Numerical Simulation of Low Energy Direct Contact Membrane Distillation
Bibliographic record
Abstract
Computational Fluid Dynamics (CFD) is used to study the steady state performance of Low Energy Direct Contact Membrane Distillation (DCMD). Two-dimensional numerical model with parallel and counter flow is developed. A case of fully developed pressure driven parabolic flow is considered entering the domain at the feed and the permeate sides at 40 C and 25 C, respectively. The model parameters were measured in the consideration of two dimensional fluid flow governed by the complete Navier-Stokes coupled with the energy equation for non-isothermal laminar flow. The feed stream is water at water 4% salinity, whereas the permeate stream is comprised of pure water. Across the membrane the temperature difference creates a pressure gradient responsible for the transport of vapor mass through the pours of the permeable membrane. The vapor flow is driven by two mechanisms, Knudson and Poiseuille flow. The membrane’s coefficients of DCMD membrane is evaluated along with the mass flux, heat flux, and temperature polarization factor and results showed a good agreement with the published theoretical work. In view of these plausible results, parametrical study is carried out accounting for parallel and counter flow, different flow rates and inlet temperature in an attempt to achieve optimal or better yield to the Multi stage flashing method.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".