Effects of spatial gradients in thermophysical properties on the topology of turbulence in heated channel flow of supercritical fluids
Bibliographic record
Abstract
The current literature suggests that large spatial gradients of thermophysical properties, which occur in the vicinity of the pseudo-critical thermodynamic state, may result in significant variations in forced-convection heat transfer rates. Specifically, these property gradients induce inertia- and buoyancy-driven phenomena that may enhance or deteriorate the turbulence-dominated heat convection process. Through direct numerical simulations, the present study investigates the role of coherent flow structures in channel geometries for non-buoyant and buoyant flows of supercritical water, with buoyant configurations involving wall-normal oriented gravitational acceleration and downstream-oriented gravitational acceleration. This sequence of simulations enables the evaluation of the relative contributions of inertial and buoyancy phenomena to heat transfer variations. In these simulations, the state of the working fluid is in the vicinity of the pseudo-critical point. The uniform wall heat flux and the channel mass flux are specified such that the heat to mass flux ratio is 3 kJ/kg, with an inflow Reynolds number of 12 000 based on the channel hydraulic diameter, the area-averaged inflow velocity, and fluid properties evaluated at the bulk temperature and pressure of the inflow plane. In the absence of buoyancy forces, notable reductions in the density and viscosity in close proximity of the heated wall are observed to promote generation of small-scale vortices, with resultant breakdown into smaller scales as they interact with preexisting larger near-wall vortices. This interaction results in a reduction in the overall thermal mixing at particular wall-normal regions of the channel. Under the influence of wall-normal gravitational acceleration, the wall-normal density gradients are noted to enhance ejection motions due to baroclinic vorticity generation on the lower wall, thus providing additional wall-normal thermal mixing. Along the upper wall, the same mechanism generates streamwise vorticity of the opposing sense of rotation in the close vicinity to the respective legs of the hairpin vortices causing a net reduction in thermal mixing. Finally, in the case of downstream-oriented gravitational acceleration, baroclinic vorticity generation as per spanwise density gradients causes additional wall-normal thermal mixing by promoting larger-scale ejection and sweep motions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".