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ABSTRACT
When a cryogenic fluid initially at a subcritical temperature is injected into a supercritical environment, it will experience a process across a pseudo-boiling point, at which the specific heat reaches its maximum value under the corresponding pressure. Large eddy simulation (LES) is conducted to explore the effects of pseudo-vaporization phenomenon around the pseudo-critical temperature on fluid jet evolution. To highlight the pseudo-vaporization effect, a cryogenic nitrogen jet with different injection temperatures, which correspond to transcritical and supercritical conditions, respectively, is injected into a chamber with same supercritical conditions. All of the thermophysical and transport properties are determined directly from fundamental theories combined with a real fluid equation of state. It is found that when the fluid transits through the pseudo-boiling point, the constant-pressure specific heat reaches a local maximum, while the thermal conductivity and viscosity become minimum. The condition-averaged constant-pressure specific heat suggests that the pseudo-boiling point has the effect of increasing the density gradients. Vorticity and Q-criterion analysis reveals that high-temperature injection facilitates the mixing of jet fluid with ambient gas. Also, the high-temperature injection of supercritical fluid can earlier transit into the full developed region.
Nomenclature
| = | slope of the linear regression | |
| EOS | = | equation of state |
| et | = | total energy |
| H | = | energy flux |
| = | sub-grid scale energy fluxes | |
| LES | = | large eddy simulation |
| Lρ | = | half-width |
| P | = | pressure |
| Pc | = | critical pressure |
| R | = | universal gas constant |
| = | sub-grid scale strain-rate tensor | |
| SRK | = | Soave–Redlich–Kwong |
| T | = | temperature |
| Tc | = | critical pressure |
| Tinj | = | inject temperature |
| T∞ | = | environment temperature |
| t | = | time |
| θH | = | HWHM spreading angle |
| ρinj | = | inject density |
| ρc | = | critical density |
| ρ∞ | = | environment density |
| ▽ρ | = | density gradient |
| Δ | = | filter width |
| ω | = | acentric factor |
| τij | = | sheer stress |
| σij | = | viscous work |
Nomenclature
| = | slope of the linear regression | |
| EOS | = | equation of state |
| et | = | total energy |
| H | = | energy flux |
| = | sub-grid scale energy fluxes | |
| LES | = | large eddy simulation |
| Lρ | = | half-width |
| P | = | pressure |
| Pc | = | critical pressure |
| R | = | universal gas constant |
| = | sub-grid scale strain-rate tensor | |
| SRK | = | Soave–Redlich–Kwong |
| T | = | temperature |
| Tc | = | critical pressure |
| Tinj | = | inject temperature |
| T∞ | = | environment temperature |
| t | = | time |
| θH | = | HWHM spreading angle |
| ρinj | = | inject density |
| ρc | = | critical density |
| ρ∞ | = | environment density |
| ▽ρ | = | density gradient |
| Δ | = | filter width |
| ω | = | acentric factor |
| τij | = | sheer stress |
| σij | = | viscous work |