On the Development of Parametrical Water Quenching Heat Transfer Model Using Quenchometer and Its Validation for All Boiling Regimes

Abstract

In the water quenching process of Aluminum 319, temperature drops rapidly from solutionizing temperatures, around 500°C, to water pool temperature. In this temperature range, the quenching process goes through three boiling regimes: film boiling, transition boiling, and nucleate boiling, before reducing to convection heat transfer. Each boiling regime has unique heat transfer characteristics governed by different physics. A common method to analyze the heat transfer rate in liquid quenching is the cooling curve analysis by quenchometer. Among several methodologies to characterize heat transfer rate, we have found successes in adapting a heat transfer framework based on Leidenfrost point (LFP), minimum heat flux (MHF), and critical heat flux (CHF) to develop a CFD model for quenching process simulation. The CFD model then can be used to calculate temperature histories as well as temperature profiles and the simulation results can be sent to FEA to predict thermal residual stress and distortion. Although the LFP, MHF, and CHF framework has been proven useful for the numerical simulation of water quenching process, these parameters are not constant and they have to be calibrated through experiments for each quenching condition. The objective of this paper is to parameterize the boiling model by quenching conditions such as water pool temperature. Then the predictive model is validated by experimental data obtained by quenchometers.

Film Boiling Conjugate Heat Transfer during Immersion Quenching

“…Realistically we could also account for the air as a distinct phase. Nevertheless, we consider the air to have identical properties with water vapour, as have been done in many previous studies without a lack of generality or accuracy [6][7][8][9][10][11][12][13][14][15][16].…”

“…Also, notice that many heat transfer correlations are based on experimental results, including the radiation impact. For this study, we follow previous research and neglect its effect [6][7][8][9][10][11][12][13][14][15][16][17][18]. In future work, we might include thermal radiation modelling when the wall heat transfer coefficient is correlated via the incorporation of the quenching tank and calculation of view factors.…”

“…where k MHF and k burn are the minimum heat flux and the burn out factors equal to 5 and 0.5, respectively. The factors are used due to the lack of the correlations generality and need to be tuned to experimental results [9,15]. θ represents an interpolation factor bounded by values 0 and 1, found by employing the precalculated temperatures T LEID and T DNB through:…”

“…Inadequate cooling can cause samples to distort and crack, resulting from thermal stress developed due to significant temperature gradients [4]. Despite the fact that there have been several research papers dedicated to computational techniques for immersion quenching [6][7][8][9][10][11][12][13][14][15][16][17][18], improvements are still necessary. The manufacturing industry would greatly benefit from a well-functioning, accurate, and efficient computational technique that predicts the temperature profile of the solid during the quenching process and the resulting mechanical stresses.…”

“…Nonetheless, the thermal homogeneous assumption was applied, with the interfacial phase heat transfer coefficient set to a very high value which homogenised the equations. The latest research papers using AVL FIRE discussed the influence and calibration of various coefficients and values within the heat transfer framework, which usually need to be chosen and tuned to achieve valid results [15,16].…”