Bibliographic record
Abstract
Desalination by freeze crystallization is a freezing-melting process in which water is crystallized to ice and separated from saline solution. This area is observing a renascence to mitigate the staggering and sea rejected brine that has a negative environmental impact. Phase diagram of NaCl-H2O is the key point of designing freeze desalination systems. All freeze crystallization methods follow the same process, starting from nucleation, crystal growth, separation, and finally melting. Direct contact, indirect contact, vacuum, and eutectic point are the basic methods of crystallization. Furthermore, suspension freezing and freezing on a cold plate by indirect contact with refrigerant are the found to be the most suitable methods for desalination. Initial concentration, refrigerant temperature, growth rate, and flow rate are the main operating parameters that determine the final product properties and desalination efficiency. In this work, a quick review on the subject is brought up as the area is regaining renascence this followed with simulation of an indirect freeze crystallization process in a rectangular enclosure using computational fluid dynamics (CFD) modelling. These modeling are paradigm shift to gain more insight to the complex crystallization process being based on multiple species non-isothermal flow in a two phase flow representing the liquid and the ice formation. Results show that by combined CFD in multiple species modelling much insight into freeze crystallization can be revealed, optimized and re-designed.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".