The theory of parallel channels manifolds (Ladder networks) revisited part 1: Discrete mesoscopic modelling
Bibliographic record
Abstract
Abstract This article proposes a theoretical overview of the distribution of fluid flow through manifolds composed of parallel channels connected through T‐junctions to a distributor and to a collector channel, thus composing a ladder‐like network. Such networks are used in solar heaters, fuel cells, heat exchanger plates, and other engineering devices, one issue being to achieve a nearly uniform distribution. This first part focuses on the discrete mesoscopic momentum and energy balances governing the T‐junctions, with particular attention to the empirical, flow‐rate and geometry dependent, pressure change coefficients. By “mesoscopic”, it is meant that the control volume for the balance equations includes the junction zone and that the local flow‐field in that zone is not described. The existing results and correlations for these coefficients are reviewed, compared, and synthesized. In keeping with the discrete character of the channel network, the overall network relations are compacted as a single non‐linear finite‐difference equation relating the flow‐rates in the different segments of the distributor. This formulation is suitable for convenient numerical resolution even when all the coefficients are allowed to vary with local conditions. The conditions for simplifications, such as assuming constancy of certain coefficients, are carefully investigated. A number of approximate analytical, semi‐explicit or explicit solutions are constructed. In particular, an original view of the structure of these solutions is proposed, relying on an invariance property which is demonstrated, and on the analogy with the classical McCabe‐Thiele construction in chemical engineering. These approximations are compared to exact numerical solutions.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".