Improved Wave Equation Analysis and Economic Impact Studies for Driven Steel Piles in Rock-Based Intermediate Geomaterials
Bibliographic record
Abstract
Abstract Assigning static and dynamic properties to rock-based Intermediate Geomaterials (R-IGMs) remains a challenge in the Wave Equation Analysis Program (WEAP) to accurately predict the pile performance during construction. This was partly attributed to the absence of reliable methods to determine pile resistances in R-IGMs. Furthermore, the recommended Smith parameters are developed based on pile load test data in soils, but not IGMs. Using 95 dynamic load test results of steel H and pipe piles from five state DOTs, improved WEAP and Load and Resistance Factor Design (LRFD) procedures are recommended for piles driven in R-IGMs. The proposed WEAP procedures are based on newly developed static analysis methods and back-calculated dynamic parameters for R-IGMs. Sixteen independent test pile data are collected to validate the recommendations. Compared to the default WEAP procedure, the proposed WEAP procedure reduces the underprediction of pile resistances by 12%, improves reliability by 5%, and yields a higher calibrated resistance factor of 0.70. Our economic impact assessment on 116 test pile data found that the proposed WEAP method yields, on average, a smaller difference in steel weight during construction based on pile types and bearing IGM types.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".