Novel nanomagnetic-based slurry for grouting fractured rocks
Bibliographic record
Abstract
In geo-engineering and underground infrastructure projects, flaws and discontinuities in rocks are typically grouted to enhance hydraulic properties, reduce permeability, and mitigate hazards. Traditional grouts, however, often exhibit poor dispersion resistance and bonding properties, highlighting the need for alternative grouting technologies for fractured rocks. Moreover, the mechanisms by which grout materials seal fractured rocks and respond to in-situ compressional stresses remain inadequately understood. This study proposes a novel nanomagnetic-based grout, characterized by its natural expansiveness, which can induce compressive stress and potentially enhance rock fracture grouting, in addition to evaluating the efficacy of this nanomagnetic slurry as a grout for rock masses, and its ability to modify bulk rock strength (uniaxial compressive strength, UCS ; Young’s modulus, E ). Mechanical properties of the rock samples were obtained via uniaxial compression tests conducted before and after grouting treatment. Microstructural analysis and material uniformity were assessed using Scanning Electron Microscopy (SEM). Additionally, changes in rock density before and after grouting were analyzed via grout flow performance to understand its flowability. The results indicate that the proposed nanomagnetic grout can significantly improve the UCS of treated samples and effectively plug fractured rocks. The optimal grout treatment, containing 15% nanomagnetic material content, resulted in greater bulk UCS by up to 42%, E by up to 31%, and bulk rock density. Further analyses suggest that the nanomagnetic grout can alter rock microstructure and ensure good material uniformity with efficient flow rates. This work provides new insights into the development of eco-friendly reinforcement and void-filling materials for mitigating geohazards around high-risk and challenging underground infrastructures by using nanomaterials, advancing rock engineering applications, and enhancing the understanding of rock grouting from a rock mechanics perspective.
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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".