A comparative study of two combustion models based on non-premixed assumption and partially premixed assumptions using the overall models of Zimont Turbulent Flame Speed Closure Method (ZTFSC) and Extended Coherent Flamelet Method (ECFM) are conducted through Reynolds stress turbulence modelling of Tay model gas turbine combustor for the first time. The Tay model combustor retains all essential features of a realistic gas turbine combustor. It is seen that the non-premixed combustion model fails to predict the combustion completely due to an incorrect assumption of diffusion flame scenario invoking infinitely fast chemistry in complicated flow environments while the two partially premixed combustion models accurately predict the flame pattern in the primary region of the combustor. The ZTFSC model outperformed the ECFM model by producing a better temperature agreement with the experimental result. The latter model predicts lower temperature due to the underestimation of reaction progress. Additionally, a cross-comparison of the present RSM prediction invoking ZTFSC model with LES prediction reported in the literature is conducted. The former produces more accurate species concentration and flame pattern than the latter. This is mainly due to the incorrect assumption of nonpremixed combustion used in LES prediction reported in the literature. It is interesting to find that when nonpremixed combustion model is used for both RSM and LES predictions, the LES predicts higher temperature closer to the injection nozzle of combustor than the RSM model, though the flame shape in both cases is incorrect. This is mainly due to the fact that the traditional RANS model dissipates the energy of swirling flow too fast in the primary region of the combustor. The weaker centre recirculation zone (CRZ) created by vortex breakdown recirculate less air to the area near the injection nozzle resulting in fuel rich combustion. It indicates that the temperature difference between predicted results using RSM in conjunction with ZTFC model and experimental results can be improved by using less energy dissipating turbulence models such as scale resolving simulation (SRS). 1. Introduction The advent of Gas-Turbine for military purposes tracks back to 1940s, and it is subsequently used for aviation and later for ground level power [1]. The main challenge of aviation industries nowadays is the efficiency, stability of combustion and pollutant control, such as the emission of carbon dioxide (CO2), nitrogen oxide, sulphur dioxide and etc. In order to design combustors with desired features and meet with relevant criteria, improved understanding of turbulent combustion through both realistic experimental observation and numerical simulation and validation is required. The former alone is expensive for industries before a more cost-effective numerical prediction is performed. However, the accuracy of the numerical simulation is doubtful as it is highly dependent on the turbulence and combustion models, i.e. the mixing and chemical reactions. To i...

This study assessed two cavitation models for compressible cavitating flows within a single hole nozzle. The models evaluated were SS (Schnerr and Sauer) and ZGB (Zwart-Gerber-Belamri) using realizable k-epsilon turbulent model, which was found to be the most appropriate model to use for this flow. The liquid compressibility was modeled using the Tait equation, and the vapor compressibility was modeled using the ideal gas law. Compressible flow simulation results showed that the SS model failed to capture the flow physics with a weak agreement with experimental data, while the ZGB model predicted the flow much better. Modeling vapor compressibility improved the distribution of the cavitating vapor across the nozzle with an increase in vapor volume compared to that of the incompressible assumption, particularly in the core region which resulted in a much better quantitative and qualitative agreement with the experimental data. The results also showed the prediction of a normal shockwave downstream of the cavitation region where the local flow transforms from supersonic to subsonic because of an increase in the local pressure.

This study assesses the predictive capability of the ZGB (Zwart-Gerber-Belamri) cavitation model with the RANS (Reynolds Averaged Navier-Stokes), the realizable k-epsilon turbulence model, and compressibility of gas/liquid models for cavitation simulation in a multi-hole fuel injector at different cavitation numbers (CN) for diesel and biodiesel fuels. The prediction results were assessed quantitatively by comparison of predicted velocity profiles with those of measured LDV (Laser Doppler Velocimetry) data. Subsequently, predictions were assessed qualitatively by visual comparison of the predicted void fraction with experimental CCD (Charged Couple Device) recorded images. Both comparisons showed that the model could predict fluid behavior in such a condition with a high level of confidence. Additionally, flow field analysis of numerical results showed the formation of vortices in the injector sac volume. The analysis showed two main types of vortex structures formed. The first kind appeared connecting two adjacent holes and is known as “hole-to-hole” connecting vortices. The second type structure appeared as double “counter-rotating” vortices emerging from the needle wall and entering the injector hole facing it. The use of RANS proved to save significant computational cost and time in predicting the cavitating flow with good accuracy.

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The copper oxide nanoparticles (nano‐CuO)/nitrocellulose (NC)/triethyleneglycol dinitrate (TEGDN)/diaminoglyoxime (DAG) nanocomposites were successfully prepared as a convenient propellants. The catalytic effect of nano‐CuO on the thermal behavior and the decomposition kinetics of the samples were precisely verified via thermogravimetry (TGA) and differential scanning calorimetry (DSC). The CuO nanoparticles significantly altered the thermal pattern of the studied energetic materials, e. g., the temperatures corresponded to the DSC peaks were changed by increasing the nano‐CuO amount. Moreover, the catalyst resulted in the decrement in the activation energy of the decomposition stage by ∼30–50 kJ mol−1 and also improved the thermal stability of TEGDN/NC/DAG composite. The thermokinetic and thermodynamic parameters of the energetic nanocomposites were explained by using the Kissinger and Starink differential methods and the integral methods of Coats Redfern and Flynn‐Wall‐Ozawa. The mechanism function and the kinetic equation of the main exothermal decomposition step for the parent composite was found to be different from that of the 1–3 % CuO‐contained nanocomposites.