Experimental Investigation on the Behavior of Iron Powder‐Reinforced Sand under Electromagnetic Field
Bibliographic record
Abstract
Applications of soil improvement have proliferated in recent years. To date, we have limited studies on the quantitative analyses of the autoadaptive material and specifically to model its stress‐strain relationship. This paper explored an autoadaptive material, iron‐powdered Ottawa sand, which was temporarily solidified by applying an electromagnetic field. A series of compression triaxial tests were carried out with various relative densities of specimens (60% and 80%), in four electromagnetic fields (0 A, 0.5 A, 1 A, and 2 A) and under three confining pressures (103 kPa, 206 kPa, and 310 kPa). The test results indicate that the strength of specimens increased while initial stiffness and brittleness reduced by adding iron powder. Moreover, the strength of the specimens increased by increasing the magnitude of the applied electromagnetic field. The behavior of the iron‐powdered sand was described by using a revised Duncan–Chang model. The revised model was evaluated by comparing the simulated results with the corresponding test data. The comparison showed that the revised model can better capture the nonlinear stress‐strain behavior of the specimens. With the application of the revised Duncan–Chang model, the standard error of the estimate between the experimental and predicted results is lowered down to 0.39 from 4.7. Future research is geared towards practical applications for temporary solidification of soil.
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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".