Modeling and Analysisof Flow, Thermal, and Energy Fields Within Stacks of Thermoacoustic Engines Filled With PorousMedia: A Conjugate Problem
Bibliographic record
Abstract
Abstract In this paper, an analytical study has been conducted on the flow and energy transfer of an unsteady compressible oscillating flow through channels filled with porous media representing stacks in thermoacoustic engines and refrigerators. The flow in the porous material is described by the Darcy momentum equation. The thickness of the channel wall is considered to be nonzero, and the entire problem is treated as a conjugate heat transfer problem, i.e., by considering conduction heat transfer inside the channel walls. Analytical expressions for the oscillating temperature, complex Nusselt number, and energy flux density are obtained after linearizing and solving the governing differential equations with long wave, short stack, and small amplitude oscillation approximations. To verify the present study, the energy flux density expression derived in this paper is compared with the expression available in the existing thermoacoustic literature. The two expressions match quantitatively for the limiting case of infinitely large pores. For infinitely large pore limits, the Nusselt number (nondimensional heat transfer between the porous media and the channel wall) obtained in the present study also agrees quantitatively with the nonporous medium expression reported in the literature. The present study indicates that refrigeration performance comparable to that of a traditional plastic parallel plate stack is achievable using reticulated vitreous carbon foam (ϕ=0.95, Lck=2.11) as a porous medium, which is also supported by other researchers. The system of equations developed in the present study is a helpful tool for thermal engineers and physicists to design porous stacks for thermoacoustic devices.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".