In this article, we describe a newly developed modeling procedure to simulate the immersion quench cooling process using the commercial code AVL-FIRE. The boiling phase change process, triggered by the dipping hot solid part into a subcooled liquid bath and the ensuing two-phase flow is handled using an Eulerian two-fluid method. Mass transfer effects are modeled based on different boiling modes such as film or nucleate boiling regime prevalent in the system. Separate computational domains constructed for the quenched solid part and the liquid (quenchant) domain are numerically coupled at the interface of the solid-liquid boundaries using the AVL-Code-Coupling-Interface (ACCI) feature. The advanced ACCI procedure allows the information pertaining to the phase change rates in the liquid domain to appear as cooling rates on the quenched solid boundaries. As a consequence, the code handles the multiphase flow dynamics in the liquid domain in conjunction with the temperature evolution in the solid region in a tightly coupled fashion. The methodology, implemented in the commercial code AVL-FIRE, is exercised in simulating the quenching of solid parts. In part I of the present research, phase change models are validated by simulating a work piece quenching process for which measurement data are available for various water temperature ranging from 20C to 80C. The computations provide a detailed description of the vapor and temperature fields in the liquid and solid domain at various time instants. In particular, the modifications arising in the liquid-vapor flow field in the near vicinity of the solid interface as a function of the boiling mode is well accommodated. The temperature history predicted by our model at different monitoring points, under different subcooling conditions, correlate very well with the experimental data wherever available. In part II, the model is further applied to real engine cylinder head quenching process and assessment is made for the cooling curves for various measuring points. Overall, the predictive capability of the new quenching model is well demonstrated.

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