HPMC viscous fluid for centrifuge modelling
Bibliographic record
Abstract
Dynamic pile installation is a challenging aspect of the realization of offshore infrastructure. Due to the large-scale and specialized hardware involved, researchers have resorted to centrifuge modelling to study this process at a manageable scale and in a controlled environment. However, in centrifuge models, a discrepancy between the dynamic and diffusive timescales is introduced. By using a viscous fluid, the discrepancy is mitigated, thereby synchronizing both timescales. Hydroxypropylmethylcellulose (HPMC) is a versatile and affordable thickening agent, widely used in centrifuge modelling of dynamic processes. However, the rheological behavior of HPMC solutions can vary based on the type of HPMC and the solution concentration. This study investigates how the rheological behavior of HPMC solutions is influenced by the concentration and the type of HPMC. We present a detailed preparation protocol for preparing aqueous HPMC solutions and propose a generic power-law function that unifies experimental results from our study and those of previous works. We investigate the implications of varying degrees of shear thinning, as observed across different HPMC products, by examining the pore pressure response during the dynamic installation of a pile in dense sand saturated with fluids of similar dynamic viscosity. Our findings support the use of viscous fluids for studying dynamic events in the centrifuge but also emphasize the importance of selecting a viscous fluid whose rheology does not vary considerably within the range of expected shear rates. In broader terms, this work streamlines the manufacturing of viscous fluids for use in the centrifuge and advances research efforts related to modelling dynamic phenomena in geotechnical engineering.
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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".