A Computational Fluid Dynamics and Chemistry Model for Jet Fuel Thermal Stability

1992 ◽  
Vol 114 (1) ◽  
pp. 104-110 ◽  
Author(s):  
J. L. Krazinski ◽  
S. P. Vanka ◽  
J. A. Pearce ◽  
W. M. Roquemore

This paper describes the development of a model for predicting the thermal decomposition rates of aviation fuels. A thermal deposition model was incorporated into FLANELS-2D, an existing computational fluid dynamics (CFD) code that solves the Reynolds-averaged conservation equations of mass, momentum, and energy. The decomposition chemistry is modeled by three global Arrhenius expressions in which the fuel decomposition was assumed to be due to an autoxidation reaction with dissolved oxygen. The deposition process was modeled by assuming that all deposit-forming species transported to the wall adhered and formed a deposit. Calibration of the model required the determination of the following parameters for a given fuel: (1) the pre-exponential constant and activation energy for the wall reaction, (2) the pre-exponential constant and activation energy for the bulk autoxidation reaction, and (3) the pre-exponential constant and activation energy for the precursor decomposition reaction. Values for these parameters were estimated using experimental data from published heated-tube experiments. Results show that the FLANELS-2D code performed well in estimating the fuel temperatures and that the three-equation chemistry model performed reasonably well in accounting for both the rate of deposition and the amount of dissolved oxygen present in the fuel at the end of the heated tube.

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 68
Author(s):  
Timilehin Martins Oyinloye ◽  
Won Byong Yoon

Computational fluid dynamics (CFD) was utilized to investigate the deposition process and printability of rice paste. The rheological and preliminary printing studies showed that paste formed from rice to water ratio (100:80) is suitable for 3D printing (3DP). Controlling the ambient temperature at C also contributed to improving the printed sample’s structural stability. The viscoelastic simulation indicated that the nozzle diameter influenced the flow properties of the printed material. As the nozzle diameter decreased (1.2 mm to 0.8 mm), the die swell ratio increased (13.7 to 15.15%). The rise in the swell ratio was a result of the increasing pressure gradient at the nozzle exit (5.48 × 106 Pa to 1.53 × 107 Pa). The additive simulation showed that the nozzle diameter affected both the residual stress and overall deformation of the sample. CFD analysis, therefore, demonstrates a significant advantage in optimizing the operating conditions for printing rice paste.


Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7284
Author(s):  
Karel Petera ◽  
Štěpán Papáček ◽  
Cristian Inostroza González ◽  
José María Fernández-Sevilla ◽  
Francisco Gabriel Acién Fernández

High concentration of dissolved oxygen within microalgae cultures reduces the performance of corresponding microalgae cultivation system (MCS). The main aim of this study is to provide a reliable computational fluid dynamics (CFD)-based methodology enabling to simulate two relevant phenomena governing the distribution of dissolved oxygen within MCS: (i) mass transfer through the liquid–air interface and (ii) oxygen evolution due to microalgae photosynthesis including the inhibition by the same dissolved oxygen. On an open thin-layer cascade (TLC) reactor, a benchmark numerical study to assess the oxygen distribution was conducted. While the mass transfer phenomenon is embedded within CFD code ANSYS Fluent, the oxygen evolution rate has to be implemented via user-defined function (UDF). To validate our methodology, experimental data for dissolved oxygen distribution within the 80 meter long open thin-layer cascade reactor are compared against numerical results. Moreover, the consistency of numerical results with theoretical expectations has been shown on the newly derived differential equation describing the balance of dissolved oxygen along the longitudinal direction of TLC. We argue that employing our methodology, the dissolved oxygen distribution within any MCS can be reliably determined in silico, and eventually optimized or/and controlled.


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