Dynamic process modeling on depressurization by cooling-controlled condensation in a closed chamber

It has long been realized that condensation in a chamber prefilled with condensable vapor leads to chamber depressurization, and the condensation rate can be cooling controlled. While the final state can be reasonably estimated based on the thermodynamic equilibrium, the dynamic process of depressurization is not only transient but also in thermal non-equilibrium. This transient and non-equilibrium characteristics, mainly governed by the rate of condensation, has not been satisfactorily modeled, which is due to the complicated coupling mechanisms of heat and mass transfer during the condensation, the presence of non-condensable gas (NCG) within vapor, as well as the complex geometry and properties of chamber and cooling device involved. In this paper, we have conducted an experimental study on depressurization by steam condensation onto an internal cooling coil in a steam-prefilled closed chamber. To reveal various parametric effects on the depressurization process, a parametric model consisting of a set of coupled ordinary differential equations has been established, with some simplified assumptions including lumped heat capacity sub-models for chamber walls, cooling coils and the gas phase. To further explore the thermal non-equilibrium characteristics during the process, a full-field and transient simulation of computational fluid dynamics (CFD) is also conducted using FLUENT with user-defined function (UDF) on boundary of condensation. Both parametric and CFD models consider the existence of NCG that is pre-mixed with the vapor as impurity. By comparison with the experimental measurements, both models reasonably predict the dynamic and asymptotic characteristics of depressurization with time. The CFD simulation indicates an almost instant equilibrium in pressure within the chamber and yet non-equilibrium in temperature with noticeable temperature gradients over the gas phase. The simplified parametric model gives quick predictions of some major parametric effects (e.g., vapor purity, coolant flow rate, and vessel volume) on the rate of depressurization. The detailed mechanistic understanding, gained from proposed models, provides insights essential to the optimized design and operation of the depressurization by cooling-controlled condensation.