Design and Performance of 6.3-m-High, Block-Faced Geogrid Wall Designed Using K-Stiffness Method
Bibliographic record
Abstract
A high-density polyethylene (HDPE) geogrid soil-reinforced dry-cast concrete block retaining wall 6.3-m high was designed using the K-stiffness method as part of a highway-widening project southeast of Seattle, Washington. The amount of reinforcement needed for the original wall design using the K-stiffness method was approximately 50% of that required using the AASHTO simplified method. This paper describes the construction, instrumentation program, and interpretation of the measurements. Geogrid strains were measured using strain gauges and extensometers attached to reinforcement layers. An extensive materials testing program was conducted to characterize the backfill soil properties and geogrid stiffness properties and to calibrate strain gauge readings. The reinforcement loads deduced from the measured strains are compared with Class A, B, and C1 predictions using the AASHTO simplified and K-stiffness methods. These comparisons demonstrate that the simplified method significantly overestimated reinforcement loads, whereas the K-stiffness method provided estimates that were consistent with the measured results. This paper describes lessons learned, the influence of construction activities on wall performance, and the limitations of both methods in estimating connections loads.
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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) | 0.001 | 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".