Numerical simulation of thermal energy storage system inside a spherical capsule under periodic boundary conditions

In this work, inward solidification process of a spherical capsule subjected to a periodic boundary condition is numerically studied. The temperature transforming technique is utilized to solve the 1D phase change model and an in-house model developed in C++. The interface position and the transient temperature profiles are evaluated with respect to the different oscillation amplitudes and oscillation frequencies of the periodically oscillating surface temperature. The results demonstrate that in the situation where the amplitude is 30, the elapsed time for total solidification is dropped by 23.7% compared to the case without oscillation. It is also found that there is a 21.8% reduction in the time for total solidification when the frequency is changed from omega = pi/64 to omega = 0

Novel Saturated Flow Boiling Heat Transfer Correlation for R32 Refrigerant

[No Abstract Available

Novel saturated flow boiling correlations for R600a and R717 refrigerants

This research study provides a detailed analysis of the two-phase flow boiling heat transfer coefficients of R600a and R717. In addition, it proposes novel saturated flow boiling heat transfer correlations for these two refrigerants. In this context, 1306 experimental data points for R600a and 885 data samples for R717 are extracted from the literature works to develop new flow boiling models. Two different correlations are constructed under different forms of baseline frameworks for each refrigerant. The proposed flow boiling model for R600a utilizes the dimensionless numbers and operational parameters of the best performing literature correlations for this refrigerant while the model developed for R717 takes the advantage of piecewise continuous correlation form which successfully trace the tendencies of heat transfer coefficient with varying vapor qualities. It is found that the new model for R600a has a mean absolute error of 12.4% and mean relative error of 0.1, predicting 78.5% of the entire database within +/- 20.0% error band whereas the proposed correlation for R717 has an absolute error value of 17.3% having 65.3% of the data within +/- 20.0% error band, which are much better and accurate estimations compared to those obtained by the existing flow boiling models for R717 refrigerant