Pressure-Pulse Test for Field Hydraulic Conductivity of Soils: Is the Common Interpretation Method Adequate?
Bibliographic record
Abstract
Pressure-pulse tests are performed in boreholes in either impervious rock or clayey formations. According to the usual theory, they give the hydraulic conductivity, k, and the storativity, S, of the tested material. However, comparative testing programs have shown that the usual interpretation method may give k values that are quite different from those given by other methods. It gives also unrepresentative (much too low) values of S for the tested formations. Several reasons for the discrepancies are examined. First, the theory came from a heat conduction problem but the mass and energy transfers in a pulse test are quite different from those in the heat conduction problem. Thus the usual interpretation method is derived from equations that do not represent correctly the physical phenomena involved in a pulse test. A correct theory should use equations that consider medium deformation to be partly instantaneous (undrained) and partly delayed (drained) during and after the pulse. This is not the case in the commonly used theory. It should also consider that both the testing system and the formation wall are deformed during the pulse, which is ignored by the usual theory. Besides this theoretical inadequacy, the usual interpretation method is frequently affected by an inaccurate knowledge of the local piezometric level for the test. This level is frequently guessed prior to testing, and this estimate may be incorrect. However, a velocity graph technique can be used to analyze the test data and establish the real piezometric level for the test. Considering the inadequacy of the usual equations and interpretation method, it is proposed to interpret the test data as those of a slug test after having determined the local piezometric level using the velocity graph method. Hvorslev's method is used after introducing an imaginary open tube with an inside diameter that is defined by the volume of injected water associated with the initial pulse. A detailed example is treated where this interpretation method yielded a k-value close to that obtained from a constant-head test in the same injection cavity, both values being 50 times lower than the k-value derived from the usual superposition method.
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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 | 0.019 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.010 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".