program, including site characterization, pile load tests, and hydrotest, was performed. The test data were used to calibrate and assess four different methods for group settlement calculation, including the equivalent raft method, equivalent pier and equivalent raft method, nonlinear interaction factor method, and 3D continuum finite element method. The parametric analyses were further conducted using these methods to evaluate the effects of different factors on the group settlement. This study highlights (1) the importance of considering the deep soil condition (below pile toe to a depth of 1.5 times group diameter), which contributes to 78%–89% of the total settlement, (2) the drastic difference in load transfer mechanisms between central piles and perimeter piles, and (3) the need for considering the self‐weight of tanks in the settlement analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".