Evaluating Impact Resonance Testing As a Tool for Predicting Hydraulic Conductivity and Strength Changes in Cement-Stabilized Soils
Bibliographic record
Abstract
In this paper the impact resonance (IR) test method is used as a nondestructive tool to examine the curing progression, freeze/thaw (f/t) resistance, and healing potential of cement-stabilized soils. Resonant frequency (RF) measurements on specimens moist cured for up to 241 days indicate that the main portion of the hydration process is completed after about 60 days. Results of RF measurements on immature (i.e., cured for 16 days) and mature (i.e., cured for over 110 days) specimens exposed to 12 cycles of f/t indicate that the initial f/t exposure had a significant effect on the degradation of the structure. After the initial f/t cycle, some specimens exhibited continued reductions in RF values to as low as 10% of the initial measurements, while several specimens showed signs of recovery leading to minor increases in the RF values. Changes in RF values are compared with the hydraulic conductivity changes measured on the same specimens reported in a previous publication by the authors. Based on the results, a prescreening scheme is proposed that can significantly reduce the time required for f/t studies of cement-stabilized soils. Also, RF measurements after 120 days of a post-exposure healing period show a significant potential for recovery in RF values for f/t exposed specimens. However, the recoveries in RF values are not proportional to the hydraulic conductivity recovery of the specimens.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".