Temperature and Velocity Effects on Mass and Momentum Transport in Spacer-Filled Channels for Reverse Electrodialysis: A Numerical Study
Bibliographic record
Abstract
Concentration polarization is one of the main challenges of membrane-based processes such as power generation by reverse electrodialysis. Spacers in the compartments can enhance mass transfer by reducing concentration polarization. Active spacers increase the available membrane surface area, thus avoiding the shadow effect introduced by inactive spacers. Optimizing the spacer-filled channels is crucial for improving mass transfer while maintaining reasonable pressure losses. The main objective of this work was to develop a numerical model based upon the Navier–Stokes and Nernst–Planck equations in OpenFOAM, for detailed investigation of mass transfer efficiency and pressure drop. The model is utilized in different spacer-filled geometries for varying Reynolds numbers, spacer conductivity and fluid temperature. Triangular corrugations are found to be the optimum geometry, particularly at low flow velocities. Cylindrical corrugations are better at high flow velocities due to lower pressure drop. Enhanced mass transfer and lower pressure drop by elevating temperature is demonstrated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".