Modeling Vapor Flow from a Pervaporative Irrigation System
Bibliographic record
Abstract
Experimental and modeling results were used to develop a conceptual understanding of the process of pervaporative irrigation in dry soils. When irrigating in this way, a pervaporative membrane is formed into a tube, buried in the soil, and filled with water. If the surrounding soil is dry, a chemical potential gradient across the membrane draws water into the soil. Water can only desorb from the membrane as a vapor, however, so it enters the soil in the vapor phase. This study corroborates previous evidence that vapor flow can significantly affect the flux from the irrigation membrane under arid conditions. A new model of water transport from a pervaporative irrigation membrane in unvegetated soils was developed, taking into account transport in both liquid and vapor phases, and successfully simulated experimental observations of the total water flux, relative humidity, and water content distribution in three soil types. Modeling results showed that the capacity for moisture sorption within different soil types affects both condensation in the soil and the subsequent flux from the pervaporative membrane. A mathematical relationship for the moisture sorption isotherm for a soil can therefore be used to predict the flux across the membrane in that soil. If condensation is significant, liquid flows through the soil also affect the flux from the membrane. Model simulations suggest that the flux from the pervaporative membrane is primarily limited by humid conditions within the soil rather than the transport of water across the membrane, thus plant interactions with the soil conditions should increase the irrigation flux.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".