Application of Monte Carlo Simulation to Find Travel Time of Groundwater in the Iraqi Western Desert
Bibliographic record
Abstract
In this study, a computerized mathematical method represented by Monte Carlo simulation was used to predict the travel time of the groundwater flow in the Iraqi western desert. During the run of the simulations, all the hydraulic parameters of Darcy’s Law were fixed but the hydraulic conductivity. The input data of the hydraulic conductivity is compared to the triangular distribution function to find the best number of iteration to run the simulations. The results showed that an iteration number of 5000 was enough to achieve best match between the input data of the hydraulic conductivity and the fitted distribution function. In addition, the estimated travel time of the groundwater flow is broadly varied through the entire area and ranges from 1983 years to 113 741 years based on 10 000 m of travel distance. Furthermore, hydraulic conductivity of the aquifer has high impact on the estimated travel time of the groundwater flow. However, head difference of groundwater elevation among the selected wells considerably influences the expected travel time of the groundwater flow.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".