Model Validation and Sensitivity Analysis of Coupled Non‐Equilibrium Heat and Mass Transfer in Porous Media With Application to Evaporation From Bare Soils
Bibliographic record
Abstract
Abstract Mathematical models in engineering play an important role in understanding and predicting the behavior of a system. A mechanistic coupled liquid water, water vapor and heat transfer model incorporating kinetic phase change accounting for real‐time interfacial area between water and gas phases was developed to predict coupled subsurface processes and evaporation (drying) rates from bare soils. To enhance the model capability to predict evaporation rates, the air resistance associated with the viscous sublayer was implemented in energy and mass exchange across the soil‐air interface (the land‐atmosphere boundary condition [BC]). The atmospheric stability condition was also considered in the calculation of sensible heat and vapor fluxes at the ground surface. This comprehensive model was validated against measured field data from bare soil test plots from a green roof study, during temperate summer conditions in Canada, demonstrating that the model captured the main coupled processes in the subsurface of bare soil during drying periods. A sensitivity analysis was performed to determine the importance of various components of the comprehensive model. Removal of viscous sublayer resistance in the vapor transfer BC resulted in poorer predictions of evaporation (drying) rates. Incorporating the atmospheric stability function accounting for real‐time atmospheric conditions did not improve the predictive capability for the simulated drying events compared to the case when only a neutral atmospheric condition was implemented. Neglecting heat transfer associated with hydrodynamic dispersion of water vapor in the subsurface had limited impact on subsurface temperature predictions.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".