Computer simulation of mass transport in groundwater : affect of macroscopic heterogeneities in hydraulic conductivity
Bibliographic record
Abstract
In this study a computer model was used to simulate dissolved chloride movement through alluvial sediments which border the Canadian River in Hutchinson County, Texas. Hydraulic conductivity values of the sediments were required in order to calculate groundwater velocities in the system. The most realistic representation of conductivity variations in porous media is expressed by frequency distributions rather than by averaged values of conductivity. Numerous sedimentological environments exhibit log-normal conductivity distributions; therefore, one was used in this investigation. A number of conclusions can be based on the results of this study. First, certain conductivity distributions account for the observed spread of chloride in the aquifer. The best match of observed chloride dispersion was obtained with autocorrelated log-normal conductivity distributions. Secondly, the degree of spatial dependence between adjacent conductivity values affected numerous results. These include the amount of chloride dispersion and the extent of uncertainty in calculated hydraulic head and chloride distributions. For comparative purposes the chloride distribution was also modeled using an average conductivity value. Under this condition the chloride plume moved at an average rate of 10 meters/year. Another result was that longitudinal and transverse dispersivities of 46 meters and 9 meters, respectively, were required to obtain a match between observed and modeled chloride distributions.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".