Exact analysis of the transient free convection flow of nanofluids between two vertical parallel plates in the presence of radiation
Bibliographic record
Abstract
The transient free convection flow of nanofluids between two long vertical parallel plates has been investigated analytically in the presence of thermal radiation by considering prescribed wall temperature (PWT) and prescribed wall heat flux (PWHF) at one boundary while the other boundary is maintained at the initial fluid temperature. The exact analytical solutions for the nanofluid velocity, temperature, skin friction, and Nusselt number are derived in the form of rapidly converging series with the help of Laplace transform technique. Five different types of water‐based nanofluids containing copper (Cu), silver (Ag), copper oxide (CuO), titanium oxide (TiO2), and aluminium oxide (Al2O3) are considered in the analysis. The effects of nanoparticle volume fraction, radiation parameter, and temporal variable on the velocity, temperature, skin friction, Nusselt number, volume flow rate, and vertical heat flux have been discussed in detail. Some new heat and fluid flow characteristics of nanofluids have been presented. The present results can be used as a benchmark to validate the numerical solutions of transient free convection flow of nanofluids in a vertical channel for limiting cases. Also, the results are useful in gaining a deeper insight into the relevant practical systems.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".